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YININGWANG
CFD INVESTIGATION OF GAS-SOLID FLOW DYNAMICS IN MONOLITHIC MICRO
CIRCULATING FLUIDIZED BED REACTORS
Mémoire présenté à la Faculté des études supérieures de l'Université Laval
dans le cadre du programme de maîtrise en génie chimique pour l'obtention du grade de maître ès sciences (M. Sc.)
DÉPARTEMENT DE GÉNIE CHIMIQUE FACULTÉ DES SCIENCES ET DE GÉNIE
UNIVERSITÉ LA V AL QUÉBEC
2008
© Yining WANG, 2008
RÉSUMÉ
La biomasse est une des sources importantes d'énergie primaire et renouvelable. Le
développement d'un procédé basé sur la conversion de celle-ci en énergie tout en
demeurant respectueux de l'environnement, fait l'objet de recherches intenses aussi bien
dans les mondes académique qu'industriel. La gazéification pour produire un gaz de
biosynthèse est considérée comme une des options les plus prometteuses via la valorisation
des sources de résidus de biomasse. La thermodynamique et la cinétique intrinsèque
imposent que les réactions de gazéification de la biomasse doivent être effectuées à des
températures élevées, exigeant la fourniture et la récupération de chaleur de manière
efficace. Le concept de gazéification allotherme (par opposition à son pendant autotherme)
offre une solution attrayante pour la mise en œuvre à haute température du couplage de
réactions fortement endothermique avec des réactions exothermiques. Toutefois, la mise en
œuvre pratique du concept sous haute température n'est pas aisée.
Dans ce travail, un nouveau concept pour la gazéification de résidus de la biomasse
est proposé impliquant l'hybridation de réactions à hautes températures de la gazéification
et de la combustion dans un réacteur monolithique structuré. Clairement, le design et
l'optimisation de ce nouveau procédé hybride requiert la compréhension précise, non
seulement des phénomènes physico-chimiques de la conversion thermochimique de la
biomasse, mais aussi du comportement hydrodynamique, complexe, des deux phases mises
en œuvre dans un microréacteur monolithique à lit fluidisé. À cet égard, la caractéristique
hydrodynamique de la distribution des écoulements des phases gaz-solide au sein du
réacteur revêt une importance cruciale pour la prédiction du comportement des processus
de gazéification/combustion et pour l'examen de stratégies d'opération du procédé. En
particulier, en raison de la nature complexe de l'interaction entre le gaz et les particules
solides ainsi que la phase stationnaire représentée par le microréacteur monolithique, un
des défis dans le design et l'opération de ces réacteurs est la prévention de la
maldistribution des phases. Dans ce travail, la mécanique des fluides numériques (MFN)
est mise à profit comme outil de simulation permettant d'explorer les distributions des
écoulements gaz-solide dans un réacteur monolithique. L'ensemble des sections structurée
111
(le monolithe) et les parties terminales non-structurées (lits fixes aléatoires permettant
l'alimentation et l'évacuation de la suspension gaz-solide) est globalement considéré dans
la simulation afin de capturer les tendances lourdes des mécanismes contribuant à la
dynamique gaz-solide. Les résultats des simulations ont démontré la capacité de la MFN à
capturer la caractéristique de non-uniformité de l'écoulement dans ce type de géométrie.
iv
ABSTRACT
Biomass is one of the important pnmary and renewable energy sources. The
development of a biomass-based but energy-efficient and environment-friendly system is
seen to be very seductive. Gasification to produce biosyngas is regarded as one of the most
promising options for utilizing biomass sources. Therrnodynamics and intrinsic kinetics
dictate that endotherrnic biomass gasification reactions have to be carried out at high
temperatures, which demands efficient heat supply and recovery policy. The concept of
allothermal gasification offers an attractive solution for implementing high-temperature
reactions by coupling strongly endothermic reactions with exotherrnic reactions. However,
implementation of the concept under high-temperature conditions . in practice is not
straightforward.
In this work, an innovative process concept for biomass gasification is proposed,
which involves the hybridization of high-temperature gasificationlcombustion reactions in
a monolithic structured reactor. Evidently, the design and optimization of this novel hybrid
process requires accurate understanding of not only the physicochemical phenomena of
biomass thermochemical c0I?-version but also the two-phase hydrodynamics behaviour in
the monolithic micro-fIuidized reactor which are highly complex in nature. In this regard,
the fIow distribution characteristic of the gas-solid two-phase hydrodynamics in monolithic
structured reactor is significantly important for prediction of gasification/combustion
performance and examination of strategies for process operation. Especially, due to the
complex nature of the interaction between gas and particulate phases and the stationary
monolith backbone, one of the challenges in the design and operation of the monolith
reactors is the prevention of fIow maldistribution. In this work, computational fIuid
dynamics (CFD) is used as a tool to investigate the gas-solids two-phase fIow distribution
in a monolithic structured reactor. The assemblage of monolithic structured packings with
through-fIow gas-particulate fIows is globally considered in the simulation to capture the
dominant possible mechanisms contributing to the final overall gas and granular dynamics.
The simulation results demonstrated the ability of our CFD simulation to capture the non
uniform fIow characteristics in monolithic structured packings.
v
FOREWORD
There are four chapters in this thesis. Among them, chapter 3 is composed of a research
article which was submitted to the scientific journal lndustrial & Engineering Chemistry
Research at the time of this thesis deposit for evaluation (August 2008). This research
article is entitled:
Yi-Ning Wang, Faïçal Larachi, Shantanu Roy. Simulating the Dynamics of Gas-Solid
Flows in a Multichannel Micro-Circulating Fluidized Bed, lndustrial & Engineering
Chemistry Research, 2008 (Accepted).
From its integrity viewpoint, this chapter consists of the research article. Nonetheless,
the figures and tables were displaced from the end of the research article to where the y are
mentioned in the text. The size of the figures and tables as weIl as the size of the characters
were also adjusted to fit the requirement of the thesis writing.
The research article was prepared on my own and revised by my research supervisor,
Prof. Faïçal Larachi and my research co-supervisor, Prof. Shantanu Roy, who were
included in this article as co-authors.
VI
ACKOWLEDGEMENTS
First of aU, 1 would like to express my sincere gratitude and appteciation to my
research supervisor, Prof. Faïçal Larachi, for granting me the opportunity and resources to
study the Master pro gram and offering his invaluable thoughtful insights and unique source
of knowledge throughout this research project.
1 would like to sincerely thank my research co-supervisor, Prof. Shantanu Royat the
Department of Chemical Engineering in Indian Institute of Technology (lIT) for his helpful
discussions and suggestions as weIl as his consistent support. His experience and
professional attitude inspired me throughout this work.
1 would like to express my appreciation to the technical and administrative staff at the
Department of Chemical Engineering in Laval University for their continuous assistance
and cooperation all along the Master program.
1 would like to thank and convey my gratitude to the graduate students, post
doctorates and colleagues in our research group (Soumaine, Cedric, Simon, Florin, Bora,
Mugurel, Mohsen, David, Olivier, Insaf, Samira, Lyes, Aziz, Pouya and Elahe) with whom
1 had the pleasure to share great moments during the past years. 1 am also taking the
occasion to specially thank Mf. Mohsen for his friendly help in the course of this project.
FinaUy, 1 am deeply grateful to my family members for their eternal and implicit
support during my study. Most important of aU, 1 would like to thank my wife, Ying SUN,
for her endless love and encouragement. My special thanks go to my lovely daughter, Ya
Xuan WANG, who always makes my coming home in the evening a joyful event with her
smiling face and loving hug.
VIl
LIST OF TABLES
Chapter 2
Table 2.1 List of heterogeneous and homogeneous reactions involved in biomass
gasification ........................... ........................................................................................ 12
Table 2.2 Summary of important investigations of the gasification of biomass in fluidized
beds .............................................................................................................................. 13
Table 2.3 Summary of recent important attempts at reactor modeling of biomass
gasification ................................................................ ................ .. ................................ 16
Table 2.4 Candidates of PCM for high temperature application (Maruoka et al.,2002) .. ... 24
Table 2.5 Comparisons of numerical schemes for modeling phase change phenomena .... 26
Table 2.6 Recent attempts at CFD modeling of circulating fluidized bed reactor
performances ............... .................................................................................... : ........... 32
Chapter 3
Table 3.1 Basic simulation conditions used in this work .................................................... 58
Table 3.2 Effect of particle size and radial porosity distribution of nonstructured packings
on the flow characteristics in monolith .................................................... .. ... .............. 69
VIn
LIST OF FIGURES
. Chapter 2
Figure 2.1 Paths for the conversion of raw materials to final products (via syngas
production step) ....................................................................................................... .. .... 5
Figure 2.2 Three routes to syngas .......................................................................................... 7
Figure 2.3 Proposed novel process concept .......................................................................... 9
Figure 2.4 Van Krevelen diagram for various solid fuels (Prins et al.,2007) ...................... Il
Figure 2.5 General reaction mechanism for the gasification of a biomass fuel (Higman and
van der Burgt,2003) ..................................................................................................... 12
Figure 2.6 Schematic representation of the monolith reactor (Tomasic, 2007) .................. 18
Figure 2.7 Vertical distribution of solid in different contacting regimes (Kunii &
Levenspiel, 1997) ..................................... " ............................................................. " ....... 29
Chapter 3
Figure 3.1 Proposed process concept .................................................................................. 49
Figure 3.2 Radial variation of bed porosity in packed-bed sections ................................... 52
Figure 3.3 Two-dimensional computation al geometry with the assemblage of three-section
structured/non-structured packings (yellow line, 2D symmetric plane) ..................... 57
Figure 3.4 Solids biomass flux of suspended phase in different packing sections .............. 60
Figure 3.5 Gas mass fluxes mirroring Figure 4 simulations ............................................... 60
Figure 3.6 Channel dependence of gas-phase velocity, solid velocity, and solid holdup (z=
0.4m) ...................... ~ ..................................................................................................... 61
Figure 3.7 The gas-phase velocity in single-phase flow simulation ................................... 63
Figure 3.8 Comparison of gas-phase velocities under single-phase/two-phase simulation
conditions (z=0.4m) with and without the nonstructured packings ............................ 64
Figure 3.9 Comparison of monolith-section flow distribution characteristics (z=0.4m) with
and without the nonstructured packing in the downstream section ............................. 65
IX
Figure 3.10 Details of the channel locations and centerline-based pressure sampling in the
three-section monolith system ..................................................................................... 67
Figure 3.11 Effect of particle size and porosity radial distribution on the solid mass flux
distribution in the composite monolith system ............................................................ 70
x
TABLE OF CONTENTS
RÉSUMÉ .............................................................................................................................. iii
ABSTRACT ................ .......................................................................................................... v
FOREWORD ........................................................................................................................ vi
ACKOWLEDGEMENTS ................................................................................................... vii
LIST OF TABLES ............................................................................................................. viii
LIST OF FIGURES .............................................................................................................. ix
TABLE OF CONTENTS ..................................................................................................... xi
Chapter 1 General Introduction ............................................................................................ 1
1.1 Research Background & Problem Statement .............................................................. 1
1.2 Research Objectives and Scope of the Thesis ............................................................. 2
Chapter 2 Literature Review ................................................................................................ 4
2.1 Introduction ................................................................................................................. 4
2.2 Hybridization of Gasification/Combustion Processes: A Novel Process Concept ..... 6
2.3 Physicochemical Processes in Biomass Gasification and Modelling ........................ Il
2.3.1 Physicochemical processes in biomass gasification ......................................... Il
2.3.2 Modeling of biomass gasification process ....................................................... 14
2.4 Monolithic Structured Reactor and Modelling Methodology ................................... 17
2.4.1 Monolithic structured reactors .......................................................................... 17
2.4.2 Modeling of monolithic structured reactors ..................................................... 19 \
2.5 High-Temperature Phase-Change Material and Modelling Approaches .................. 23
2.5.} High-temperature phase-change material ......................................................... 23
2.5.2 Modeling of solidification and melting processes in phase-change-material .. 24
2.6 Gas-Solid Fluidization in Micro-Fluidized Bed Reactors and Modeling Methodology
......................................................................................................................................... 27
2.6.1 Monolithic micro-fluidized bed reactors and gas-solid fluidization ................ 27
Xl
2.6.2 Modeling of circulating fluidized bed reactors ................................................ 29
2.7 Summary and Conclu ding Remarks .......................................................................... 32
References .......................... ............................................................................................. 34
Chapter 3 Simulating the Dynamics of Gas-Solid Flows in . a Multichannel Micro-
Circulating Fluidized Bed ................................................................................................ 46
Abstract ................................................................. ' ........................................................... 46
3.1 Introduction ............................................................................................................... 47
3.2 Hybridization of Gasification/Combustion Processes in Monolithic Structured
Reactors ............. , ............................................................................................................. 48
3.3 Representation of Nonuniform Porosity Distribution for Packed-bed Sections ....... 50
3.4 Eulerian-Eulerian Multifluid Model for Gas-Solid Flow in Monolithic Structured
Reactor ............................................................................................................................. 52
3.4.1 Continuity and momentum conservation equations ......................................... 52
3.4.1.1 Mass conservation equations of gas and particulate phases .. .................... 52
3.4.1.2 Momentum conservation equation of gas and particulate phases .............. 53
3 .4.2 Kinetic theory of granular flow equations ........................................................ 53
3.4.3 Closure relationships for interphase interactions ............................................. 54
3.4.4 Definition of maldistrioution quantities ........................................................... 56
3.5 Computational Geometry, Boundary Conditions and Numerical Solution ............... 56
3.6 Results and Discussion .............................................................................................. 58
3.6.1 Modeling of two-phase flow behavior in monolith structured packings .......... 59
3.6.2 Comparison of gas-solid two-phase flow with single-phase flow .................... 62
3.6.3 Effect of downstream-section packing mode on flow distribution in monolith64
3.6.4 Effect of particle size of nonstructured packings on flow characteristics in
monolith ..................................................................................................................... 66
3.7 Conclusions ................................................................................................................ 71
Acknowledgement ....... ~ ................................................................................................... 72
Nomenclature .................................................................................................................. 72
Literature Cited ........................................................................ ........................................ 75
XlI
Chapter 4 Conclusions and Recommendations .................................................................. 79
4.1 General conclusions ........................................................ ..... ...................................... 79
4.2 Recommendations for future investigations .............................................................. 81
X1l1
Chapter 1 General Introduction
1.1 Research Background & Problem Statement
Biomass is one of the important primary and renewable energy sources. With the
depletion of fossil fuel sources as weIl as the evolving global warming issues, the need
for utilization of biomass for energy is seen to be imperative, particularly because it is
believed that energy obtained from biomass has a carbon-neutral cycle. This situation
calls for the development of a biomass-based but energy efficient and environment
friendly system with better environmental acceptability and economic viability.
Gasification to produce biosyngas is regarded as one of the most promising options for
utilizing biomass. However, due to the thermodynamic and kinetic limitations,
endothermic biomass gasification reactions have to be carried out at high temperatures,
which demands an efficient heat supply and heat recovery. The concept of allothermal
gasification offers an attractive solution for implementing high-temperature reactions by
coupling strongly endothermic reaction with exothermic reactions. However,
implementing the concept in practice is not straightforward.
> Steam gasification of solid carbonaceous fuels is highly endothermic, which demands
the input of additional heat source to drive the reactor system. This is a challenge because
the input of energy reduces the maximum efficiency of the process. A further challenge is
the provision of the additional heat without compromising the quality of the products.
Methods to meet this energy shortfall involve: (i) the combustion of a fraction of the
biomass fuel or unconverted biomass residue to generate heat; (ii) the use of a fraction of
the combustible product gases to generate energy. In convention al gasifiers, the energy
required for heating the reactants and for the heat of reaction is supplied by burning a
significant portion of the feedstock, either directly by internaI combustion or indirectly by
external combustion. InternaI combustion, as applied in autothermal reactors, results in
the contamination of the gaseous products, while external combustion, as applied in
allothermal reactors, results in lower thermal efficiency because of the irreversibilities
associated with indirect heat transfer.
As far as biomass gasification conversion process is concemed, there are a number of
potential problems which could be encountered in the energy management of the process:
(i) If biomass is reacted with both air and steam in one reactor, then nitrogen is present in
the product stream and is costly to remove; (ii) If trying to avoid this proble~ by using
oxygen instead of air, then a source of pure oxygen would be needed, which is also a
costly proposition; (iii) It is possible to circumvent the separation issues by running the
oxygenless gasification and the combustion reactions in different locations (spatial
segregation), in which transferring heat from one location to the other would be
accompanied with heat losses; (iv) AIso, in aIl of these schemes, if the product gas is
rapidly cooled, th en tar forms, which is also afflicting process stability and efficiency. To
avoid this, the product gases must be kept hot for a while to let the tars crack into lower
molecular weight compounds.
tn view of the aforementioned problems, an innovative process concept which
involves the hybridization of biomass gasification/combustion reactions in a monolithic
. structured reactor is proposed in this work to address sorne of the above potential "show
stoppers". In this novel process, the monolith is operated periodically between an
endothermic gasification step and an exothermic combustion step. High-temperature
phase-change-materials are used to intensif y the process heat management. The heat
released during combustion is stored using a high-temperature phase-change material
(like LiF-CaF2), which is expected to discharge heat during the endothermic gasification
step. The biomass is supplied to the monolith by fine granulation and subsequent
pneumatic conveying, essentially creating monolithic micro-circulating fluidized beds.
Hence, the process intensification is achieved both by temporal segregation of
gasification and combustion as weIl as the use of a monolithic micro-fluidized bed
reactor.
1.2 Research Objectives and Scope of the Thesis
To effectively design and optimize this novel process, knowledge from different
important fields (including biomass gasification, mon?lith reactor engineering, high-
2
temperature phase change material, and gas-solids fluidization) is required. Among them,
modeling and understanding of gas-solid (biomass particles) flow hydrodynamics in
monolithic structured reactor is very important, in view of the complexity of two-phase
flow in structured packings. In this regard, the flow distribution characteristic of the gas
solid two-phase hydrodynamics in monolithic structured reactor is significantly essential
for prediction of gasification/combustion performance and examination of strategies for
process operation. Especially, due to the complex nature of the interaction between gas
and particulate phases and the stationary monolith backbone, one of the challenges in the
design and operation of the monolith reactors is the prevention of flow maldistribution.
In this thesis, following the proposaI of this novel process concept as weIl as the
review of the relevant literature, the research focus is oriented to the CFD investigation of
gas-solids (biomass particles) two-phase flow dynamics in monolithic multichannel
micro-circulating fluidized bed. The computational fluid dynamics approach is used as a
tool to investigate the gas-solids two-phase flow distribution in a monolithic structured
reactor. A 2-D Euler-Euler multiphase model with the kinetic theory of granular flow has
been solved for the detailed monolithic packing geometry. The assemblage of structured
monolithic section with non-structured packed-bed sections is globally considered in the
simulation, allowing comprehensive capture of various possible mechanisms contributing
to the final overall aero/granular dynamics.
3
Chapter 2 Literature Review
2.1 Introduction
Sustainable development requires sustainable energy resources. It is now widely
acknowledged that combustion of fossil fuels contributes to the buildup of CO2 in the
atmosphere, which in turn contributes to the greenhouse effect, gradually warming the
planet. Biomass is considered to be one of the most promising alternatives to replace
fossi! fuels (Negro et al. , 2008). As a diverse energy carrier with a multitude of potential
sources, biomass is the most important fuel worldwide following coal, oil and natural gas.
Furthermore, it is considered to be a carbon-neutral and renewable energy source,
offering substantial advantages for environmental protection and much shorter C02-
circuits compared to fossil fuels. Therefore, biomass has a considerable potential for
future energy supply and to dramatically improve our environment, economy and energy
security. In view of its remarkable contribution to the reduction of CO2 emission, the
development of innovative utilization technologies of biomass has become increasingly
important (Kobayashi et al., 2008; Florin and Harris, 2008).
Biofuels are expected to become increasingly important in the future to reduce CO2-
emissions, improve local emissions, and obtain security of supply. Much research and
developemnt efforts worldwide focus on ways to produce so-called second generation
biofuels, that are characterised by excellent environmental performance as weIl as high
biomass feedstock flexibility. Making syngas (composed primarily of carbon monoxide
and hydrogen) from biomass is a crucial step in the production of most second gener'ation
biofuels (van der Drift and Boerrigter, 2006). The convention al way to convert biomass
for energy production is direct combustion: Biomass can be combusted in grate firing
systems, in fluidised bed combustion chambers, or even in pulverised co-combustion
systems. However, the direct combustion of biomass raises certain issues su ch as high
temperature chlorine corrosion, low-melting temperature of biomass ash (especially of
straw) and the agglomeration in fluidised bed combustion chambers (Karallas et al.,
2008). The gasification of biomass is generally considered to be one of the most
4
promising technologies to convert biomass into useful products. The gasification process
can convert the carbonaceous materials into synthesis gas, and typical raw materials used
in gasification include biomass, coal, petroleum-based materials (crude oil, petroleum
coke, and other refinery residuals) and municipal solid waste (MSW).
Energy source Syngas production Conversion technology. Products :a .. ~ .. :t ......... ~ ••• ~ la ... a".1l4 ~ . ....... .. " ..... ~ ... .. .. ;,. ... .... :0 ....... " ." . ........... Of .. ., .. " ".A .. .......... .... .. ... .. .... .... :0 .......... : . . . .
:'t :f( $ .~ * .* .t 'il '"t ;~ ~ ~ ;J :+ ~ 'K: .t; .x ,." :~ .x. .x .;.; ". ~ .~ .x '* .. ~ .;.. .:.1 "<$ ":0; » ~ .li! 6: • :~ Je '* ~ :V • ..;r
~
Figure 2. 1 Paths for the conversion of raw materials to final products (via syngas producti on step) .
The syngas from biomass can be further upgraded into methanol, dimethylether,
Fischer-Tropsch liquid fuels or other chemical products, as shown in Figure 2.1. The
advantage of gasification is that using the syngas is more efficient than direct combustion
of the original fuel and more of the energy contained in the fuel is extracted.
Due to the thermodynamic and kinetic limitations, endothermic reactions like
gasification of solid carbonaceous materials have to be carried out at high temperatures,
which asks for an efficient heat suppl y and heat recovery. Multifunctional reactor concept
offers an attractive solution for implementing high-temperature reactions by coupling
5
strong endothermic reaction with exothermic reaction, which has been a subject of vital
research and development (Agar, 1999; Kolios et al., 2000; Kolios et al., 2002;
Ramaswamy et al. ,2006). Gasification technologies are divided into autothenhal and
allothermal ones. In the autothermal gasification, the partial combustion of biomass
provides the required heat for the gasification. In the allothermal gasification process, the
necessary heat is usually provided from an external source (Karallas et al.,2008). The key
challenge of the allothermal gasification is the need to transfer the heat-of-reaction for the
endothermic gasification reactions from an external heat source into the gasifier.
In this chapter, we will first propose an innovative biomass gasification process
concept in which the allothermal coupling of gasification/combustion processes with
high-temperature phase change material will be implemented in a monolithic . structured
reactor and intensified by periodic operation mode. Then, the literature work on the
relevant aspects is reviewed, which includes biomass gasification, monolithic reactor,
high-temperature phase change material, and fluidized bed reactor. Finally, a concluding
remark is made.
2.2 Hybridization of GasificationlCombustion Processes: A Novel Process Concept
Steam gasification of solid carbonaceous fuels is highly endothermic, which demands
the input of additional heat source to drive the reactor system. This is a challenge because
the input of energy reduces the maximum efficiency of the process. A further challenge is
the provision of the addition al heat without compromising the quality of the products
(Frolin et al., 2008). Methods to meet this energy shortfall involye: (i) the combustion of
a fraction of the biomass fuel or unconverted biomass residue to generate heat; (ii) the
use of a fraction of the combustible product gases to generate energy (Lutz et al., 2003).
In conventional gasifiers, the energy required for heating the reactants and for the heat of
reaction is supplied by burning a significant portion of the feedstock, either directly by
internaI combustion or indirectly by external combustion. InternaI combustion, as applied
in autothermal reactors, results in the contamination of the gaseous products, while
external combustion, as applied in allothermal reactors, results in lower thermal
efficiency because of the irreversibilities associated with indirect heat transfer.
6
For practical implementation of the gasification in converting solid carbonaceous
materials (like biomass), there are a number of potential problems which could be
encountered in view of the energy management and product control (Levenspiel, 2005):
(i) If biomass is reacted with both air and steam in one reactor, then nitrogen is present in
the product stream and is costly to remove; (ii) If trying to avoid this problem by using
oxygen instead of air, then a source of pure oxygen would be needed, again costly; (iii) It
is possible to avoid the nitrogen separation problem by running the two reactions in
different locations, but then transferring heat from one location to the other will be a
problem; (iv) AIso, in aIl of these schemes, if the product gas is rapidly cooled, then tar
forms, and this is also costly to remove. To avoid this, the product gases must be kept hot
for a while to let the tars crack into lower molecular weight compounds.
In a recent paper, Levenspiel (2005) has suggested coal as a replacement for
petroleum; and three distinct coal-to-syngas routes are identified for producing syngas
CO +H! +waste
a ir+steam +coal
Route 1
COfIlbusto.f
(sfmuftaneou.sJy coupfed)
waste steam +coaJ
Route 2
gasifier
(spatia Hy.segŒga ted)
waste
a ir +coal
Route 3
tife ~
steanl +coal
CO+Hz
{chronofogi caUy s e·gœg:a ted)
~-----------------v? ----------------~
Figure 2.2 Three routes to syngas
7
from the solid carbonaceous fuel (coal), which are schematically illustrated in Figure 2.2.
ln route l , both gasification and combustion reactions are gasification and combustion
reactions are simultaneously coupled in one reactor, and then separate the wanted from
the unwanted products. The co st of the units needed to separate the waste gases,
especially nitrogen, from syngas is high. In route II, the gasification and combustion
reactions are spatially segregated using two different reactors which require the transfer
heat from one to the other. In route III, the gasification and combustion reactions taking
place in one single reactor are chronologically segregated and the whole process
operation is of cyclic nature. In a combustion step, only air (not oxygen) is used. Hence,
there is no need for nitrogen removal either before or after the gasification step. In
addition, there is no . need for an oxygen separation plant. Furthermore, because fresh
syngas has to pass through the hot bed, tar formed at the heat front will hopefully be
destroyed. However, up to now the giant corporations aIl takes the same route l , leaving
the other alternative routes (route II and route III) untouched. In his paper, the author
(Levenspiel, .2005) highlighted the necessity and importance of exploring these two
alternatives. However, there is no mention of biomass materials in this paper. As a very
promising and competitive option, the importance of syngas production from biomass
through gasification has been widely recognized by scientific community (Wang et al. ,
2008; Panigrapi et al., 2003). Therefore, it is of great importance to initialize the research
efforts to address these aforementioned alternative routes which are equally interesting
and important in the framework of biomass utilization and thermochemical conversion.
ln the present work, a novel process concept is proposed for syngas production
through biomass gasification, which involves the allothermal coupling of the biomass
gasification and combustion processes in monolith structured reactors. The principle of
the allothermal process concept is schematically illustrated in Figure 2.4. In this novel
process, the monolithic micro-circulating fluidized bed will be used as the reactor unit for
gasification-combustion of biomass. The exothermic combustion step and endothermic
gasification step will be undertaken in one single monolithic reactor. The process
intensification by periodic operation mode is used to chronologically segregate the
gasification/combustion step. The wall of the monolithic reactor is constru·cted by
8
Figure 2.3 Proposed novel process concept
intemally encapsulating high-temperature phase-change-material, for example, LiF-CaF2
(Pletka et al., 2001 a,b) which serves for heat storage and heat release in cyclic operation.
The di lute mixture of biomass (solid) and air/steam (fluid) flows in the monolithic reactor
in pneumatic conveying fluidization mode. The gasification conversion of biomass is
undertaken, using steam as the gasifying agent, the resulting product gas is rich in H2.
The use of steam, instead of air or CO2, leads to higher H2 yields due to the additional H2
produced from the decomposition of H20. In addition, compared with partial oxidation
using substoichiometric air, the product gas has a higher heating value and the dilution
with N2 is avoided (Franco et al., 2003~ Frolin et al., 2008). The proposaI of this new
process is supported by the recent advances in: (1) the development of micro-fluidized
bed concept for biomass conversion (Potic et al., 2005)~ (2) the development of high
temperature PCM and its application in biomass gasification (Pletka et al., 200Ia,b)~ and
9
(3) the pioneering experimental investigation in flow hydrodynamics of gas-solid two
phase mixture in monolith (Ding et al., 2005, 2006).
B Y checking our proposed process concept with the aforementioned three routes
highlighted by Levenspiel (2005), it can be regarded that our present effort is an attempt
to address one of the two important alternatives (i.e., route III). In this proposed process,
the coal-to-syngas route is adapted for the biomass-to-syngas route. And the
implementation of route III for syngas production is conducted through the
chronologically-segregated hybridization of gasification/combustion processes in one
single monolithic structured reactor. The main feature of the novel process is that the
gasification and combustion of biomass are chronologically isolated from each other, and
so are their gas streams. In this way, the product gas from gasification step is not diluted
by the flue gas from combustion step. Furthermore, since there is no concern about
dilution of the product gas by the flue gas, ait can be used as an oxidizing agent for the
biomass combustion, instead of costly pure oxygen.
U nderstanding and modeling complex flow hydrodynamics and thermochemical
conversion behavior is very essential for effectively design and operate the suggested
novel gasification-combustion coupling process. The knowledge from the different
important fields (including biomass gasification, monolithic reactor, high-temperature
phase change material, and fluidized bed reactor) is required for this purpose.
Furthermore, the mathematical descriptions of these important aspects should be
integrated together to realize a comprehensive capture of the fluidization hydrodynamics
and reaction behavior. To this end, the literature review will be conducted in the
following sections with a view to gaining a systematical understanding of the states-of
the-arts in these relevant aspects.
10
2.3 Physicochemical Processes in Biomass Gasification and Modelling
2.3.1 Physicochemical processes in biomass gasification
Gasification is a thermochemical conversion of solid carbonaceous materials by
means of free or bound oxygen at elevated temperatures. This technology has been
primarily used for coal gasification, but more recently it has been used for biomass and
1.3
1.6
1,4
o
Anthracite
02 0,4
• \Vood .. U gnin
- • Cellulose
Figure 2.4 Van Krevelen diagram for various solid fuels (Prins et al.,2007)
cellulose-rich wastes which have different C-H-O compositions from coal (see Figure
2.4). Several chemical aspects of the gasification of solid carbonaceous materials are
summarized in the literature (Schlosberg, 1 985; Vorres, 1999; Furimsky, 1999).
Biomass gasification generally refers to the thermochemical conversion of solid
biomass fuels using a gasifying agent (e.g. steam, substoichiometric air, or CO2) to a
mixture of combustible product gases (including H2, CH4, CO and CO2) along with
heavy hydrocarbons with low dew points known as tar (Frolin et aL, . 2008). In the
gasification processes, the fuel conversion takes place by various mechanisms, that is,
drying, primary pyrolysis, secondary tar cracking, gasification, and combustion. During
drying, fuel moisture evaporates followed by pyrolysis, which is the thermal
Il
decomposition of the solid fuel that forms gases, tar, and solid char residues (Figure 2.5).
In addition to pyrolysis, thermal cracking of tar occurs. Gasification comprises a complex
Biomass fùe} L pyrolysis
il . ~c.rac~ng & volatiles ~ fct onmng
tar
char
product gas:
1I2• CH4• CO. CO2·, Ci H4'
C1H6·
Figure 2.5 General reaction mechanism for the gasification of a biomass fuel (Higman and van der Burgt,2003)
set of heterogeneous reactions between CO2, H20, and the solid char. Table 2.1 gives the
possible heterogeneous and homogeneous reaction involved in the gasification of
biomass (Radmanesh et al.,2006; Wurzenberger et al., 2002; Di Blasi, 2004). And sorne
important experimental investigations of biomass gasification using fluidized bed are
summarized in Table 2.2.
Table 2.] List of heterogeneous and homogeneous reactions involved in biomass gasification
No. ChemicaJ reaction
Rl
R2
R3
R4
RS
R6
R7
R8
R9
Heterogeneous reactions
Homongeneous reactions
Tar cracking reaction
Tar combustion
12
Table 2.2 Summary of important investigations of the gasification of biomass in fluidized beds
Investigator Solid fuel Gasifying agent Pressure(kPa) Temperature(OC)
Walawender et al. (1985) CelJulose H20 101.325 592-787
Boateng et al . (1992) Rice hulls H20 111.457 700-800
Corella et al. (1991) Chips, straw H20 111.457 650-850
Herguido et al. (1992) Pine sawdust 90% H20 101.325 650-780
Tum et al. (1998) Sawdust Air and H20 101.325 750-950
Gil et al. (1999) Pine wood chips Air, Air+H20 , H20 101.325 750-830
Franco et a1. (2003) Pine and eucalyptus H20 101.325 735-900
Cao et al. (2006) Wood sawdust Air 101.325 730-890
Radmanesh et al. (2006) Beech wood particles Air, H20 101.325 800-815
Ross et al. (2007) Eucalyptus and wood pellet Air + H20 106.300 800-840
Lim et al. (2008) Wood chip Air 101.325 718-733
Campoy et al. (2008) Wood pellets Air, Air+ H20 101.325 730-815
Gasification differs from combustion in several ways. When oxygen is limited in the
gasification reaction, combustible products like hydrogen, carbon monoxide, and
methane are produced. As a result, the carbonaceous feedstock is converted to a low- or
medium-value synfuel gas, which is rich in carbon monoxide, methane, and hydrogen. If
sufficient oxygen is provided, as it is in combustion, the products fully oxidize to water
vapor and carbon dioxide. While combustion is useful for providing immediate heat, the
produced gases have liule chemical energy remaining.
As a complex thermochemical conversion process, the biomass gasification process
is quite similar to that of coal gasification, yielding in both cases a mixture of gases \vith
the same principal components (Zuberbuhler et al., 2005). However, the distribution of
the resulting gases is different for biomass and coal, and the reaction conditions for
biomass are milder than for coal gasification, due to the higher reactivity of biomass
(Klass, 1998). As in the case of coal gasification, biomass gasification under elevated
pressure conditions favors the production of methane and carbon dioxide, whereas
increasing the temperature tends to increase the concentration of hydrogen and carbon
monoxide. Steam is. often used as the gasification agent for syngas production. Blended
with oxygen or air, it promotes the formation of H2 and CO. Undesirable by-products and
emissions encountered in the product gas, such as tar, are the main complications for its
13
use in the downstrearn synthesis or electricity production (Klass, 1998; Zuberbuhler et al. ,
2005).
Tar derived frorn biornass gasification or pyrolysis is condensible compound and
causes sorne troubles in downstream equipment such as blocking and fouling of fuel
lines, filters , engines and turbines. It was reported that tar content in the syngas from an
air-blown circulating fluidized bed (CFB) biomass gasifier was about 10 g/m3. For other
types of gasifier, tar content varied from about 0.5 to 100 g/m3 (Asadullah et al. , 2003;
Lopamudra et al. , 2003; Paasen, 2004). However, most applications of product gases
require a Iow tar content of the order 0.05 g/m3 or Iess. Hence, tar disposaI becomes one
of the most necessary and urgent problems during biomass gasification (Lopamudraet al. ,
2003, Han and Kim, 2008).
2.3.2 Modeling of biomass gasification process
Research on biornass pyrolysis, gasification and combustion processes has attracted
growing attention during recent years due to the increasing use of renewable biomass
energy. As important aspects, the optimization of thermal efficiency and the reduction of
furnace emissions iequire accurate understanding of the physical and chemical effects in
the reactor which are highly complex in nature. Mathematical modeling which allows
quantitative representation of various phenomena is a powerful tool for process design,
prediction of gasification performances, understanding of evolution of pollutants,
analysis of process transients, and examination of strategies for effectivecontrol (Di
Blasi, 2004). Although a lot of studies on the modeling of coal gasification can be found
in the literature, modeling biornass gasification has not been amply addressed and only a
very limited number of numerical models have been proposed for biomass gasification.
Recently, several significant modeling efforts have been devoted to the simulation of
biomass gasification in which much more comprehensive descriptions of related complex
chemical and physical processes have been taken intQ account (see Table 2.3).
Wurzenberger et al. (2002) developed a comprehensive transient model for packed
bed biomass gasifier, which consists of a combined transient single particle and fuel-bed
14
model. Drying was modeled using an equilibrium approach, and primary pyrolysis was
described by independent parallel-reactions. Secondary tar cracking, homogeneous gas
reactions, and heterogeneous char reactions were modeled using kinetic data from
literature. First, simulations of single particles, decoupled from the packed bed model,
were performed. These simulations were compared with experimental investigations and
showed the validity of the chosen overall approach for drying, pyrolysis, gasification, and
combustion. Second, operation conditions of a moving bed combustor were chosen and
the combined packed-bed and single-particle model were used to predict the overall
behavior of this system.
Di Blasi (2004) formulated a . one-dimensional, unsteady mathematical model to
simulate countercurrent fixed-bed wood gasifiers, which coupled heat and mass transport
with wood drying and devolatilization, char gasification, and combustion of both char
and gas-phase species. The main processes modeled included: (1) moisture
evaporation/condensation; (2) finite-rate kinetics of wood devolatilization and tar
degradation; (3) heterogeneous gasification (steam, carbon dioxide, and hydrogen) and
combustion of char; (4) combustion of volatile species; (5) finite-rate gas-phase water
gas shift; (6) extraparticle mass transfer resistances, through the introduction of apparent
rates for the heterogeneous reactions according to the unreacted core model; (7) heat and
mass transfer across the bed resulting from macroscopic (convection) and molecular
(diffusion and conduction) exchanges; (8) absence of thermal equilibrium (different solid
and gas temperatures); (9) solid- and gas-phase heat transfer with the reactor walls; (10)
radiative heat transfer through the porous bed; and (11) variable solid and gas flow rates.
The model ~as used to simulate the structure of the reaction fronts and the gasification
behavior of a laboratory-scale plant as the reactor throughput and. the air-to-wood (or
char) weight ratio were varied. Predictions showed the existence of four main regions
along the gasifier axis. In the first, gasification and combustion overlapped, the second
was essentially the inert heating of a descending bed of char particles, and the last two
were associated with wood devolatilization and drying, respectively. This structure of the
reaction fronts was qualitatively similar to that reported for coal gasification.
15
Yang et al. (2006) developed a CFD-based model for simulating substoichiometric
conversions of municipal solid wastes and as weIl as biomass fuel in packed-bed and
moving-bed gasifier. The governing equations for mass, momentum and heat transfer for
both solid and gaseous phases in a moving bed in a solid-waste incineration fumace were
described and relevant sub-models were presented. Radiation heat transfer in the bed was
simulated by a two-flux model. Mathematical simulation showed that countercurrent,
substoichiometric conversion of both municipal solid wastes and biomass in moving
grate' systems was possible without loss in throughput or conversion efficiency. Char
conversion rate was significantly lower than the devolatilization rate and the char
conversion process occupies 1/2 of the total bed length, whereas fuel devolatilization
occuped only around 1/3 of the bed length. The averaged devolatilization rate of biomass
was twice as high as that for municipal solid wastes as a result of less moisture and ash
contents. Biomass fuel also required a shorter distance to be ignited.
Radmanesh et al. (2006) recently developed a one-dimensional transient model for
biomass gasification in a bubbling fluidized bed reactor. The model took into account the
pyrolysis and various heterogeneous and homogeneous reaction kinetics as weIl as the
hydrodynamics of the bed and freeboard. A two-phase model w'as used to de scribe the
gas phase in the bed, whereas a countercurrent back-mixing model was applied for the
char mixing in the bed. It was shown that pyrolysis is an important step in the overall
gasification model that can determine the distribution of products and thus the heating
value of product fuel gas. The model also showed good agreement with experiments on
steam gasification of wood, wheieby concentrations of H2, and CO2 rise and that of CO
drops.
Table 2.3 Summary of recent important attempts at reactor modeling of biomass gasificati on
Investigators Fuel characteri sti cs Reactor type Remarks ---------------------------------' ----,
Wurzenberger et al. (2002) wood Moving bed 1 D + transient model
+ detaiJed single-particJe model
Di Blasi (2004) wood Counter-current fixed-bed ID + transient model
+ shrinking core particJe model
Yang et al. (2006) Biomass and solid wastes Fixed-bed and rnoving bed 20 + transient model (CFD mode!)
+ two-f1u x radi ation
Radmanesh et al. (2006) beech wood particJes Bubbling f1uidi zed bed 10+ transient model
16
2.4 Monolithic Structured Reactor and Modelling Methodology
2.4.1 Monolithic structured reactors
Structured reactors/supports are increasingly considered for use ln multi-phase
processes, because of the potential imp~ovements they offer with respect to the
decoupling of heat and mass transfer phenomena, operation under reduced pressure drop
conditions and at high gas/solid flow rates, and a greater resistance to attrition. One might
also expect that the uniformity of channel structure may give improved homogeneity in
performance compared to that of a fixed bed of traditional catalyst packing material,
which is· inherently associated with significant flow heterogeneity.
Monoliths, which contain catalysts with certain structures or arrangements, belong to
the new family of the so-called structured catalysts and/or reactors (the border between
'catalyst' and 'reactor' vanishes in these reaction systems) (Tomasic, 2007). Usually
monolith reactors refer to those containing catalysts with parallel straight channels inside
the catalyst block (see Figure 2.6). The straight channels normally have circular, square
or triangular cross-sections. A monolith structure is sometimes referred to as a
(a) monolithic reactor /channel wal1 / washcoat with catalyst
17
SOLID PHASE .~~~!!~~~ Hète~rQgEmeôus
GAS PHASE
CenterHneof the m·ooQlith Qh~nne~
(b) transport/reaction phenomena in a monolith channel.
Figure 2.6 Schematic representation of the monolith reactor (Tomasic , 2007).
honeycomb structure, although in the technical context monolith has a much broader
meaning, generally referred to as the large uniform block of a single building material.
Monolith catalysts or monolith reactors have sorne cornmon features in most of their
applications. These features or characteristics include (Chen et al, 2008): (i) low pressure
drop especially under high fluid throughputs; (ii) elimination of external mass transfer
and internaI diffusion limitations; (iii) low axial dispersion and backmixing, and therefore
high product selectivity; (iv) larger external surface; (v) uniform distribution of ftow (gas
phase); (vi) elimination of fouling and plugging, and thus extended catalyst lifetirne; (vii)
easy scale-up. In view of their salient characteristics, monolithic catalysts and/or reactors
appear to be one of the most significant and promising developments in the field of
heterogeneous catalysis and chemical engineering of recent years. The use of monoliths
in solid-catalyzed gas phase (single phase) chemical reactions is weIl established.
In the last years, monoliths as multiphase reactors have receiveêl more and more
attention (Roy et al, 2004a; Roy et al, 2004b; Irandoust & Andersson, 1988a). For
example, monoliths can be used both for co-current and counter-CUITent operation in gas
liquid reaction systems. They can combine the advantages of the slurry and trickle-bed
reactor and eliminate the disadvantages such as discontinuous operation, stirring energy
input, and catalyst attrition or ineffective catalyst use, liquid maldistribution, and local
hotspots that may develop and cause runaways (Roy et al, 2004b, Charpentier, 2007).
18
However, the majority of the multiphase applications of monolith reactors have been
mainly limited to the gas-liquid (or gas-liquid-solid) flow contact based reaction systems.
The application of monoliths to gas-solid two-phase flow and reactions is not weIl
advanced. Up to now, literature research on hydrodynamic studies for gas-solid two
phase flow in monolith (particularly of the gas-solid flow distribution) is very scarce.
Only very recently, the pioneering experimental work on gas-solid two-phase mixtures
through multichannel monolithic geometry has been reported for the first time by a
research group of University of Leeds (Ding et al., 2005, 2006).
Ding et al. (2005) carried out the study on the macroscopic behavior of a gas-solid
two-phase mixture flowing through monolith channels. The work showed that for pure
gas 'flows, the laminar-to-turbulent transition in monolith channels occurred at a Reynolds
number of about 620, much lower than the conventional transition criterion of 2200 for
large pipes. For gas-solid two-phase flows, the pressure drop was shown to be
significantly lower than that thr~ugh packed particle beds with even a lower specifie
surface area. It was also shown that the measured pressure drop was considerably lower
than the semi-theories developed for pneumatic conveying.
In a subsequent paper, Ding et al. (2006) employed the non-intrusive positron
emission particle tracking (PEPT) technique to investigate three-dimensional solids
motion and microscopie behavior of suspended particles. Processing of the PEPT data
gave solids velocity and occupancy in the monolith. channel. The results showed a non
uniform radial distribution of both the solids velocity and concentration. The highest
solids concentration took place at a position approximately 0.7 times the column radius.
2.4.2 Modeling of monolithic structured reactors
Mathematical modeling of monolithic catalysis has been an area attracting significant
interest. The performance of the monolith reactor is a complex function .. of design
parameters (channel geometry, length and diameter of the channel, channel wall
thickness), operating conditions (temperature, velocity) and the properties of both the
catalyst (active species loading, washcoat loading, etc.) and the re.action mixture
19
(Tomasic, 2007). ) In addition, complexities arise from continuously changing inlet
conditions that require a transient description of the monolith reactor. Therefore,
modeling and simulation of monolith reactors can help to understand the complexity of
interactions between various physical and· chemical processes that occur within the
channels and in the channel walls (Tomasic, 2007; Chen et al.,2008).
Till now, a great number of mathema"tÏcal models have been proposed to conduct
various modeling and simulation for monolith reactors. However, the majority of
modeling and simulation r~search has been focused on gas phase monolith reactors or
catalytic converters (Chen et al., 2008). In literature, there is also several modeling
research addressing on multiphase monolith reactors, which are mostly limited to gas
liquid flow/reaction systems (Irandoust & Andersson, 1988b; Edvinsson & Cybulski,
1994; Stankiewicz et al., 2001, Roy et al., 2004a; Bauer et al., 2005). For modeling work
on gas-solid two-phase mixture in monolith, there is no single report available in the open
literature. Compared to the two-phase flow, the single~phase flow corresponds to a two
phase flow with zero solids holdup. From this standpoint, the knowledge from the
modeling of single-phase flow behavior in gas-phase mORolith reactors could be to sorne
extent helpful in understanding the two-phasè flow in monolith blocks. Therefore, in the
following of this section, the modeling research on single-phase flow in monolith will be
addressed.
The models of monolithic reactors have been developed at di fferent levels of
complexity. These models can be classified as one-, two-, or three-dimensional models,
or classified as washcoat level , single-channel model, or multichannel model (Chen et al.,
2008). The choice of complexity of the model is a tradeoff between specific modeling
objectives and computational resource limitations.
As the indi vidual channels within a monolith are separatecÎ from each other in terms
of mass transfer, modeling of a single channel can often provide a wealth of information
pertaining to the chemical behavior of the catalyst. In particular, it helps to identify and
understand the rate limiting processes and the interplay between transport and
heterogeneous surface reactions (Mazumder & Sengupta, 2002). Up to now, single
channel modeling is the most extensively applied to describe the behaviors of a monolith
20
reactor, and much work has been done with the single-channel model (Deutschmann et
al., 1999,2000; Tischer et al., 2001; Zerkle et al., 2000; Raja et al., 2000; Hayes et al. ,
1996; Wilber & Boehman, 1999; Boehman &Dibble, 2000; Canu & Vecchi, 2002;
Kumar & Mazumder, 2008). At this scale of modeling, it is assumed that every channel
in the monolith reactor behaves exactly the same and can represent the entire reactor.
However, under certain circumstances, modeling-a single monolith channel might be
inadequate. Such circumstances include non-uniform inlet gas distribution, blocked or
deactivated channels, -etc. (James et al., 2003; Chen et al. , 2008). In this case, all of the
channels which interact with each other, because of the strong coupling of the individual
channels through heat transfer and the inherent nonuniformities in flow distril)ution
within monolith reactors. To address the differences in flow and temperature in different
channels, multi-channel model has _ to be chosen by accounting for a number of
representative channels, or ev en the whole monolith block (Chen et al. , 2008; James et al.,
2003). Although full-scale model provides more details and gives highest accuracy, it
demands expensive computing facilities (Mazumder, 2007). As alternative modeling
methodology, the equivalent continuum approach (Zygourakis and Aris, 1982; Chen et
al., 1988; Zygourakis,1989) appears to be one of the most attractive solutions for
simplifying the modeling of monolithic reactors.
In recent years, computational fluid dynamics (CFD) has been introduced to model
monolith reactors and has shown to be of significant importance in design and
optimization of monolith reactors. However, much work has been done with the single
channel CFD model. As opposed to the single-phase modeling abundantly available in
literature, the studies on CFD modeling of whole monolith reactor are very limited in the
published literature (Holmgren et al., 1997; Jeong and Kim, 1997,1998,2000; Shuai et
al. , 2000; Chakravarthy et al., 2003; Liu et al , 2007; Mazumder & Sengupta, 2002;
Mazumder, 2007).
Chakravarthy et al. (2003) used a multi-channel model to study the impact of flow
non-uniformity during cold-start transient operations of a catalytic converter. It was seen
that inlet zone recirculation can lead to significant non-uniformity of the flow in the
monolith , and this non-uniformity can lead to significant differences in ignition
21
characteristics among the channels. These ignition differences were especially
pronounced at lower exhaust temperatures, where the axial location of ignition can vary
from one channel to another.
Liu et al. (2007) modeled a reverse flow catalytic converter used for a lean bum
natural gas engine using a 3D model to study methane ignition. A dual zone approach
was used for the heterogeneous model, where double ceIIs , or nodes are used to
distinguish between fluid and solid temperatures. It is demonstrated that methane ignition
can be achieved at a lower inlet gas temperature under conditions of reverse flow,
compared to uni-direction al flow. The selection of flow mode must be selected depending
on the inlet condition.
Mazumder (2007) discussed and demonstrated two approaches that make simulation
of full-scale catalytic converters with complex chemistry feasible. The proposed two
different approaches were subgrid scale modeling and in situ adaptive tabulation. The
first approach was one where only the larger sc ales were resolved by a grid, while the
physics at the smallest scale (channel scale) were modeled using subgrid scale models
whose development entailed detailed flux balances at the imaginary fluid-solid interfaces
within each computational celI. The second approach made use of the in situ adaptive
tabulation algorithm, after significant reformulation of the underlying mathematics, to
accelerate computation of the surface reaction boundary conditions. Preliminary results
shown for a catalytic combustion application indicated that both methods had the
potential of improving computational efficiency by several orders of magnitude.
It is important to note that for gas-solid two-phase flow/reactions through monolith 1
structured reactors, the modeling research work has not appeared in the open literature so
far. However, the modeling methodologies and ideas which have been applied in single
phase monolith reactors could be borrowed to a . great extent and imparted into the
modeling of gas-solid two-phase flow/reactions in monolithic reactors.
22
2.5 High-Temperature Phase-Change Material and Modelling Approaches
2.5.1 High-temp~rature phase-change material
Thermal Energy Storage (TES) has received increasing attention over the last years.
A widely used class of en erg y storage media is the so-called Phase Change Materials
(PCMs). These media, characterized by a high value of latent heat per unit mass, seem to
offer the better performance in thermal energy storage, due to their capability of
absorbing/releasing high rates of energy as weIl as its relatively constant storage
temperature. The phase changes of material are caused by the heat transfer to and from
both of the phases on either side of the interface. This yields melting if the net heat is
added to the solid part of the interface and solidification when the net heat is subtracted. /
The observed addition al heat, which is involved in the conversion of one phase to
another, is the latent heat; and the entire heat transport problem is usually referred to as
the Stefan problem.
Latent heat thermal storage using PCMs have been used in many applications as, for
instance, in thermal control systems to reduce the temperature oscillations, or in space
application for power production using closed Bray ton cycle. In addition, thermal energy
storage using PCMs is seen to be one of the effective ways for solar energy utilization
(Hall et al., 1997), due to the following advantages: (i) the PCMs have high latent heat
storage capacity (ii) the PCMs melt and solidify at a nearly constant temperature (3) a
small volume is required for a latent heat storage system, thereby the heat los ses from the
system maintains in a reasonable level during the charging and discharging of heat.
Moreover, the application of PCMs for recovering high-temperature waste heat have
attracted much interest in recent yearS (Maruoka & Akiyama,2006).
Recently, the development of high-temperature phase change material has become a
very interesting topic (Maruoka et al.,2002; Maruoka & Akiyama,2006). Table 2.4 gives
the various properties of the PCM for the high temperature applications (Maruoka et
al.,2002).
23
Table 2.4 Candidates of PCM for hjgh temperature application (Maruoka et a1. ,2002)
Malarial Comp. [mol%) T",,,, [t<] D.H [kJ / mol M [g/mol] D.H [KJ / kg ] Density [kg! m ") bH (kJ/ mJ J Price~ [~/kil [ kJ/ lJ] k [ W/ m· k)
Ag - 1235 11.3 108.0 104.6 10500 I .099E+06 22.600 0.005 377
NaF - 1269 - 42.0 796.0 2780 2.21 3E+06 40,000 0.020 -
MgF2- NaF 64- 36 1273 - 55.0 794.0 3017 2.395E+06 15,000 0.053 -KF-MgF2 31-69 1281 _. 6LO 71 0.0 2943 2.089E-t06 20,000 0.036 -
Au - 1337 12.7 197.0 64.5 19300 1.244E+06 10,000.000 0.000 272
Sm - 1345 8.6 150.0 57.5 7700 4.430E-tOS 2,500.000 0.000 -
No2O - 1405 - 62.0 770,0 2390 L840E+06 - - -MgFz- MgO 91.5- 8.5 1502 - 60A 922.0 3187 2.938E+06 12,000 0.077 -
Mn - 15 17 14.6 55.0 265.5 7420 1.970E -I-06 170 1.561 8 MgF~ - 1536 - 62.3 942.0 3150 2.967E+06 11 ,200 0.084 -
Gd - 1535 10.1 157.0 64.0 7870 5.038E+05 2.500.000 0.000 -Si - 1685 39.6 28.0 1414.3 2340 3.309E+Q6 6.000 0.236 148 Co - 1767 17.2 59.0 291.5 8800 2.565E+06 6900 0.042 99
With its high storage density and small temperature variation from storage to
retrieval, latent-heat thermal storage using high-temperature PCMs has been applied in
gasification of biomass (Pletka et al., 200Ia,b; Cummer & Brown, 2005). In the process,
heat released during combustion is stored as latent heat in phase change material sealed in
tubes immersed in the reactor. This heat is released during the pyrolysis stage of the
cycle .. The phase change material may be an inorganic salt or metal alloy. The reactor
employs a fluidized bed to obtain uniform and rapid distribution of heat from the phase
change material to the pyrolyzing fuel. It was demonstrated through the experimental
results that the indirectly heated gasification of biomass is feasible to produce medium
enthalpy producer gas (Pletka et al., 200Ia,b).
2.5.2 Modeling of solidification and melting processes in phase-change-material
In a latent heat storage system, energy is stored during melting and recovered during
solidification of the PCMs. Prediction of such altemating melting-solidification heat
transfer processes is the key to optimal design of the energy storage system. However,
theoretical analysis of problems involving melting or solidification is not an easy task. In
fact, during the solid-liquid phase change, the interface between the two phases moves
through the medium and its position is priori not known. The fact introduces a non
linearity into the mathematical model which is very difficult to deal with, especially in
24
two- or three-dimensional problems. Moreover, many other factors such as variation of
material properties and/or boundary conditions variable with arbitrary laws, increase the
complexity of the problem (Pinelli & Piva, 2003).
In the literature significant efforts have been devoted toward the development of
mathematical models and numerical algorithms to study the transport phenomena
occurring during the solidification/melting processes. Mathematically, the problem of
solid-liquid change belongs to the class of the so-called 'moving boundary problems',
due to the existence of moving phase-change boundary. Such problems are nonlinear and
analytical solutions of the phase change problem are difficult to obtain except for a mere
handful of physical situations with simple geometries and boundary conditions. Therefore,
in most cases, the numerical methods have been resorted for the solution of phase-change
problems. Basically, two different approaches have been used for numerical simulation of
the phase change processes: (i) front-tracking formulation, and (ii) fixed-domain
formulation. In the front-tracking approach, the position of the solid-liquid interface
needs to be continuously tracked. The variable grid method (variable space grid and
variable time step) provides the way to track the phase front explicitly. This approach
works efficiently for pure substances. However, serious complications are encountered
for solidification /melting problems involving multi-component systems, due mainly to
topologically complicated diffusion interfaces characterizing the phase-transition
morphology. In addition, this approach is poorly suited to multi-dimensional problems,
due to the difficulties with algorithms of implementation and the penalty in
computational cost.
As an alternative, the fixed-domain formulation emerged as a more convenient
strategy (VoIler & Swaminathan, 1990). With this approach, the need for explicit
tracking of the solidificationlmelting fronts is eliminated and the entire computational
dOll)ain is modeled with a single set of volume-averaged continuum conservation
equations. One popular method akin to this approach is the enthalpy method, in which
enthalpy is treated as ind~pendent variable. A fixed-grid is applied to the physical space
and latent heat is accounted fro by using suitable source ' terms in the energy equation.
25
Table 2.5 Comparisons of numerical schemes for modeling phase change phenomena
Investigators Grid Method Time-stepping Primary variable
Murray & Landis (1959) Front track Finite difference Two-step Temperature
Morgan et al. (1979) Fixed grid Finite element Two-step Apparent h
Lemmon ' (1979) Front track Finite difference Explicit Basic H
Rubisky & CravahJo (1981) Front track Finite element Explicit Fictitious h
Voiler & Cross (1981) Front track Finite difference Explicit Basic H
Rolph & Bathe (1982) Fixed grid Finite element ,Implicit Fictitious h
Voiler & Cross (1983) Front track Finite difference ExplicitJImplicit Basic H
Roose & Storrer (1984) Fixed grid Finite element Explicit Fictitious h
Pham (1986) Fixed grid Finite element Two-step Basic H
Crivelli & Idel sohn (1986) Fixed grid Finite element Implicit Temperature
Dalhuijsen & Segal (1986) Fixed grid Finite eJement Two-step Apparent h
Weaver & Viskanta (1986) Front track Finite difference Implicit Temperature
Askar (1987) Front track Finite eJement C-N Temperature
Dhatt et al. (1989) Fixed grid Finite element Explicit Basic H
Comini et al. (1990) Fixed grid Finite eJement Two-step Apparent h
Kim & Kaviany (1990) Front track Finite difference Explicit Basic H
Vo]Jer (1990) Fixed grid Finite difference Implicit Apparent h
Tamma & Namburu (1990) Fixed grid Finite element Implicit Apparent h
Celentano et al. (1994) Fixed grid Finite element Implicit Temperature
Esen & Ayhan (1996) Fixed grid Finite volume Implicit Apparent h
Gong & Mujumdar (1997) Fixed grid Finite element three time-IeveJ scheme TeJTlperature
Ha]] et al. (1997) Fixed grid Finite volume Explicit Apparent h
Costa et al. (1998) Fixed grid Finite volume Implicit Apparent h
Cui et al. (2003) , Fixed grid Finite volume Explicit Temperature
Xing et al. (2004) Fixed grid Finite volume Explicit Apparent h
Elgafy-et al. (2004) Fixed grid Finite volume Explicit Temperature
Sharma et al. (2005) Fixed grid Finite difference Implicit Apparent h
Xu et al (2005) Fixed grid Finite difference Implicit Temperature
Trp (2005) Fixed grid Finite volume Implicit Temperature
Halaw et al. (2005) Fixed grid Finite difference lmplicit Apparent h
Frusteri et al. (2006) Fixed grid Finite difference C-N Temperature
Fang & Chen (2007) Fixed grid Finite difference Implicit Apparent h
Chen et al. (2008) Fixed grid Finite difference Implicit Apparent h
This method is particularly suitable for alloys and plastics for which the change of phase
occurs over a finite temperature range. Another method akin to the fixed-domain
approach is the use of coordinate transformation. In the coordinate transformation method,
the moving boundary is immobilized by using suitable transformation, which maps the
physical plane onto the transformed plane. By scaling space and time, it permits
26
simplification of the solution which can be realized in the fixed domain. This method is
particularl y useful for phase change at a fixed temperature, such as that for pure metals.
In Table 2.5, the comparison of various numerical schemes used for modeling phase
change phenomena are detailed. Among them, sorne of the modeling works have been
attempted to address the phase-change phenomena for high-temperature PCMs (Hall et
al., 1997; Gong & Mujumdar, 1997; Cui et al., 2003; Xing et al., 2004; Eigafy et al. ,2004).
2.6 Gas-Solid Fluidization in Micro-Fluidized Bed Reactors and Modeling
Methodology
2.6.1 Monolithic micro-fluidized bed reactors and gas-solid fluidization
Very recently, miniaturization of fluidized beds is receiving increasing interest, due to
that a small-size bed has good operability and availability for sorne particularly required
characteristics. Such microfluidic-based microsystems represent the potential to 'shrink'
convention al bench chemical systems to sm aIl size systems with major advantages in
terms of performance, integration and portability. The concept of micro fluidized beds
(MFBs) was first put forward by Potic et al. (2005) to refer to the beds with inner
diameters of a few millimeters. The numbering-up concept is often regarded as a
technique suited for increasing the throughput of a microreactor system. In this concept,
the throughput is increased by parallelizing many identical microreactors or
microchannels. Numbering-up is sometimes regarded as one of the advantages of
microreactor technology. When the optimal microreactor design and its operating
conditions are found in laboratory experiments, a commercial scale production plant can
be designed in this concept more quickly than in the convention al scaling-up approach,
which requires repetitive performance testing and process modification at several
different throughput levels. In this context, the flow of gas-solid two-phase mixtures
through monolith can be regarded as the consequence from the numbering-up (or scale
out) of a single micro-fluidized reactor. At the same time, the flow behavior in monolith
could be fundamentally similar to that in microchannels, which has emerged as an
important area of research in the past two decades due to their potential applications in
27
micropower generation, microelectro-mechanical systems (MEMS), biomedical use,
biotechnology, and computer chips (Ding et ~l, 2005). Therefore, understanding of the
gas-solid two-phase fIuidization hydrodynamics behavior in a single channel (of
monolith) is of great interest
In fact, gas-solid fIuidized beds are highly complex in fIuidization hydrodynamics
(Kunii and Levenspiel, 1997), as in Figure 2.7. However, due to their favorable mass
and heat transfer characteristics and their continuous particle handling ability, they are
extensively applied in a variety of industries. In view of chemical reaction processes, they
are particularly suitable for highly exothennic and temperature-sensitive reactions , since
the particle motion gives them a unique ability to rapidly transport heat and maintain a
uniform temperature. In chemical reactors, not only the degree of particle mixing, but
also the degree of gas mixing is of considerable importance.
For biomass gasification application, the advantage of fIuidized bed reactors are
(van der Drift et al., 2001; Yin et al., 2002; Wang et al., 2008): (i) short residence time;
(ii) high productivity; (iii) uniform temperature distribution in gasifiers; (iv) low char
or/and tar contents; (v) high cold gas energy efficiency; (vi) reduced ash-related problems;
and (vii) the possibility of in-bed use of a catalyst for tar cracking. Fluidized bed
gasification performs better than fixed bed gasification to reduce ash-related problems
since the bed temperature of fluidized bed gasification can be kept uniformly below the
ash slagging temperature. The low gasification temperature can also reduce the
volatilization of ash elements such as sodium and potassium into 'the syngas, thus
improving the quality of syngas (Wang et al., 2008).
28
Fast fluidization ... ---~_ ...... -. low SOfld throughflow félle
• high Solid throughflow rats
Turbulent fluîdization
Bubblîng bed
o 0.2 OA 0 .6
Volume traction solids: f
Figure 2.7 Vertical distribution of so1id in different contacting regimes (Kunii & Levenspiel , 1997)
2.6.2 Modeling of circulating fluidized bed reactors
With the advent of high-performance computers and the advances in numerical
techniques and algorithm, computational fluid dynamics (CPD) analysis of multiphase
systems has evolved to become a strong tool and approach for understanding the
hydrodynamics and transfer mechanism as weIl as designing and developing equipment
units. In recent years, the application of CFD for modeling and simulating gas-solid
fluidized bed systems has been intensively explored to gain insight into the detailed local
flow patterns and structures (Ding and Gidaspow, 1990~ Samuelsberg and Hjertager,
1996~ Mathiesen et al., 2000~ Ibsen et al., 2001~ Agrawal et al., 2001~ Zhang and Van der
Heyden, 2001 ; Benyahia et al., 2007).
GeneraIly, there are two different approaches dominating in the ~eld of numerical
simulations of fluidized bed systems. Commonly, the y are referred to as the Eulerian
Eulerian approach and the Eulerian-Lagrangian approach (Ibsen et al., 2004). The
fundamental difference between them is how the particles are treated. In the Lagrangian
29
approach, the particles are treated individually and the motion of particles is obtained
directly by solving Newton's second law for each particle. The reference frame thus
moves with the particle as the individual tracked particles move through the domain.
When applied to granular systems, such models are referred to as discrete element
methods (DEM) or a particle-tracking approach. In contrast, in the Eulerian-Eulerian
approach, the particle phase is modeled as interpenetrating continua, and its conservation
equations have a form similar to those of the other phases. For gas-particle flows , the
Eulerian-Eulerian model is often referred to as the two-fluid model (TFM). When solving
the TFM, a set of models, either physical or empirical, is required in order to close the
system of equations, including the interfacial terms and solid stress. One important
closure is the particulate phase stress (namely, viscosity and normal stresses). Basically,
two approaches exist today for treating the particulate phase stress. The first approach
uses a constant particle viscosity (CPV) and an exponential power law for the particle
particle interaction force (Rietema, 1973; Gidaspow and Ettehadieh, 1983; Syamlal and
Obrien, 1988; Bouillard et al., 1989). The second approach uses the kinetic theory of
granular flow (KTGF), which is derived in analogy with the kinetic theory of gases (Lun
et al., 1984; Ding and Gidaspow, 1990; Gidaspow et al, 2001). In the TFM models, the
conservation equations for each of the two phases are derived to obtain a set of equations
that have similar mathematical structure for both phases, which makes the mathematical
manipulation of the system relatively easier and minimize the computation co st. From the
point of view of computation, the TFM approach is much more feasible for practical
applications to complex multiphase floes. The Eulerian-Lagrangian approach IS
computationally intensive or even impossible for systems with a large number of
particles. Thus, the Eulerian-Eulerian approach is convenient in simulating systems su ch
as fluidized beds.
A coupling between prediction of flow patterns and chemical reactions in riser flows
is of great interest. In the past decade, significant progress has ' been made on CFD
modeling of gas-solid circulating fluidized bed (CFB) systems. However, most of the
works have been focused on modeling and simulating hydrodynamic behavior and flow
patterns. So far, the attempts at coupling flow hydrodynamics with reaction kinetics by
using CFD approach for the simulation of CFB reactors (riser) are still very limited in the
30
literature. Table 2.6 gives a summary of the recent attempts on CFD modeling of CFB
reactors.
Gao et al. (1999) developed a 3D two-fluid CFD flow-reaction model to predict flow
and chemical reactions taking place in a FCC riser. This model combines a modified two
phase turbulent model with realistic 13-lump reaction kinetics. The various key
engineering aspects of the two-phase reacting flow in a catalytic riser reactor (including
catalyst concentration distribution, the velocity distribution of both phases, interphase slip
velocity, the temperature distribution of both phases, and the yield distribution over the
entire reactor) can be predicted using this model. The predicted results showed that the
gas-particulate turbulent reacting flow in the FCC riser reactors was very complicated
due to feed efflux. The flow fields, particle concentration, temperature distribution, and
yield distributions showed significant inhomogeneities in the axial, radial, and
circumferential directions.
Therdthianwong et al." (2003) developed a two-dimensional model for describing the
performance of the ozone decomposition reaction in CFB system. The effect of solid
viscosity on flow structure was explored by using two different models of sol id viscosity
(namely, the constant solid viscosity coefficient model and the kinetic theory model). It
showed that the solid viscosity calculated from different models had a significant effects
on gas-solid flow pattern. The solid volume fraction profile calculated from the kinetic
theory model with restitutive coefficient of 0.9999 matched the experimental value better
than the constant solid viscosity coefficient model.
Benyahia et al. (2003) used a transient isothermal gas/solid flow model to simulate the
cracking reaction in an industrial FCC riser by using a 3-lumps reaction model. The
hydrodynamic predictions, based on kinetic theory for granular flow, were compared to
similar predictions found in literature. The cracking reactions" of heavy oil showed an
increase in the gas axial velocity along the height of the riser, which had a significant
impact on the gas/solid flow hydrodynamics.
Das et al. (2004a,b) developed a three-dimensional simulation of a dilute phase riser
reactor using a novel density based solution algorithm and following the Eulerian-
31
Eulerian approach. The kinetic theory of granular flow was applied. The gas phase
turbulence was accounted for via a k-& model. The simulations showed a core-annulus
flow pattern emerges on a time-averaged basis. Industrial data of the simultaneous
adsorption of S02 and NOx in ariser were weIl simulated with a 3D reactor model.
Comparison of simulations with a 1 D and a 3D model showed that the use of 1 D model
was limited to riser configurations and conditions for which the effects induced by the
outlet configuration were only small. For more restrictive outlet configurations, a 3D
simulation was required.
Hansen et al. (2004) modeled ozone conversion in a circulating fluidized bed (CFB)
using a three dimensional multi-fluid CFD code. The gas phase was modeled using a LES
model and the turbulent motion of the particulate phase was modeled by use of the
kinetic theory of granular flow. The ozone conversion was modeled as a one-step
catalytic reaction. The predicted ozone concentrations in the riser of the CFB were in
good agreement with the experimental results. The radial variation in ozone concentration
in 3D representation was better captured than in the 2D case.
Table 2.6 Recent attempts at CFD modeling of circulating fluidized bed reactor performances
Investigators
Gao et al. (1999)
Therdthianwong et al. (2003)
Benyahiya et al. (2003)
Das et al. (2004a,2004b)
Hansen et al. (2004)
FCC= fluid catalytic cracking .
Reactor type
FCC riser
CFB riser
FCC riser
Dilute riser
CFB riser
reactions
Catalytic cracking of crude oil
0 3 decomposition
Catalytic cracking of crude oil
SOx-NOx adsorption
0 3 decomposition
2.7 Summary and Conclu ding Remarks
Remarks
Two fluid + ] 3-lump kinetics
Two f1uid + simple kinetics
Two f1uid + 3-lump kinetics
Two fluid + adsorption kinetics
Two fluid + simple kinetics
In this chapter, a novel process concept is proposed for coupling biomass
gasification and combustion processes in monolithic structured reactors. Following the
proposaI of this process concept, the literature review is performed to establish a global
and systematical understanding of the states-of-the-arts in the relevant aspects (including
biomass gasification, monolithic reactor, high-temperature phase change material, and
fl uidized bed reactor).
32
Evidently, to effectively design and optimize this proposed process, an in-depth
understanding of the coupling between themochemical reactions and fluid mechanics in
monolithic structured reactor is very crucial. The treatment of generalized · local
information demands the help of computational fluid dynamics (CFD) which can be used
for simulating flow phenomena, understanding the impact of complex flow geometries on
mixing and reaction phenomena, and obtaining information on the detailed quantitative
flow pattern in multiphase flows.
From product design and control point of view, those models which can be used to
achieve a comprehensive description of the complex chemistry and transport phenomena
occurring in biomass gasification are of primary importance and preferred. The use of
monolith structured reactors allows decoupling of the chemistry, transport phenomena,
and hydrodynamics, and the like to tailor the reactor independently to satisfy optimal
operation conditions . . However, modeling of multiphase monolithic reactors is not an
easy task and the choice of complexity of the models allows us to tailor the appropriate
models for our purpose. The integration of biomass gasification/combustion processes
with monolithic structured reactors will increase greatly the complexity of the whole
system. This requires an integrated approach for modeling of coupled momentum-, heat-,
and mass-transfer phenomena and complex kinetic processes which happen on different
scales. Meanwhile, this calls for a further research into modeling strategies,
methodologies, and tools to organize the levels of complexity and integrate the
know ledge from the different fields of relevance.
Testing the efficacy of the proposed process concept through modeling and
experimentation is part of our ongoing project. Recognizing that understandinggas-solid
flow distribution characteristics in monolith is significantly important for the
development of the proposed process concept, the research focus of this Master thesis
work is oriented to the CFD investigation of gas-solids (biomass particles) two-phase
flow dynamics in monolithic multichannel micro-circulating fluidized bed (as detailed in
Chapter 3).
33
References
Agar DW. Multifunctional reactors: Old preconceptions and new dimensions, Chemical
Engineering Science, 1999, 54 (10): 1299-1305 .
Agrawal K, Loezos PN, Syamlal M, Sundaresan S. The role of meso-scale structures in
. rapid gas-solid flows, Journal of Fluid Mechanics , 2001, 445: 151-185.
Asadullah M, Miyazawa T, Kunimori K. Catalyst development for the gasification of
biomass in the dual-bed gasifier, Appl Catal A: Gen, 2003,255: 169-180.
Askar HG. The front tracking scheme for the one-dimensional freezing problem, Int. J.
Numer. Methods Eng., 1987,24: 859-869.
Bauer T, Guettel R, Roy S, Schubert M, AI-Dahhan M, Lange R. ModeBing and
simulation of the monolithic reactor for gas-liquid-solid reactions, Chemical
Engineering Research & Design, 2005, 83(A 7): 811-819.
Benyahia S, Ortiz AG, Paredes lIP. Numerical analysis of a reacting gas/solid flow in the
riser section of an industrial fluid catalytic cracking unit, International Journal of
Chemical Reactor Engineering, 2003, 1, A41.
Benyahia S, Syamlal M, O'Brien Tl. Study of the ability of multiphase continuum models
to predict core-annulus flow, AIChE~Journal, 2007, 53 (10): 2549-2568.
Boateng AA, Walawender WP, Fan LT, Chee CS. Fluidized-Bed Steam Gasification of
Rice Hull, Bioresource Technology, 1992, 40 (3): 235-239.
Boehman AL, Dibble RW. Experimental and numerical investigation on the influence of
tempora~ fuel/air unmixedness on NOx emissions of lean premixed catalytically
stabilized and non-catalytic combustion, Catalysis Today, 2000, 59 (1-2):131-140.
Bouillard lX, Lyczkowski RW, Folga S, Gidaspow D, Berry GF. Hydrodynamics of
erosion of heat-exchanger tubes in fluidized-bed combustors, Canadian Journal of
Chemical Engineering, 1989,67(2): 218-229.
Campoy M, G6mez-Barea A, Villanueva AL, OBero P. Air-steam gasification of
biomass in a fluidized bed under simulated autothermal and adiabatic conditions,
Industrial & EngineeringChenûstry Research, 2008, DOl: 10.1021/ie800220t (in
press).
Canu P, Vecchi S. CFD Simulation of Reactive Flows: Catalytic Combustion ln a
Monolith, AIChE Journal, 2002,48(12): 2921-2935.
34
Cao Y, Wang Y, Riley JT, Pan WP, A novel biomass air gasification process for
producing tar-free higher heating· value fuel gas, Fuel Processing Technology, 2006,
87:343-353.
Celentano D, Onate E, OlIer S. A temperature-based formulation for finite element
analysis of generalized phase-change problems, lnt. J. Numer. Methods Eng. , 1990,
37: 3441-3465.
Chakravarthy VK, Conklin JC, Daw CS, D'Azevedo EF. Multi-dimensional simulations
of cold-start transients in a catalytic converter under steady inflow conditions,
Applied Catalysis A: General, 2003,241 (1-2): 289-306.
Charpentier JC. Modern Chemical Engineering in the Framework of Globalization,
Sustainability, and Technical Innovation, Ind. Eng. Chem. Res. ,2007, 46, 3465-3485.
Chen CR, Sharma A, Tyagi SK, Buddhi D. Numerical heat transfer studies of PCMs used
in a box-type solar cooker, Renewable Energy, 2008, 33(5): 1121-1129.
Chen DKS, Oh SH, Bissett EJ, Van Ostrom DL. A three-dimensional model for the
analysis of transient thermal and conversion characteristics of monolithic catalytic
converters, in: Proceedings of the International Congress & Exposition, SAE Paper
No. 880282, Detroit, MI, 1988.
Chen JW, Yang H, Wang N, Ring Z, Dabros T. Mathematical modeling of monolith
catalysts and reactors for gas phase reactions, Applied Catalysis A: General, 2008,
345:1-11
Comini G, Guidice SD, Saro O. A conservative algorithm for multidimensional
conduction phase change, lnt. J. Numer. Methods Eng., 1990, 30: 697-709.
Corella J, Aznar MP, Delgado J, Aldea E. Steam gasification of cellulosic wastes in a
fluidized-bed with downstream vessels, Indus trial & Engineering Chemistry
Research, 1991,30 (10): 2252-2262.
Costa M, Buddhi D, Oliva A. Numerical simulation of a latent heat thermal energy
storage system with enhanced heat conduction, Energy Conversion and
Management, 1998, 39 (3-4): 319-330.
Crivelli LA, Idelsohn SR. A temperature-based finite element solution for phase-change
problems, lnt. J. Numer. Methods Eng., 1986,23: 99-119.
35
Cui HT, Hou XB, Yuan XG. Energy analysis of space solar dynamic heat rec~ivers , Solar
Energy, 2003, 74:303-308.
Cummer K, Brown RC. Indirectly heated biomass gasification using a latent-heat ballast -
part 3: refinement of the heat transfer model, Biomass & Bioenergy, 2005, 28 (3):
321-330.
Dalhuijsen Al, Segal A. Comparison of finite element techniques for solidification
problems, Int. J. Numer. Methods Eng., 1986,23: 1807-1829.
Das AK, De Wilde l , HeynderickxGl, Marin GB, Vierendeels l, Dick E. CFD simulation
of dilute phase gas-solid riser reactors: Part l - a new solution method and flow
model validation, Chemical Engineering Science, 2004a, 59 (1): 167-186.
Das AK, De Wilde l, Heynderickx Gl, Marin GB, Vierendeels l, Dick E. CFD simulation
of dilute phase gas-solid riser reactors: part II - simultaneous adsorption of S02-NOx
from flue gases, Chemical Engineering Science, 2004b, 59 (1): 187-200.
Deutschmann 0, Maier LI, Riedel U, Stroemman AH, Dibble RW. Hydrogen assisted
catalytic combustion of methane on platinum, Catalysis Today, 200, 59 (1-2):141-
150.
Deutschmann 0, Behrendt F, Warnatz l. FormaI treatment of catalytic combustion and
. catalytic conversion ofmethane, Catalysis Today, 1998,46 (2-3): 155-163.
Dhatt G, Song R, Cheikh AN. 1989. Direct enthalpy method for solidification
calculation, in Gruber, R. et al. (eds.), Prods. of the Fifth Int. Symp. on Numerical
Methods in Engineering, Boston, 487-494.
Di Blasi C. Modeling wood gasification in a countercurrent fixed-bed reactor, AIChE
Journal, 2004, 50 (9): 2306-2319.
Ding l, Gidaspow D. A bubbling fluidization model using kinetic-theory of granular
flow, AIChE Journal , 1990, 36 (4): 523-538.
Ding YL, Wang ZL, Ghadiri M, Wen DS. Vertical upward flow of gas-solid two-phase
mixtures through monolith channels, Powder Technology , 2005, 153 (1): 51-58.
Ding YL, Wang ZL, Wen DS, Ghadiri M, Fan XF, Parker D. Solids behavior i~ a dilute
gas-solid two-phase mixture flowing through monolith channels, Chemical
Engineering Science , 2006, 61(5): 1561-1570.
36
Edvinsson RK, Cybulski A. A comparative analysis of the trickle-bed and the monolithic
reactor for three-phase hydrogenations, Chemical Engineering Science, 1994,
49(24 )c: 5653-5666.
Elgafy A, Mesalhy 0, Lafdi K. Numerical and experimental investigations of melting and
solidification processes of high melting point peM in a cylindrical enclosure,
'Jol:lrnal of Beat Transfer- Transactions of the ASME, 2004, 126(5): 869-875.
Esen M, Ayhan T. Development of a model compatible with solar assisted cylindrical
energy storage tank and variation of stored energy with time for different phase
change materials, Energy Conversion and Management, 1996,37(12): 1775-1785.
Fang M, Chen GM. Effects of different multiple PCMs on the performance of a latent
thermal energy storage system, Applied Thermal Engineering, 2007, 27(5-6): 994-
1000.
Florin NH, Harris AT. Enhanced hydrogen production from biomass with in situ carbon
dioxide capture using calcium oxide sorbents, Chemical Engineering Science, 2008,
63:287-3.16.
Franco C, Pinto F, Gulyurtlu I, Cabrita I. The study of reactions influencing the biomass
steam gasification process, Fuel, 2003, 82 (7): 835-842.
Frusteri F, Leonardi V, Maggio G. Numerical approach to de scribe the phase change of
an inorganic peM containing carbon fibres, Applied Thermal Engineering, 2006, 26:
1883~ 1892.
Furimsky E. Gasification in petroleum refinery of 21 st century. Oil Gas Sci. Technol. .
1999,54,597-618.
Gao JS, Xu CM, Lin SX, Yang GH, Guo YC. Advanced model for turbulent gas-solid
flow and reaction in FCC riser reactors, AIChE Journal, 1999,45 (5): 1095-1113.
Gidaspow D, Ettehadieh B. Fluidization in two-dimensional beds with a jet .2.
hydrodynamic modeling, Industrial & Engineering Chemistry Fundamentals, 1983,
22 (2): 193-201.
Gidaspow D, Jung JW, Singh RK. Hydrodynamics of fluidization usirtg kinetic theory: an
emerging paradigm 2002 Flour-Daniel lecture, Powder Technology, 2001,148 (2-3):
123-141.
37
Gil J, Corella J, Aznar MP, Caballero MA. Biomass gasification in atmospheric and
bubbling fluidized bed: effect of the type of gasifying agent on the product
distribution, Biomass Bioenergy, 1999, 17: 389.
Halaw E, Bruno F, Saman W. Numerical analysis of a PCM thennal storage system with
varying wall temperature, Energy Conversion and Management, 2005, 46: 2592-
2604.
Hall CA, Glakpe EK, Cannon JN. Modeling Cyclic Phase Change and Energy Storage in
Solar Heat Receivers, Proceedings of 32nd AlAA Thermophysics Conference, Atlanta,
USA, 1997.
Han J, Kim H. The reduction and control technology of tar during biomass
gasification/pyrolysis: an overview, Renewable and Sustainable Energy Reviews,
2008, 12:397-416.
Hansen KG, Solberg T, Hjertager BH. A three-dimensional simulation of gas/particle
flow and ozone decomposition in the . riser of a circulating fluidized bed, Chemical
Engineering Science, 2004,59 (22-23): 5217-5224.
Hayes RE, Kolaczkowski ST, Thomas WJ, Titiloye J. Transient experiments and
modeling of the catalytic combustion of methane in a monolith reactor, lndustrial &
Engineering Chemistry Research, 1996, 35(2): 406-414.
Herguido J, Corella J, Gonzalezsaiz J. Steam Gasification of Lignocellulosic Residues in
A Fluidized-Bed at A Small Pilot Scale - Effect of The Type of F,eedstock, lndustrial
& Engineering Chemistry Research, 1992,31 (5): 1274-1282.
Higman C, van der Burgt M. Gasification, Gulf Professional Publishing, United States of
America, 2003.
Holmgren A, Gronstedt T, Andersson B. Improved flow distribution in automotive
monolith converters, React. Kinet. Catai. Leu., 1997, 60 (2): 363-371.
Ibsen CH, Solberg T, Hjertager BH. Evaluation of a three-dimensional numerical model
of a scaled circulating fluidized bed, lndustrial & Engineering Chemistry Research,
2001,40 (23): 5081-5086.
Ibsen CH, Helland E, Hjertager BH, Solberg T, Tadrist L, Occelli R. Comparison of
multifluid and discrete particle modelling in numerical predictions of gas particle
flow in circulating fluidised beds, Powder Technology, 2004, 149 (1): 29-41.
38
Irandoust S, Andersson B. Monolithic catalysts for nonautomobile applications, Catai.
Rev. -Sei. Eng., 1988a, 30: 341-392.
Irandoust S, Andersson B. Mass transfer and liquid-phase reactions in a segmented two
phase flow monolithic catalyst reactor, Chemical Engineering Science, 1988b, 43(8):
1983-1988.
James A, Brindley J, Mclntosh AC. Multi-channel monolith reactors as dynamical
systems, Combustion and Flame, 2003, 134(3): 193-205.
Jeong S, Kim T, CFD investigation of the three-dimensional unsteady flow ln the
catalytic converter, in: Proceedings of the International Congress & Exposition, SAE
Paper No. 971025, Detroit, MI, 1997.
J eong S, Kim W, A numerical approach to investigate transient thermal and conversion
characteristics of automotive catalytic converters, in: Proceedings of the
International Congress & Exposition, SAE Paper No. 980881, Detroit, MI, 1998.
Jeong S, Kim W, Numerical analysis of light-off performance and thermo-fluid
characteristics in a three-way monolithic catalytic converter, in: Proceedings of the
Seoul 2000 FISITA' World Automotive Congress, 2000.
Karellas S, Karla J, Kakarasb E. An innovative biomass gasification process and its
coupling with microturbine and fuel cell systems, Energy, 2008, 33:284-291
Kim CJ, Kaviany M. A numerical method for phase change problems, Int. J. Heat Mass
Transfer, 1990,33: 2721-2734.
Klass DL, in Biomass for renewable energy, fuels and chemicals, Academic press, San
Diego, London, 1998.
Kobayashi N, Guilin P, Kobayashi J, Hatano S, Itaya Y, Mori S. A new pulverized
biomass utilization technology, Powder Technology, 2008, 180: 272-283.
Kolios G, Frauhammer J, Eigenberger G. Autothermal fixed-bed reactor concepts,
Chemical Engineering Science, 2000, 55 (24): 5945-5967.
Kolios G, Frauhammer J, Eigenberger G. Efficient reactor concepts for coupling of
endothermic and exothermic reactions, Chemical Engineering Science, 2002, 57 (9):
1505-1510.
39
Kumar A, Mazumder S. Assessment of various diffusion models for the prediction of
heterogeneous combustion in monolith tubes, Computers & Chemical Engineering,
2008,32 (7): 1482-1493.
Kunii D, Levenspiel O. Circulating fluidized-bed reactors, Chemical Engineering
Science, 1997,52 (15): 2471-2482.
Lemmon EC. Phase change techniques for finite element codes. in Lewis, R.W. and
Morgan, K. (eds.), Numerical Methods in Thermal Problems, Swansea, 1979, pp149-
158.
Levenspiel O. What will come after petroleum? Industrial & Engineering Chemistry
Research, 2005, 44 (14): 5073-5078.
Lim MT, Alimuddin Z. Bubbling fluidized bed biomass gasification-performance,
process findings and energy analysis, Renewable Energy, 2008, 33: 2339-2343.
Liu B, Hayes RE, Yi Y, Mmbaga J, Checkel MD, Zheng M. Three dimensional modeling
of methane ignition in a reverse flow catalytic converter, Computers & Chemical
Engineering, 2007, 31(4): 292-306.
Lopamudra D, Ptasinski KJ, Janssen FJJG. A review of the primary measures for tar
elimination in biomass gasification processes. Biomass Bioenerg, 2003,24: 125-140.
Lun CKK, Savage SB, Jeffrey DJ, Chepumiy N. Kinetic theories for granular flow -
inelastic particles in couette-flow and slightly inelastic particles in a general flow
field, Journal of Fluid Mechanics, 1984,140: 223-256.
Lutz AE, Bradshaw RW, Keller JO, Witmer DE. Thermodynamic analysis of hydrogen
production by steam reforming, International Journal of Hydrogen Energy, 2003, 28,
159-167.
Mamoka N, Akiyama T. Exergy recovery from steelmaking off-gas by latent heat storage
for methanol production, Energy, 2006, 31 (10-11): 1632-1642.
Mamoka N, Sato K, Yagi J , Akiyama T. Development of PCM for recovering high
temperature waste heat and utilization for producing hydrogen by reforming reaction
ofmethane, ISIJ International, 2002, 42 (2): 215-219.
Mathiesen V, Solberg T, Arastoopour H, Hjertager BH. Experimental and computational
study of multiphase gas/particle flow in a CFB riser, AIChE Journal, 1999, 45 (12):
2503-2518.
40
Mazumder S, Sengupta D. Sub-grid scale modeling of heterogeneous chemical reactions
and transport in full-scale catalytic converters, Combustion and Flame, 2002, 131 (1-
2): 85-97.
Mazumder S. Modeling full-scale monolithic catalytic converters: Challenges and
possible solutions, Journal of Hf!at Transfer-Transactions of the ASME, 2007, 129
(4): 526-535.
Morgan K, Lewis, RW, Zienkiewicz, OC . An improved algorithm for heat conduction
problems with phase change, Int. J. Numer. Methods Eng., 1978,12:1191-1195
Murray WD, Landis F. Numerical and machine solutions of transient heat conduction
problem involving meltingor freezing, J. Heat Transfer, 1959, 81: 106-112.
Negro SO, Suurs R AA, Hekkert MP. The bump road of biomass gasification in the
Net.herlands: Explaining the rise and faB of an emerging innovation system,
Technological Forecsting & Socil Change, 2008,75: 57-77.
Paasen SVB. Tar formation in fluidized-bed gasification-impact of gasifier operating
c.onditions. The 2nd world conference and technology exhibition on biomass for
energy, industry and climate protection, 2004. pp. 130-138.
Panigrahi S,Dalai AK, Chaudhari ST, Bakhshi NN. Synthesis gas production from steam
gasification of biomass-derived oil, Energy Fuel, 2003, 17(3): 637-642.
Pham QT. The use of lumped capacitance in the finite-element solution of heat
conduction problems with phase change, Int. J. Heat Mass Tran., 1986,29: 285-291.
Pinelli M, Piva S. Solid/liquid phase change in presence of natural convection: A thermal
energy storage case study, Journal of Energy Resources Technology-Transactions of
The ASME, 2003,125 (3): 190-198.
Pletka R, Brown RC, Smeenk J. Indirectly heated biomass gasification using a latent heat
ballast - 1: experimental evaluations, Biomass & Bioenergy, 2001a, 20 (4): 297-305.
Pletka R, Brown RC, Smeenk J. Indirectly heated biomass gasification using a latent heat
ballast. Part 2: modeling, Biomass & Bioenergy, 2001 b, 20 (4): 307-315.
Potic B, Kersten SRA, Ye M, van der Hoef MA, Kuipers JAM, van Swaaij WPM.
Fluidization with hot compressed water in micro-reactors, Chemical Engineering
Science, 2005, 60 (22): 5982-5990.
41
Prins MJ, Ptasinski KJ, Janssen FJJG. From coal to biomass gasification: comparison of
thermodynamic efficiency, Energy, 2007,32(7): 1248-1259.
Radmanesh R, Chaouki J, Guy C. Biomass gasification in a bubbling fluidized bed
reactor: Experiments and modeling, AIChE Journal, 2006, 52 (12): 4258-4272.
Raja LL, Kee RJ, Deutschmann 0, Warnatz J, Schmidt LD. A critical evaluation of
Navier-Stokes, boundary-Iayer, and plug-flow models of the flow and chemistry in a
catalytic-combustion monolith, Catalysis Today, 2090, 59 (1-2):47-60.
Ramaswamy RC, Ramachandran PA, Dudukovic MP. Recuperative coupling of
exothermic and endothermic reactions, Chemical Engineering Science, 2006,61 (2):
459-472.
Rietema K. Effect of Interparticle Forces On Expansion of a Homogeneous Gas
Fluidized Bed, Chemical Engineering Science, 1973,28 (7): 1493-1496.
Rolph WD, Bathe ~J. An efficient algorithm for analysis of nonlinear heat transfer with
phase changes, Int. J. Numer. Methods Eng., 1982, 18: 119-134.
Roose J, Storrer O. Modelization of phase changes by fictitous heat flow, Int. J. Numer.
Methods Eng., 1984, 20: 217-225.
Ross D, Noda R, Horio M, Kosminski A, Ashman P, Mullinger P. Axial gas profiles in a
bubbling fluidised bed biomass gasifier, Fuel, 2007, 86 (10-11): 1417-1429.
Roy S, Heibel AK, Liu W, Boger T. Design of monolithic catalysts for multiphase
reactions, Chemical Engineering Science, 2004a, 59: 957- 966.
Roy S, Bauer T, AI-Dahhan M, Lehner P, Turek T. Monoliths as multiphase reactors: a
review, AIChE Journal, 2004b, 50 (11): 2918-2938.
Rubinsky B, Cravahl0 EG. A finite element method for the solution of one-dimensional
phase change problems, Int. J. Beat Mass Tran., 1981,24: 1987-1989.
Samuelsberg A, Hjertager BH. Computation al modeling of gas/particle flow in ariser,
AIChE Journal, 1996,42 (6): 1536-1546.
Schlosberg RH. Chemistry of coal conversion; Pl~num: New York, 1985.
Sharma A, Won LD, Buddhi D, Park JU. Numerical heat transfer studies of the fatty
acids for different heat exchanger materials on the performance of a latent heat
storage system, Renewable Energy, 2005, 30: 2179-2187.
42
Shuai S, Wang J, Zhuang R, Numerical simulation and optimum design of automotive
catalytic converters, in: Proceedings of the Seoul 2000 FISITA World Automotive
Congress, 2000.
Stankiewicz A. Process intensification in in-line monolithic reactor, Chemical
Engineering Science, 2001, 56:359-364.
Syamlal M, Obrien TJ. Simulation of granular layer inversion in liquid fluidized-beds,
International Journal of Multiphase Flow, 1988, 14(4): 473-481.
Tomasic V. Application of the monoliths in DeNOx catalysis, Catalysis Today, 2007',
119: 106-113.
Tamma K, Namburu R. Recent advances, trends and new perspe~tive via enthalpy-based
finite element formulations for applications to solidification problems, Int. J. Numer.
Methods Eng., 1990,30: 803-820.
Therdthianwong A, Pantaraks P, Therdthianwong S. Modeling and simulation of
circulating fluidized bed reactor with catalytic ozone decomposition reaction,
Powder Technology, 2003, 133 (1-3): 1-14.
Tischer S, Correa C, Deutschmann O. Transient three-dimensional simulations of a
catalytic combustion monolith using detailed models for heterogeneous and
homogeneous reactions and transport phenomena, Catalysis Today, 2001, 69 (1-4):
57-62.
Trp A. An experimental and numerical investigation of heat transfer during technical
grade paraffin melting and solidification in a shell-and-tube latent thermal energy
storage unit, Solar Energy, 2005,79: 648-660.
Turn S, Kinoshita C, Zhang Z, Ishimura D, Zhou J. An experimental investigation of
hydrogen production from biomass gasification, International Journal of Hydrogen
Energy, 1998, 23 (8): 641-648.
van der Drift A, van · Doorn J, Vermeulen JW. Ten residual biomass fuels for circulating
fluidized-bed gasification, Biomass & Bioenergy, 200 1, 20:45-56.
van der Drift A, Boerrigter H. Synthesis gas from biomass for fuels and chemicals, ECN
report, 2006.
VoIler V, Cross, M. Accurate solutions of moving boundary problems using the enthalpy
method~ Int. J. Heat Mass Tran., 1981,24: 545-56.
43
VoIler V, Cross M. An explicit numerical method to track a moving phase change front,
Int. J. Heat Mass Tran., 1983,26: 147-150.
VoIler V, S waminathan CR, Thomas BG. Fixed grid techniques for phase change
problems: a review, Int. J. Numer. Methods Eng., 1990,30: 875-898.
VoIler VR. Fast implicit finite-difference method for the analysis of phase-change
problems, Numerical Heat Transfer Part B-Fundamentals, 1990, 17(2): 155-169.
Vorres KS. Coal. In Concise encyclopedia of chemical technology, 4th ed.; Kirk, R. E.,
Othmer, D. F., Eds.; Wiley: New York, 1999; pp 458-462.
Walawender WP, Hoveland DA, Fan LT. Steam gasification of pure cellulose. 1. uniform
temperature profile, Indus tria 1 & Engineering Chemistry Process Design and
Development, 1985, 24 (3): 813-817 .
Wang LJ, WeIler CL, Jones DD, Hannab MA. Contemporary issues in thermal
gasification of biomass and its application to electricity and fuel production, Bioma~s
and Bioenergy, 2008, 32: 573-581.
Weaver JA, Viskanta R. Freezing of liquid saturated porous media. J. Heat Mass
Transfer, 1986,33: 2721-2734.
Wilber RA, Boehman AL. Numerical modeling of the reduction of nitric oxide by
ethylene over Cu-ZSM-5 under lean conditions, Catalysis Today, 1999,50 (1): 125-
132.
Wurzenberger JC, Wallner S, Raupenstrauch H, Khinast JG. Thermal conversion of
biomass: Comprehensive reactor and particle modeling, AIChE Journal, 2002, 48
(10): 2398-2411.
Yin XL, Wu CZ, Zheng SP, Chen Y. Design and operation of a CFB gasification and
pow~r generation system for rice husk. Biomass & Bioenergy, 2002,23: 181-187.
Xu X, Zhang YP, Lin KP, Di HF, Yang R. Modeling and simulation on the thermal
performance of shape-stabilized phase change material floor used in passive solar
buildings, Energy and Buildings~ 2005, 37: 1084-1091.
Yang YB, Sharifi VN, Swithenbank J. Substoichiometric conversion of biomass and
solid wastes to energy in packed beds, AIChE Journal, 2006, 52 (2): 809-817.
44
Zerkle OK, Allendorf MD, Wolf M, Oeutschmann O. Understanding homogeneous and
heterogeneous contributions to the platinum-catalyzed partial oxidation of ethane in a
short-contact-time reactor, Journal ofCatalysis, 2000,196 (1): 18-39.
Zhang OZ, VanderHeyden WB. High-resolution three-dimensional numerical simulation
of a circulating fluidized-bed, Powder Teehnology, 2001, 116 (2-3): 133-141.
Zuberbuhler U, Specht M, Bandi A. Gasification of biomass: an overview on available
technologies, RENEW -1 st European summer school on renewable motor fuels, 2005.
(http://www.conference-biomass.comlpdfs/Visual-Presentations Wednesday
Friday.pdD
Zygourakis K, Aris R. Heat transfer. in the array of passages of a monolith reactor, in:
Proeeedings of the AIChE 75th Annual Meeting, Los Angeles, CA, 1982.
Zygourakis K. Transient operation of monolith catalytic converters: a two-dimensional
reactor model .and the effects of radially nonuniform flow distributions, Chem. Eng.
Sei., 1989, 44(9):2075-2086.
45
Chapter 3 Simulating the Dynamics of Gas-Solid Flows in a Multichannel Micro-Circulating Fluidized Bed
Yi-Ning WangI, Faïçal Larachi1*, Shantanu Roy2
'Department of Chemical Engineering, Laval University, Quebec (QC), G1K 7P4, Canada. 2Department of
Chemical Engineering, Indüm Institute of Technology (IIT) - Delhi, New Delhi 110016, India.
Abstract
The dynamics of gas-solid flows and distribution in monolithic multichannel micro
circulating fluidized-bed reactors was analyzed using a computational fluid dynamics
(CFD) modeling approach. A 2-D Euler-Euler multiphase model with the kinetic theory
of granular flow has been solved for the detailed monolithic packing geometry. The
assemblage of monolithic structured packings with through-flow gas-particulate flows is
globally considered in the simulation to capture the dominant mechanisms contributing to
the final overall aero/granular dynamics. Due to the complex nature of the interactions
between gas and particulate phases and the stationary monolith backbone, one of the
challenges in the design and operation of the monolith reactors is the prevention of flow
maldistribution. The work presented in this paper forms the basis for a comprehensive
reactor-scale model for exploring the intriguing possibilities that the proposed process
intensification concept offers for chemical reactions of energy/environmental relevance
such as biomass gasification and combustion.
Keywords: CFD simulation; monolithic structured reactor; maldistribution; hybridization
of gasification/combustion; biomass.
* To whom correspondence should be addressed. Tel.: +14186563566; fax: +14186565993. E-mail: [email protected] (F. Larachi).
46
3.1 Introduction
Biomass is one of the important pnmary and renewable energy sources. With
evidence of depleting fossil fuel sources as weIl as the evolving global warming issues,
the need for utilization of biomass for energy is very seductive, particularly because it is
believed that energy obtained from biomass has a carbon-neutral cycle. This situation
calls for the development of a biomass-based but energy efficient and environment
friendly processes with better environmental acceptability and economic viability.l ,2
Gasification to produce biosyngas is regarded as one of the most promising options
for biomass conversion and utilization. However, thermodynamics and intrinsic kinetics
dictate that endothermic biomass gasification reactions have to be carried out at high
temperatures, which demands efficient heat supply and recovery policy. The concept of
allothermal gasification offers an attractive solution for implementing high-temperature
reactions by coupling strongly endothermic reactions with exothermic reactions?
However, implementing the concept in practice is not straightforward.
In the present work, we will first propose an innovative biomass gasification process
concept in which the coupling of gasificationlcombustion process with high-temperature
phase-change-material will be implemented in a monolithic structured reactor and
intensified by periodic operation mode. To effectivelydesign and optimize this novel
process, knowledge from different important fields (including biomass gasification,
monolith reactor engineering, high-temperature phase change material, and fluidized bed
reactor) is required. In addition, modeling and understanding of gas-solid (biomass
particles) flow hydrodynamics in monolithic structured reactor is very important, in view
of the complexity of two-phase flow within such confined micro-structured packings.
Specifically, due to the complex nature of the interactions between gas and particulate
phases and the stationary packing, one of the major challenges in the design and
operation of the monolith reactors is prevention of flow mal-distribution. In order to
overcome the limitations posed by this phenomenon, flow distribution characteristics in
this type of reactors need to be quantitatively studied and understood. In this work,
following the introduction of the novel process concept, the gas-solid two-phase flow
distribution characteristics in a monolithic structured reactor have been investigated using
47
a computational fluid dynamics (CFD) simulation approach. A two-dimensional
multifluid Euler-Euler CFD model with closure laws according to the kinetic theory of
granular flow has been solved. To effectively characterize flow distribution, an
assemblage of structured monolithic section with non-structured packed-bed sections is
fully considered in our simulation, allowing comprehensive capture of various possible
mechanisms contributing to the final overall aero/granular dynamics. The packed-bed
sections are treated as porous media by imposing radial porosity distribution and
interphase interactions through user defined functions (UDFs).
3.2 Hybridization of Gasification/Combustion Processes in Monolithic Structured
Reactors
Steam gasification of sol id carbonaceous fuels is highly endothermic, which
demands input of additional heat to drive reactor conversion. This poses a major
challenge because the input of energy reduces the maximum process efficiency. There are
a number of potential problems3 which could be encountered in developing process
concepts for biomass gasification with steam: (i) If the biomass is reacted with both air
and steam in one reactor, then nitrogen is present in the product stream and is costly to
remove; (ii) If one attempts to avoid this problem by using oxygen instead of air, then a
source of pure oxygen would be needed, which is again a costly option; (iii) It is possible
to circumvent the separation issues by running the "oxygen-Iess" gasification and the
combustion reactions in different locations, but then transferring heat from one location
to the other is accompanied with heat losses; (iv) AIso, in all of these schemes, potential
rapid cooling of the product gases leads to tar formation, . which adversely affects the
process stability and efficiency as weIl. To avoid this, the product gases must be kept hot
for an optimal duration of their residence time, which allows the tars to crack into lower
molecular weight compounds.
In the present work, a process concept which involves time-segregated hybridization
of biomass gasification/combustion reactions in a monolithic structured reactor is
proposed, as illustrated in Figure 3.1. In this process, the monolithic micro-circulating
48
• ste.am COZ+H2;O Tibiom.3ss
C fi> lim e i ~ ~ E o o
ai r +biom ass
CO+Hz
Figure 3.1 Proposed process concept
fluidized bed is used as the reactor unit for gasificationlcombustion of biomass (Figure
3.1). At -the heart of the proposed process is a monolithic reactor through which gas
solids cocurrent flow occurs, much as in a conventional circulating fluidized bed reactor.
However, the presence of the numerous monolith channels serves to segregate the gas
solids flow into these individual cells, which helps to intensif y the process. Both the
exothermic combustion step and the endothermic gasification step are undertaken in the
same monolithic reactor. The process intensification by periodic operation mode is used
to temporally segregate the gasification and combustion steps. This is made possible by
coating the walls of the monolith channels with high-temperature phase-change-materials
(PCM)4,s serving for successive heat storage and heat release in a cyclic operation. The
biomass is supplied to the monolithic reactor aft.er fine granulation and subsequent
pneumatic conveying. Hence, the process intensification is achieved both by temporal
segregation of gasification and combustion as well as the use of a monolithic micro
fluidized bed reactor with walls coated with PCM. The proposed novel process is
supported by the recent advances in: (1) the development of micro-fluidized bed concept
49
for biomass conversion;6 (2) the development of high-temperature PCM and its
application in biomass gasification;4,s and (3) the pioneering experimental investigation
in flow hydrodynamics of gàs-solid two-phase mixture in monolith.7,s The proposed
concept incorporates the diverse notions proposed by the above referenced papers onto a
single platform. Testing the efficacy of the concept through modeling and
experimentation is part of our ongoing work and the present contribution is a summary of
our first full set of results in addressing a key enabling technology for the concept.
The design and optimization of this novel hybrid process requires accurate
understanding of not only the phenomena of biomass thermochemical conversion but also
the two-phase hydrodynamics behavior in the monolithic micro-fluidized reactor which
are highly complex in nature. In this regard, the flow distribution characteristics of gas
solids two-phase hydrodynamics in monolithic structured reactor are significantly
important for prediction of gasification/combustion performance and examination of
strategies for process operation. In the following sections, the development of Euler
Euler CFD multifluid simulation as weIl as its application for exploring maldistribution
of two-phase flow in monolithic packing will be discussed in details.
3.3 Representation of Nonuniform Porosity Distribution for Packed-bed Sections
The reactor computational geometry considered in the present work consists of three
sections: upstream random-packing fixed-bed distributor section, central monolithic
section and downstream random-packing fixed bed section (details are given in Section
3.5). This corresponds to the system geometry reported in the literature by Ding et a1.7,s,
in which the monolith section is sandwiched between the two packed-bed sections. For
the fixed bed randomly packed with solid particles with low D/dp ratios, the flow is
remarkably affected by radial porosity distribution which is function of bed diameter (D),
and particle diameter (dp) and shape. Therefore, it is essential to define and implement
porosity distribution in the simulations to capture the radial distribution characteristics in
randomly packed beds. Experimental and computational investigations have shown that
in low D/dp ratio beds the porosity is high near the vicinity of the wall and it oscillates
50
significantly in the near wall region, by following a damped oscillatory function until it
reaches a constant value about 5 particle diameters from the wall. Mueller (1992)
developed a correlation for radial variation of porosity, as a function of particle diameter
and bed diameter, which has the following form: 9
E ( r) = E B + (1- E B ) Jo ( ar * ) e -br
where
a =
(
8,2, 43 12.98 (D/d p -3.156)
7.383 2.932 (D/d p -9.864)
b = 0.304- 0.724 D/dp
* r r
D
for 2.61~ D/dp ~ ]3.0
for D/dp ~13.0
(la)
(lb)
(lc)
(Id)
and Jo is ' zeroth -order Bessel function of the first kind. This correlation represents the
available experimental data with reasonable ' accuracy and is widely used. Figure 3.2
presents the simulated radial porosity variations for our numerical geometry which is
characterized by low column-to-particle ratio D/dp = 5 (i.e., column of 50mm and packing
particles of 10mm). As compared to the correlation proposed by Giese et al.,l0 the
Mueller' s correlation is adopted in our work since it captures the wall-induced damped
oscillations.
51
1.0
- 0 - Mueller(1992) 0.8 - 0 - Giese (1998)
0.2
0.0 +------.--..,-------.--..,----.----,.-----.----,.-----.---1 0.0 0.5 1.0 1.5 2.0 2.5
r/dp [-]
Figure 3.2 Radial variation ofbed porosity in packed-bed sections
3.4 Eulerian-Eulerian Multifluid Model for Gas-Solid Flow in Monolithic
Structured Reactor
An Eulerian-Eulerian model with the kinetic theory of granular flow is used to model
the hydrodynamics of gas-solid flow in the three-section monolithic reactor. The
equations employed are a generalization of the Navier-Stokes equations for interacting
continua, and aIl phases are considered to be continuous and fully interpenetrating. The
model goveming equations for the gas and solid phases are as follows:
3.4.1 Continuity and momentum conservation equations
3.4.1.1 Mass conservation equations of gas and particulate phases
Mass conversation equation for each phase (q=g,s) is described by:
~(p a )+V(p a ~q )=O dt q q q q (2)
Each computational cell is shared by the interpenetrating phases, the sum over aIl volume
fractions is therefore unit y:
(3)
52
3.4.1.2 Momentum conservation equation of gas and particulate phases
Momentum conservation for the gas phase is written as:
Momentum conservation for the particulate phase can be expressed as
:/ (aA ~' )+ v( a,p, v,v,) = -a,Vp + vp, + V . ~, +a,p, g - fJg , (v g -v, )+s,
= =
(4)
(5)
where Tg and Ts are the phase stress tensors for gas and sol id phases, respectively; and
/3gS is the drag coefficient between phases . .
3.4.2 Kinetic theory of granular flow equations
Closure of the particulate phase momentum equation requires constitutive relations
for calculating solid pressure, Ps ' solid shear viscosity, fls ' and solid bulk viscosity, Àç ,
which can be derived from the granular kinetic theory.l1 The kinetic energy of fluctuation
is accounted for by defining a granular temperature, (}ç :
1 ( '2) () -- v s 3 s
(6)
where v~ is the particulate fluctuating velocity. The granular temperature conservation
equation is:
(7)
where (-p) +;s ) : v~s is the generation of energy by the solid stress t~nsor, v' (kB, V (}ç) is
the diffusion of energy, and YB, is the collisional dissipation of energy.
The solid pressure, Ps , is composed of a kinetic term that dominates in the dilute flow
regions and a collision contribution that is significant in the dense flow region: Il
53
(8)
where ess is the coefficient of restitution for particle collisions. The radial distribution
function, go' is a correction factor that modifies the probability of interparticle collisions.
The solid shear viscosity, J.1s
, Îs calculated by12,13
(9)
The solids bulk viscosity, À:~ , is expressed as: Il
(10)
3.4.3 Closure relationships for interphase interactions
The interaction coefficient between the gas phase and flowing particulate phase can be
described by a combination of Wen and Yu14 and Ergun15 equations. The final drag
coefficient for this combination is expressed as
f3. = ~c a~ag Pg I ~s - ~g 1 a-2.65
Erg lin 4 D dl' g
2
fJw"-y,, = 150 :< ~~ + 1.75 a:g Iv, - Vg 1 g .\ S
(11)
The drag coefficient CD is evaluated by
l~. [1+0.15(a ReJo687
] CD = ag Re~ g
0.44
Res < 1000 (12)
Re, ~ 1000
with the relative Reynolds number, Res ,defined by
P d I~ s -~g l Re = _ g _s~_-,-
s J.1 g
(13)
54
To avoid discontinuity from the two equations, Gidaspow ·(1994) 13 introduced a switch
function that gives a smooth but rapid transition from one regime to the other:
arctan[150x1.75x(0.2-a )] f/Jgs = s +0.5
J[ (14)
Thus, the interaction coefficient between fluid particle phases is finally expressed as
(15)
The interaction between the gas phase and the stationary packing phase, i.e. , lower and
upper packed bed sections, can be expressed using an Ergun-type equation 15
(16)
In literature there are a few attempts made to evaluate the interaction force between
powder and packing particle phases. 16-18 In this work, the interaction between the flowing
suspended phase and the stationary packing phase is expressed by:17,19
(17)
where
(18)
" 2d p (l-ë) D=---
3ë (19)
(20)
where ()~ = Vs . (a~ E) is the superficial suspended solids velocity vector.
55
. ~
3~4.4 Definition of maldistribution quantities
To quantify the flow non-uniformity of two-phase flow distribution in each channel,
the flow factor, ri, which is the estimated ratio of the actual flow rate to the theoretical
flow rate at uniform distribution,20 is here used:
(21)
where miq denotes the mass flow-rate of the qth phase in ith channel in actual cases, while
mi,o is the theoretical uniform flow-rate of the qth phase in ilh channel. In actual cases, the
value of ri may be greater than or less than 1.0, representing a jlow excess or jlow
starvation state in each channel, respectively.
Besides the flow factor, the maldistribution factor, M f ' which was first introduced by
Hoek et al.21 and modified by Marcandelli et al.,22 is also adopted in this work to
determine the flow distribution over the entire cross-section of the monolith block:
(22)
where N ell is the number of · channels. MJ equals 0.0 when the flow is distributed
uniformly; and MJ approaches 1.0 when the flow is highly selective to one single
channel.
3.5 Computational Geometry, Boundary Conditions and Numerical Solution
The monolith geometry reported in the literature by Ding et al. 7,8 is considered in
our simulation, which has a length of 600 mm and a (square) cell size of 3 mm (cell size
represents clearance without cell wall thickness), see Table 3.1. As far as the cold unit
simulations are concerned, this selected block length is judged representative for
highlighting the gas and solids flow maldistribution issues. Should it be necessary and
56
depending on the reactions to be hosted in the future studies, the monolith length is
extensible to make it compatible with the reaction characteristic times. The monolith
section is connected to an upstream packed bed (length: 300 mm, sphere diameter:
10mm) which serves as distributor. In addition, a packed-bed section (length: 100 mm,
sphere diameter: 10 mm) is hyphenated downstream to the monolith section. In the
present study, the global assemblage of the three sections is taken into account. This low
column-to-particle-ratio is chosen as the base condition as it reflects an experimental
setup representative of that studied by Ding et al. 7,8 Larger ratios could mn the risk of
inducing depth filtration and capture of particles in the pre- and post-distributors, which
may not be desirable. As a first approximation, a two-dimensional symmetric domain is
considered, providing a simplified scenario to get insight into the packed-bed-induced
maldistribution flow characteristics in monolithic structured reactor. The computational
geometry is schematically shown in Figure 3.3.
solid ph<rse
Gas phase
Figure 3.3 Two-dimensional computational geometry with the assemblage of three-secti on structuredlnon-structured packings (yellow . line, 2D symmetri c plane)
57
The solid volume fraction at the inlet is given by13, assuming homogeneous flow:
(23)
where ug is the superficial gas velocity, and G.I' is the solids mass flux. Flat velocity
profiles are set as inlet boundary conditions for gas and suspended phases, which are
calculated as follows:
(24)
(25)
where u)s the axial interstitial solids velocity, and ug is the axial interstitial gas velocity.
A no-slip condition is used for aIl the impermeable walls.
The model equations are solved in steady state using commercial software Fluent
(version 6.3). The porosity distribution model and the interphase momentum exchanges
are implemented via user defined functions. The second-order upwind scheme is used for
the convection terms of momentum equations. The velocity-pressure coupling is treated
using the SIMPLE algorithm.
3.6 Results and Discussion
In this work, an attempt is made to investigate gas-solid two-phase flows through the
aforementioned composite monolith geometry. The gas continuous phase considered is
Parameter
Operation pressure (Pa)
Gas phase (air):
- Density (kg/m3)
- Viscosity (kg/m-s)
- Inlet velocity (m/s)
Solid phase (biomass particles):
- Density (kg/m3)
Table 3.1 Basic simulation conditions used in thi s work
58
Value
l . lE5
1.225
1.7894E-5
2.]4
450.0
- ParticJe diameter (m) 55E-6
- !nlet velocity (mis) 2.14
- !nlet solid volume fraction 6.4269E-4
Upstream packed-bed section:
-Length (m) 0.300
-Colurnn diameter (m) 0.050
-ParticJe diameter (m) 0.010
Central monolith section:
-Length (m) 0.600
-Diameter (m) 0.050
-Channel size (m) 3.0E-3
-Pitch (m) 3.3E-3
Downstream packed-bed section:
-Length (m) 0.100
-Co]urnn diameter (m) 0.050
-Particle diameter (m) 0.010
air and the sol id suspended phase is biomass particles. The size of solid particles is 55 J.lm.
The basic simulation parameters used in this work are listed in Table 3.1.
3.6.1 Modeling of two-phase flow behavior in monolith structured packings
Figure 3.4 shows the radial solid mass fluxes of the suspended phase in different
packing sections (z (m) < 0: lower packed bed; 0 < z < 0.6: monolith block; z > 0.6: upper
packed bed). It can be seen that the suspended particles are distributed unevenly across
the monolith assemblage cross-section. The highest biomass solids flux takes place at r =
0.0165m, i.e., 0.66 x column radius. It is very close to the value reported experimentally
by Ding et al. 8 for glass beads using a positron emission particle tracking technique. In
their work, it was found that the dominant peak of solid concentration occurs in the
annular region around rI R ~ 0.7. Although the suspended particles (biomass particles)
used in this simulation differ from those used by Ding et al. 8, it can be conservatively
concluded that the model has the ability to capture non-uniform distribution features of
solid phase flow in monolithic structured packing, definitely within what may be
regarded as qualitative approximations. In addition, it can also be seen that for the
packed-bed sections, there is a dominant peak at . a position close to the wall, which
corresponds to a main feature of the measurement in gas-solid flow through packed
bed.23,24 This suggests that our model can be used to capture the main features from the
experimental findings.
59
10.-------~------~------~------~----__,
~ 8~ ····· · · ····· · ····· ··~ · · · · · · · · ·· ··· · · · · · · ····~ · ·· ···· .. .• • •• . •.. • .. :.- . •• . ...... ~ .......• . : . . . .. . . . . .. ....... .. .. ·1
NE 0, ~ 6 x :::l ~
--- z=-0.25m --z=-0.10m
+. z= 0.40m
--z=0.65m CfJ CfJ cu 4~ · .. · .. · .. .. .. · ...... : .. · .. · .. ·· .... · .. .... .. ; .. ····· .. .. .. · .. · .. · .. ; .. · .. · .. ·1
E Q) CfJ cu ..c 2~ .. ·· .. · ·· · .. ·· ~ .. ·· .... · .. · .. · .. .. · .. ~ .. · .. .... .. r · :~ · .. .. : .. · ,' "" ,~,,· ~ · D~·11 ·~ .. · .... ·· .... ·· .... 1
0...
~ o (J)
0.000 0.005 0.010 0.015 0.020 0.025
Radial coordinate (m)
Figure 3.4 Solids biomass flux of suspended phase in different packing sections
Ci) N
E 0, ~ x :::l ~
en en cu E Q) en cu
..c 0.. <il cu
<.9
16
14
12
10
8
6
4
2
0
-1 .. .... .. . .. .... . --- z=-0.25m
---- z=-0.1 Dm z= 0.40m
----....-z=0.65m
0.000 0.005 0.010 0.015 0.020
Radial coordinate (m)
Fi gure 3.5 Gas mass fluxes mirroring Fi gure 4 simulations
60
0.025
Figure 3.5 shows the gas mass fluxes in different packing sections. It is shown that
there exists a very strong near-wall channeling for the gas flow in the lower fixed-bed
random packing. Due to the block effect of monolith structured geometry and no-slip
effect from wall, the packed-bed induced maldistribution for gas phase is reduced to · a
great extent in the monolith section. However, the gas-phase maldistribution in different
channels is still remarkable. The channel adjacent to the column wall is responsible for
significant transport of the gas phase.
Figure 3.6 compares the radial profiles · at z = +0.4 m of solid and gas velocities as
weIl as the variation of solid volume fractions inside the monolith channels. It can be
seen that the non-uniform distribution characteristics for the gas and solid phases are
completely different. The non-uniform distribution of the solid phase is evident, as
reflected by both the sol id velocity and the solid volume fraction. For the solids phase,
6
- gas-phase velocity -<>- solid-phase velocity
-0- solid volume fraction
0.012
0.010
Cf)
Q. 0.008 ~
< o C-
0.006 ~
n> 0.004 g
o :::J
0.002
o -+---M-....--~-----r4l~~-~-~-~-...---l~-~ 0.000 0.000 0.005 0.010 0.015 0.020 0.025
Radial coordinate (m)
Figure 3.6 Channel dependence of gas-phase veJocity, solid velocity, and solid holdup (z= D.4m)
the highest solid velocity can be found in two channels which are located two-channel
away from the column wall. It is interesting to note that these two channels also
correspond to the highest solid volume fraction, contributing to the largest solid transport
61
capacity. It is also observed that the velocities of the gas phase are generally several times
, higher than those of the solid phase.
3.6.2 Comparison of gas-solid two-phase flow with single~phase flow
It is of interest to compare the two-phase and single-phase flow behaviors. For
comparison purposes, two simulation cases for single-phase flow are considered in this
work. In the first case, the random packing is not taken into account. That is, no packing
Îs arranged in the upstream and downstream fixed-bed sections. In the second case, the
packings in fixed-bed sections are enabled. Compared to the two-phase flow, the single
phase flow corresponds to a two-phase flow with zero solids volume fraction. Figure 3.7
shows the variation of gas-phase velocity with the radial coordinate at different axial
locations. It can be seen from Figure 3.7(a) that for disabled random-packings (empty
5.0 --z=-O.25m
4.5 -z=-O.10m
en 4.0 .... z= 0.40m
~z=O.65m
Ê 3.5
.è 3.0 'u 0
ID 2.5 > ID 2.0 en .~
E 1.5 cu ~ 1.0 W,
0.5
0.0 0.000 0.005 0.010 0.015 0.020 0.025
Radial cbordinate (m)
(a) single-phase si mulati on wühout random packings
62
30 r---------------------------~
U> E
25
è 20 ·0 o ~ 15 ID CI)
.~ 10 E cu ~
êi5 5
-z=-O.25m -z=-O.10m __ A,.">.~_ z= 0.40m
--z= O.65m
0.000 0.005 0.010 0.015 0.020
Radial coordinate (m)
(b) single-phase simulation with random packings
0.025
Figure 3.7 The gas-phase velocity in single-phase f10w simulation
pipe), the .distribution of gas velocity in the monolithic _ channels is almost uniform,
justifying that in most cases only one single-channel simulation is performed in literature
to predict/represent the behavior of whole monolith. However, when the empty parts of
the upstream and downstream sections are packed with non-structured packings of
spheres, uniformity is broken. As shown in Figure 3.7(b), the monolith gas flow
distribution is susceptible to the upstream maldistribution.
As a comparison, Figure 3.8 shows the gas-phase velocity profiles under single
phase/two-phase simulation conditions. From this figure, single-phase flow with random
packings brings about most serious anisotropic characteristic of flow in the monolith
channels. And the introduc;tion of solid phase can mitigate seriousness of maldistribution
to sorne degree; however, the problem of solid-phase flow distribution will arise (as
shown in Figures 3.4 and 3.6). Compared to single-/two-phase flow with non-structured
packing, the disabled packings (empty pipe) offer much uniform distribution of gas-phase
flow in the monolith channels, except sorne mal distribution in the channel closest to the
colurnn wall due to the empty pipe velocity profile.
63
16
en E 12
8
4
~ two-phase flow (with nonstructured packirY,;)s)
---v- single-phase flow (with nonstructured packings) ,,,',.w_ single-phase flow (without nonstructured packings)
t\ À Al\ &~~f~l;\ / \j o -ptW 'f , r~~<O~~l , (ij~ ,~~~ë~~~~h~Zr 0.000 0.005 0.010 0.015 0.020 0.025
Radial coordinate (m)
Figure 3.8 Comparison of gas-phase velocities under single-phase/two-phase simulation conditions (z=OAm) with and without the nonstructured packjngs
3.6.3 Effeet of downstream-seetion paeking mode on flow distribution in monolith
It is also of interest to investigate whether or not the downstream-section packing
mod~ has any noticeable impact on flow distribution in monolith section. In this work,
comparative simulations have been performed to examine three different cases with
different packing modes for the downstream section. The first case is default one in
which the downstream section is packed with particles of 10mm in diameter. The second
case is a null packing (empty pipe) which allows the clear fluids to pass in this section.
The last case corresponds to a non-homogeneous composite packing mode. In this case,
while maintaining the larger packed particles (diameter=10mm) in the upstream section,
smaller particles of 5.0mm in diameter are considered in the downstream-section packing,
being entailed with higher flow resistance as opposed to the aforementioned two cases. It
is noted here that in aIl these cases the upstream packing modes are kept same ( i.e.,
64
en en crs E Q) en crs .c Q.
~ "0 Cf)
Ci)
E 5
è 4 ~u o
Q) > 3 en crs 0')
Q) en 2 .~
E crs ~ (jj
~downstream section (dp=10mm particle) - ;)- downstream section (empty pipe) ---6-downstream section (dp=5mm particle)
04--4~--~~--~~-r~~--~6---~~~~~~~~
0.000 0.005 0.010 0.015 0.020 0.025
Radial coordinate (m)
(a) Comparison of the gas velocities
.-------------------------~------------------------, 0.008
2
~downstream section (dp=10mm part icle) ---6-downstream section (empty pipe) -<>-downstream section (dp=5mm particle)
-downstream section (dp=10mm particle) --A.-downstream section (empty pipe) ,,-,""·'~· downstream section (dp=5mm particle)
0.000 0.005 0.010 0.015 0.020
Radial coordinate (m)
(b) Compari son of the solid mass fluxes and the solids holdups
0.006 Cf)
Q. ë2 < o C
0.004 3 CD
0) Q. o·
0.002 ~
0.025
Figure 3.9 Compalison of monolith-section flow distribution characteristics (z=OAm) with and without the nonstructured packing in the downstream section
65
randomly packed with lOmm-in-diameter particles). Figure 3.9 shows the detailed
comparison between the three packing modes for the gas and suspended solid phases. As
in Figure 3.9a, there are sorne appreciable differences in gas-velocities of the three cases
for the two channels near the column wall. However, the overall change of gas velocities
for the whole multichannel system is generally insignificant. In addition, the comparison
of solid-phase mass fluxes and solids pynamic holdups is further performed. Figure 3.9b
depicts a fairly high-degree matching of solid flow distribution characteristic between the
three cases. These simulated results indicate that the effect of downstream-section
packing mode on monolith maldistribution characteristics is generally negligible under
our simulation conditions.
3.6.4 Erreet of partiele size or nonstruetured paekings on flow eharaeteristies in
monolith
The size of the particles in the packed-bed sections affects .not only the near-wall
channeling phenomena but also the pressure drop of reactor system. To reasonably select
the particle sizes for a composite monolith, the effect of particle size in the nonstnlctured
packing sections on the flow characteristic in monolith section needs to be understood. In
this section, the influence of particle size of nonstructured packings on the monolith
maldistribution characteristic and the pressure drop is systematically investigated. In our
simulation, two scenarios characterized by nonuniform and uniform radial porosity
distributions are taken into account, as shown in Table 3.2. For the nonuniform-porosity
scenario, the radial porosity distribution is assessed by Mueller' s correlation and three
particle sizes (diameter= 1 Omm, 5.0mm, and 2.5mm) are considered to be packed in the
upstream and downstream sections. Here, the three simulation cases are referred to as
DplO_Mueller, Dp5.0_Mueller, and Dp2.5_Mueller for brevity (referring to Table 3.2).
In our uniform-porosity scenario, a mean porosity is used as input, which is determined
by averaging the radial porosity distribution based on Mueller' s correlation (for
dp=lOmm). To further gain insight into the contribution mechanisms in interphase
momentum interactions, the inclusion and exclusion of the phase interactions between the
stationary packing and the flowing solid (or gas ) phase are considered here for
decoupling mechanism contribution purpose. As in Table 3.2, three simulation cases
66
(labeled as DplO_GlS l, DplO_GlSO, and DplO_GOSO) are considered for the uniform
porosity scenario. It is noted here that the number 'l ' and '0' denote inclusion and
exclusion, respectively. And 'G' and 'S ' den ote interphase interaction between gas phase
and packed phase and interphase interaction between suspended solid phase and packed
phase, respectively.
Table 3.2 presents the detailed comparison of pressure drop and flow maldistribution
in monolithic channels for the two scenarios (nonuniform radial porosity distribution and
uniform radial porosity di stribution). As shown in thi s table , the pressure drop
contributions from different packing sections, the monolith maldistribution factor and
flow factors for each phase are calculated as the comparison indexes. The relevant details
of the channel locations and the centerline-based pressure sampling in the three-section
monolith system are graphically illustrated in Figure 3.10. The effect of particle size is
0.7 ! '! i i
0.6 ti) t~
0 .5
E 0.4
Q)
êâ 0 ~ N
c 0.3 0 0
=0 -' -' -' (J.) (J.) (J.) ~ c c c 0 c c c 0 cu cu cu 0 0.2 .c. .c. .c.
0 0 0
ëa c =0
0.1 1 :ê i '& c
• & 0 0 ~ Ç) ...J 1 i
-0.1 1 i i i
-0 .2 1 i ! !
-0 .3 ,"~~.
0 0 .005
l' ~ '1'
i i 1
t? 9 ~il
i ! i ! 1
M ~ 0 0
i -' -' (J.) Q) c c c c ! cu cu .c. .c. 0 0
! 1
i i ,,~ ~'
i t!} ~
1
~ 1
1
i A'.~
0.01 0.015
Radial coordinate (m)
Il) 0
-' (J.) c c cu .c. 0
w o -' Q) c c cu
.c. o
l
i ê) 1
! ! ! i i,... : 0, I~ • c • c I~ • 0
! 1
i {!\
0.02 0.025
Figure 3.10 Detai ls of the channel locati ons and centerl ine-based pressure sampling in the three-section monolith system
67
evaluated in case of nonuniform radial porosity distribution. It can be seen from Table
3.2 that that the reduction of particle size results in the increase of bed pressure drops in
the upstream and downstream packed sections, as expected. The pressure drop in the
. monolith section is found to increase as the particle size decreases. Due to the near wall
channeling, the differences in pressure drop between the near-wall region and the bulk
region can be observed in the three packing sections. These differences are magnified in
case of employing packed particle of larger size, corresponding to the lower column-to
particle ratio. The . decrease of particle size will bring a positive contribution to the
improvement of the overall flow maldistribution for the gas phase, as indicated by the
decreasing trend iQ gas-phase maldistribution factor. The gas-phase flow factors in
monolith channels demonstrate specifically the contribution of reducing particle size in
suppressing the severity of the near-wall channeling. As compared to the gas phase, the
effect of decreasing particle size on the maldistribution behavior is not so evident for the
solid phase. With decreasing the particle size, the value of solid-phase maldistribution
factor increases first and then decreases again, showing a non-linear variation relationship.
The solid-phase flow factors in monolith channels also disclose the details of the
nonlinear change, including both the change in peak magnitude and the migration in peak
location. Note that reduction in particle size in the upstream and downstream packed beds
would increase the risk for these sections to plug with biomass particles. Since the
filtration ability of the beds was not included in the model analysis, it is believed that
smaller particle beds would exhibit different maldistribution behaviors as the
permeability of the bed could evolve with biomass particle capture.
Averaging the radial porosity distribution of the DplO_Mueller case leads to a mean
porosity value of 0.4439, which is used as the input of porosity for the uniform-radial
porosity simulation cases (DpIO_GISI, DpIO_GISO, and DpIO_GOSO). It is interesting
to make a direct c~mparison between the DpIO_GISl and DplO_Mueller simulation
cases. In practice, the two cases represent different methodologies in treating the
nonuniformity of radial porosity distribution. From physical viewpoint, the latter takes
into account the radial nonuniformity in porosity distribution while the former neglects
this kind of nonuniformity by simplifying it as flat distribution. It can be seen in Table
3.2 that the DpIO_GISI simulation case with the uniform-radial-porosity assumption can
68
Tab le 3.2 Effect of particle size and radial poros ity distribution of nonstructured packings on the tlow characteristics in monolith
Nonuniforrn radial porosity distribution Uniform radial porosity distribution
Dp lO_Mueller Dp5.0_Mueller Dp2.5_Mueller DplO_GIS I DplO_G l S0 DplO_GOSO Empty-pipe
Pressure drop (Palrn)
Average pressure drop
- upstrearn section -5143.8 -15417. 1 -42 157.9 -7065.4 -6481.3 -23 .8 -24.2
- mono li th secti on -750.8 -770 .2 -949 .8 -855.4 -856.9 -840.2 -840.2
- downstream section -5297.5 - 15335.0 -42338.8 -7035 .0 -6460.0 -31.3 -30.0
Wall-adjacent pressure drop
- upstream section -4743.3 -15300.0 -42256 .7 -7086.7 -6500.0 -36.7 -36.7
- monolith section -898,3 -831.7 -948 .3 -843 .3 -846.7 -835 .0 -835 .0
- downstream section -5100.0 -15360.0 -42380.0 -7060.0 -6480.0 -30 .0 -30.0
Maldistribution Factor
- solids phase 0.298 0.353 0.220 0.077 0.065 0 .030 0.024
- gas phase 0.1 2 1 0.109 0.080 0.031 0.027 0.009 0.007
Flow Factor
- solids phase:
channel_OO 0.822 0.729 0.760 0.973 1.006 1.052 1.062
channel_Ol 0.522 0.654 0.746 0.992 0.992 1.136 1.094
channel_02 0.628 0.653 0.731 0.992 1.005 1.058 1.008
channeL03 0.678 0.690 0.776 0.995 1.026 0 .972 0.957
channel_04 2.122 1.072 0.976 l.018 1.099 0 .931 0.958
channel_05 2.538 3.400 2.180 1. 136 1.240 0 .967 1.0 16
channel_06 0.388 0.602 1.639 1.338 1.04 1 1.021 1.028
channel_07 0.301 0.200 0.191 0.556 0.591 0 .863 0.877
- gas phase:
channel_OO 0.865 0.896 0.956 0.997 0.990 0 .989 0.985
channel_OI 1.069 0.946 0.966 0.991 0.994 0.962 0.974
channel_02 1.034 0.965 0.969 0.99 1 0.991 0.983 1.000
channel_03 0.897 0.934 0.975 0.990 0.984 1.010 1.016
channel_04 0.735 0.815 0.928 0.983 0.963 1.023 1.014
channel_OS 0.699 0.655 0.810 0.948 0 .925 1.007 0.990
channel_06 0.9 13 1.098 0.858 0.899 0.976 0.985 0.983
channel_07 1.787 1.692 1.540 1.202 1.177 1.042 1.037
• These values are calcu lated/averaged using the multichannel centerline sampli ng data (see Figure 10 for the geometri cal detail s)
69
. -~
render a remarkably improved flow distribution characteristics for both the phases, as
opposed to its counterpart (Dp 1 O_Mueller). However, judging from the distribution of
two-phase flow factors , it is found that the near-wall higher loading transport for the gas
phase as weIl as the appearance of dominant peak in the solid-phase mass flux are still
noticeable even in this ideal case. To further get insight into the phenomena, decoupling
interphase interaction is attempted in this work to observe the evolutionary change in
1' 2 .2
·.'~.?1.' '~.; .i", 8.2
illi n lA 0.0
15 .'
••..• :.?:,'.,~ ••..•. ,' ••.• ,.:.,. 4 .. 6
.," 40
:\1 ;~ ,::}: 2.3 .. ;:.,. 1.7
,ù' 1.1 0 .6 0 .0
~ Nonunlfo,m ,ad"" pomsll. d'st"buUon
13.3
:,",;'.',.:.·.·,.'.' •• :.· •. '.·1· ;:
Ji 2 .2 ""'<' 1.6
~~;; ~ .~ ~w 0.7
OA 0 .0 1
1.5
::H'I ~ .; il· ~:~ : .• ,.:,:~,:.:.:.r,:.:1 0.
7 ,":;': 0 .5 ·,:,:':;, 0 .3
0 .2 0.0 1
2 .5
~:~~ . .; 2 .2
.,:. '.'~.I ~: !jll g . 0 .3
0 .0
Uniform radial porosity distribution
11.9
':,:.:" ..• '.'." •••... 1.7 " 1.5 ,'::': 1.3 i} 1.0 ';:::) 0 .8
J'; ~ .~ 0.2 0 .0
Figure 3.11 Effect of parti cie size and porosity radial di stribution on the solid mass flux distribution in the composite monolith system
flow distribution. To this end, the additional simulation cases (Dp 1 0_ G 1 SO and
Dp10_GOSO) are introduced for comparison purpose. By comparing the three simulation
cases, one may conclude that the interphase interaction mechanisms have an
'incremental' contribution in affecting the flow maldistribution; and . the graduaI
exclusions of the interphase interactions lead to improved flow distribution for both the
phases. FinaIly, we present the global contour comparison of the solid-phase mass flux in
the composite monolith for aIl these simulation ,cases (with/without considering non
uniformity in radial porosity distribution), as shown in Figure 3.11. The null-packing case
70
(empty pipe) is also presented here. Comparing with Dp10_00S0, the null-packing case
can be regarded as a variant of Dp 1 0_ OOSO with the porosity value of 1.0. As indicated
in Figure 3.11, the nonuniformity of flow distribution in monolith structured packing
section is to a great extent imprinted with the unique flow characteristics in the upstream
nonstructured (random) packing section.
3.7 Conclusions
In the present work, a process concept for biomass gasification is firstly proposed
which involves the hybridization of gasificationlcombustion reactions in a monolithic
structured reactor by using high-temperature phase-change material to intensif y the
process heat management. Following the proposaI of this concept, a computational fluid
dynamics model is developed to investigate the gas-solid (biomass particles) two-phase
flow distribution characteristics in monolithic structured packings. This model is based
on Eulerian-Eulerian multifluid modeling approach with closure laws according to the
kinetic theory of granular flow. An assemblage of monolithic structured packings with
non-structured packed-bed sections is fully considered in our simulations with a view to
effectively characterizing the flow maldistribution. The non-structured random packed
bed sections are treated as porous media by implementing the non-uniformity of radial
porosity distribution and the interphase interactions through user defined functions
(UDFs).
The numerical investigation was carried out to systematically explore the two-phase
flow distribution in the three-section composite monolith system. The simulation results
indicate that there exists a very strong near-wall channeling for the gas-phase flow in the
fixed-bed random packings. The suspended particles are distributed unevenly across the
monolith assemblage cross-section and the highest biomass solids flux takes place at a
dimensionless column radius 0.66. The effect of downstream-section packing mo.des on
monolith maldistribution characteristics can be generally consideredas negligible under
our simulation conditions. The reduction of particle size in the non-structured packing
sections results in an increase of pressure drop in the monolith section. In addition,
71
decreasing particle sizes leads to a positive improvement in the overall flow distribution
for the gas phase and a nonlinear variation trend in flow maldistribution for the solid
phase. Compared to the nonuniform-radial-porosity assumption, the uniform-radial
porosity assumption provides considerably improved flow distribution characteristics for
both the gas and solid phases. The interphase interaction mechanisms are found to exhibit
"incremental" contributions in affecting the flow mal-distribution. GraduaI exclusion of
the interphase interactions leads to an improved flow distribution for both the phases. The
non-uniformity of flow distribution in monolith structured packing section is shown to be
imprinted to a great extent with the unique flow characteristics in the upstream
nonstructured packing section. The simulation results indicate the ability of CFD models
to capture the non-uniformities of the flow pattern in monolithic structured packing,
which we believe will further aid our development of the process concept.
Acknowledgement
Financial support from the "Chaire de recherche du Canada en procédés et matériaux
pour des énergies durables" of the N aturai Sciences and Engineering Research Council
(NSERC) is gratefully acknowledged.
Nomenclature
a constant in Eq.(l)
ag
volume fraction of phase g
aq
volume fraction of phase q
as volume fraction of phase s
b constant in Eq.(l) or coefficient in turbulence model
Cf) drag coefficient
d p diameter of packed particle, m
d~ diameter of suspended parti cIe, m
72
D diameter of column, m
D* hydraulic diameter of a packed bed, m
e,fS restitution coefficient of particle collisions
fk interaction coefficient between suspended phase and packed particles
F,. Froude number
g gravitational constant, m2/s
go radial distribution function of interparticle collisions
G,~ flux of suspended phase, kg/m2
s
1 unit tensor
12D second invariant of the deviatoric stress tensor
Jo zeroth order Bessel function
ke, diffusion coefficient for granular energy, kg/s m
mi.O
theoretical uniform flow-rate of the qth phase in ith channel, kg/s
miq realistic mass flow-rate of the qth phase in th channel, kg/s
M q maldistribution factor of the qth phase in ith channel f
Neil number of channels
Nq
number of phases
p fluid pressure, N/m2
Ps solid pressure, N/m2
r radial coordinate, m
r * dimensionless radial coordinate, [-]
Re~ relative Reynolds number
S g source term due to gas-packing interaction
73
s~ source term due to particulate-packing interaction
time, s
U g axial interstitial gas velocity at the inlet, mis
Us axial interstitial solids velocity at the inlet, mis
Ü s superficial suspended solids velocity vector
V g superficial ' gas velocity
V g velocity of gas phase, mis
Vq velocity of phase q, mis
V s velocity of solid phase, mis
v~ particulate fluctuating velocity, mis
Greek letters
f3 combined coefficient of interphase momentum exchange, kg/m3 s
f3gs coefficient of interphase momentum exchange, kg/m3 s
f3Erglln fluid-solid interaction coefficient of the Ergun equation, kg/m3 s
f3wen-: YII fluid-solid interaction coefficient of the Wen-Yu equation, kg/m3 s
E voidage of packed bed
EB constant in Eq.(l)
qJgs switch function
YB, collisional dissipation of energy,kg/s3 m
li flow factor of the qth phase in {h channel
À\ bulk v.iscosity of solid phase, Pa s
f.1g
shear viscosity of gas phase,Pa s
74
J1s shear viscosity of solid phase, Pa s
(}ç granular temperature,m2 /S2
Pg density of phase g, kg/m3
Pq density of phase q, kg/m3
Ps density of phase s, kg/m3
Tg gas stress tensor, N/m2
Ts solid stress tensor, N/m2
Subseripts
g gas phase
i-th channel
q q-th phase
s solid suspended phase
Literature Cited
(1) Kobayashi, N., Guilin, P., Kobayashi, J., Hatano, S., Itaya, Y., Mori, S. , A new
pulverized biomass utilization technology, Powder Teehnology, 2008,180(3):272-283.
(2) Florin, N. H., Harris, A. T., Enhanced hydrogen production from biomass with in
situ carbon dioxide captùre using calcium oxide sorbents, Chem. Eng. Sei., 2008,
63(2):287 -316.
(3) Levenspiel, O., What will come after petroleum?, Ind. Eng. Chem. Res., 2005,
44(14): 5073-5078.
75
(4) Pletka R, Brown RC, Smeenk J. Indirectly heated biomass gasification using a
latent heat ballast.l:experimental evaluations, Biomass & Bioenergy, 2001, 20(4): 297-
305.
(5) Pletka R, Brown RC, Smeenk J. Indirectly heated biomass gasification ' using a
latent heat ballast. Part 2:modeling, Biomass & Bioenergy, 2001, 20 (4): 307-315.
(6) Potic, B., Kersten, S. R. A., Ye, M., van der Hoef, M. A., Kuipers, J. A. M., van
Swaaij, W. P. M., Fluidization with hot compressed water in micro-reactors, Chem. Eng.
Sei., 2005, 60(22): 5982-5990.
(7) Ding, Y. L., Wang, Z. L., Ghadiri M, Wen, D. S., Vertical upward flow of gas
solid two-phase mixtures through monolith channels, Powder Teehnology, 2005,153 (1):
51-58.
(8) Ding, Y. L., Wang, Z. L., Wen, D. S., Ghadiri, M., Fan, X. F., Parker, D., Solids
behavior in a di lute gas-solid two-phase mixture flowing through monolith channels,
Chem. Eng. Sei., 2006,61(5): 1561-1570.
(9) Mueller, G. E., Radial void fraction distributions in randomly packed fixed beds
of uniformly sized spheres in cylindrical containers, Powder Technology, 1992,72: 269-
275.
(10) Giese, M., Rottschafer, K., Vortmeyer, D., Measured and modeled superficial
flow profiles in packed beds with liquid flow, AIChE Journal, 1998,44(2):484-490.
(11) Lun, C. K. K., Savage, S. B., Jeffrey, D. J., Chepumiy, N., Kinetic theories for
granular flow: inelastic particles in Couette flow and slightly inelastic particles in a
general flow field, J. Fluid Mech., 1984,140:223-256.
(12) Gidaspow, D., Bezburuah, R., Ding, J., Hydrodynamics of circulating fluidized
beds, kinetic theory approach. In: Potter OE, Nicklin DJ (Eds.), Fluidization VII,
Proceedings of the 7th Engineering Foundation Conference on Fluidization, New York,
1992, pp.75-82.
76
(13) Gidaspow, D., Multiphase Flow and Fluidization: Continuum and Kinetic
Theory Descriptions. Academic Press, New York, 1994.
(14) Wen, C. Y., Yu, Y. H., A generalized method for predicting minimum
fluidizationvelocity, AIChE Journal, 1966,12(3): 610.
(15) Ergun, S., Fluid fIow through packed columns, Chemical Engineering Progress ,
1952,48(2): 89-94.
(16) Yamaoka, H., Mechanisms of hanging caused by dust in a shaft fumace, ISIJ
International, 1991,31 :939-946.
(17) Shibata, K., Shimizu, M., Inaba, 5., Inaba, S., Takahashi, R., Yagi, J., Pressure
loss and hold up powders for gas-powder two phase fIow in packed beds, ISIJ
International, 1991,31: 434-439.
(18) Van der Ham, A. G. J., Prins, W., Van Swaaij, W. P. M., Hydrodynamics of a
pilot-plant scale regularly packed circulating fluidized bed, AIChE Symp. Ser. , 1993,89:
53-72.
(19) Dong, X. F., Zhang, S. J., Pinson, D., Yu, A. B. , Zulli , P., Gas-powder flow
and powder accumulation in a packed bed: II-numerical study, Powder Technology,
2004,149:10-22.
(20) Boremans, D., Rode, S., Wild, G. , Liquid fIow distribution and particle-fluid
heat transfer in trickle-bed reactors: the influence of periodic operation, Chemical
Engineering and Processing, 2004,43: 1403-1410.
(21) Hoek, P. J. , Wesseling J. A., Zuiderweg, F. J. , Small scale and large scale liquid
maldistribution in packed columns, Chem. Eng. Res~ Des., 1986, 64:431-449.
(22) Marcandelli, C. , Wild G. , Lamine, A. S. , Bernard, J. R., Liquid distribution in
trickle-bed reactors, oil and gas science and technology - rev, IFP, 2000,55:407-415.
77
(23) Ding, Y. L., Wang, Z. L., Wen, D. S., Ghadiri, M., Fan, X. F., Parker, D., Solids
behaviour in a gas-so1id two-phase mixture flowing through a packed partic1e bed, Chem.
Eng. Sei., 200S,60( 19):5231-5239.
(24) Liu, S. Q., Ding, Y. L., Wen, D. S., He, Y. R., Modelling of the behaviour of
gas-so1id two-phase mixtures flowing through packed beds,Chem. Eng. Sei., 2006,61:
1922 -193l.
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Chapter 4 Conclusions and Recommendations
4.1 General conclusions
Biomass is a very important renewable energy source and it holds great potential for
sustainable energy conversion processes. With the depletion of fossil fuel sources as well
as the concem over the evolving global warming, there is considerable worldwide interest
in exploiting the utilization of biomass renewable energy sources, particularly because it
is believed that energy obtained from biomass has a carbon-neutral cycle. This situation
calls for the development of a biomass-based but energy efficient and environment
friendly system with better environmental acceptability. Gasification to produce
biosyngas is regarded as one of the most promising options for biomass beneficiation.
However, thermodynamics and intrinsic kinetics dictate that endothermic biomass
gasification reactions have to be carried out at high temperatures, which demands
efficient heat supply and recovery policy. The concept of allothermal gasification offers
an attractive solution for implementing high-temperature reactions by coupling strongly
endothermic reactions with exothermic reactions. However, implementing the concept in
practice is not straightforward.
In this work, an innovative biomass gasification process concept is proposed, which
involves coupling of the gasification and combustion processes in monoliths with high
temperature phase-change-material. The proposed process is implemented in a monolithic
structured reactor and intensified by periodic operation mode. To effectively' design and
optimize . this novel process, knowledge from different important fields (including
biomass gasification, monolith reactor engineering, high-temperature phase change
material, and gas-solids fluidization) is required. Among them, modeling and
understanding of gas-solid (biomass particles) flow hydrodynamics in monolithic
structured reactor is very important, in view of the complexity of two-phase flow in
structured packings. This work relates to our understanding of the hydrodynamics, as
deduced from Euler-Euler computational fluid dynamics (CFD) modeling. A
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computational fluid dynamics model is developed to investigate the gas-solid (biomass
particles) two-phase flow distribution characteristics in monblithic structured packings.
This model is based on Eulerian-Eulerian multifluid modeling approach with closure
laws according to the kinetic theory of granular flow. A three-region composite
monolithic structured reactor is con'sidered in our simulations with a view to effectively
characterizing the flow maldistribution. The non-structured packed-bed sections are
treated as porous 'media by implementing the non-uniformity of radial porosity
distribution and the interphase interactions through user defined functions (UDFs).
The numerical investigation is carried out to systematically explore the two-phase
flow distribution in the three-section composite monolith system. The simulation results
indicate that there exists a very strong near-wall channeling for the gas-phase flow in the
fixed-bed random packings. The suspended particles are distributed unevenly across the
monolith assemblage cross-section and the highest biomass solids flux takes place at a
position of 0.66 times the column radius. The effect of downstream-section packing
modes on monolith maldistribution characteristics can be generally negligible under our
simulation conditions. The reduction of particle size in the nonstructured packing sections
results in an increase of pressure drop in the monolith section. In addition, decreasing
particle size leads to a positive improvement in the overall flow maldistribution for the
gas phase and a nonlinear variation trend in flow maidistribution for solid phase.
Compared to the nonuniform-radial-porosity assumption, the uniform-radial-porosity
assumption can render considerably improved flow distribution characteristics for both
the gas and solid phases. The interphase interaction mechanisms are found to have an
'additive ' contribution to affect the flow maldistribtution and the graduaI exclusions of
the interphase interactions lead to an evolutionarily positive improvement in flow
distribution for both the phases. The nonuniformity of flow distribution in monolith
structured packing section is shown to be imprinted to a great ex~ent with the unique flow
characteristics in the upstream nonstructured packing section.
The simulation results demonstrate the ability of CFD models to capture the non
uniformities of the flow pattern in monolithic structured packing, which we believe will
further aid our development of the process concept. It is suffice to say that the present
80
model has been an important enabling step in the direction of our research on the process
concept.
4.2 Recommendations for future investigations
The following recommendations are made regarding the logical progression and
continuance of the present work:
(1) Future work is recommended to address the coupling of the gas-solid flow
dynarnics with transient biornass gasification/cornbustion process in rnonolithic
structured reactor by using the multichannel flow model;
(2) Future work is recommended to introduce the present 2D modeling
methodology to explore a full-scale 3D simulation of the unconventional
composite monolith geometry, using improved computational resource;
(3) Future work is recommended to investigate the turbulence effect and its impact
on multichannel flow distribution characteristics in monolith structured reactors.
81
