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姓名	丁公平(Cong-binh Dinh)  查詢紙本館藏	畢業系所	機械工程學系
論文名稱	應用於生質物快速熱裂解之氣泡流體化床反應器其熱傳遞現象之模擬分析研究 (CFD modeling of hydrodynamics with heat transfer in bubbling fluidized-bed reactors applied to fast pyrolysis of biomass)
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摘要(中)	本研究探討在生物質快速熱裂解過程中發生的流體力學和熱傳遞現象。透過結合尤拉多重流體模型和顆粒流的動力學理論之數值方法並將其應用到模擬氣泡流化床反應器的氣-固流動行為。在這項研究中，具有特定屬性的稻殼和石英砂在此分別作為生物質和熱惰性物質。由於這些系統的動態特性往往是混亂的，故該模型首先以先前的研究結果加以驗證其可行性，接下來就參數方面進行一廣泛的研究，以確定其對流動分佈和相位之間的熱傳遞的主要變量的影響。該組統御及組成方程式是由商業計算流體力學程式軟體，ANSYS FLUENT 13.0.0解得。在此，各個方面，如固相體積分率，速度，床體混合，粒子溫度，熱溫度，壓力，排除輻射熱傳遞機制也進行了詳細研究。從兩個不同的拖曳模式，即，Syamlal-O′Brien和Gidaspow結果的比較，也包涵在本論文中。結果發現，不同拖曳模型和預測壓降之間沒有顯著差異，而隨著增加的進氣速度而稍微的增加。壓降則隨著生物質初始體積分率的的減少而增加。 　固相體積分率和速度剖面的分佈分別可在不同的情況下獲得。雖然結果顯示流化床仍保持固有的混沌性質，但所獲得的總體趨勢仍然與以前的研究有良好的一致性。本結果還表明，該固體混合是受到入口氣體速度和生物質的初始體積分率的強烈影響。較佳的粒子混合可以通過增加入口氣體速度來獲得。 兩模式固體顆粒溫度被發現在床體底部和頂部附近會比較高。它隨著入口氣體速度的增加而增加，但是隨著生質物量初始百分比的增加而降低。發生在流化床內的熱傳遞是由固體的溫度，熱傳導係數的變化和表面熱通量的分佈所描述。這兩種熱傳遞量在密相床區被觀察到佔有一定主導地位，因為他們在流化床中強烈地取決於固體濃度。由於強烈攪拌，生質物的溫度分佈在床體區域相當均勻。不斷增加的進氣速度提升固體顆粒的混合，從而導致了顆粒間和壁面對於粒子之間的有效熱傳遞。模擬中的總表面熱通量和不同拖曳模型之間沒有顯著差異。 　總體而言，目前的結果是基於一些假設和受限於此工作過程中的時間和計算量的限制而以二維模式呈現。因此，這些結果不能充分地描述在流化床反應器中發生的熱物理過程。今後的工作應考慮到用更少的假設，建立一個完整的三維空間模型。此外，模擬與實驗結果的定量比較，亦可進一步驗證吾人所建議設置的實驗設備。
摘要(英)	The present study investigates the hydrodynamics and heat transfer phenomena that occur during the biomass fast pyrolysis process. A numerical approach that combines an Eulerian multifluid model and the kinetic theory of granular flow applied to simulate the gas-solid flow in a bubbling fluidized bed reactor. In this study, rice husk and quartz with specified properties have been used as biomass and inert material, respectively. Since the dynamics of these systems are often chaotic, the model was first validated the feasibility using previous findings, then an extensive parametric study was conducted to determine the effects of the major variables on the flow distribution and the heat transfer between the phases. The set of governing and constitutive equations was solved by the commercial computational fluid dynamics code, ANSYS FLUENT 13.0.0. Herein, various aspects such as solid volume fraction, velocities, bed mixing, granular temperature, thermal temperature, pressure, heat transfer mechanisms excluding radiation were studied in detail. A comparison of results from two different drag models, namely, Syamlal-O’Brien and Gidaspow, was also included in this thesis. It was found that there was no significant difference between the predicted pressure drops for different drag models, whereas it slightly increased with the increasing inlet gas velocity. The pressure drop increased with decreasing the initial volume fraction of biomass. The distribution of solid volume fraction and velocity profiles were obtained for different cases. Although the results revealed the inherently chaotic nature of fluidized bed, the general trends were still obtained which agree good with previous studies. The results also indicated that the solids mixing was strongly influenced by the inlet gas velocity and the initial volume fraction of biomass. Better particle mixing could be obtained by increasing the inlet gas velocity. The granular temperatures of both solids were found to be higher near the bottom and the top portion of the bed. It increased with the increasing inlet gas velocity but with the decreasing initial percentage of biomass. The heat transfer happening inside the fluidized bed was described by the distribution of solids temperature, the variation of heat transfer coefficients and the surface heat fluxes. Both heat transfer quantities were observed to be dominant in the dense bed regions as they strongly depend on the solids concentration in the fluidized bed. Due to the strong mixing, the distribution of biomass temperature was fairly homogeneous in the bed region. The increasing inlet gas velocity promoted the mixing of solid particles, thus resulted in effective heat transfer between the particles and wall to particles. There was no significant difference between the simulated total surface heat fluxes for different drag models. Overall, the current results were based on some assumptions and in two-dimensions only due to the limit of time and computational effort during this work. Therefore, those results could not describe the adequately thermo-physical processes occurring in the fluidized bed reactor. A full three-dimensions model with less assumptions should be taken into account in future work. Furthermore, a quantitative comparison of the simulations with the experimental results can be done to further validate the utility of the suggested setup.
關鍵字(中)	★ 生質物快速熱裂解 ★ 流體化床反應器 ★ 流體動力學 ★ 計算流體力學 ★ 固體混合 ★ 尤拉多重流體模型	關鍵字(英)	★ biomass fast pyrolysis ★ fluidized bed reactor ★ hydrodynamics ★ computational fluid dynamics ★ solids mixing ★ Eulerian multifluid model
論文目次	Acknowledgement i Abstract ii Table of Contents iv List of Figures viii List of Tables xii Nomenclature xiii Chapter 1: Introduction 1 1.1. The potentials of biomass energy and the computational fluid dynamics (CFD) modeling of biomass pyrolysis process 1 1.2. Research motivation and objectives . 2 1.2.1. Motivation 2 1.2.2. Objectives 3 1.3. Thesis structure . 4 Chapter 2: Fundamental overview 5 2.1. Overview of biomass energy resources 5 2.1.1. What is biomass? 5 2.1.2. Biomass structure and constituents 6 2.1.3. A brief information about rice husk 6 2.2. Biomass conversion technologies 7 2.2.1. Motivation for biomass conversion 7 2.2.2. Basic features and classification of thermochemical technologies 8 a) Combustion 8 b) Gasification 9 c) Pyrolysis 9 2.3. Fluidized bed technology – overview 11 2.3.1. Development of fluidized bed technology 11 2.3.2. Fluidized bed reactor: characteristics, advantages and disadvantages 12 a) Characteristics 12 b) Distributor 12 c) The advantages and disadvantages 13 2.3.3. Regimes of fluidization and their characteristics 13 a) Bubbling regime 13 b) Slugging regime 14 c) Turbulent regime 14 d) Pneumatic transport regime 14 2.3.4. Geldart’s classification of particles 15 2.3.5. Quality of fluidization 16 2.4. Fluidized-bed fast pyrolysis of biomass systems 16 2.4.1. Reactor 17 2.4.2. Feeding system 18 2.4.3. Char separators and collection system 18 2.4.4. Condensers and liquid collecting system 18 2.4.5. Heating system and other devices 18 2.5. Heat transfer mechanisms in pyrolyzers 19 2.5.1. Methods of heating to pyrolysis reactor 19 2.5.2. Heat of pyrolysis reaction 20 2.5.3. Heat transfer at the level of single particle 20 2.6. Modeling chemical and physical processes of biomass pyrolysis 21 2.6.1. Chemical kinetics of biomass pyrolysis 21 2.6.2. Transport models of biomass particle pyrolysis 22 2.7. Definition of some important parameters and concepts 22 2.7.1. Solid mixing and segregation 22 2.7.2. Superficial gas velocity 25 2.7.3. Minimum fluidization velocity 26 2.7.4. Bed expansion 27 2.7.5. Pressure drop 27 2.7.6. Restitution coefficient 28 2.7.7. Specularity coefficient 29 2.7.8. Mass flow rate 29 2.7.9. Heat transfer coefficient – Heat flux 29 Chapter 3: Methodology and Model descriptions 31 3.1. An overview on CFD simulation technology for designing and optimising reactors 31 3.2. Introduction of the CFD software, ANSYS FLUENT version 13.0.0 32 3.2.1. Pre-processing 32 3.2.2. Solving 32 3.2.3. Post-processing 32 3.2.4. Simulation procedure for multiphase flow model 33 3.3. Eulerian multiphase flow model for gas-solid flow 35 3.3.1. Governing equations 35 3.3.2. Constitutive relations 36 3.3.3. The momentum transfer between the phases 37 a) The momentum transfer between the gas and the solid phases 37 b) The momentum transfer between the solid phases 39 3.4. Kinetic theory of granular flow (KTGF) for granular phases 39 3.4.1. Granular temperature 40 3.4.2. The radial distribution function 41 3.4.3. Granular conductivity 41 3.5. Turbulent model 42 3.5.1. The standard k-ε turbulent model 42 3.5.2. The turbulence variables used for boundary conditions 43 a) Turbulence intensity 43 b) Turbulent viscosity ratio 43 c) Turbulence length scale 44 d) Calculating turbulence values for boundary conditions 44 3.6. Heat transfer model 44 3.6.1. The energy balance for the gas phase and solid phases (conservation of energy) 44 3.6.2. Heat transfer in particle scale 46 3.7. A coupled DPS-CFD model 46 3.8. Literature review – Advances in modeling and simulation of biomass pyrolysis in fluidized bed reactor 47 3.8.1. Numerical analysis of the segregation and mixing behavior of binary mixtures in a gas–solid fluidized bed reactor 47 3.8.2. Numerical investigation of mechanisms in gas-solid fluidized bed reactors 51 3.8.3. Modeling and simulation of hydrodynamics and heat transfer in fluidized bed reactors applied for biomass pyrolysis process 56 3.9. Present works - Model descriptions 60 3.9.1. Assumptions 60 3.9.2. Methodology 61 3.9.3. Model descriptions 62 a) General 63 b) Models 63 c) Materials 64 d) Phases 65 e) Boundary conditions 67 f) Solution methods 72 g) Solution controls 73 h) Solution initialization 74 i) Run calculation 76 j) Results 77 Chapter 4: Results and Discussion 78 4.1. Generalized flow behaviors in fluidized bed reactor 78 4.1.1. The contours of volume fraction of gas and solid phases in the reactor 79 4.1.2. Study of the pressure fluctuation and pressure drop 82 4.1.3. Study of the mixing and segregation 84 4.1.4. The velocity vectors of gas and solid phases in the reactor 85 4.1.5. The contours of static temperature of gas and solid phases in the reactor 87 4.1.6. Study of the heat transfer between the phases 91 a) Heat fluxes 91 b) Heat transfer coefficients 94 4.1.7. Study of the heating-up rate 96 4.2. Effects of superficial inlet gas velocity 96 4.3. Effects of bed compositions 101 4.4. Effects of drag models 105 4.5. Effects of thermal conditions 109 4.6. The sensitivity analysis with effect of mesh sizes 112 Chapter 5: Conclusions and Future works 115 5.1. Conclusions 115 5.2. Future works 116 References 117
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指導教授	蕭述三(Shu-san Hsiau)	審核日期	2014-7-25
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