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研究生: 謝勝強
Qiang, Sia Sheng
論文名稱: 生質物流體化床快速熱裂解模擬與生質裂解油改質製程研究
Analysis of biomass fluidized bed fast pyrolysis based on CFD and study on bio-oil upgrading process towards hydrogenation
指導教授: 王偉成
WANG, WEI-CHENG
學位類別: 碩士
Master
系所名稱: 工學院 - 航空太空工程學系
Department of Aeronautics & Astronautics
論文出版年: 2018
畢業學年度: 106
語文別: 英文
論文頁數: 54
中文關鍵詞: 生質物熱裂解數值模擬生質燃料氫化反應加氫脫氧
外文關鍵詞: Biomass Fast pyrolysis, Computational Fluid Dynamics, Hydrodynamics, Pyrolytic oils, Hydrodeoxygenation
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  • 傳統石化燃料仍然是現今工業應用能源的主要供應源,這樣不僅會加速溫室氣體的排放,間接的也會造成全球暖化。除了環境污染的問題之外,石化燃料的供給還能持續多久也成為一大考量,勢必在未來必須得有新的替代燃油。生質物快速熱裂解會是另一個選擇,它能將農業廢棄物或是任何一種生質物轉化為可使用的生質物裂解油。由於裂解油的一些特性,在應用端上因此被局限,加氫脫氧製程可以有效的解決裂解油的不好特性,並將其提升至更為接近運輸燃料的性質,提高使用效率,並提供一個可再生的綠色燃油。但在生產裂解油之前,其量化系統的建造是一大難題,現階段的設備都是依照經驗以及實驗室規模的架設為參考進行修改的,過程中將需要消耗大量的資金以及時間進行測試才能得知結果。這部分若能以電腦計算流體力學數值分析(CFD)來當做輔助工具的話,在成本開銷以及時程上將能有非常顯著減少。近年來CFD已有非常大的進步,其中收入了各項流體力學計算方式,并也能有效的提供可靠的仿真結果。在業界中也早已被投入使用與操作上的實際情況進行驗證,證明了CFD確實有可靠的重現性。這篇研究利用CFD商業軟體進行模組建構,針對流體化床生質物熱裂解內部物性與化性進行模擬,計算出不同試驗參數對於產量的影響,藉由計算結果可以看出模組的可行性,在後續量化設備建構中將會有很大的幫助。後段再建構氫化技術,對裂解油進行加氫脫氧,改善并優化至接近運輸燃料的油品特性,由結果得知,裂解油在進行優化后,其氧含量可從原先的51%有效的降低至1%。

    At present, Computational fluid dynamics (CFD) has been widely applied as assistant tool in both industrial application and scientific research. In this study, a lab-scale fluidized bed biomass fast pyrolysis performed as a continuous type in an euler-euler multiphase framework. For the model, a multiple component and stage model scheme have utilized for the description of the chemical reaction and fluid dynamics mechanism. The composition of biomass consists with three major components: Cellulose, Hemicellulose, and Lignin, which are the dominant in overall. Products from the pyrolysis process are categorized into the several groups: incondensable gas, bio oil, and solid bio char. In our work, we focuses on the variation of the experimental conditions to each of the products yield. This model is built and employed to study the detailed kinetic mechanism in a lab-scale reactor. With the CFD results, a better known of the hydrodynamic mechanism involves in different range of reactor can be predict. Furthermore, optimizing process to an industrial-scale applications will also be compromised. In additions, Fossil fuels remain to be the major sources of the energy for industrial applications. However, non-renewable fuels contribute to global warming as increasing the greenhouse gas (GHG) emissions, Asides the issues of pollution, uncertainties still exist on how long can the limitation reserves will last. Hydro-deoxygenation (HDO) is an effective method to upgrade the heavy pyrolytic oils into valuable fuels and to become an alternative in the future. Catalyst Palladium supported on active carbon, namely, Pd/C used in the upgrading process of heavy pyrolytic oils. In this study, a series of operating parameters were prepared, characterized and evaluated. The continuous flow reactor at a temperature between 300ºC and 360ºC under 6 MPa pressure indicate that with a high operating temperature can effectively upgrade the pyrolytic oils by converting the heavy species (long chain carbohydrates) into lighter species as the coking tendency reduce instead. The high pressure of hydrogen condition ensures the solubility through the catalyst to have a fine reaction.

    Content ABSTRACT III 中文摘要 IV ACKNOWLEDGEMENT V CONTENT VI LIST OF TABLES VIII LIST OF FIGURES IX NOMENCLATURE XI CHAPTER I 1 INTRODUCTION 1 CHAPTER II 9 NUMERICAL APPROACH 9 2.1 Numerical description 9 2.2 Governing equations 10 2.3 Boundary & initial condition 13 2.4 Phases and chemical reactions 15 2.5 Modeling Procedure 18 CHAPTER III 19 EXPERIMENTAL SETUP 19 3.1 Materials 19 3.2 Equipment 19 3.3 Experimental procedures 20 3.4 Analytical methods 21 CHAPTER IV 24 RESULTS AND DISCUSSION 24 4.1 CFD simulation 24 4.1.1 Flow regime comparison 24 4.1.2 Fluidized bed reactor hydrodynamics 26 4.1.3 Temperature contribution to product yield 30 4.1.4 Biomass particle size contribution to product yield 31 4.1.5 Feeding rate contribution to product yield 32 4.2 Hydrodeoxygenation of heavy species bio-oil 33 4.2.1 Experimental products qualitative 33 4.2.2 Variation of temperature against product distribution 37 4.2.3 Variation of hydrogen pressure against product distribution 39 4.2.4 Variation of LHSV against product distribution 41 4.2.5 Variation of H2-to-Feedstock ratio against product distribution 43 CHAPTER V 45 CONCLUSION 45 REFERENCES 47

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