淡江大學覺生紀念圖書館 (TKU Library)
進階搜尋


下載電子全文限經由淡江IP使用) 
系統識別號 U0002-2407200601302100
中文論文名稱 薄膜反應器之最適化-應用基因演算法
英文論文名稱 Optimization for Membrane Reactor using Evolutionary Algorithm
校院名稱 淡江大學
系所名稱(中) 化學工程與材料工程學系碩士班
系所名稱(英) Department of Chemical and Materials Engineering
學年度 94
學期 2
出版年 95
研究生中文姓名 張程凱
研究生英文姓名 Cheng-Kai Chang
學號 693360801
學位類別 碩士
語文別 中文
口試日期 2006-06-26
論文頁數 188頁
口試委員 指導教授-張煖
委員-程學恆
委員-陳錫仁
中文關鍵字 基因演算法  最適化  薄膜反應器  氫氣生成  甲醇合成  模擬 
英文關鍵字 Evolutionary Algorithm  Genetic Algorithm  Optimization  Membrane Reactor  Hydrogen Production  Methanol Synthesis  Simulation 
學科別分類
中文摘要 本論文建立了自甲烷的自熱重組生成氫氣系統及由二氧化碳和氫氣反應合成甲醇的觸媒薄膜反應器之ㄧ維非等溫的嚴謹模式及電腦程式,包括了觸媒顆粒內部的反應及質傳機制的考量,可用以模擬此二應用之薄膜反應器性能並結合基因演算法進行最適化分析。
本論文並應用精英非優異揀選基因演算法分別完成了氫氣生成與甲醇合成的薄膜反應器系統之多目標函數最適化,即目標產物產率、主要進料流量及系統可用能損失之三目標函數,分析個案包括基本個案及改變反應器裝置尺寸,薄膜面積與厚度,之不同個案。對於各個案之最適解,並完成了目標函數和變數間之關聯性分析。
兩個系統最適解均顯現目標產物流量與主要進料流量及可用能損失間之妥協特性。增加薄膜面積或減少薄膜厚度所獲得最適解之產物產率均較高,對氫氣系統而言,改變薄膜面積較改變薄膜厚度之影響為大,對甲醇系統而言,則是影響程度相當。目標函數與變數間之相關性隨薄膜面積及厚度不同而有不同。

英文摘要 For the systems of hydrogen production from autothermal reforming of methane and methanol synthesis from carbon dioxide and hydrogen, rigorous models and computer programs of catalytic membrane reactors are established. The models are one-dimensional and nonisothermal, and the intraparticle reaction and mass diffusion are considered. The models are incorporated into the Genetic Algorithm for multiobjective optimization.
Elitist Non-dominated Sorting Genetic Algorithm (NSGA-Ⅱ) is adopted for the multibojective optimization of the membrane reactor of these two systems. The triple objective functions are hydrogen or methanol production rate, methane or hydrogen feed rate, and the exergy loss. Optimization analyses are accomplished for several different cases with different membrane area as well as membrane thickness. For each case, correlations between objective functions and variables are analyzed for the optimal solutions.
For both systems, the optimal solutions show trade-offs between the hydrogen or methanol production rate and the other two objective functions, i.e. the methanol or hydrogen feed rate and the exergy loss. The increase of membrane area or decrease of membrane thickness can bring about the increase of product rate. The characteristics of the correlations between objective functions and variables are different for cases with different membrane area and/or thickness.
論文目次 目錄
誌謝 .....................................................i
中文摘要 ................................................ii
英文摘要 ...............................................iii
目錄 ....................................................iv
圖目錄 ................................................viii
表目錄 .................................................xii
第一章 前言 ..............................................1
第二章 文獻回顧 ..........................................4
第三章 薄膜反應器之系統與模擬 ............................9
3.1氫氣薄膜反應器 ........................................9
3.1.1 化學反應和反應動力 ..........................9
3.1.2 薄膜特性 ...................................12
3.1.3 反應器配置 .................................12
3.1.4 模式建立 ...................................14
3.1.5 數值方法及程式架構 .........................17
3.1.6 模式驗證 ...................................18
3.1.7 系統操作變數之影響 .........................21
3.2 甲醇薄膜反應器 ..................................28
3.2.1 化學反應和反應動力 .........................28
3.2.2 薄膜特性 ...................................30
3.2.3 設備配置 ...................................31
3.2.4 模式建立 ..........................................32
3.2.5 數值方法及程式架構 .........................35
3.2.6 模式驗證 ...................................36
3.2.7 系統操作變數之影響 .........................39
第四章 基因演算法最適化 .................................46
4.1 基因演算法 ......................................47
4.1.1 初始族群(Initial Population) ..............49
4.1.2 目標函數計算(Objective Function Evaluation) 49
4.1.3 鋒線(面)決定(Front Decide) .................50
4.1.4 計算擁擠距離(Evaluation Crowding Distance ) 51
4.1.5 二者競賽淘汰(Binary Tournament Selection)...51
4.1.6 交越(Crossover) ............................52
4.1.7 突變(Mutation) .............................53
4.2 薄膜反應器之最適化 ..............................54
4.2.1 氫氣生成系統 ...............................54
4.2.2 甲醇合成系統 ...............................55
4.3 基因演算法參數決定 ..............................56
第五章 薄膜反應器最適化 .................................59
5.1 氫氣生成系統 ....................................59
5.1.1 基本個案最適化分析 ................................59
5.1.2 基本個案關聯性分析 ........................71
5.1.3 反應器裝置參數之影響 ......................74
5.2 甲醇合成系統 ........................................81
5.2.1 基本個案最適化分析 ............................81
5.2.2 基本個案關聯性分析 ........................90
5.2.3改變設備裝置之影響 .........................92
第六章 結論 .............................................99
符號說明 ...............................................102
參考文獻 ...............................................107
附錄A 全域雲規正交配置法說明 .........................111
附錄B 氫氣生成系統不同裝置尺寸個案之最適解變數資料 ....113
附錄C 甲醇合成系統不同裝置尺寸個案之最適解變數資料 ....123
附錄D 氫氣生成系統不同裝置尺寸個案下最適解之變數及目標函數分佈圖 .................................................135
附錄E 甲醇合成系統不同裝置尺寸個案下最適解之變數及目標函數分佈圖 .................................................159

圖目錄
圖3-1 氫氣薄膜反應器之配置 .............................13
圖3-2 程式架構圖-氫氣薄膜反應器 ........................18
圖3-3 不同甲烷進料流率對氫氣產率之影響 .................20
圖3-4 反應器內部之溫度分佈 .............................20
圖3-5 反應器內部氫氣產率分佈 ...........................21
圖3-6 氫氣生成系統觸媒顆粒內部各成份濃度之分佈 .........23
圖3-7 氫氣生成系統操作變數對性能之影響 .................25
圖3-8 甲醇薄膜反應器之配置 .............................31
圖3-9 程式架構圖-甲醇薄膜反應器 ........................35
圖3-10(a) 進料氣體流率對甲醇產率之影響 .................37
圖3-10(b) 溫度對甲醇產率之影響 .........................37
圖3-10(c) 壓力對甲醇產率之影響 .........................38
圖3-10(d) 進料氣體流率對甲醇產收率之影響 ...............38
圖3-11 進料氣體流率對甲醇產收率之影響 ..................39
圖3-12 甲醇合成系統觸媒顆粒內部各成份濃度之分佈 .......42
圖3-13 甲醇合成系統操作變數對性能之影響 ................44
圖4-1 Pareto圖 .........................................46
圖4-2 精英非優異揀選基因演算法基本步驟 .................48
圖4-3 鋒面分佈圖 .......................................49
圖4-4 改變基因演算法參數之最適解分佈 ...................58
圖5-1 氫氣生成系統基本個案之Pareto圖 ...................60
圖5-2 氫氣生成系統基本個案目標函數一對變數分佈 .........62
圖5-3 氫氣生成系統基本個案目標函數二對變數分佈 .........63
圖5-4 氫氣生成系統基本個案目標函數三對變數分佈 .........64
圖5-5(a) 氫氣生成系統基本個案部分解之反應器內部殼側溫度分佈 .....................................................69圖5-5(b) 氫氣生成系統基本個案部分解之反應器內部管側氫氣累積產率分佈 ..............................................69
圖5-5(c) 氫氣生成系統基本個案部分解之反應器內部甲烷流量分佈 ......................................................70
圖5-5(d) 氫氣生成系統基本個案部分解之反應器內部水蒸汽流量分佈 ....................................................70
圖5-5(e) 氫氣生成系統基本個案部部分解之反應器內部氧氣流量分佈 ....................................................71
圖5-6(a) 氫氣生成系統基本個案氫氣產率對各變數和目標函數之關聯係數 ................................................72
圖5-6(b) 氫氣生成系統基本個案甲烷進料量對各變數和目標函數之關聯係數 ..............................................73
圖5-6(c) 氫氣生成系統基本個案可用能損失對各變數和目標函數之關聯係數 ..............................................73
圖5-7 氫氣生成系統不同膜厚之最適解 .....................75圖5-8 氫氣生成系統不同薄膜面積之最適解 .................75圖5-9 氫氣生成系統不同膜厚及薄膜面積之最適解 ...........76圖5-10 氫氣生成系統不同裝置參數個案之最適解 ............76圖5-11 氫氣生成系統不同裝置尺寸個案之關聯性分析 ........78
圖5-12 甲醇合成系統基本個案之Pareto圖 ..................82
圖5-13 甲醇合成系統基本個案目標函數一對變數分佈 ........84
圖5-14 甲醇合成系統基本個案目標函數二對變數分佈 ........85
圖5-15 甲醇合成系統基本個案目標函數三對變數分佈 ........86
圖5-16 (a) 醇合成系統基本個案部分解之反應器內部管側溫度分佈 ......................................................88
圖5-16 (b) 甲醇合成系統基本個案部分解之反應器內部殼側和管側甲醇累積產率分佈 ......................................88
圖5-16 (c) 甲醇合成系統基本個案部分解之反應器內部管側氫氣流量分佈 ................................................89
圖5-16 (d) 醇合成系統基本個案部分解之反應器內部管側二氧化碳流量分佈 ..............................................89
圖5-17 (a) 甲醇合成系統基本個案產物甲醇產率對各變數和目標函數之關聯係數 ..........................................90
圖5-17 (b) 甲醇合成系統基本個案氫氣進料量對各變數和目標函數之關聯係數 ............................................91
圖5-17 (c) 甲醇合成系統基本個案系統可用能損失對各變數和
目標函數之關聯係數 ......................................91
圖5-18 甲醇合成系統不同膜厚之最適解 ....................93
圖5-19 甲醇合成系統不同薄膜面積之最適解 ................93
圖5-20 甲醇合成系統不同膜厚及薄膜面積之最適解 ..........94
圖5-21 甲醇合成系統不同裝置參數個案之最適解 ............94
圖5-22 甲醇合成系統不同裝置尺寸個案之關聯性分析 ........96

表目錄
表3-1 氫氣生成系統反應速率常數之參數值 .................11
表3-2 氫氣生成系統吸附係數之參數值 .....................11
表3-3 氫氣薄膜反應器的尺寸參數 .........................13
表3-4 程式模擬結果與工業上以及文獻上之結果比較 .........19
表3-5 甲醇合成系統反應速率常數之參數值 .................29
表3-6 甲醇合成系統吸附係數之參數值 .....................29
表3-7 甲醇薄膜反應器的尺寸參數 .........................32
表4-1 氫氣系統各變數範圍表 .............................55
表4-2 甲醇系統各變數範圍表 .............................56
表4-3 基因演算法參數值改變之影響 .......................57
表5-1 氫氣生成系統基本操作部分解之變數內容 .............68
表5-2 氫氣生成系統不同裝置參數部份最適解 ...............77
表5-3 甲醇合成系統基本操作部分解之變數內容 .............87
表5-4 甲醇合成系統不同裝置參數部份最適解 ...............95
參考文獻 Amenomiya, Y. and T. Tagawa,“ Infrared study of methanol synthesis from CO2+H2 on supported copper-zinc oxide catalysts,” Proc. 8th Int. Congr. Catalysis Berlin, 2, 557-567, 1984.

Basile, A., L. Parurzo and F. Gallucci,“ An experimental study of CO2 hydrogenation into methanol involving a zeolite membrane reactor,” Chem. Eng. Pro., 43, 1029-1036, 2004.

Basile, A., L. Parurzo and F. Lagana,“ The partial oxidation of methane to syngas in a palladium membrane reactor: simulation and experiment studies,” Catal. Today, 67, 65-75, 2001.

Deb, K., A. Patap, S. Agarwal and T. Meyarivan,“ A Fast and Elitist Multiobjective Genetic Algorithm:NSGA-Ⅱ,“ IEEE. Tran. Evol. Comput., 6, 182-197, 2002.

De Groote, A. M. and G. F. Froment,“ Simulation of the catalytic partial oxidation of methane to synthesis gas,” App. Catal. A: Gen., 138, 245-264, 1996.

Freni, S., G. Calogero and S. Cavallaro,“ Hydrogen production from methane through catalytic partial oxidation reactors,” J. Power Sources, 87, 28-38, 2000.

Farrauto, R. J. and C. H. Bartholomew,” Fundamentals of industrial catalutic process,” AIChE J., 340-347, 2006.

Graaf, G. H., H. Scholtens and E. J. Stamhuis,“ Intra-particle diffusion limiotations in low-pressure methanol synthesis,” Chem. Eng. Sci., 45, 773-783, 1990.

Graaf, G. H., E. J. Stamhuis and A. A. C. M. Beenackers,“ Kinetics of low-pressure methanol synthesis,” Chem. Eng. Sci., 43, 3185-3195, 1988.

Graaf, H. G., B. J. Lommerts and A. A. C. M. Beenackers,” Mathematical modeling of internal mass transport limitations in methanol synthesis,” Chem. Eng. Sci., 55, 5589-5598, 2000.
Haryanto, A., S. Fernando, N. Murali and S. Adhikari,“ Current Stats of Hydrogen Production Techniques by Steam Reforming of Ethanol: A Review,” Energy and Fuels, 19, 2098-2106, 2005.

Inamdar, S. V., S. K. Gupta and D. N. Saraf,“ Multi-objective optimization of an industrial crude distillation unit using the elitist nondominated sorting genetic algorithm,“ Chem. Eng. Res. Des., 82, 611-623, 2004.

Ji, P., H. J. van de Kooi and J. S. de Arons,“ Simulation and thermodynamic analysis of an integrated process with H2 membrane CPO reactor for pure H2 production,” Chem. Eng. Sci., 58, 3901-3911, 2003.

Jin, W., X.Gu, S.Li, P. Huang, N. Xu and J. Shi,“ Experiment and Simulation study on a catalyst packed tubular dense membrane reactor for partial oxidation of methane,” Chem. Eng. Sci., 55, 2617-2625, 2000.

Ji, P., H. J. van de Kooi and J. S. de Arons,“ Comparison of Three Integrated Catalytic Partial Oxidation (CPO) Processes Producing H2 for Fuel Cell Application,” Ind. Eng .Chem. Res., 43, 2005-2016, 2004.

Kasat, B. R., D. Kunzru, D. N. Saraf and S. K. Gupta,“ Multiobjective optimization of industrial FCC units using elitist nondominated sorting genetic algorithm,” Ind. Eng. Chem. Res., 41, 4765-4776, 2002.

Kameyama, T., M. Dokiya, M. Fujishige, H. Yokokawa and K. Fikuda,“ Possibility for effect production of hydrogen from hydrogen sulfide by means of a porous vycor glass membrane,” Ind. Eng .Chem. Fund., 20, 97-99, 1981.

Noble, R. D. and S. A. Sterm, “Membrane separations technology principle and applications,” Mem. Sci. & Tech. Ser, 2, 1995.

Oh, P. P., G. P. Rangaiah and A. K. Ray,“ Simulation and multiobjective optimization of an industrial hydrogen plant based on refinery off-gas,” Ind. Eng. Chem. Res., 41, 2248-2261, 2002.

Ostrowski, T., A. Giroir-Fendler, C. Mirodatos and L. Mleczko, “ Comparative study of the catalytic partial oxidation of methane to synthesis gas in fixed-bed and fluidized-bed membrane reactors,” PartⅠ: A modeling approach, Catal. Today, 40, 181-190, 1998.

Ostrowski, T., A. Giroir-Fendler, C. Mirodatos and L. Mleczko, “Comparative study of the catalytic partial oxidation of methane to synthesis gas in fixed-bed and fluidized-bed membrane reactors,” PartⅡ: Development of membranes and catalytic measurements, Catal. Today, 40, 191-200, 1998.

Papoulis, A. and Unnikrishna Pillai, S.,” Probability, random variables, and stochastic processes,” 4th ed., McGraw-Hill, New York, NY, 2002.

Rajesh, J. K., S. K. Gupta, G. P. Rangaiah and A. K. Ray,“ Multiobjective optimization of steam reformer performance using genetic alogorithm,” Ind. Eng. Chem. Res., 39, 706-717, 2000.

Regnier, J., B. Sareni and X. Roboam,” System optimization by multiobjective genetic algorithms and analysis o the coupling between variables, constraints and objectives,” International Journal for Computation and Mathematics in Electrical and Electronic Engineering, 24, 805-820, 2005.

Rosen, M. A.,“ Thermodynamic investigation of hydrogen production by steam-methane reforming,” Int. J. Hyd. Ene., 16, 207-217, 1991.

Smet, C. R. H. de, M. H. J. M. de Croon, R. J. Berger, G. B. Marin and F. C. Schouten,“ Design of adiabatic fixed-bed reactors for the partial oxidation of methane to synthesis gas. Application to production of methanol and hydrogen-for-fuel-cells,” Chem. Eng. Sci., 56, 4849-4861, 2001.

Srinivas, N. and K. Deb,“ Mutiobjective optimization using nondominated sorting in genetic algorithms,” Evol. Comput., 2, 221-248, 1995.

Struis, R. P. W. J. and S. Stucki,” Verification of the membrane reactor concept for the methanol synthesis,” App. Catal. A: Gen., 216, 117-129, 2001.
Struis, R. P. W. J., S. Stucki and M. Wiedorn,“ A membrane reactor for methanol synthesis,” J. Mem. Sci., 113, 93-100, 1996.

Skrzypek, J., M. Lachowska and D. Serafin,“ Methanol synthesis from co2 and h2: dependence of equilibrium conversions and exit equilibrium concentrations of components on the main process variables,” Chem. Eng. Sci., 45, 89-96, 1990.

Struis, R. P. W. J., M. Quintilii and S. Stucki,“ Feasibility of Li-Nafion hollow fiber membranes in methanol synthesis: mechanical and thermal stability at elevated temperature and pressure,” J. Mem. Sci., 177, 215-223, 2000.

Tarafder, A., B. C. S. Lee, A. K. Ray and G. P. Rangaiah,“ Multiobjective optimization of an industrial ethylene reactor using a nondominated sorting genetic algorithm,“ Ind. Eng. Chem. Res., 44, 124-141, 2005.

Villadsen, J. and M. Michelsen,“ Solution of different equations models by polynomials approximation,” Englewood Cliffs, NJ: Prentice-Hall, 1978.

Xu, J. and G. F. Froment,“ Methane steam reforming, methanation and water gas shift: Ⅰ. Intrinsic kinetics,” AIChE J., 35, 88-96, 1989.

Xu, J. and G. F. Froment,“ Methane steam reforming : Ⅱ. Diffusional limitations and reactor simulation,” AIChE J., 35, 97-103, 1989.
論文使用權限
  • 同意紙本無償授權給館內讀者為學術之目的重製使用,於2006-07-27公開。
  • 同意授權瀏覽/列印電子全文服務,於2006-07-27起公開。


  • 若您有任何疑問,請與我們聯絡!
    圖書館: 請來電 (02)2621-5656 轉 2281 或 來信