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研究生:翁錫洲
研究生(外文):Pongsathorn Pornteparak
論文名稱:鐵路車輛蜂巢結構黏合層之 應力分析與最佳化設計
論文名稱(外文):Stress Analysis and Optimization Design of Adhesive Layer on Honeycomb Structure for Railway Vehicle System
指導教授:鄭 永 長
指導教授(外文):Cheng Yung-Chang
口試委員:孫榮宏李政鋼
口試委員(外文):Sun Rong-HungLi Zhen-Gang
口試日期:2019-07-02
學位類別:碩士
校院名稱:國立高雄科技大學
系所名稱:機械與自動化工程系
學門:工程學門
學類:機械工程學類
論文種類:學術論文
論文出版年:2019
畢業學年度:107
語文別:英文
論文頁數:90
中文關鍵詞:蜂巢結構等效應力均勻實驗設計Kriging插值法折衷規劃法基因演算法
外文關鍵詞:Honeycomb structurevon Mises stressUniform designKriging interpolationCompromise programmingGenetic algorithm.
相關次數:
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  • 下載下載:34
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本研究主要探討高速鐵路車輛蜂巢結構黏合層的應力分析與最佳設計,利用均勻實驗設計規劃一系列的模擬實驗,選擇三個尺寸做為控制因子,以SolidWorks 軟體建立分析模型,依據ASTM C297, C364和C365三個測試法規,在ANSYS/Workbench 軟體中進行邊界條件設定以及外力設定,並且求解黏合層的等效應力。使用Kriging插值法建立輸入與輸出之間的代理模型,最後,利用折衷規劃法、混料均勻設計、基因演算法以及Hooke-Jeeves方法,進行多目標最佳化設計,在三個等效應力望小的條件下,求出蜂巢結構的最佳尺寸。與原始設計相比,最佳化設計後的結構,在進行ASTM的三種法規測試分析時,等效應力的改善率最大值為45.67 %。根據分析結果顯示,本研究所提出的最佳化流程,可以有效地降低蜂巢結構黏合層的等效應力。
The purpose of this paper focuses on the strength improvement for the adhesive layer of the honeycomb composite sandwich structure under the static loads by the innovative and integrated multi-objective optimization procedure. Three system parameters of the honeycomb structure are selected as the control factors to be improved. Uniform design of experiment is applied to create a set of simulation experiments. Applying ANSYS/Workbench software, the finite element modeling is investigated and the von Mises stress of the adhesive layer in the honeycomb structure is calculated under ASTM metal-honeycomb core flatwise tensile, edgewise compression and flatwise compression testing simulations. Applying the Kriging interpolation method, the surrogate models are demonstrated by the input and output data in uniform design. Finally, integrating the compromise programming, mixture uniform design of experiment, genetic algorithm and Hooke-Jeeves method, the multi-objective optimization problem is solved and the optimal design version is obtained. Compared with the original design, the maximum improvement of the von Mises stress of the adhesive layer in the honeycomb structure under three ASTM test simulations is 45.67 %. As a result, the strength of the adhesive layer in the honeycomb structure is improved for the railway vehicle system.
Table of Contents
Abstract Chinese version…………………….………………………….…………….. i
Abstract English version………………………………………………….………….. ii
Acknowledgments…………………………….………………………….………….. iii
Table of Contents ...…………………………………………………….………..….. iv
List of Tables………………………………………………………..………………. vii
List of Figures……………………………………………………………………….. ix
Nomenclature………………………………………………………………………... xi

Chapter 1 Introduction 1
1.1 Background and motivation 1
1.2 Literature Review 2
1.2.1 Stress Analysis about Honeycomb Composite Sandwich Structure 3
1.2.2 Design of Experimental and Optimized Literature 4
1.3 Research Purpose 5
1.4 Thesis structure 6
Chapter 2 Finite element Analysis 8
2.1 Introduction of finite element analysis 8
2.2 Introduction of ANSYS/Workbench 9
2.3 ANSYS/Workbench analysis process 10
2.3.1 Pre-Processing 10
2.3.2 Analysis and Calculation 11
2.3.3 Post-Processing 11
2.4 Honeycomb composite structure testing standard 12
2.4.1 Standard Testing Method for Flatwise Strength of Sandwich Constructions (C297) 12
2.4.2 Standard Testing Method for Edgewise Compressive Strength of Sandwich Constructions (C364) 14
2.4.3 Standard Test Method for Flatwise Compressive Properties of Sandwich Cores (C365) 16
2.5 Honeycomb Model 17
2.5.1 Material Selection 18
2.6 Experimental procedure 19
2.7 Meshing Solution 22
2.7.1 Mesh Convergence Analysis 22
2.8 Result of Analysis 24
Chapter 3 Design of Experimental Analysis 27
3.1 Experiment Design 27
3.2 Uniform Design of Experiment 28
3.3 Factorial Design 29
3.4 Uniform Design Table 30
3.5 Kriging Interpolation 31
Chapter 4 Analysis Result for Design of Experiment 34
4.1 Parameter Design 34
4.2 Factor Characteristic Analysis 37
4.3 Uniform Design Table 39
4.4 Improvement for Uniform Design 43
4.5 Surrogate Model by Kriging Interpolation 43
4.6 Response Surface and Kriging Model 45
Chapter 5 Optimization 49
5.1 Multi Objective Programming 49
5.2 Compromise programming method 50
5.3 Genetic Algorithm 51
5.4 Hooke-Jeeves method 52
5.5 Description of optimization problems 53
5.6 Optimization Design Result 60
Chapter 6 Conclusion 63
6.1 Conclusion 63
6.2 Future work 63
References 65
Appendix 71


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