了得網工業技術_基於數值模擬的設計理論與方法（英文版）

	[ 收藏 ] [ 简体中文 ]
臺灣貨到付款、ATM、超商、信用卡PAYPAL付款，4-7個工作日送達，999元臺幣免運費　　　在線留言商品價格為新臺幣

商品搜索

类别：

关键字：

商品分类

基於數值模擬的設計理論與方法（英文版）
該商品所屬分類：工業技術 -> 機械/儀表工業
【市場價】	2185-3168元
【優惠價】	1366-1980元
【作者】	韓旭，劉傑
【所屬類別】	圖書工業技術機械/儀表工業機械學（機械設計基礎理論）
【出版社】	科學出版社
【ISBN】	9787030683632
【折扣說明】	一次購物滿999元台幣免運費+贈品一次購物滿2000元台幣95折+免運費+贈品一次購物滿3000元台幣92折+免運費+贈品一次購物滿4000元台幣88折+免運費+贈品
【本期贈品】	①優質無紡布環保袋，做工棒！②品牌簽字筆 ③品牌手帕紙巾

版本	正版全新電子版PDF檔
您已选择：	正版全新
溫馨提示：如果有多種選項，請先選擇再點擊加入購物車。 . 電子圖書價格是0.69折，例如了得網價格是100元，電子書pdf的價格則是69元。 . 購買電子書不支持貨到付款，購買時選擇atm或者超商、PayPal付款。付款後1-24小時內通過郵件傳輸給您。 *. 如果收到的電子書不滿意，可以聯絡我們退款。謝謝。

內容介紹

開本：16開

紙張：膠版紙

包裝：平裝-膠訂

是否套裝：否

國際標準書號ISBN：9787030683632

作者：韓旭，劉傑

出版社：科學出版社

出版時間：2021年04月

內容簡介

Thisbooksystematicallyintroducesreaderstoadvanceddesigntheoryandmethods,includingprecisemodelingbasedoninversetechniques,rapidstructurecomputation,optimizationdesign,anduncertaintyanalysis.Itdescribesmechanicaldesigntheory,focusingonthekeycommontechnologiesofsimulation-basedmechanicaldesign.

Contents
1 Introduction 1
1.1 Background and Significance 1
1.2 Key Scientific Issues and Technical Challenges 4
1.3 State-of-the-Art 7
1.3.1 Theory and Methods for High-Fidelity Numerical Modeling 7
1.3.2 Theory and Methods for Rapid Structural Analysis for Complex Equipment 9
1.3.3 Theory and Methods for Efficient Structural Optimization Design 10
1.3.4 Theory and Methods for Uncertainty Analysis and Reliability Design 11
1.4 Contents of This Book 12
References 14
2 Introduction to High-Fidelity Numerical Simulation Modeling Methods 17
2.1 Engineering Background and Significance 17
2.2 Modeling Based on Computational Inverse Techniques 20
References 26
3 Computational Inverse Techniques 29
3.1 Introduction 29
3.2 Sensitivity Analysis Methods 31
3.2.1 Local and Global Sensitivity Analysis 31
3.2.2 Direct Integral-Based GSA Method 32
3.2.3 Numerical Examples 37
3.2.4 Engineering Application: Global Sensitivity Analysis of Vehicle Roof Structure 38
3.3 Regularization Methods for Dl-Posed Problem 41
3.3.1 III-Posedness Analysis 41
3.3.2 Regularization Methods 42
3.3.3 Selection of Regularization Parameter 47
3.3.4 Application of Regularization Method to Model Parameter Identification 50
3.4 Computational Inverse Algorithms 53
3.4.1 Gradicnt Itcration-Bascd Computational Inverse Algorithm 55
3.4.2 Intelligent Evolutionary-Based Computational Inverse Algorithm 59
3.4.3 Hybrid Inverse Algorithm 61
3.5 Conclusions 63
Rcfcrenccs 64
4 Computational Inverse for Modleling Parameters 67
4.1 Introduction 67
4.2 Identification of Model Characteristic Parameters 68
4.2.1 Material Parameter ldentification for Stamping Plate 68
4.2.2 Dynamic Constitutive Parameter Identification for Concretc Matcrial 72
4.3 Identification of Model Environment Parameters 79
4.3.1 Dynamic Load Identification for Cylinder Structure 79
4.3.2 vehicle Crash Condition Identification 82
4.4 Conclusions 85
References 86
5 Introduction to Rapid Structural Analysis 89
5.1 Engineering Background and Significance 89
5.2 surrogate Model Methods 90
5.3 Model Order Reduction Methods 93
References 94
6 Rapid Structural Analysis Based on Surrogate Models 97
6.1 Introduction 97
6.2 Polynomial Response Surface Based on Structural selection Technique 98
6.2.1 Polynomial Structure Selection Based on Error Reduction Ratio 98
6.2.2 Numerical Example 100
6.2.3 Engineering Application: Nonlincar Output Force Modeling for Hydro-Pneumatic Suspension 101
6.3 Surrogate Model Based on Adaptive Radial Basis Function 105
6.3.1 Selection of Sample and Testing Points 106
6.3.2 Optimization of the Shape Parameters 108
6.3.3 RBF Model Updating Procedure 108
6.3.4 Numerical Examples 110
6.3.5 Engineering Application: Surrogate Model Construction for Crash Worthiness of Thin-Walled Beam Structure 112
6.4 High Dimensional Model Representation 115
6.4.1 Improved HDMR 116
6.4.2 Analysis of Calculation Efficiency 119
6.4.3 Numerical Example 120
6.5 Conclusions 122
References 123
7 Rapid Structural Analysis Based on Reduced Basis Method 125
7.1 Introduction 125
7.2 The RBM for Rapid Analysis of Structural Static Responses 126
7.2.1 The Flow of Rapid Calculation Based on RBM 126
7.2.2 Construction of the Reduced Basis Space 129
7.2.3 Engineering Application: Rapid Analysis of Cab Structure 130
7.3 The RBM for Rapid Analysis of Structural Dynamic Responses 132
7.3.1 Parameterized Description of Structural Dynamics 132
7.3.2 Construction of the Reduced Basis Space Based on Time Domain Integration 133
7.3.3 Projection Reduction Based on Least Squares 135
7.3.4 Numerical Example 136
7.4 Conclusions 138
References 140
8 Introduction to Multi-objective Optimization Design 141
8.1 Characteristics of Multi-objective Optimization 141
8.2 Optimal Solution Set in Multi-objective Optimization 143
8.3 Multi-objective Optimization Methods 144
8.3.1 Preference-Based Methods 144
8.3.2 Generating Methods Based on Evolutionary Algorithms 146
References 150
9 Micro Multi-objective Genetic Algorithm 153
9.1 Introduction 153
9.2 Procedure of uMOGA 154
9.3 Implementation Techniques of uMOGA 156
9.3.1 Non-dominated Sorting 156
9.3.2 Population Diversity Preservation Strategies 158
9.3.3 Elite Individual Preserving Mechanism 159
9.4 Algorithm Performance Evaluation 160
9.4.1 Numerical Examples 160
9.4.2 Engineering Testing Example 167
9.5 Engineering Applications 169
9.5.1 Optimization Design of Guide Mechanism of Vehicle Suspension 169
9.5.2 Optimization Design of Variable Blank Holder Force in Sheet Metal Forming 174
9.6 Conclusions 177
References 177
10 Multi-objective Optimization Design Based on Surrogate Models 179
10.1 Introduction 179
10.2 Multi-objective Optimization Algorithm Based on Intellige

書摘插畫