Contents1 Introduction 11.1 Background and Significance 11.2 Key Scientific Issues and Technical Challenges 41.3 State-of-the-Art 71.3.1 Theory and Methods for High-Fidelity Numerical Modeling 71.3.2 Theory and Methods for Rapid Structural Analysis for Complex Equipment 91.3.3 Theory and Methods for Efficient Structural Optimization Design 101.3.4 Theory and Methods for Uncertainty Analysis and Reliability Design 111.4 Contents of This Book 12References 142 Introduction to High-Fidelity Numerical Simulation Modeling Methods 172.1 Engineering Background and Significance 172.2 Modeling Based on Computational Inverse Techniques 20References 263 Computational Inverse Techniques 293.1 Introduction 293.2 Sensitivity Analysis Methods 313.2.1 Local and Global Sensitivity Analysis 313.2.2 Direct Integral-Based GSA Method 323.2.3 Numerical Examples 373.2.4 Engineering Application: Global Sensitivity Analysis of Vehicle Roof Structure 383.3 Regularization Methods for Dl-Posed Problem 413.3.1 III-Posedness Analysis 413.3.2 Regularization Methods 423.3.3 Selection of Regularization Parameter 473.3.4 Application of Regularization Method to Model Parameter Identification 503.4 Computational Inverse Algorithms 533.4.1 Gradicnt Itcration-Bascd Computational Inverse Algorithm 553.4.2 Intelligent Evolutionary-Based Computational Inverse Algorithm 593.4.3 Hybrid Inverse Algorithm 613.5 Conclusions 63Rcfcrenccs 644 Computational Inverse for Modleling Parameters 674.1 Introduction 674.2 Identification of Model Characteristic Parameters 684.2.1 Material Parameter ldentification for Stamping Plate 684.2.2 Dynamic Constitutive Parameter Identification for Concretc Matcrial 724.3 Identification of Model Environment Parameters 794.3.1 Dynamic Load Identification for Cylinder Structure 794.3.2 vehicle Crash Condition Identification 824.4 Conclusions 85References 865 Introduction to Rapid Structural Analysis 895.1 Engineering Background and Significance 895.2 surrogate Model Methods 905.3 Model Order Reduction Methods 93References 946 Rapid Structural Analysis Based on Surrogate Models 976.1 Introduction 976.2 Polynomial Response Surface Based on Structural selection Technique 986.2.1 Polynomial Structure Selection Based on Error Reduction Ratio 986.2.2 Numerical Example 1006.2.3 Engineering Application: Nonlincar Output Force Modeling for Hydro-Pneumatic Suspension 1016.3 Surrogate Model Based on Adaptive Radial Basis Function 1056.3.1 Selection of Sample and Testing Points 1066.3.2 Optimization of the Shape Parameters 1086.3.3 RBF Model Updating Procedure 1086.3.4 Numerical Examples 1106.3.5 Engineering Application: Surrogate Model Construction for Crash Worthiness of Thin-Walled Beam Structure 1126.4 High Dimensional Model Representation 1156.4.1 Improved HDMR 1166.4.2 Analysis of Calculation Efficiency 1196.4.3 Numerical Example 1206.5 Conclusions 122References 1237 Rapid Structural Analysis Based on Reduced Basis Method 1257.1 Introduction 1257.2 The RBM for Rapid Analysis of Structural Static Responses 1267.2.1 The Flow of Rapid Calculation Based on RBM 1267.2.2 Construction of the Reduced Basis Space 1297.2.3 Engineering Application: Rapid Analysis of Cab Structure 1307.3 The RBM for Rapid Analysis of Structural Dynamic Responses 1327.3.1 Parameterized Description of Structural Dynamics 1327.3.2 Construction of the Reduced Basis Space Based on Time Domain Integration 1337.3.3 Projection Reduction Based on Least Squares 1357.3.4 Numerical Example 1367.4 Conclusions 138References 1408 Introduction to Multi-objective Optimization Design 1418.1 Characteristics of Multi-objective Optimization 1418.2 Optimal Solution Set in Multi-objective Optimization 1438.3 Multi-objective Optimization Methods 1448.3.1 Preference-Based Methods 1448.3.2 Generating Methods Based on Evolutionary Algorithms 146References 1509 Micro Multi-objective Genetic Algorithm 1539.1 Introduction 1539.2 Procedure of uMOGA 1549.3 Implementation Techniques of uMOGA 1569.3.1 Non-dominated Sorting 1569.3.2 Population Diversity Preservation Strategies 1589.3.3 Elite Individual Preserving Mechanism 1599.4 Algorithm Performance Evaluation 1609.4.1 Numerical Examples 1609.4.2 Engineering Testing Example 1679.5 Engineering Applications 1699.5.1 Optimization Design of Guide Mechanism of Vehicle Suspension 1699.5.2 Optimization Design of Variable Blank Holder Force in Sheet Metal Forming 1749.6 Conclusions 177References 17710 Multi-objective Optimization Design Based on Surrogate Models 17910.1 Introduction 17910.2 Multi-objective Optimization Algorithm Based on Intellige
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