1 Introduction
1.1 Background and Significance
1.2 Key Scientific Issues and Technical Challenges
1.3 State-of-the-Art
1.3.1 Theory and Methods for High-Fidelity Numerical Modeling
1.3.2 Theory and Methods for Rapid Structural Analysis for Complex Equipment
1.3.3 Theory and Methods for Efficient Structural Optimization Design
1.3.4 Theory and Methods for Uncertainty Analysis and Reliability Design
1.4 Contents of This Book
References
2 Introduction to High-Fidelity Numerical Simulation Modeling Methods
2.1 Engineering Background and Significance
2.2 Modeling Based on Computational Inverse Techniques
References
3 Computational Inverse Techniques
3.1 Introduction
3.2 Sensitivity Analysis Methods
3.2.1 Local and Global Sensitivity Analysis
3.2.2 Direct Integral-Based GSA Method
3.2.3 Numerical Examples
3.2.4 Engineering Application: Global Sensitivity Analysis of Vehicle Roof Structure
3.3 Regularization Methods for Ill-Posed Problem
3.3.1 Ill-Posedness Analysis
3.3.2 Regularization Methods
3.3.3 Selection of Regularization Parameter
3.3.4 Application of Regularization Method to Model Parameter Identification
3.4 Computational Inverse Algorithms
3.4.1 Gradient Iteration-Based Computational Inverse Algorithm
3.4.2 Intelligent Evolutionary-Based Computational Inverse Algorithm
3.4.3 Hybrid Inverse Algorithm
3.5 Conclusions
References
4 Computational Inverse for Modeling Parameters
4.1 Introduction
4.2 Identification of Model Characteristic Parameters
4.2.1 Material Parameter Identification for Stamping Plate
4.2.2 Dynamic Constitutive Parameter Identification for Concrete Material
4.3 Identification of Model Environment Parameters
4.3.1 Dynamic Load Identification for Cylinder Slructure
4.3.2 Vehicle Crash Condition Identification
4.4 Conclusions
References
5 Introduction to Rapid Structural Analysis
5.1 Engineering Background and Significance
5.2 Surrogate Model Methods
5.3 Model Order Reduction Methods
References
6 Rapid Structural Analysis Based on Surrogate Models
6.1 Introduction
6.2 Polynomial Response Surface Based on Structural Selection Technique
6.2.1 Polynomial Structure Selection Based on Error Reduction Ratio
6.2.2 Numerical Example
6.2.3 Engineering Application: Nonlinear Output Force Modeling for Hydro-Pneumatic Suspension
6.3 Surrogate Model Based on Adaptive Radial Basis Function
6.3.1 Selection of Sample and Testing Points
6.3.2 Optimization of the Shape Parameters
6.3.3 RBF Model Updating Procedure
6.3.4 Numerical Examples
6.3.5 Engineering Application: Surrogate Model Construction for Crash Worthiness of Thin-Walled Beam Structure
6.4 High Dimensional Model Representation
6.4.1 Improved HDMR
6.4.2 Analysis of Calculation Efficiency
6.4.3 Numerical Example
6.5 Conclusions
References
7 Rapid Structural Analysis Based on Reduced Basis Method
7.1 Introduction
7.2 The RBM for Rapid Analysis of Structural Static Responses
7.2.1 The Flow of Rapid Calculation Based on RBM
7.2.2 Construction of the Reduced Basis Space
7.2.3 Engineering Application: Rapid Analysis of Cab Structure
7.3 The RBM for Rapid Analysis of Structural Dynamic Responses
7.3.1 Parameterized Description of Structural Dynamics
7.3.2 Construction of the Reduced Basis Space Based on Time Domain Integration
7.3.3 Projection Reduction Based on Least Squares
7.3.4 Numerical Example
7.4 Conclusions
References
8 Introduction to Multi-objective Optimization Design
8.1 Characteristics of Multi-objective Optimization
8.2 Optimal Solution Set in Multi-objective Optimization
8.3 Multi-objective Optimization Methods
8.3.1 Preference-Based Methods
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