本书共分4部分13章，是作者近10年来在复杂结构的数字化设计中的共性关键技术及应用方面研究成果的总结。复杂结构的几何、工艺及功能需求等存在高度复杂性、多样性和不确定性，这使得利用模拟的方法对其进行设计时在建模、分析、优化等方面的存在一系列技术难题，特别是复杂结构设计的精度、效率和可靠性难以保证。针对这些设计问题中的关键共性技术难题，本书深入、系统地介绍了基于模拟的复杂结构先进设计技术、算法及其工程应用，主要包括基于计算反求方法的复杂结构高精度数字化模型的建模技术、基于代理模型和缩减基方法的复杂结构快速分析技术、满足多功能需求的复杂结构多目标设计技术、基于非概率模型的复杂装备不确定性分析和设计技术。本书是对现代设计方法上的原创成果的总结与概括，可供从事机械工程、土木工程、交通工程、工程力学等领域的技术人员参考，也可以作为相关专业的教师、研究生和本科生的教学参考书。

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
8.3.2 Generating Methods Based on Evo