A Novel Adaptive Kriging Method: Time-Dependent Reliability-Based Robust Design Optimization and Case Study

2021 ◽  
pp. 107692
Author(s):  
Zhenliang Jiang ◽  
Jiawei Wu ◽  
Fu Huang ◽  
Yifan Lv ◽  
Liangqi Wan
Author(s):  
Xiaoping Du

Quality characteristics (QC’s) are often treated static in robust design optimization while many of them are time dependent in reality. It is therefore desirable to define new robustness metrics for time-dependent QC’s. This work shows that using the robustness metrics of static QC’s for those of time-dependent QC’s may lead to erroneous design results. To this end, we propose the criteria of establishing new robustness metrics for time-dependent QC’s and then define new robustness metrics. Instead of using a point expected quality loss over the time period of interest, we use the expectation of the maximal quality loss over the time period to quantify the robustness for time-dependent QC’s. Through a four-bar function generator mechanism analysis, we demonstrate that the new robustness metrics can capture the full information of robustness of a time-dependent QC over a time interval. The new robustness metrics can then be used as objective functions for time-dependent robust design optimization.


Author(s):  
Shui Yu ◽  
Zhonglai Wang

During the product design and development stage, design engineers often encounter reliability and robustness of dynamic uncertain structures. Meanwhile, time-varying and high nonlinear performance are the basic characteristics of reliability analysis and design. Hence, the time-dependent reliability analysis and integrating reliability-based design with robust design become a primary challenge in reliability-based robust design optimization. This paper proposes a multi-objective integrated framework for time-dependent reliability-based robust design optimization and the corresponding algorithms. The multi-objective integrated framework, which minimizes the mean value and coefficient of variation for the objective function at the same time subject to time-dependent probabilistic constraints, is first established. The time-dependent probabilistic constraints are then converted into deterministic constraints using a combination of moment method and the sparse grid based stochastic collocation method. The evolutionary multi-objective optimization algorithm is finally employed for the deterministic multi-objective optimization problem. Several examples are investigated to demonstrate the effectiveness of the proposed method.


Author(s):  
Shui Yu ◽  
Zhonglai Wang ◽  
Zhihua Wang

Due to the uncertain and dynamic parameters from design, manufacturing, and working conditions, many engineering structures usually show uncertain and dynamic properties. During the product design and development stages, designers often encounter reliability and robustness measures of dynamic uncertain structures. Time-varying and high nonlinear performance brings a new challenge for the reliability-based robust design optimization. This paper proposes a multi-objective integrated framework for time-dependent reliability-based robust design optimization and the corresponding algorithms. The integrated framework is first established by minimizing the mean value and coefficient of variation of the objective performance at the same time subject to time-dependent probabilistic constraints. The time-dependent probabilistic constraints are then converted into deterministic constraints using the dimension reduction method. The evolutionary multi-objective optimization algorithm is finally employed for the deterministic multi-objective optimization problem. Several examples are investigated to demonstrate the effectiveness of the proposed method.


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