Journal
JOURNAL OF MECHANICAL DESIGN
Volume 140, Issue 12, Pages -Publisher
ASME
DOI: 10.1115/1.4040883
Keywords
reliability-based design optimization (RBDO); uncertainty optimization; adaptive directional sampling method; Kriging model
Categories
Funding
- National Key R&D Program of China [2017YFB1301300]
- National Natural Science Foundation of China [11602076]
- Foundation of State Key Laboratory of Structural Analysis for Industrial Equipment from Dalian University of Technology [GZ1702]
- Fundamental Research Funds for the Central Universities of China [JZ2018HGTB0231]
Ask authors/readers for more resources
Due to the nested optimization loop structure and time-demanding computation of structural response, the computational accuracy and cost of reliability-based design optimization (RBDO) have become a challenging issue in engineering application. Kriging-model-based approach is an effective tool to improve the computational efficiency in the practical RBDO problems; however, a larger number of sample points are required for meeting high computational accuracy requirements in traditional methods. In this paper, an adaptive directional boundary sampling (ADBS) method is developed in order to greatly reduce the computational sample points with a reasonable accuracy, in which the sample points are added along the ideal descending direction of objective function. Furthermore, only sample points located near the constraint boundary are mainly selected in the vicinity of the optimum point according to the strategy of multi-objective optimization; thus, substantial number of sample points located in the failure region is neglected, resulting in the improved performance of computational efficiency. Four numerical examples and one engineering application are provided for demonstrating the efficiency and accuracy of the proposed sampling method.
Authors
I am an author on this paper
Click your name to claim this paper and add it to your profile.
Reviews
Recommended
No Data Available