ASCE will be sunsetting the Civil Engineering Database (CEDB) in the coming months. We encourage you to start using the ASCE Library to perform content searches. In the ASCE Library, you can save your search results as well as receive email content alerts when new content relevant to your area of interest is published. Try it out today at https://ascelibrary.org.

 

Use of Importance Sampling Constraints in System Optimization

by Yingwei Liu, Nanchang Aircraft Manufacturing Co, Nanchang, China,
Fred Moses, Nanchang Aircraft Manufacturing Co, Nanchang, China,



Document Type: Proceeding Paper

Part of: Probabilistic Mechanics and Structural and Geotechnical Reliability

Abstract:

An important application of system reliability analysis is to incorporate overall system risk as a constraint in a structural optimization. The paper describes the use of Monte Carlo Importance Sampling (MCIS) estimates of structural system risk in several optimization examples. It is seen that such MCIS estimates do not lead to stable derivatives needed in minimum weight search algorithms for finding an optimum design. Comparisons of MCIS estimates with conventional system reliability bounds show the latter to provide more stable reliability estimates needed for optimization.

Subject Headings: System reliability | Structural systems | Structural reliability | Monte Carlo method | Sensitivity analysis | Optimization models | System analysis

Services: Buy this book/Buy this article

 

Return to search