System reliability assessment is a challenging task when using computationally intensive models. In this work, a radial-based centralized Kriging method (RCKM) is proposed for achieving high efficiency and accuracy. The method contains two components: Kriging-based system most probable point (MPP) search and radial-based centralized sampling. The former searches for the system MPP by progressively updating Kriging models regardless of the nonlinearity of the performance functions. The latter refines the Kriging models with the training points (TPs) collected from pregenerated samples. It concentrates the sampling in the important high-probability density region. Both components utilize a composite criterion to identify the critical Kriging models for system failure. The final Kriging models are sufficiently accurate only at those sections of the limit states that bound the system failure region. Its efficiency and accuracy are demonstrated via application to three examples.
A Radial-Based Centralized Kriging Method for System Reliability Assessment
Contributed by the Design Automation Committee of ASME for publication in the JOURNAL OF MECHANICAL DESIGN. Manuscript received October 16, 2017; final manuscript received April 1, 2018; published online May 11, 2018. Assoc. Editor: Xiaoping Du.
- Views Icon Views
- Share Icon Share
- Cite Icon Cite
- Search Site
Wang, Y., Hong, D., Ma, X., and Zhang, H. (May 11, 2018). "A Radial-Based Centralized Kriging Method for System Reliability Assessment." ASME. J. Mech. Des. July 2018; 140(7): 071403. https://doi.org/10.1115/1.4039919
Download citation file:
- Ris (Zotero)
- Reference Manager