Efficient Global Optimization Reliability Analysis (EGORA) for Timedependent Limit-State Functions


If a limit-state function involves time, the associated reliability is defined within a period of time. The extreme value of the limit-state function is needed to calculate the timedependent reliability, and the extreme value is usually highly nonlinear with respect to random input variables and may follow a multimodal distribution. For this reason, a surrogate model of the extreme response along with Monte Carlo simulation is usually employed. The objective of this work is to develop a new method, called the Efficient Global Optimization Reliability Analysis (EGORA), to efficiently build the surrogate model. EGORA is based on the Efficient Global Optimization (EGO) method. Different from the current method that generates training points for random variables and time independently, EGORA draws training points for the two types of input variables simultaneously and therefore accounts for their interaction effects. The other improvement is that EGORA only focuses on high accuracy at or near the limit state. With the two improvements, the new method can effectively reduce the number of training points. Once the surrogate model of the extreme response is available, Monte Carlo simulation is applied to calculate the time-dependent reliability. Good accuracy and efficiency of EGORA are demonstrated by three examples.

Meeting Name

ASME 2014 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference (2014: Aug. 17-20, Buffalo, NY)


Mechanical and Aerospace Engineering

Keywords and Phrases

Computer aided design; Design; Global optimization; Intelligent systems; Monte Carlo methods; Reliability; Efficient global optimization; Extreme response; Input variables; Interaction effect; Limit state functions; Multimodal distributions; Time dependent reliability; Training points; Reliability analysis

International Standard Book Number (ISBN)


Document Type

Article - Conference proceedings

Document Version


File Type





© 2014 American Society of Mechanical Engineers (ASME), All rights reserved.

Publication Date

01 Aug 2014