Uncertainty Analysis for Time- and Space-Dependent Responses with Random Variables


The performance of a product varies with respect to time and space if the associated limit-state function involves time and space. This study develops an uncertainty analysis method that quantifies the effect of random input variables on the performance (response) over time and space. The combination of the first order reliability method (FORM) and the second-order reliability method (SORM) is used to approximate the extreme value of the response with respect to space at discretized instants of time. Then the response becomes a Gaussian stochastic process that is fully defined by the mean, variance, and autocorrelation functions obtained from FORM and SORM, and a sequential single loop procedure is performed for spatial and random variables. The method is successfully applied to the reliability analysis of a crank-slider mechanism, which operates in a specified period of time and space.

Meeting Name

ASME 2018 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference, IDETC2018 (2018: Aug. 26-29, Quebec City, Quebec, Canada)


Mechanical and Aerospace Engineering

Research Center/Lab(s)

Intelligent Systems Center

Keywords and Phrases

Failure; Probability; Reliability; Stochastic processes; Uncertainty analysis; Errors

Document Type

Article - Conference proceedings

Document Version


File Type





© 2018 American Society for Engineering Management (ASEM), All rights reserved.

Publication Date

29 Aug 2018