Research Papers

A Sampling Approach to Extreme Value Distribution for Time-Dependent Reliability Analysis

[+] Author and Article Information
Zhen Hu

e-mail: zh4hd@mst.edu

Xiaoping Du

e-mail: dux@mst.edu
Department of Mechanical and Aerospace Engineering,
Missouri University of Science and Technology,
290D Toomey Hall,
400 West 13th Street,
Rolla, MO 65409-0500

1Corresponding author.

Contributed by the Design Automation Committee of ASME for publication in the Journal of Mechanical Design. Manuscript received December 30, 2012; final manuscript received February 8, 2013; published online May 10, 2013. Assoc. Editor: David Gorsich.

J. Mech. Des 135(7), 071003 (May 10, 2013) (8 pages) Paper No: MD-12-1633; doi: 10.1115/1.4023925 History: Received December 30, 2012; Revised February 08, 2013

Maintaining high accuracy and efficiency is a challenging issue in time-dependent reliability analysis. In this work, an accurate and efficient method is proposed for limit-state functions with the following features: The limit-state function is implicit with respect to time. There is only one stochastic process in the input to the limit-sate function. The stochastic process could be either a general strength or a general stress variable so that the limit-state function is monotonic to the stochastic process. The new method employs a sampling approach to estimate the distributions of the extreme value of the stochastic process. The extreme value is then used to replace the corresponding stochastic process. Consequently the time-dependent reliability analysis is converted into its time-invariant counterpart. The commonly used time-invariant reliability method, the first order reliability method, is then applied to calculate the probability of failure over a given period of time. The results show that the proposed method significantly improves the accuracy and efficiency of time-dependent reliability analysis.

Copyright © 2013 by ASME
Your Session has timed out. Please sign back in to continue.



Grahic Jump Location
Fig. 1

Flow chart of the new time-dependent reliability method

Grahic Jump Location
Fig. 3

A Beam under random loading

Grahic Jump Location
Fig. 2

A Trajectory of a stochastic process

Grahic Jump Location
Fig. 8

CDFs of maximum river velocity over different time intervals

Grahic Jump Location
Fig. 4

CDFs of maximum load over different time intervals

Grahic Jump Location
Fig. 5

Probability of failure of the beam over different time intervals

Grahic Jump Location
Fig. 6

Cross section at root of the turbine blade

Grahic Jump Location
Fig. 7

River flow loading on the turbine blade

Grahic Jump Location
Fig. 9

Probability of failure of the hydrokinetic turbine blade




Some tools below are only available to our subscribers or users with an online account.

Related Content

Customize your page view by dragging and repositioning the boxes below.

Related Journal Articles
Related eBook Content
Topic Collections

Sorry! You do not have access to this content. For assistance or to subscribe, please contact us:

  • TELEPHONE: 1-800-843-2763 (Toll-free in the USA)
  • EMAIL: asmedigitalcollection@asme.org
Sign In