An Efficient Method to Calculate the Failure Rate of Dynamic Systems with Random Parameters using the Total Probability Theorem
Abstract
Using the total probability theorem, we propose a method to calculate the failure rate of a linear vibratory system with random parameters excited by stationary Gaussian processes. The response of such a system is non-stationary because of the randomness of the input parameters. A space-filling design, such as optimal symmetric Latin hypercube sampling or maximin, is first used to sample the input parameter space. For each design point, the output process is stationary and Gaussian. We present two approaches to calculate the corresponding conditional probability of failure. A Kriging metamodel is then created between the input parameters and the output conditional probabilities allowing us to estimate the conditional probabilities for any set of input parameters. The total probability theorem is finally applied to calculate the time-dependent probability of failure and the failure rate of the dynamic system. The proposed method is demonstrated using a vibratory system. Our approach can be easily extended to non-stationary Gaussian input processes.
Document Details
- Document Type
- Technical Report
- Publication Date
- May 12, 2015
- Accession Number
- ADA623247
Entities
People
- Amandeep Singh
- Igor Baseski
- Monica Majcher
- Vasileios Geroulas
- Zissimos P. Mourelatos
Organizations
- United States Army Tank Automotive Research, Development and Engineering Center