کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
5019298 | 1468201 | 2018 | 9 صفحه PDF | دانلود رایگان |
- Steady-state solution of Markov chain reliability models is considered.
- Block Gauss-Seidel method can be efficiently implemented for steady-state solution.
- Reliability model with â¼2 millions of states can be solved in just a few seconds.
This paper presents the solution of Markov chain reliability models with a large state-space. To specify a system reliability model, we use our previously proposed methodology, which is based on the Stochastic Automata Networks formalism. We model parts of the system by arrowhead matrices with functional transition rates. As a result, the infinitesimal generator matrix of the reliability model has a distinctive structure. In this paper, we demonstrate that a block Gauss-Seidel method can be applied very efficiently to such a structure. The application of the proposed methodology is illustrated by an example of a standard 3/2 substation configuration. Even though its Markov chain reliability model has almost two million states, its steady-state probabilities can be estimated in just a few seconds of CPU time.
Journal: Reliability Engineering & System Safety - Volume 169, January 2018, Pages 570-578