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Simulation Algorithms to Assess the Impact of Aging on the Reliability of Standby Systems with Switching Failures

Version 2 2024-09-18, 23:44
Version 1 2023-05-22, 19:33
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posted on 2024-09-18, 23:44 authored by N Nikolava, Kiril TenekedjievKiril Tenekedjiev, G Fan, Mark SymesMark Symes, Hong-Oanh NguyenHong-Oanh Nguyen
We analyze the influence of aging on the reliability of a two-component standby system with switching failures (2SBSF). When the backup component is aging in standby as if it is working, we have a 2SBSF with full aging. Typically, such a system is modelled with a rate diagram (where the failure rates are time-dependent) which has an adjacent system of 3 ordinary differential equations (ODEs). The reliability characteristics of the 2SBSF with full aging can be obtained from the numerical solution of the formulated Cauchy problem. Alternatively, simulation modelling can produce the same results, but without using the rate diagram. In that way we can adapt the simulation algorithms to treat the cases when either the backup component does not age in standby (2SBSF with no aging), or when the backup component ages in standby slower than in operation (2SBSF with partial aging). In the last two cases there is neither rate diagram, nor a system of ODEs since the 2SBSF is not state dependent when the full aging assumption does not hold. We develop ten algorithms to facilitate the simulation solutions of the 2SBSF with no aging and with partial aging. We emphasize on the ways to deal with the numerical problems created by working with truncated distributions and with random sampling

History

Publication title

Advances in Intelligent Systems Research and Innovation

Volume

379

Editors

V Sgurev, V Jotsov, and J Kacprzyk

Pagination

463-496

ISBN

978-3-030-78123-1

Department/School

National Centre for Maritime Engineering and Hydrodynamics, Maritime and Logistics Management

Publisher

Springer

Publication status

  • Published

Place of publication

Switzerland

Extent

21

Rights statement

Copyright 2022 The Author(s), under exclusive license to Springer Nature Switzerland AG

Socio-economic Objectives

280101 Expanding knowledge in the agricultural, food and veterinary sciences

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