Stochastic modeling and analysis of some reliability characteristics of a repairable warm standby system

2013 ◽  
Vol 7 ◽  
pp. 5847-5862 ◽  
Author(s):  
Lawan Bulama ◽  
Ibrahim Yusuf ◽  
Saminu I. Bala
Keyword(s):  
Stochastic Modeling ◽  
Modeling And Analysis ◽  
Reliability Characteristics ◽  
Standby System ◽  
Warm Standby

scholarly journals Reliability Simulation of Two Component Warm-Standby System with Repair, Switching, and Back-Switching Failures under Three Aging Assumptions

Mathematics ◽  
2021 ◽  
Vol 9 (20) ◽  
pp. 2547
Author(s):  
Kiril Tenekedjiev ◽  
Simon Cooley ◽  
Boyan Mednikarov ◽  
Guixin Fan ◽  
Natalia Nikolova
Keyword(s):  
Failure Rate ◽  
Primary Component ◽  
The Other ◽  
System Failures ◽  
First Case ◽  
Reliability Characteristics ◽  
Two Component ◽  
Standby System ◽  
Dependent Failure ◽  
Warm Standby

We analyze the influence of repair on a two-component warm-standby system with switching and back-switching failures. The repair of the primary component follows a minimal process, i.e., it experiences full aging during the repair. The backup component operates only while the primary component is being repaired, but it can also fail in standby, in which case there will be no repair for the backup component (as there is no indication of the failure). Four types of system failures are investigated: both components fail to operate in a different order or one of two types of switching failures occur. The reliability behavior of the system is investigated under three different aging assumptions for the backup component during warm-standby: full aging, no aging, and partial aging. Four failure and repair distributions determine the reliability behavior of the system. We analyzed two cases—in the First Case, we utilized constant failure rate distributions. In the Second Case, we applied the more realistic time-dependent failure rates. We used three methods to identify the reliability characteristics of the system: analytical, numerical, and simulational. The analytical approach is limited and only viable for constant failure rate distributions i.e., the First Case. The numerical method integrates simultaneous Algebraic Differential Equations. It produces a solution in the First Case under any type of aging, and in the Second Case but only under the assumption of full aging in warm-standby. On the other hand, the developed simulation algorithms produce solutions for any set of distributions (i.e., the First Case and the Second Case) under any of the three aging assumptions for the backup component in standby. The simulation solution is quantitively verified by comparison with the other two methods, and qualitatively verified by comparing the solutions under the three aging assumptions. It is numerically proven that the full aging and no aging solutions could serve as bounds of the partial aging case even when the precise mechanism of partial aging is unknown.

Introduction

2015 ◽  
Author(s):  
Habib Ammari ◽  
Elie Bretin ◽  
Josselin Garnier ◽  
Hyeonbae Kang ◽  
Hyundae Lee ◽  
...  
Keyword(s):  
Optimal Control ◽  
Wave Propagation ◽  
Elastic Wave ◽  
Stochastic Modeling ◽  
Physical Parameters ◽  
Vibration Testing ◽  
Elastic Structures ◽  
Modeling And Analysis ◽  
Elastic Inclusions ◽  
Statistical Approaches

This book is about recent mathematical, numerical and statistical approaches for elasticity imaging of inclusions and cracks with waves at zero, single or multiple non-zero frequencies. It considers important developments in asymptotic imaging, stochastic modeling, and analysis of both deterministic and stochastic elastic wave propagation phenomena and puts them together in a coherent way. It gives emphasis on deriving the best possible imaging functionals for small inclusions and cracks in the sense of stability and resolution. For imaging extended elastic inclusions, the book develops accurate optimal control methodologies and examines the effect of uncertainties of the geometric or physical parameters on their stability and resolution properties. It also presents an asymptotic framework for vibration testing and a method for identifying, locating, and estimating inclusions and cracks in elastic structures by measuring their modal characteristics.

scholarly journals Stochastic modeling and analysis of vapor cloud explosions domino effects in chemical plants

2019 ◽  
Vol 25 (1) ◽  
Author(s):  
Diego Sierra ◽  
Leonardo Montecchi ◽  
Ivan Mura
Keyword(s):  
Stochastic Modeling ◽  
Operating Conditions ◽  
Chemical Plants ◽  
Domino Effect ◽  
Modeling And Analysis ◽  
Modeling Methodology ◽  
Vapor Cloud ◽  
Maintenance Activities ◽  
Support Decision Making

Abstract Because of the substances they process and the conditions of operation, chemical plants are systems prone to the occurrence of undesirable and potentially dangerous events. Major accidents may occur when a triggering event produces a cascading accident that propagates to other units, a scenario known as domino effect. Assessing the probability of experiencing a domino effect and estimating the magnitude of its consequences is a complex task, as it depends on the nature of the substances being processed, the operating conditions, the failure proneness of equipment units, the execution of preventive maintenance activities, and of course the plant layout. In this work, we propose a stochastic modeling methodology to perform a probabilistic analysis of the likelihood of domino effects caused by propagating vapor cloud explosions. Our methodology combines mathematical models of the physical characteristics of the explosion, with stochastic state-based models representing the actual propagation among equipment units and the effect of maintenance activities. Altogether, the models allow predicting the likelihood of major events occurrence and the associated costs. A case study is analyzed, where various layouts of atmospheric gasoline tanks are assessed in terms of the predicted consequences of domino effects occurrence. The results of the analyses show that our approach can provide precious insights to support decision-making for safety and cost management.

Stochastic modeling and analysis of drivers’ decision making

2007 ◽  
Author(s):  
Shun Taguchi ◽  
Shogo Sekizawa ◽  
Shinkichi Inagaki ◽  
Tatsuya Suzuki ◽  
Soichiro Hayakawa ◽  
...  
Keyword(s):  
Decision Making ◽  
Stochastic Modeling ◽  
Modeling And Analysis

A semi-regenerative process of two-unit warm standby system

1982 ◽  
Vol 22 (3) ◽  
pp. 483-489
Author(s):  
Kohyu Uematsu ◽  
Masashi Kowada
Keyword(s):  
Regenerative Process ◽  
Standby System ◽  
Warm Standby
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