Application of quantitative accelerated life models on load sharing redundancy

Mettas, Adamantios; Vassiliou, P.

doi:10.1109/rams.2004.1285463

Cited by 12 publications

(13 citation statements)

References 2 publications

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“…The basic definitions are given here, and more detailed information is available in references by Liu 22 and Mettas and Vassiliou. 23 The system's reliability function is given by…”

Section: Load-sharingmentioning

confidence: 99%

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Time-dependent reliability analysis of wind turbines considering load-sharing using fault tree analysis and Markov chains

Coolen

2019

Proceedings of the Institution of Mechanical Engineers, Part O:

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Due to the high failure rates and the high cost of operation and maintenance of wind turbines, not only manufacturers but also service providers try many ways to improve the reliability of some critical components and subsystems. In reality, redundancy design is commonly used to improve the reliability of critical components and subsystems. The load dependencies and failure dependencies among redundancy components and subsystems are crucial to the reliability assessment of wind turbines. However, the redundancy components are treated as a parallel system, and the load correlations among them are ignored in much literature, which may lead to the wrong system’s reliability and much higher costs. For this reason, this article explores the influences of load-sharing on system reliability. The whole system’s reliability is quantitatively evaluated using fault tree analysis and the Markov-chain method. Following this, the optimisation of the redundancy allocation problem considering the load-sharing is conducted to maximise the system reliability and reduce the total cost of the system subjecting to the available system cost and space. The results produced by this methodology can show a realistic reliability assessment of the entire wind turbine from a quantitative point of view. The realistic reliability assessment can help to design a cost-effective and more reliable system and significantly reduce the cost of wind turbines.

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“…The basic definitions are given here, and more detailed information is available in references by Liu 22 and Mettas and Vassiliou. 23 The system's reliability function is given by…”

Section: Load-sharingmentioning

confidence: 99%

“…The two-unit load-sharing system with two-parameter Weibull distribution is used in this paper. The basic definitions are given here, and more detailed information is available in references by Liu 22 and Mattas 23 .…”

Section: Load-sharingmentioning

confidence: 99%

Time-dependent reliability analysis of wind turbines considering load-sharing using fault tree analysis and Markov chains

Coolen

2019

Proceedings of the Institution of Mechanical Engineers, Part O:

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“…Yun and Nakagawa [37] compared the hot standby and the cold standby configurations when common causes and component failures are competing with exponential distributions. Mettas and Vassiliou [23] numerically compared the hot standby and the load-sharing configurations for two components following a Weibull lifetime distribution.…”

Section: Introductionmentioning

confidence: 99%

Reliability Comparison of Two Unit Redundancy Systems Under the Load Requirement

Kim¹

2020

Prob. Eng. Inf. Sci.

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This paper compares the reliability functions of the cold standby, hot standby, and load-sharing redundancy configurations, each of which is composed of two identical components for meeting a given system requirement. Thus far, no research has been done into the conditions that make one configuration more reliable than another because their reliability functions have no closed forms even when the component follows a Weibull lifetime distribution. In this paper, two analytical results are obtained given that the reliability of each configuration is expressed in terms of the design and operational loads of the component. First, higher reliability can be achieved in a cold standby configuration than in a load-sharing configuration if the increase in the component reliability obtained from the reduction in the operational load is not significant. Second, a cold standby configuration exhibits better reliability and carries a higher load than a hot standby configuration if the design load can be increased with a less decrease in the component reliability.

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“…3 There exist numerous papers that consider loadsharing systems. But most work based on the failure rate and there are several kinds of models, such as: proportional hazard model, 4 accelerated failure time model, 5 damage failure rate model, 6 and cumulative damage model. 7 Amari et al 8 studied the load-sharing models called tampered failure rate load-sharing models, and used the cumulative failure mode to consider the effect of load history to failure rate.…”

Section: Introductionmentioning

confidence: 99%

Reliability analysis of load-sharing parallel systems considering equivalent strength degradation

Song

et al. 2020

Proceedings of the Institution of Mechanical Engineers, Part O:

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In this paper, a new reliability method for load-sharing parallel systems with dependent components that share the workload equally before and after some components have failed is studied. In the working process of a load-sharing parallel system, after the failure of some components, the surviving components share the original system workload with higher components loads. The states of all the components are dependent. The failure behavior of a component impacts the strength degradation process of the remaining working components. For a load-sharing parallel system, one component works the whole system works, which means the component with the largest initial strength works, the whole system works. Firstly, we use the equivalent strength degradation theory to get the remaining strength of the component with the largest initial strength after some components fail. Then, the stress-strength interference model will be used to calculate the reliability after some components fail. Finally, the proposed method is illustrated by a numerical example and verified by the Monte Carlo simulation method.

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Application of quantitative accelerated life models on load sharing redundancy

Cited by 12 publications

References 2 publications

Time-dependent reliability analysis of wind turbines considering load-sharing using fault tree analysis and Markov chains

Time-dependent reliability analysis of wind turbines considering load-sharing using fault tree analysis and Markov chains

Reliability Comparison of Two Unit Redundancy Systems Under the Load Requirement

Reliability analysis of load-sharing parallel systems considering equivalent strength degradation

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