Abstract

This paper presents a novel single loop approach to design the components of the load sharing systems by optimally allocating the failure probabilities to each component, thereby satisfying the overall system reliability requirement. The Reliability–Based Design Optimization (RBDO) of load sharing systems is computationally intensive due to the dynamic nature of component failure probabilities, since the failure of one component will vary the failure probabilities of other working components. Many RBDO methods have been successfully utilized to design individual components, however using these methods for handling system level reliability constraints is still a challenging task. This is because of a drop in accuracy and computational efficiency, especially when considering a load sharing system, where there is dependency in failure probabilities of components. The key idea is to integrate Stress–Strength Interference (SSI) theory with discrete (or) continuous time-discrete state Markov model for the reliability assessment of system, with the states being the condition of components (working/failed). This method takes advantage of the state transition probability matrix to represent the dynamic nature of the system performance. A numerical example of a simple load sharing system with two I-Beams is presented to illustrate and evaluate the performance of the proposed methodology.

Highlights

  • The Reliability–Based Design Optimization (RBDO) of mechanical systems is an iterative process and involves two steps, one being optimization and the other being reliability assessment [1,2]

  • To validate the results of our single loop formulation, the Monte Carlo (MC) simulation was used as benchmark [27]

  • In the case of Stress–Strength Interference (SSI)–Continuous Time Markov Chain (CTMC), the time unit of 25 years is specified by the customer

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Summary

Introduction

The RBDO of mechanical systems is an iterative process and involves two steps, one being optimization and the other being reliability assessment [1,2]. Few methods can handle both the system and component level reliability, with most of them devoid of handling repair rates of the system [1,5,6,7,8,9]. Traditional methods such as joint distribution approach, compound events, minimal cut sets, probability modeling or minimal path sets method are not efficient and intractable when the number of components increases [1,5,6,7]. The development of efficient and accurate RBDO framework for the system level design optimization, especially for the load sharing systems is essential but not an easy task

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