Proceedings Of The Institution Of Mechanical Engineers, Part O: Journal Of Risk And Reliability 

About: Proceedings Of The Institution Of Mechanical Engineers, Part O: Journal Of Risk And Reliability is an academic journal published by SAGE Publishing. The journal publishes majorly in the area(s): Computer science & Reliability (semiconductor). It has an ISSN identifier of 1748-006X. Over the lifetime, 124 publications have been published receiving 66 citations. The journal is also known as: Journal of risk and reliability.

Automatic simulation-based testing of autonomous ships using Gaussian processes and temporal logic

Abstract: A methodology for automatic simulation-based testing of control systems for autonomous vessels is proposed. The work is motivated by the need for increased test coverage and formalism in the verification efforts. It aims to achieve this by formulating requirements in the formal logic Signal Temporal Logic (STL). This enables automatic evaluation of simulations against requirements using the STL robustness metric, resulting in a robustness score for requirements satisfaction. Furthermore, the proposed method uses a Gaussian Process (GP) model for estimating robustness scores including levels of uncertainty for untested cases. The GP model is updated by running simulations and observing the resulting robustness, and its estimates are used to automatically guide the test case selection toward cases with low robustness or high uncertainty. The main scientific contribution is the development of an automatic testing method which incrementally runs new simulations until the entire parameter space of the case is covered to the desired confidence level, or until a case which falsifies the requirement is identified. The methodology is demonstrated through a case study, where the test object is a Collision Avoidance (CA) system for a small high-speed vessel. STL requirements for safety distance, mission compliance, and COLREG compliance are developed. The proposed method shows promise, by both achieving verification in feasible time and identifying falsifying behaviors which would be difficult to detect manually or using brute-force methods. An additional contribution of this work is a formalization of COLREG using temporal logic, which appears to be an interesting direction for future work.

Optimizing a joint reliability-redundancy allocation problem with common cause multi-state failures using immune algorithm

Abstract: Redundancy-reliability allocation problem (RRAP) is a well-known problem in reliability area. In general, this problem aims to maximize a system’s reliability or minimize a system’s costs under some constraints. In this paper, we develop a RRAP for a series-parallel system with multi-state components. Thus, the subsystems’ components, the system’s subsystems, and the system have different working states with corresponding working probabilities. The RAP in the paper is a RAP with mix components (RAPMC). We consider the choice of allocating non-identical components to each sub-system. Moreover, we consider the common cause failure (CCF) for the components, which causes simultaneous failure of all identical components of a subsystem. We assume the component’s failure state probability is reduced by conducting technical activities, and the reduced probability is added to the component’s working states’ probabilities. The model’s objective function is to minimize the system’s costs under a minimum reliability level and other constraints by allocating the optimal set of components to each subsystem and determining each component’s technical activities level. Since the RRAP belongs to the Np-Hard category of problems, an immune algorithm is used to solve the developed problem. The results indicate considering the technical activities decreases the system’s costs.

Automatic simulation-based testing of autonomous ships using Gaussian processes and temporal logic

Abstract: A methodology for automatic simulation-based testing of control systems for autonomous vessels is proposed. The work is motivated by the need for increased test coverage and formalism in the verification efforts. It aims to achieve this by formulating requirements in the formal logic Signal Temporal Logic (STL). This enables automatic evaluation of simulations against requirements using the STL robustness metric, resulting in a robustness score for requirements satisfaction. Furthermore, the proposed method uses a Gaussian Process (GP) model for estimating robustness scores including levels of uncertainty for untested cases. The GP model is updated by running simulations and observing the resulting robustness, and its estimates are used to automatically guide the test case selection toward cases with low robustness or high uncertainty. The main scientific contribution is the development of an automatic testing method which incrementally runs new simulations until the entire parameter space of the case is covered to the desired confidence level, or until a case which falsifies the requirement is identified. The methodology is demonstrated through a case study, where the test object is a Collision Avoidance (CA) system for a small high-speed vessel. STL requirements for safety distance, mission compliance, and COLREG compliance are developed. The proposed method shows promise, by both achieving verification in feasible time and identifying falsifying behaviors which would be difficult to detect manually or using brute-force methods. An additional contribution of this work is a formalization of COLREG using temporal logic, which appears to be an interesting direction for future work.

Subset simulation for optimal sensors positioning based on value of information

Abstract: Greedy and non-greedy optimization methods have been proposed for maximizing the Value of Information (VoI) for equipment health monitoring by optimal sensors positioning. These methods provide good solutions, but still with limitations and challenges: greedy optimization does not guarantee to find the optimal solution, due to the non-submodularity of the VoI; non-greedy optimization does not suffer from the non-submodularity of the VoI but requires computationally expensive and tedious simulations to find the optimal solution. In this work, the Subset Simulation (SS) method is originally proposed to address these limitations and challenges. A real case study is considered concerning the condition monitoring of a Steam Generator (SG) of a Prototype Fast Breeder Reactor (PFBR). Results show that SS, even if initialized with a small number of Monte Carlo samples, is capable of finding the optimal set of sensors positions in a very short computational time and is insensitive to the non-submodularity of VoI.

Reliability analysis and optimal replacement for a k-out-of-n system under a δ -shock model

Abstract: Consider a k-out-of-n system which is subject to shocks that arrive at random times. This study develops δ -shock model, among the variants of well-known shock models, for such system which consists of independent components. In a δ -shock model, the system fails when the inter-arrival between two consecutive shocks is less than a critical threshold value of δ . Depending on the number of components that fail due to the occurrence of the shocks, we introduce two δ -shock models. The reliability function and mean time to failure of the system are discussed when the time between shocks has an arbitrary distribution. Furthermore, the problem of finding the optimal preventive time concerned with minimizing a mean cost per unit time is investigated. Numerical examples based on a simulation study are also provided to illustrate theoretical achievement.