Cost Optimization and Reliability Parameter Extraction of a Complex Engineering System

Abstract

Nowadays, the transformation of the various energy system is the core objective of the dedicated sustainable development goal related to energy sustainable world within the new United Nations development agenda. Different nuclear regulatory authorities around the globe, sets Technical Specifications (TSs) for ensuring the human and environmental safety of various highly volatile and complex Nuclear Power Generation Plants (NPGPs). TSs define numerous measures and limitations related to safety and sustainability that must be followed by all NPGPs around the world. Reliability, availability and cost components associated with a NPGPs form important bases for the setting of TSs. In this work, a framework based on few recent metaheuristics like Cuckoo Search Algorithm (CSA), Grey Wolf Optimizer (GWO), Hybrid PSO GWO algorithm (HPSOGWO) has been presented for cost optimization and reliability parameter extraction of a complex engineering system named Heat Removal System (HRS) of a nuclear power generation plant safety system (NPGPSS). A multi-criteria decision-making (MCDM) method named Weighted-Sum Method (WSM) has also been employed for prioritizing the available metaheuristics based on available beneficial and non-beneficial criteria’s.

An Archimedean Copulas-Based Approach for m-Consecutive-k-Out-of-n: F Systems with Exchangeable Components

“…Moreover, the dilemma of whether the cold standby redundancy is more effective when it is applied at system level or at component level has attracted the attention of some researchers (see, e.g., [13][14][15][16]). For additional surveys concerning the cost optimization or optimal allocation in reliability structures, the interested reader is referred to [17][18][19].…”