Metaheuristics Algorithm-Based Optimization for High Conductivity and Hardness CuNi(2)Si(1) Alloy

基于元启发式算法的高导电性和高硬度CuNi(2)Si(1)合金优化

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Abstract

The optimization of CuNi(2)Si(1) alloy's mechanical and electrical properties was achieved through a combination of experimental approaches and metaheuristic algorithms. Optimizing hardness and electrical conductivity through a variation in aging temperature (450-600 °C) and aging duration (1-420 min) was taken under consideration in the present work. Cold rolling with 50% strain after solution annealing aided in microstructure refinement and accelerated Ni(2)Si precipitates' development, and property improvement increased. Optimum temperature and holding period were 450 °C and 30 min, respectively, with 266 HV and 13 MS/m and 167 HV and 11.2 MS/m for non-deformed samples, respectively. SPBO, genetic algorithm (GA), and particle swarm optimization (PSO) metaheuristic algorithms were considered, and SPBO exhibited the best prediction accuracy. SPBO predicted 450 °C for 61.75 min, and experimental testing exhibited 267 HV and 14 MS/m, respectively. Polynomial regressions with 0.98 and 0.96 values for R(2) confirmed these values' accuracy. According to this work, computational optimization proves effective in optimizing development and property tailoring for application in industries including aerospace and electrical engineering.

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