Metaheuristics Algorithm-Based Optimization for High Conductivity and Hardness CuNi<sub>2</sub>Si<sub>1</sub> Alloy

Konieczny J., Labisz K., ÜRGÜN S., YİĞİT H., FİDAN S., BORA M. Ö., ...Daha Fazla

MATERIALS, sa.5, 2025 (SCI-Expanded) identifier identifier

  • Yayın Türü: Makale / Tam Makale
  • Basım Tarihi: 2025
  • Doi Numarası: 10.3390/ma18051060
  • Dergi Adı: MATERIALS
  • Derginin Tarandığı İndeksler: Science Citation Index Expanded (SCI-EXPANDED), Scopus, Academic Search Premier, Aerospace Database, CAB Abstracts, Communication Abstracts, Compendex, INSPEC, Metadex, Veterinary Science Database, Directory of Open Access Journals, Civil Engineering Abstracts
  • Kocaeli Üniversitesi Adresli: Evet

Özet

The optimization of CuNi2Si1 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 degrees 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 Ni2Si precipitates' development, and property improvement increased. Optimum temperature and holding period were 450 degrees 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 degrees 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.