Optimization of porosity behavior of hybrid reinforced titanium metal matrix composite through RSM, ANN, and GA for multi-objective parameters

Abstract Titanium matrix composites (TMCs) have high specific strength and stiffness, and high-temperature TMCs can reduce weight by up to 50% when compared with monolithic super alloys while preserving equal stiffness and strength in jet engine systems for propulsion. The purpose of this work exami...

詳細記述

書誌詳細

出版年:	Journal of Engineering and Applied Science
主要な著者:	Birhane Assefa Gemeda, Devendra Kumar Sinha, Getinet Asrat Mengesha, Satyam Shivam Gautam
フォーマット:	論文
言語:	英語
出版事項:	SpringerOpen 2024-05-01
主題:	Hybrid titanium metal matrix composite Porosity Response surface methodology Artificial neural networks Genetic algorithm
オンライン･アクセス:	https://doi.org/10.1186/s44147-024-00436-4