IJE TRANSACTIONS C: Aspects Vol. 30, No. 12 (December 2017) 1457-1466    Article in Press

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M. Mahdavi, G. R. Khayati, M. Hosseini and H. Danesh-Manesh
( Received: April 02, 2017 – Accepted: September 08, 2017 )

Abstract    This paper deals with modeling and optimization of roll-bonding process of Ti/Cu/Ti composite for determination of the best roll-bonding parameters leading to the maximum Cu/Ti bond strength by combining neural network and genetic algorithm. An artificial neural networks (ANNs) program proposed to determine the effect of practical parameters, i.e., rolling temperature, reduction in thickness, post-annealing time, post-annealing temperature and rolling speed on the bond strength of Ti/Cu composite. The most suitable model with coefficient of determination (R2) 0.98 and mean absolute error (MAPE) 3.5 was determined and using genetic algorithm (GA) the optimum practice condition was proposed. Moreover, the sensitivity analysis results showed the post-annealing temperature with negative effects is the most influential parameter on the strength bonding.


Keywords    Ti/Cu/Ti clad composite; Roll-bonding; Bond strength; Genetic algorithm; Artificial neural network


چکیده    این مقاله به مدل‌سازی و بهنیه‌سازی فرایند اتصال نوردی کامپوزیت Ti/Cu/Ti با هدف تعیین مناسب‌ترین پارمترهای منجر به حداکثر استحکام پیوند با استفاده از ترکیب شبکه عصبی و الگوریتم ژنتیک می‌پردازد. یک برنامه از شبکه‌های عصبی مصنوعی (ANNs) برای تعیین اثر پارامتر‌های اثرگذار نظیر دمای نورد، کاهش در ضخامت، زمان تابکاری اولیه، دمای تابکاری اولیه و سرعت نورد بر استحکام پیوند کامپوزیت Ti/Cu اتخاذ شد. بهترین مدل با ضریب تعیین (R2) 98/0 و میانگین مطلق خطای (MAPE) 5/3 تعیین شد و با استفاده از الگوریتم ژنتیک (GA) شرایط بهینه عملیات پیشنهاد شد. علاوه بر این، نتایج آنالیز حساسیت نشان داد که دمای تابکاری اولیه با تاثیر منفی اثرگذارترین عامل بر استحکام پیوند است.

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