Establishing process-structure linkages using Generative Adversarial Networks

Autor:	Safiuddin, Mohammad, Reddy, CH Likith, Vasantada, Ganesh, Harsha, CHJNS, Gangolu, Srinu
Rok vydání:	2021
Předmět:	Condensed Matter - Materials Science Computer Science - Machine Learning
Druh dokumentu:	Working Paper
Popis:	The microstructure of material strongly influences its mechanical properties and the microstructure itself is influenced by the processing conditions. Thus, establishing a Process-Structure-Property relationship is a crucial task in material design and is of interest in many engineering applications. We develop a GAN (Generative Adversarial Network) to synthesize microstructures based on given processing conditions. This approach is devoid of feature engineering, needs little domain awareness, and can be applied to a wide variety of material systems. Results show that our GAN model can produce high-fidelity multi-phase microstructures which have a good correlation with the given processing conditions. Comment: 16 pages, 9 figures
Databáze:	arXiv
Externí odkaz:	http://arxiv.org/abs/2107.09402 Zobrazit plný text záznamu View this record from Arxiv