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Computational Simulation of Composite Ply Micromechanics Using Artificial Neural Networks
Author(s) -
Brown D. A.,
Murthy P. L. N.,
Berke L.
Publication year - 1991
Publication title -
computer‐aided civil and infrastructure engineering
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 2.773
H-Index - 82
eISSN - 1467-8667
pISSN - 1093-9687
DOI - 10.1111/j.1467-8667.1991.tb00179.x
Subject(s) - artificial neural network , micromechanics , computer science , computation , composite number , component (thermodynamics) , artificial intelligence , software , machine learning , algorithm , physics , thermodynamics , programming language
Artificial neural networks can provide improved computational efficiency relative to existing methods when an algorithmic description of functional relationships is either totally unavailable or is complex in nature. For complex calculations, significant reductions in elapsed computation time are possible. The primary goal of this project is to demonstrate the applicability of artificial neural networks to composite material characterization. As a test case, a neural network has been trained to accurately predict composite hygral, thermal, and mechanical properties when provided with basic information concerning the environment, constituent materials, and component ratios used in the creation of the composite. A brief introduction to neural networks is provided along with a description of the software tools and interfaces used in the project. Finally, the project results are presented.