A new family of Constitutive Artificial Neural Networks towards automated model discovery

• Published in: Computer methods in applied mechanics and engineering Vol. 403; p. 115731
• Main Authors: Linka, Kevin, Kuhl, Ellen
• Format: Journal Article
• Language: English
• Published: Amsterdam Elsevier B.V 01.01.2023; Elsevier BV
• Subjects: Artificial neural networks; Automated model discovery; Automated science; Automation; Axial stress; Computer architecture; Constitutive Artificial Neural Networks; Constitutive modeling; Constitutive models; Constitutive relationships; Incompressibility; Machine learning; Mathematical models; Modelling; Neural Networks; Parameters; Shear modulus; Source code; Stiffness; Thermodynamics; Thermodynamics; Constitutive Artificial Neural Networks; Machine learning; Neural Networks; Automated science; Constitutive modeling; Automated model discovery

For more than 100 years, chemical, physical, and material scientists have proposed competing constitutive models to best characterize the behavior of natural and man-made materials in response to mechanical loading. Now, computer science offers a universal solution: Neural Networks. Neural Networks...