شماره ركورد كنفرانس :
5364
عنوان مقاله :
Data-Driven modeling of an elastomer bushing system under various visco-hyperelastic deformations
پديدآورندگان :
Daareyni Amirmohammad School of Mechanical Engineering, College of Engineering, University of Tehran, Tehran, Iran , Baghani Mostafa School of Mechanical Engineering, College of Engineering, University of Tehran, Tehran, Iran
كليدواژه :
Data , Driven# Constitutive Modeling# Viscoelasticity# Neural Networks# Elastomers
عنوان كنفرانس :
سي امين همايش سالانه بين المللي انجمن مهندسان مكانيك ايران
چكيده فارسي :
Since visco-hyperelastic materials are vastly used in different industries, a proper constitutive model plays a key role in predicting materials’ behavior. On the other hand, due to the substantial leap in data science and machine learning methods, it is beneficial to use these models to simplify the constitutive modeling procedure. This paper aims to develop a new modeling approach based on machine learning that can accurately predict the visco-hyperelastic behavior of materials in different loading conditions.
