A generic physics-informed neural network-based constitutive model for soft biological tissues
Constitutive modeling is a cornerstone for stress analysis of mechanical behaviors of
biological soft tissues. Recently, it has been shown that machine learning (ML) techniques …
biological soft tissues. Recently, it has been shown that machine learning (ML) techniques …
A mechanics‐informed artificial neural network approach in data‐driven constitutive modeling
A mechanics‐informed artificial neural network approach for learning constitutive laws
governing complex, nonlinear, elastic materials from strain–stress data is proposed. The …
governing complex, nonlinear, elastic materials from strain–stress data is proposed. The …
Automated model discovery for muscle using constitutive recurrent neural networks
The stiffness of soft biological tissues not only depends on the applied deformation, but also
on the deformation rate. To model this type of behavior, traditional approaches select a …
on the deformation rate. To model this type of behavior, traditional approaches select a …
A comparative study on different neural network architectures to model inelasticity
M Rosenkranz, KA Kalina, J Brummund… - … Journal for Numerical …, 2023 - Wiley Online Library
The mathematical formulation of constitutive models to describe the path‐dependent, that is,
inelastic, behavior of materials is a challenging task and has been a focus in mechanics …
inelastic, behavior of materials is a challenging task and has been a focus in mechanics …
[HTML][HTML] A new family of Constitutive Artificial Neural Networks towards 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 …
competing constitutive models to best characterize the behavior of natural and man-made …
Data-driven modeling of the mechanical behavior of anisotropic soft biological tissue
Closed-form constitutive models are currently the standard approach for describing soft
tissues' mechanical behavior. However, there are inherent pitfalls to this approach. For …
tissues' mechanical behavior. However, there are inherent pitfalls to this approach. For …
Structure-based constitutive model can accurately predict planar biaxial properties of aortic wall tissue
Abstract Structure-based constitutive models might help in exploring mechanisms by which
arterial wall histology is linked to wall mechanics. This study aims to validate a recently …
arterial wall histology is linked to wall mechanics. This study aims to validate a recently …
Recurrent neural networks (RNNs) learn the constitutive law of viscoelasticity
G Chen - Computational Mechanics, 2021 - Springer
Recurrent neural networks (RNNs) have demonstrated very impressive performances in
learning sequential data, such as in language translation and music generation. Here, we …
learning sequential data, such as in language translation and music generation. Here, we …
[HTML][HTML] A review of artificial neural networks in the constitutive modeling of composite materials
Abstract Machine learning models are increasingly used in many engineering fields thanks
to the widespread digital data, growing computing power, and advanced algorithms. The …
to the widespread digital data, growing computing power, and advanced algorithms. The …
Learning nonlinear constitutive laws using neural network models based on indirectly measurable data
Artificial neural network (ANN) models are used to learn the nonlinear constitutive laws
based on indirectly measurable data. The real input and output of the ANN model are …
based on indirectly measurable data. The real input and output of the ANN model are …