A review on data-driven constitutive laws for solids
This review article highlights state-of-the-art data-driven techniques to discover, encode,
surrogate, or emulate constitutive laws that describe the path-independent and path …
surrogate, or emulate constitutive laws that describe the path-independent and path …
[HTML][HTML] Constitutive artificial neural networks: A fast and general approach to predictive data-driven constitutive modeling by deep learning
In this paper we introduce constitutive artificial neural networks (CANNs), a novel machine
learning architecture for data-driven modeling of the mechanical constitutive behavior of …
learning architecture for data-driven modeling of the mechanical constitutive behavior of …
Virtual, digital and hybrid twins: a new paradigm in data-based engineering and engineered data
Engineering is evolving in the same way than society is doing. Nowadays, data is acquiring
a prominence never imagined. In the past, in the domain of materials, processes and …
a prominence never imagined. In the past, in the domain of materials, processes and …
Neural networks for constitutive modeling: From universal function approximators to advanced models and the integration of physics
Analyzing and modeling the constitutive behavior of materials is a core area in materials
sciences and a prerequisite for conducting numerical simulations in which the material …
sciences and a prerequisite for conducting numerical simulations in which the material …
Automated constitutive modeling of isotropic hyperelasticity based on artificial neural networks
Herein, an artificial neural network (ANN)-based approach for the efficient automated
modeling and simulation of isotropic hyperelastic solids is presented. Starting from a large …
modeling and simulation of isotropic hyperelastic solids is presented. Starting from a large …
Propagation of uncertainty in the mechanical and biological response of growing tissues using multi-fidelity Gaussian process regression
A key feature of living tissues is their capacity to remodel and grow in response to
environmental cues. Within continuum mechanics, this process can be captured with the …
environmental cues. Within continuum mechanics, this process can be captured with the …
Measuring stress field without constitutive equation
The present paper proposes a coupled experimental-numerical protocol to measure
heterogeneous stress fields in a model-free framework. This work contributes to developing …
heterogeneous stress fields in a model-free framework. This work contributes to developing …
[HTML][HTML] Discrete data-adaptive approximation of hyperelastic energy functions
Phenomenological constitutive modeling is prone to uncertainty and results in loss of
information as data coming from experiments are not used directly in calculations. Data …
information as data coming from experiments are not used directly in calculations. Data …
Structural-Genome-Driven computing for composite structures
The aim of this work is to propose a new approach, named Structural-Genome-Driven (SGD)
computing, for composite structures, where the structural-genome database is collected …
computing, for composite structures, where the structural-genome database is collected …
Machine Learning in Computer Aided Engineering
The extraordinary success of Machine Learning (ML) in many complex heuristic fields has
promoted its introduction in more analytical engineering fields, improving or substituting …
promoted its introduction in more analytical engineering fields, improving or substituting …