peer reviewedA material network consists of discrete material nodes, which, when interacting, can represent complex microstructure responses. In this work, we investigate this concept of material networks under the viewpoint of the hierarchical network interactions. Within this viewpoint, the response of the material network is governed by a well-defined system of equations and an arbitrary number of phases can be considered, independently of the network architecture. The predictive capability is achieved by, on the one hand, sufficiently deep and rich network interactions to tie the discrete material nodes together, and, on the other hand, an efficient offline training procedure. For this purpose, a unified and efficient framework for a...
Soft network materials exist in numerous forms ranging from polymer networks, such as elastomers, to...
The toughness of a polymer material can increase significantly if two networks are combined into one...
In this paper we present a combined finite element (FE) \u2013 artificial neural network (ANN) appro...
peer reviewedA material network consisting of discrete material nodes and their interactions can rep...
In a concurrent (FE2) multiscale modeling is an increasingly popular approach for modeling complex m...
Modern material systems with properly designed microstructures offer new avenues for engineering mat...
Driven by the need to accelerate numerical simulations, the use of machine learning techniques is ra...
Abstract Recent developments integrating micromechanics and neural networks offer promising paths fo...
Fracture processes in fibre-reinforced quasi-brittle materials were studied with a threedimensional ...
Deep material networks (DMNs) are a recent multiscale technology which enable running concurrent mul...
peer reviewedA material network, as pioneered by [1] and consisting of discrete material nodes and ...
Deep material networks (DMN) are a promising piece of technology for accelerating concurrent multisc...
International audienceWe present a micro-mechanical model based on the network theory for the descri...
Abstract Developing accurate yet fast computational tools to simulate complex physical phenomena is ...
In this paper we present a combined finite element (FE) - artificial neural network (ANN) approach f...
Soft network materials exist in numerous forms ranging from polymer networks, such as elastomers, to...
The toughness of a polymer material can increase significantly if two networks are combined into one...
In this paper we present a combined finite element (FE) \u2013 artificial neural network (ANN) appro...
peer reviewedA material network consisting of discrete material nodes and their interactions can rep...
In a concurrent (FE2) multiscale modeling is an increasingly popular approach for modeling complex m...
Modern material systems with properly designed microstructures offer new avenues for engineering mat...
Driven by the need to accelerate numerical simulations, the use of machine learning techniques is ra...
Abstract Recent developments integrating micromechanics and neural networks offer promising paths fo...
Fracture processes in fibre-reinforced quasi-brittle materials were studied with a threedimensional ...
Deep material networks (DMNs) are a recent multiscale technology which enable running concurrent mul...
peer reviewedA material network, as pioneered by [1] and consisting of discrete material nodes and ...
Deep material networks (DMN) are a promising piece of technology for accelerating concurrent multisc...
International audienceWe present a micro-mechanical model based on the network theory for the descri...
Abstract Developing accurate yet fast computational tools to simulate complex physical phenomena is ...
In this paper we present a combined finite element (FE) - artificial neural network (ANN) approach f...
Soft network materials exist in numerous forms ranging from polymer networks, such as elastomers, to...
The toughness of a polymer material can increase significantly if two networks are combined into one...
In this paper we present a combined finite element (FE) \u2013 artificial neural network (ANN) appro...