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We propose to homogenize a periodic (along one direction) structure, first in order to verify the quasi-static prediction of its response to an acoustic wave arising from mixing theory, then to address the question of what becomes of this…

Applied Physics · Physics 2018-03-14 Armand Wirgin

This paper presents a new adaptive multiscale homogenization scheme for the simulation of damage and fracture in concrete structures. A two-scale homogenization method, coupling meso-scale discrete particle models to macro- scale finite…

Computational Engineering, Finance, and Science · Computer Science 2017-02-03 Roozbeh Rezakhani , Xinwei Zhou , Gianluca Cusatis

We introduce structural heterogeneity, a new topological characteristic for semi-ordered materials that captures their degree of organisation at a mesoscopic level and tracks their time-evolution, ultimately detecting the order-disorder…

Effective properties of materials with random heterogeneous structures are typically determined by homogenising the mechanical quantity of interest in a window of observation. The entire problem setting encompasses the solution of a local…

Numerical Analysis · Mathematics 2021-10-22 Felipe Rocha , Simone Deparis , Pablo Antolin , Annalisa Buffa

Porous structures are materials consisting of minuscule pores, where the microstructure morphology significantly impacts their macroscopic properties. Integrating different porous structures through a blending method is indispensable to…

Graphics · Computer Science 2024-06-03 Depeng Gao , Yang Gao , Yuanzhi Zhang , Hongwei Lin

Micro-Electro-Mechanical Systems (MEMS) normally have fixed or moving structures with cross-sections of the order of microns ($\mu m$) and lengths of the order of tens or hundreds of microns. These structures are often plates or array of…

Computational Physics · Physics 2007-05-23 N. Majumdar , S. Mukhopadhyay

Material properties such as permeability fields in heterogeneous porous media are often represented as discontinuous, piecewise constant data tied to a given spatial discretization. Such representations are inherently mesh-dependent,…

Numerical Analysis · Mathematics 2026-05-19 Kapil Chawla , Sanghyun Lee , Yeonjong Shin

This work presents a neural network that consists of nodes with heterogeneous sensitivity. Each node in a network is assigned a variable that determines the sensitivity with which it learns to perform a given task. The network is trained by…

Computer Vision and Pattern Recognition · Computer Science 2019-06-06 Hyunjoong Cho , Jinhyeok Jang , Chanhyeok Lee , Seungjoon Yang

The morphology of nanostructured materials exhibiting a polydisperse porous space, such as aerogels, is very open porous and fine grained. Therefore, a simulation of the deformation of a large aerogel structure resolving the nanostructure…

Numerical Analysis · Mathematics 2024-03-04 Axel Klawonn , Martin Lanser , Lucas Mager , Ameya Rege

The local geometrical randomness of metal foams brings complexities to the performance prediction of porous structures. Although the relative density is commonly deemed as the key factor, the stochasticity of internal cell sizes and shapes…

Machine Learning · Computer Science 2022-11-04 Da Chen , Nima Emami , Shahed Rezaei , Philipp L. Rosendahl , Bai-Xiang Xu , Jens Schneider , Kang Gao , Jie Yang

Rigorous theories connecting physical properties of a heterogeneous material to its microstructure offer a promising avenue to guide the computational material design and optimization. We present here an efficient Fourier-space based…

Materials Science · Physics 2024-12-13 Wenlong Shi , Yang Jiao , Salvatore Torquato

This paper proposes a computational approach to form-find pin-jointed, bar structures subjected to combinations of tension and compression forces. The generated equilibrium states can meet force and geometric constraints via gradient-based…

Computational Engineering, Finance, and Science · Computer Science 2022-09-09 Rafael Pastrana , Patrick Ole Ohlbrock , Thomas Oberbichler , Pierluigi D'Acunto , Stefana Parascho

Recently, heterogeneous Graph Neural Networks (GNNs) have become a de facto model for analyzing HGs, while most of them rely on a relative large number of labeled data. In this work, we investigate Contrastive Learning (CL), a key component…

Machine Learning · Computer Science 2021-09-01 Yanqiao Zhu , Yichen Xu , Hejie Cui , Carl Yang , Qiang Liu , Shu Wu

Much of our understanding of complex structures is based on simplification: for example, metal-organic frameworks are often discussed in the context of "nodes" and "linkers", allowing for a qualitative comparison with simpler inorganic…

Materials Science · Physics 2020-05-21 Thomas C. Nicholas , Andrew L. Goodwin , Volker L. Deringer

Many material response functions depend strongly on microstructure, such as inhomogeneities in phase or orientation. Homogenization presents the task of predicting the mean response of a sample of the microstructure to external loading for…

Machine Learning · Computer Science 2022-10-04 Reese Jones , Cosmin Safta , Ari Frankel

Continuous-time Bayesian networks (CTBNs) are graphical representations of multi-component continuous-time Markov processes as directed graphs. The edges in the network represent direct influences among components. The joint rate matrix of…

Artificial Intelligence · Computer Science 2012-07-02 Nir Friedman , Raz Kupferman

There is an increasing interest in the fabrication of cement-based materials via additive manufacturing (AM) techniques. However, the processing-induced heterogeneities and interfaces represent a major challenge. The role of processing in…

Applied Physics · Physics 2018-08-02 Mohamadreza Moini , Jan Olek , Bryan Magee , Pablo Zavattieri , Jeffrey Youngblood

Tendon-bone enthesis connects tendon and bone, two mechanically dissimilar materials, while effectively minimizing stress concentrations, a capability rarely achieved in engineering materials. Its hierarchical organization and graded…

Soft Condensed Matter · Physics 2026-04-14 Zhangke Yang , Zhaoxu Meng

This article investigates the application of computer vision and graph-based models in solving mesh-based partial differential equations within high-performance computing environments. Focusing on structured, graded structured, and…

Machine Learning · Computer Science 2024-06-04 Jens Decke , Olaf Wünsch , Bernhard Sick , Christian Gruhl

In this paper, we present a robust and efficient unfitted concurrent multiscale method for continuum-continuum coupling, based on the Cut Finite Element Method (CutFEM). The computational domain is defined using approximate signed distance…

Computational Engineering, Finance, and Science · Computer Science 2023-06-02 Ehsan Mikaeili , Pierre Kerfriden , Susanne Claus