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Related papers: Stochastic Modelling of Elasticity Tensor Fields

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We introduce a new concept of sparsity for the stochastic elliptic operator $-{\rm div}\left(a(x,\omega)\nabla(\cdot)\right)$, which reflects the compactness of its inverse operator in the stochastic direction and allows for spatially…

Numerical Analysis · Mathematics 2015-06-22 Thomas Y. Hou , Pengfei Liu

Inverse design of morphing slender structures with programmable curvature has significant applications in various engineering fields. Most existing studies formulate it as an optimization problem, which requires repeatedly solving the…

Soft Condensed Matter · Physics 2025-08-28 JiaHao Li , Weicheng Huang , YinBo Zhu , Luxia Yu , Xiaohao Sun , Mingchao Liu , HengAn Wu

The elasticity difference tensor, used in [1] to describe elasticity properties of a continuous medium filling a space-time, is here analysed from the point of view of the space-time connection. Principal directions associated with this…

General Relativity and Quantum Cosmology · Physics 2008-11-26 E. G. L. R. Vaz , Irene Brito

Random fields play a central role in the analysis of spatially correlated data and, as a result, have a significant impact on a broad array of scientific applications. This paper studies the cepstral random field model, providing recursive…

Statistics Theory · Mathematics 2014-01-17 Tucker S. McElroy , Scott H. Holan

Latent variable models are an elegant framework for capturing rich probabilistic dependencies in many applications. However, current approaches typically parametrize these models using conditional probability tables, and learning relies…

Machine Learning · Computer Science 2012-10-19 Ankur P. Parikh , Le Song , Mariya Ishteva , Gabi Teodoru , Eric P. Xing

This paper presents a new way of describing cross fields based on fourth order tensors. We prove that the new formulation is forming a linear space in $\mathbb{R}^9$. The algebraic structure of the tensors and their projections on…

Computational Geometry · Computer Science 2020-03-12 Alexandre Chemin , François Henrotte , Jean-François Remacle , Jean Van Schaftingen

This paper studies a tensor-structured linear regression model with a scalar response variable and tensor-structured predictors, such that the regression parameters form a tensor of order $d$ (i.e., a $d$-fold multiway array) in…

Machine Learning · Computer Science 2020-11-26 Talal Ahmed , Haroon Raja , Waheed U. Bajwa

Stochastic geometry provides a powerful framework for modelling complex random structures, with applications in physics, materials science, biology, and other fields. The three-dimensional microstructure of polycrystalline materials is…

Mathematical Physics · Physics 2025-07-22 Oleksandr Kornijčuk , Luděk Heller , Zbyněk Pawlas , Viktor Beneš

Term "asymmetrical pseudoelasticity" refers to the theory, in which a symmetrical stress tensor and a symmetrical strain tensor are connected by means of an asymmetrical material tensor. An 6-dimensional asymmetrical matrix of elasticity…

Mathematical Physics · Physics 2010-06-23 V. O. Bytev , L. I. Shkutin

In this work the linear elastic properties of materials containing spherical voids are calculated and compared using finite element simulations. The focus is on homogeneous solid materials with spherical, empty voids of equal size. The…

Real-world signals typically span across multiple dimensions, that is, they naturally reside on multi-way data structures referred to as tensors. In contrast to standard ``flat-view'' multivariate matrix models which are agnostic to data…

Signal Processing · Electrical Eng. & Systems 2019-12-04 Bruno Scalzo Dees , Anh-Huy Phan , Danilo P. Mandic

Latent space models are powerful statistical tools for modeling and understanding network data. While the importance of accounting for uncertainty in network analysis has been well recognized, the current literature predominantly focuses on…

Statistics Theory · Mathematics 2025-08-15 Jinming Li , Shihao Wu , Chengyu Cui , Gongjun Xu , Ji Zhu

We present two different arguments using stochastic analysis to construct super-renormalizable tensor field theories, namely the $\mathrm{T}^4_3$ and $\mathrm{T}^4_4$ models. The first approach is the construction of a Langevin dynamic…

Probability · Mathematics 2024-03-06 Ajay Chandra , Léonard Ferdinand

This paper presents a probabilistic approach to represent and quantify model-form uncertainties in the reduced-order modeling of complex systems using operator inference techniques. Such uncertainties can arise in the selection of an…

Machine Learning · Statistics 2024-11-08 Jin Yi Yong , Rudy Geelen , Johann Guilleminot

We study inverse problems in anisotropic elasticity using tools from algebraic geometry. The singularities of solutions to the elastic wave equation in dimension $n$ with an anisotropic stiffness tensor have propagation kinematics captured…

Differential Geometry · Mathematics 2025-05-01 Maarten V. de Hoop , Joonas Ilmavirta , Matti Lassas , Anthony Várilly-Alvarado

Integral expressions are determined for the elastic displacement and stress fields due to stationary or moving dislocation loops in finite samples. These general expressions are valid for anisotropic media as well. Specifically for the…

Condensed Matter · Physics 2017-02-08 Rodrigo Arias

We consider the general class of time-homogeneous stochastic dynamical systems, both discrete and continuous, and study the problem of learning a representation of the state that faithfully captures its dynamics. This is instrumental to…

Machine Learning · Computer Science 2024-03-15 Vladimir R. Kostic , Pietro Novelli , Riccardo Grazzi , Karim Lounici , Massimiliano Pontil

We propose bending energies for isotropic elastic plates and shells. For a plate, we define and employ a surface tensor that symmetrically couples stretch and curvature such that any elastic energy density constructed from its invariants is…

Soft Condensed Matter · Physics 2022-06-22 E. Vitral , J. A. Hanna

Commonly used linear and nonlinear constitutive material models in deformation simulation contain many simplifications and only cover a tiny part of possible material behavior. In this work we propose a framework for learning customized…

Graphics · Computer Science 2020-10-27 Bin Wang , Yuanmin Deng , Paul Kry , Uri Ascher , Hui Huang , Baoquan Chen

A generator of spatio-temporal pseudo-random Gaussian fields that satisfy the "proportionality of scales" property (Tsyroulnikov, 2001) is presented. The generator is based on a third-order in time stochastic differential equation with a…

Data Analysis, Statistics and Probability · Physics 2018-05-15 Michael Tsyrulnikov , Dmitry Gayfulin