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A method of modelling the three-dimensional microstructure of random isotropic two-phase materials is proposed. The information required to implement the technique can be obtained from two-dimensional images of the microstructure. The…

Disordered Systems and Neural Networks · Physics 2009-10-31 Anthony Roberts

The 3D microstructure of solid oxide fuel cell anodes significantly influences their electrochemical performance, but conventional methods for acquiring high-resolution microstructural 3D data such as focused ion beam scanning electron…

Materials Science · Physics 2025-10-24 Léon F. Schröder , Sabrina Weber , Lukas Fuchs , Volker Schmidt , Benedikt Prifling

The issue addressed in this paper is that of testing for common breaks across or within equations of a multivariate system. Our framework is very general and allows integrated regressors and trends as well as stationary regressors. The null…

Statistics Theory · Mathematics 2018-01-12 Tatsushi Oka , Pierre Perron

Machine learning techniques have been widely employed as effective tools in addressing various engineering challenges in recent years, particularly for the challenging task of microstructure-informed materials modeling. This work provides a…

Materials Science · Physics 2024-05-29 Xiang-Long Peng , Mozhdeh Fathidoost , Binbin Lin , Yangyiwei Yang , Bai-Xiang Xu

This paper reviews the current state-of-the-art in the simulation of the mechanical behavior of polycrystalline materials by means of computational homogenization. The key ingredients of this modelling strategy are presented in detail…

Materials Science · Physics 2018-11-22 J. Segurado , R. A. Lebensohn , J. LLorca

This work proposes a novel procedure to test for common structures across two high-dimensional factor models. The introduced test allows to uncover whether two factor models are driven by the same loading matrix up to some linear…

Methodology · Statistics 2026-03-17 Marie-Christine Düker , Vladas Pipiras

Modelling of inspection data for large scale physical systems is critical to assessment of their integrity. We present a general method for inference about system state and associated model variance structure from spatially distributed time…

Methodology · Statistics 2013-02-26 David Randell , Michael Goldstein , Philip Jonathan

A simple micromechanical model of polycrystalline materials is proposed, which enables us to swiftly produce grain-boundary-stress distributions induced by the uniform external loading (in the elastic strain regime). Such statistical…

Materials Science · Physics 2024-05-24 Timon Mede , Samir El Shawish

A general model is formulated for elasto-plastic materials undergoing linear kinematic hardening to describe microstructure evolution associated with phase transformations. Using infinitesimal strain theory, the model is based on…

Computational Engineering, Finance, and Science · Computer Science 2026-02-20 Sarah Dinkelacker-Steinhoff , Klaus Hackl

We present a simple theoretical framework, and corresponding practical procedures, for comparing probabilistic models on real data in a traditional machine learning setting. This framework is based on the theory of proper scoring rules, but…

Machine Learning · Statistics 2015-02-13 Mithun Chakraborty , Sanmay Das , Allen Lavoie

We used first-principles methods to perform a systematic search for potentially-stable phases of multiferroic BiFeO3. We considered a simulation cell compatible with the atomic distortions that are most common among perovskite oxides, and…

Materials Science · Physics 2013-05-29 Oswaldo Diéguez , O. E. González-Vázquez , Jacek C. Wojdeł , Jorge Íñiguez

Predicting the structural response of advanced multiphase alloys and understanding the underlying microscopic mechanisms that are responsible for it are two critically important roles modeling plays in alloy development. An alloys…

Materials science inherently spans disciplines: experimentalists use advanced microscopy to uncover micro- and nanoscale structure, while theorists and computational scientists develop models that link processing, structure, and properties.…

Machine Learning · Computer Science 2026-03-25 Simon Daubner , Alexander E. Cohen , Benjamin Dörich , Samuel J. Cooper

Synchrotron Laue microdiffraction and Digital Image Correlation measurements were coupled to track the elastic strain field (or stress field) and the total strain field near a general grain boundary in a bent bicrystal. A 316L stainless…

We discuss existing and new computational analysis techniques to classify local atomic arrangements in large-scale atomistic computer simulations of crystalline solids. This article includes a performance comparison of typical analysis…

Materials Science · Physics 2012-06-13 Alexander Stukowski

The structural information in high-dimensional transposable data allows us to write the data recorded for each subject in a matrix such that both the rows and the columns correspond to variables of interest. One important problem is to test…

Methodology · Statistics 2015-06-18 Anestis Touloumis , Simon Tavaré , John C. Marioni

There is currently a gap in theory for point patterns that lie on the surface of objects, with researchers focusing on patterns that lie in a Euclidean space, typically planar and spatial data. Methodology for planar and spatial data thus…

Statistics Theory · Mathematics 2020-02-11 Scott Ward , Edward A. K. Cohen , Niall Adams

Testing covariance structure is of importance in many areas of statistical analysis, such as microarray analysis and signal processing. Conventional tests for finite-dimensional covariance cannot be applied to high-dimensional data in…

Statistics Theory · Mathematics 2013-10-31 Rongmao Zhang , Liang Peng , Ruodu Wang

Floorplanning is the first stage of VLSI physical design. An effective floorplanning engine definitely has positive impact on chip design speed, quality and performance. In this paper, we present a novel mathematical model to characterize…

Hardware Architecture · Computer Science 2022-10-10 Ximeng Li , Keyu Peng , Fuxing Huang , Wenxing Zhu

The Voronoi diagram of a finite set of objects is a fundamental geometric structure that subdivides the embedding space into regions, each region consisting of the points that are closer to a given object than to the others. We may define…

Computational Geometry · Computer Science 2020-10-01 Frank Nielsen , Jean-Daniel Boissonnat , Richard Nock