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Atomic-scale phase-field modeling formulates the probability densities of atomic vibrations as Gaussian distributions and derives a free energy functional using variational Gaussian theory and interatomic potentials. This framework permits…

Materials Science · Physics 2025-09-17 Kairi Masuda , Yu Kumagai

Numerous full-field numerical methods exist concerning the digital description of polycrystalline materials and the modeling of their evolution during thermomechanical treatments. However, these strategies are globally dedicated to the…

Computational Engineering, Finance, and Science · Computer Science 2022-08-22 Nitish Chandrappa , Marc Bernacki

Hot-rolling is a metal forming process that produces a workpiece with a desired target cross-section from an input workpiece through a sequence of plastic deformations; each deformation is generated by a stand composed of opposing rolls…

Computational Engineering, Finance, and Science · Computer Science 2020-07-30 R. Omar Chavez-Garcia , Emian Furger , Samuele Kronauer , Christian Brianza , Marco Scarfò , Luca Diviani , Alessandro Giusti

Meshfree simulation methods are emerging as compelling alternatives to conventional mesh-based approaches, particularly in the fields of Computational Fluid Dynamics (CFD) and continuum mechanics. In this publication, we provide a…

Machine Learning · Computer Science 2024-03-21 Paulami Banerjee , Mohan Padmanabha , Chaitanya Sanghavi , Isabel Michel , Simone Gramsch

Estimating the free energy, as well as other thermodynamic observables, is a key task in lattice field theories. Recently, it has been pointed out that deep generative models can be used in this context [1]. Crucially, these models allow…

High Energy Physics - Lattice · Physics 2022-09-21 Kim A. Nicoli , Christopher Anders , Lena Funcke , Tobias Hartung , Karl Jansen , Pan Kessel , Shinichi Nakajima , Paolo Stornati

We propose a machine learning framework based on Flow Matching (FM) to identify critical properties in many-body systems efficiently. Using the 2D XY model as a benchmark, we demonstrate that a single network, trained only on configurations…

Statistical Mechanics · Physics 2026-01-06 Qian-Rui Lee , Daw-Wei Wang

Change point analyses are concerned with identifying positions of an ordered stochastic process that undergo abrupt local changes of some underlying distribution. When multiple processes are observed, it is often the case that information…

Methodology · Statistics 2022-01-21 José J. Quinlan , Garritt L. Page , Luis M. Castro

We develop a thermodynamic theory for machine learning (ML) systems. Similar to physical thermodynamic systems which are characterized by energy and entropy, ML systems possess these characteristics as well. This comparison inspire us to…

Machine Learning · Computer Science 2024-04-23 Dong Zhang

Superconductors have been among the most fascinating substances, as the fundamental concept of superconductivity as well as the correlation of critical temperature and superconductive materials have been the focus of extensive investigation…

Atomistic simulations have become a powerful tool in materials research due to the extremely fine spatial and temporal resolution provided by such techniques. In order to understand the fundamental principles which govern material behavior…

Materials Science · Physics 2014-08-26 Jason F. Panzarino , Timothy J. Rupert

In this work, we present the modelling and numerical simulation of a molten glass fluid flow in a furnace melting basin. We first derive a model for a molten glass fluid flow and present numerical simulations based on the Finite Element…

Fluid Dynamics · Physics 2024-07-24 Francesco Ballarin , Enrique Delgado Ávila , Andrea Mola , Gianluigi Rozza

The solidification and macro-segregation problem involving unsteady multi-physics and multi-phase fields is typically a complex process with mass, momentum, heat, and species transfers among solid, mushy, and liquid phase regions. The…

Fluid Dynamics · Physics 2023-03-21 Xiaoyu Feng , Huangxin Chen , Bo Yu , Shuyu Sun

One of the most important and complicated problems in modern industry is to obtaining materials with the required chemical composition, structure and mechanical and physical properties. Solving this problem involves great deal of time and…

Materials Science · Physics 2018-10-31 Konstantin Borodianskiy , Michael Zinigrad

The prediction of material properties through electronic-structure simulations based on density-functional theory has become routinely common, thanks, in part, to the steady increase in the number and robustness of available simulation…

Finite element models without simplifying assumptions can accurately describe the spatial and temporal distribution of heat in machine tools as well as the resulting deformation. In principle, this allows to correct for displacements of the…

Computational Engineering, Finance, and Science · Computer Science 2018-11-20 Andreas Naumann , Daniel Ruprecht , Joerg Wensch

In the last few years several ``universal'' interatomic potentials have appeared, using machine-learning approaches to predict energy and forces of atomic configurations with arbitrary composition and structure, with an accuracy often…

Thermal fracture is prevalent in many engineering problems and is one of the most devastating defects in metal additive manufacturing. Due to the interactive underlying physics involved, the computational simulation of such a process is…

Materials Science · Physics 2022-12-28 Hui Ruan , Shahed Rezaei , Yangyiwei Yang , Dietmar Gross , Bai-Xiang Xu

At the Institute for Thermodynamics and Thermal Process Engineering (ITT) about 100 molecular models for pure substances have been developed so far. These models reproduce vapor pressure, saturated liquid density, and enthalpy of…

Computational Physics · Physics 2009-04-22 Bernhard Eckl , Martin Horsch , Jadran Vrabec , Hans Hasse

We consider three-dimensional models for rate-independent processes describing materials undergoing phase transformations with heat transfer. The problem is formulated within the framework of generalized standard solids by the coupling of…

Analysis of PDEs · Mathematics 2011-04-29 Laetitia Paoli , Adrien Petrov

The thermal conductivity of organic liquids is a vital parameter influencing various industrial and environmental applications, including energy conversion, electronics cooling, and chemical processing. However, atomistic simulation of…