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The variational multiscale (VMS) formulation is used to develop residual-based VMS large eddy simulation (LES) models for Rayleigh-B\'{e}nard convection. The resulting model is a mixed model that incorporates the VMS model and an eddy…

Computational Physics · Physics 2020-05-21 David Sondak , Thomas M. Smith , Roger P. Pawlowski , Sidafa Conde , John N. Shadid

For today's electronics manufacturing process, the emphasis on stable functionality, durability, and fixed physical forms is designed to ensure long-term usability. However, this focus on robustness and permanence complicates the…

Human-Computer Interaction · Computer Science 2024-06-17 Tingyu Cheng , Zhihan Zhang , Han Huang , Yingting Gao , Wei Sun , Gregory D. Abowd , HyunJoo Oh , Josiah Hester

With robots increasingly operating in human-centric environments, ensuring soft and safe physical interactions, whether with humans, surroundings, or other machines, is essential. While compliant hardware can facilitate such interactions,…

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In this work we report some results, obtained within the framework of the ERC Project CHANGE, on the impact on the performance of the virtual element method of the shape of the polygonal elements of the underlying mesh. More in detail,…

Deploying Large Language Model (LLM) applications, particularly those relying on Retrieval-Augmented Generation (RAG), remains challenging due to high computational demands, outdated knowledge bases, and the need to manually select optimal…

Material selection plays a pivotal role in many industries, from manufacturing to construction. Material selection is usually carried out after several cycles of conceptual design, during which designers iteratively refine the design…

Machine Learning · Computer Science 2024-07-16 Yash Patawari Jain , Daniele Grandi , Allin Groom , Brandon Cramer , Christopher McComb

Representation Engineering (RepE) is a novel paradigm for controlling the behavior of LLMs. Unlike traditional approaches that modify inputs or fine-tune the model, RepE directly manipulates the model's internal representations. As a…

Machine Learning · Computer Science 2025-10-09 Jan Wehner , Sahar Abdelnabi , Daniel Tan , David Krueger , Mario Fritz

The formation of microstructures in metallic alloys during hot metal forming involves simultaneous metallurgical complex phenomena. Traditional high-fidelity numerical frameworks used on the polycrystalline scale tend to focus on…

Materials Science · Physics 2024-05-24 Nitish Chandrappa , Marc Bernacki

In Materials Science, material development involves evaluating and optimizing the internal structures of the material, generically referred to as microstructures. Microstructures structure is stochastic, analogously to image textures. A…

Machine Learning · Computer Science 2024-08-06 Sayed Sajad Hashemi , Michael Guerzhoy , Noah H. Paulson

We present a Virtual Element Method (VEM) for possibly nonlinear elastic and inelastic problems, mainly focusing on a small deformation regime. The numerical scheme is based on a low-order approximation of the displacement field, as well as…

Numerical Analysis · Mathematics 2023-07-19 L. Beirão da Veiga , C. Lovadina , D. Mora

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

We investigate the implications of a given symmetry of a random microstructure on the obtained effective tensor and its fluctuation in the context of thermal conductivity, and study strategies for enforcing these symmetries in…

Computational Engineering, Finance, and Science · Computer Science 2025-11-07 Binh Huy Nguyen , Matti Schneider

High performance materials, from natural bone over ancient damascene steel to modern superalloys, typically possess a complex structure at the microscale. Their properties exceed those of the individual components and their knowledge-based…

Materials Science · Physics 2019-03-25 Carl Kusche , Tom Reclik , Martina Freund , Talal Al-Samman , Ulrich Kerzel , Sandra Korte-Kerzel

We present a virtual element method (VEM) for the numerical approximation of the electromagnetics subsystem of the resistive magnetohydrodynamics (MHD) model in two spatial dimensions. The major advantages of the virtual element method…

Numerical Analysis · Mathematics 2020-04-27 S. Naranjo Alvarez , V. A. Bokil , V. Gyrya , G. Manzini

Simulation of fracturing processes in porous rocks can be divided into two main branches: (i) modeling the rock as a continuum which is enhanced with special features to account for fractures, or (ii) modeling the rock by a discrete (or…

Numerical Analysis · Mathematics 2017-02-07 Halvor Møll Nilsen , Idar Larsen , Xavier Raynaud

The newly proposed microstructural constitutive model for polycrystal viscoplasticity in cold and warm regimes (Motaman and Prahl, 2019), is implemented as a microstructural solver via user-defined material subroutine in a finite element…

Computational Physics · Physics 2019-09-11 S. Amir H. Motaman , Konstantin Schacht , Christian Haase , Ulrich Prahl

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…

Direct numerical simulation of hierarchical materials via homogenization-based concurrent multiscale models poses critical challenges for 3D large scale engineering applications, as the computation of highly nonlinear and path-dependent…

Computational Engineering, Finance, and Science · Computer Science 2022-12-29 Shiguang Deng

3D volume rendering is widely used to reveal insightful intrinsic patterns of volumetric datasets across many domains. However, the complex structures and varying scales of volumetric data can make efficiently generating high-quality volume…

Graphics · Computer Science 2023-10-17 Jianxin Sun , David Lenz , Hongfeng Yu , Tom Peterka

Constructing efficient and diverse datasets is essential for the development of accurate machine learning potentials (MLPs) in atomistic simulations. However, existing approaches often suffer from data redundancy and high computational…