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The behavior of materials is influenced by a wide range of phenomena occurring across various time and length scales. To better understand the impact of microstructure on macroscopic response, multiscale modeling strategies are essential.…

Reduced order models are computationally inexpensive approximations that capture the important dynamical characteristics of large, high-fidelity computer models of physical systems. This paper applies machine learning techniques to improve…

Machine Learning · Computer Science 2015-11-11 Azam Moosavi , Razvan Stefanescu , Adrian Sandu

An automatically differentiable, high-order non-oscillatory finite volume shallow water dynamic core has been constructed on a cubed sphere grid. This dynamic core has four advantageous properties: high order accuracy, essential…

Fluid Dynamics · Physics 2025-01-03 Lilong Zhou

Soft materials (e.g., enveloped viruses, liposomes, membranes and supercooled liquids) simultaneously deform or display collective behaviors, while undergoing atomic scale vibrations and collisions. While the multiple space-time character…

Soft Condensed Matter · Physics 2014-01-03 Peter Ortoleva , Abhishek Singharoy , Stephen Pankavich

Molecular dynamics simulations are indispensable for exploring the behavior of atoms and molecules. Grounded in quantum mechanical principles, quantum molecular dynamics provides high predictive power but its computational cost is dominated…

Chemical Physics · Physics 2025-09-10 Siu Wun Cheung , Youngsoo Choi , Jean-Luc Fattebert , Daniel Osei-Kuffuor

Modern GPUs are equipped with large amounts of high-bandwidth memory, enabling them to support mini-batch sizes of up to tens of thousands of training samples. However, most existing optimizers struggle to perform effectively at such a…

Machine Learning · Computer Science 2026-02-10 Yishun Lu , Wesley Armour

In this paper, we propose a unified two-phase scheme to accelerate any high-order regularized tensor approximation approach on the smooth part of a composite convex optimization model. The proposed scheme has the advantage of not needing to…

Optimization and Control · Mathematics 2020-07-06 Bo Jiang , Tianyi Lin , Shuzhong Zhang

Innovative membrane technologies optimally integrated into large separation process plants are essential for economical water treatment and disposal. However, the mass transport through membranes is commonly described by nonlinear…

Motivated by variational models in continuum mechanics, we introduce a novel algorithm to perform nonsmooth and nonconvex minimizations with linear constraints in Euclidean spaces. We show how this algorithm is actually a natural…

Analysis of PDEs · Mathematics 2015-03-20 Marco Artina , Massimo Fornasier , Francesco Solombrino

Meshless methods approximate operators in a specific node as a weighted sum of values in its neighbours. Higher order approximations of derivatives provide more accurate solutions with better convergence characteristics, but they come at…

Distributed, Parallel, and Cluster Computing · Computer Science 2025-09-12 Jon Vehovar , Miha Rot , Gregor Kosec

We present SCOPE, a fast and efficient framework for modeling and manipulating deformable linear objects (DLOs). Unlike conventional energy-based approaches, SCOPE leverages convex approximations to significantly reduce computational cost…

Robotics · Computer Science 2026-01-28 Ali Jnadi , Hadi Salloum , Yaroslav Kholodov , Alexander Gasnikov , Karam Almaghout

With recent advances in variable-length structures for use in soft actuation, energy harvesting, energy dissipation and metamaterials, the mathematical modelling and numerical simulation of physical systems with time-varying domains is…

Soft Condensed Matter · Physics 2024-10-31 Panagiotis Koutsogiannakis , Theodosios Papathanasiou , Francesco Dal Corso

Robot programming tools ranging from inverse kinematics (IK) to model predictive control (MPC) are most often described as constrained optimization problems. Even though there are currently many commercially-available second-order solvers,…

Robotics · Computer Science 2023-07-03 Hakan Girgin , Tobias Löw , Teng Xue , Sylvain Calinon

We exploit analogies between first-order algorithms for constrained optimization and non-smooth dynamical systems to design a new class of accelerated first-order algorithms for constrained optimization. Unlike Frank-Wolfe or projected…

Optimization and Control · Mathematics 2025-05-02 Michael Muehlebach , Michael I. Jordan

This paper presents the first application of the direct parametrisation method for invariant manifolds to a fully coupled multiphysics problem involving the nonlinear vibrations of deformable structures subjected to an electrostatic field.…

Numerical Analysis · Mathematics 2023-12-25 Attilio Frangi , Alessio Colombo , Alessandra Vizzaccaro , Cyril Touzé

Accurate deformable object manipulation (DOM) is essential for achieving autonomy in robotic surgery, where soft tissues are being displaced, stretched, and dissected. Many DOM methods can be powered by simulation, which ensures realistic…

Robotics · Computer Science 2024-05-31 Xiao Liang , Fei Liu , Yutong Zhang , Yuelei Li , Shan Lin , Michael Yip

This paper presents a method to generate valid high order meshes with optimized geometrical accuracy. The high order meshing procedure starts with a linear mesh, that is subsequently curved without taking care of the validity of the high…

Computational Physics · Physics 2016-03-23 Thomas Toulorge , Jonathan Lambrechts , Jean-François Remacle

Numerical simulations of high-speed forming and welding are of significant interest to industry, but are challenging due to the coupled physics and dynamic nature of the processes. With the advancement in hardware and computational…

Applied Physics · Physics 2019-12-24 Ali Nassiri , Tim Abke , Glenn Daehn

Micro-structured materials consisting of an array of microstructures are engineered to provide the specific material properties. This present work investigates the design of cellular materials under the framework of level set, so as to…

Computational Engineering, Finance, and Science · Computer Science 2018-11-13 Jie Gao , Hao Li , Zhen Luo , Liang Gao , Peigen Li

The paper proposes an approach for the efficient model order reduction of dynamic contact problems in linear elasticity. Instead of the augmented Lagrangian method that is widely used for mechanical contact problems, we prefer here the…

Numerical Analysis · Mathematics 2021-07-27 Diana Manvelyan , Bernd Simeon , Utz Wever