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We present approaches for the study of fluid-structure interactions subject to thermal fluctuations. A mixed mechanical description is utilized combining Eulerian and Lagrangian reference frames. We establish general conditions for…

Soft Condensed Matter · Physics 2023-02-28 Paul J. Atzberger

Physical simulation predicts future states of objects based on material properties and external loads, enabling blueprints for both Industry and Engineering to conduct risk management. Current 3D reconstruction-based simulators typically…

Machine Learning · Computer Science 2026-02-20 Yicheng Cao , Zhuo Huang , Yu Yao , Yiming Ying , Daoyi Dong , Tongliang Liu

Universal machine-learning interatomic potentials (uMLIPs) enable reactive molecular simulations with near-DFT accuracy, yet applying them efficiently to large, realistic condensed-phase systems remains computationally demanding. Here we…

Materials Science · Physics 2026-03-25 Yu Miyazaki , Atsuhiro Tomita , Akihide Hayashi , So Takamoto , Mizuki Takemoto , Hodaka Mori

We introduce a new computational method for embedding Lagrangian sink particles into an Eulerian calculation. Simulations of gravitational collapse or accretion generally produce regions whose density greatly exceeds the mean density in the…

Astrophysics · Physics 2009-11-10 Mark R. Krumholz , Christopher F. McKee , Richard I. Klein

We introduce a framework for designing primal methods under the decentralized optimization setting where local functions are smooth and strongly convex. Our approach consists of approximately solving a sequence of sub-problems induced by…

Optimization and Control · Mathematics 2020-06-15 Yossi Arjevani , Joan Bruna , Bugra Can , Mert Gürbüzbalaban , Stefanie Jegelka , Hongzhou Lin

It is well known that the number of particles should be scaled up to enable industrial scale simulation. The calculations are more computationally intensive when the motion of the surrounding fluid is considered. Besides the advances in…

Computational Physics · Physics 2014-07-28 Hao Zhang , F. Xavier Trias , Assensi Oliva , Dongmin Yang , Yuanqiang Tan , Shi Shu , Yong Sheng

N-body simulations are essential for understanding the formation and evolution of structure in the Universe. However, the discrete nature of these simulations affects their accuracy when modelling collisionless systems. We introduce a new…

Cosmology and Nongalactic Astrophysics · Physics 2015-11-18 Oliver Hahn , Raul E. Angulo

Detection and modeling of change-points in time-series can be considerably challenging. In this paper we approach this problem by incorporating the class of Dynamic Generalized Linear Models (DGLM) into the well know class of Product…

We propose QPALM, a nonconvex quadratic programming (QP) solver based on the proximal augmented Lagrangian method. This method solves a sequence of inner subproblems which can be enforced to be strongly convex and which therefore admit a…

Optimization and Control · Mathematics 2024-04-17 Ben Hermans , Andreas Themelis , Panagiotis Patrinos

A new and effective computational approach is presented for analyzing transient heat conduction problems. The approach consists of a meshless Fragile Points Method (FPM) being utilized for spatial discretization, and a Local Variational…

Computational Engineering, Finance, and Science · Computer Science 2020-01-27 Yue Guan , Rade Grujicic , Xuechuan Wang , Leiting Dong , Satya N. Atluri

Machine learning interatomic potentials (MLIPs) are one of the main techniques in the materials science toolbox, able to bridge ab initio accuracy with the computational efficiency of classical force fields. This allows simulations ranging…

Materials Science · Physics 2025-03-20 Bruno Focassio , Luis Paulo Mezzina Freitas , Gabriel R. Schleder

To predict flow behavior of entangled polymer melt, we have developed multiscale simulation composed of Lagrangian fluid particle simulation and coarse-grained polymer dynamics simulation. We have introduced a particle deformation in the…

Soft Condensed Matter · Physics 2014-01-31 Takahiro Murashima

In this paper we study decomposition methods based on separable approximations for minimizing the augmented Lagrangian. In particular, we study and compare the Diagonal Quadratic Approximation Method (DQAM) of Mulvey and Ruszczy\'{n}ski and…

Optimization and Control · Mathematics 2013-09-02 Rachael Tappenden , Peter Richtarik , Burak Buke

In this paper we present a new Eulerian finite element method for the discretization of scalar partial differential equations on evolving surfaces. In this method we use the restriction of standard space-time finite element spaces on a…

Numerical Analysis · Mathematics 2022-12-26 Hauke Sass , Arnold Reusken

Currently, Eulerian flow solvers are very efficient in accurately resolving flow structures near solid boundaries. On the other hand, they tend to be diffusive and to dampen high-intensity vortical structures after a short distance away…

Numerical Analysis · Mathematics 2015-06-05 Artur Palha , Lento Manickathan , Carlos Simao Ferreira , Gerard van Bussel

Extending 3D Gaussian Splatting (3DGS) to 4D physical simulation remains challenging. Based on the Material Point Method (MPM), existing methods either rely on manual parameter tuning or distill dynamics from video diffusion models,…

Computer Vision and Pattern Recognition · Computer Science 2026-02-03 Yikun Ma , Yiqing Li , Jingwen Ye , Zhongkai Wu , Weidong Zhang , Lin Gao , Zhi Jin

The augmented Lagrangiam method (ALM), widely used in quantum chemistry constrained optimization problems, is applied in the context of the nuclear Density Functional Theory (DFT) in the self-consistent constrained Skyrme…

Nuclear Theory · Physics 2014-11-21 A. Staszczak , M. Stoitsov , A. Baran , W. Nazarewicz

The standard approach to densely reconstruct the motion in a volume of fluid is to inject high-contrast tracer particles and record their motion with multiple high-speed cameras. Almost all existing work processes the acquired multi-view…

Computer Vision and Pattern Recognition · Computer Science 2019-11-25 Katrin Lasinger , Christoph Vogel , Thomas Pock , Konrad Schindler

First-order methods (FOMs) have been widely used for solving large-scale problems. A majority of existing works focus on problems without constraint or with simple constraints. Several recent works have studied FOMs for problems with…

Optimization and Control · Mathematics 2021-02-10 Zichong Li , Yangyang Xu

This paper presents numerical simulations of metal machining processes with Eulerian and Total Lagrangian Smoothed Particle Hydrodynamics (SPH). Being a mesh-free method, SPH can conveniently handle large deformation and material…

Computational Engineering, Finance, and Science · Computer Science 2019-04-05 Md Rushdie Ibne Islam , Ankur Bansal , Chong Peng
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