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Molecular Dynamics simulations can help scientists to gather valuable insights for physical processes on an atomic scale. This work explores various techniques for SIMD vectorization to improve the pairwise force calculation between…

Distributed, Parallel, and Cluster Computing · Computer Science 2025-12-04 Luis Gall , Samuel James Newcome , Fabio Alexander Gratl , Markus Mühlhäußer , Manish Kumar Mishra , Hans-Joachim Bungartz

Simulating the dynamics of ions near polarizable nanoparticles (NPs) using coarse-grained models is extremely challenging due to the need to solve the Poisson equation at every simulation timestep. Recently, a molecular dynamics (MD) method…

Computational Physics · Physics 2019-11-01 JCS Kadupitiya , Geoffrey C. Fox , Vikram Jadhao

Molecular dynamics (MD) simulations allow atomistic insights into chemical and biological processes. Accurate MD simulations require computationally demanding quantum-mechanical calculations, being practically limited to short timescales…

Many applications of computational fluid dynamics require multiple simulations of a flow under different input conditions. In this paper, a numerical algorithm is developed to efficiently determine a set of such simulations in which the…

Numerical Analysis · Mathematics 2017-05-29 Max Gunzburger , Nan Jiang , Zhu Wang

Polymers are a versatile class of materials with widespread industrial applications. Advanced computational tools could revolutionize their design, but their complex, multi-scale nature poses significant modeling challenges. Conventional…

A novel method combining the ensemble refinement by maximum entropy principle and the force field fitting approach is presented. Its formulation allows to continuously interpolate in between these two methods, which can thus be interpreted…

Chemical Physics · Physics 2024-01-30 Ivan Gilardoni , Thorben Fröhlking , Giovanni Bussi

A methodology is built to model and simulate the dynamics of domain coarsening of a two-phase ternary liquid with an arbitrary phase diagram. High numerical performance is obtained through the use of the phase field-method for interface…

Materials Science · Physics 2024-09-06 Werner Verdier , Alain Cartalade , Mathis Plapp

We introduce a reinforcement learning (RL) based adaptive optimization algorithm for aerodynamic shape optimization focused on dimensionality reduction. The form in which RL is applied here is that of a surrogate-based, actor-critic policy…

For most finite element simulations, boundary-conforming meshes have significant advantages in terms of accuracy or efficiency. This is particularly true for complex domains. However, with increased complexity of the domain, generating a…

Numerical Analysis · Mathematics 2021-04-07 Jan Helmig , Fabian Key , Marek Behr , Stefanie Elgeti

Chaotic free surface flows are challenging problems to simulate numerically, mainly due to the significant changes in geometry and frequent topological changes. Methods that track the evolution of the fluid in a Lagrangian formulation are a…

Fluid Dynamics · Physics 2025-12-24 Thomas Leyssens , Jonathan Lambrechts , Jean-François Remacle

The computational cost associated with simulating fluid flows can make it infeasible to run many simulations across multiple flow conditions. Building upon concepts from generative modeling, we introduce a new method for learning neural…

Computational Physics · Physics 2019-12-17 Jeremy Morton , Freddie D. Witherden , Mykel J. Kochenderfer

We present a new approach for computing planar hexagonal meshes that approximate a given surface, represented as a triangle mesh. Our method is based on two novel technical contributions. First, we introduce Coordinate Power Fields, which…

Graphics · Computer Science 2021-05-07 Kacper Pluta , Michal Edelstein , Amir Vaxman , Mirela Ben-Chen

Electronic structure methods offer in principle accurate predictions of molecular properties, however, their applicability is limited by computational costs. Empirical methods are cheaper, but come with inherent approximations and are…

Chemical Physics · Physics 2023-11-16 Moritz Thürlemann , Sereina Riniker

We describe and characterize a method for estimating the pressure field corresponding to velocity field measurements, such as those obtained by using particle image velocimetry. The pressure gradient is estimated from a time series of…

Fluid Dynamics · Physics 2014-01-22 John O. Dabiri , Sanjeeb Bose , Brad J. Gemmell , Sean P. Colin , John H. Costello

Since the 1960's the finite element method emerged as a powerful tool for the numerical simulation of countless physical phenomena or processes in applied sciences. One of the reasons for this undeniable success is the great versatility of…

Numerical Analysis · Mathematics 2018-12-05 Vitoriano Ruas

The Position Based Fluids (PBF) method is a state-of-the-art approach for fluid simulations in the context of real-time applications like games. It uses an iterative solver concept that tries to maintain a constant fluid density…

Graphics · Computer Science 2016-08-17 Marcel Köster , Antonio Krüger

Machine learning algorithms have recently emerged as a tool to generate force fields which display accuracies approaching the ones of the ab-initio calculations they are trained on, but are much faster to compute. The enhanced computational…

Computational Physics · Physics 2019-09-17 Claudio Zeni , Kevin Rossi , Aldo Glielmo , Francesca Baletto

The solidification behavior of liquid metal in a container under rapid cooling process is one of the major concerns to be analyzed. In order to analyze its fundamental behavior, a three- dimensional (3D) fluid dynamics simulation was…

Fluid Dynamics · Physics 2013-09-18 Raden Ahnaf Faqih S , Christian Fredy Naa

Accurate modeling of chemically reactive systems has traditionally relied on either expensive ab initio approaches or flexible bond-order force fields such as ReaxFF that require considerable time, effort, and expertise to parameterize.…

Materials Science · Physics 2022-09-21 Jonathan Vandermause , Yu Xie , Jin Soo Lim , Cameron J. Owen , Boris Kozinsky

We present a way to dramatically accelerate Gaussian process models for interatomic force fields based on many-body kernels by mapping both forces and uncertainties onto functions of low-dimensional features. This allows for automated…

Computational Physics · Physics 2021-03-23 Yu Xie , Jonathan Vandermause , Lixin Sun , Andrea Cepellotti , Boris Kozinsky