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A new methodology is developed to integrate numerically the equations of motion for classical many-body systems in molecular dynamics simulations. Its distinguishable feature is the possibility to preserve, independently on the size of the…

Statistical Mechanics · Physics 2009-10-31 I. P. Omelyan , I. M. Mryglod , R. Folk

We study compressible fluid flow in narrow two-dimensional channels using a novel molecular dynamics simulation method. In the simulation area, an upstream source is maintained at constant density and temperature while a downstream…

Condensed Matter · Physics 2009-10-22 M. Sun , C. Ebner

Computational fluid dynamics and aerodynamics, which complement more expensive empirical approaches, are critical for developing aerospace vehicles. During the past three decades, computational aerodynamics capability has improved…

The concept of a fluid algebra was introduced by Sullivan over a decade ago as an algebraic construct which contains everything necessary in order to write down a form of the Euler equation, as an ODE whose solutions have invariant…

Analysis of PDEs · Mathematics 2025-04-09 Ofir Aharoni , Daniel An , Alice Kwon , Ruth Lawrence , Dennis Sullivan

The equations for a self-similar solution of an inviscid incompressible fluid are mapped into an integral equation which hopefully can be solved by iteration. It is argued that the exponent of the similarity are ruled by Kelvin's theorem of…

Fluid Dynamics · Physics 2016-11-22 Yves Pomeau

The resolution of the Poisson equation is usually one of the most computationally intensive steps for incompressible fluid solvers. Lately, Deep Learning, and especially Convolutional Neural Networks (CNN), has been introduced to solve this…

Fluid Dynamics · Physics 2021-09-24 Ekhi Ajuria Illarramendi , Michaël Bauerheim , Bénédicte Cuenot

We present an Eulerian vortex method based on the theory of flow maps to simulate the complex vortical motions of incompressible fluids. Central to our method is the novel incorporation of the flow-map transport equations for line elements,…

Graphics · Computer Science 2024-09-17 Sinan Wang , Yitong Deng , Molin Deng , Hong-Xing Yu , Junwei Zhou , Duowen Chen , Taku Komura , Jiajun Wu , Bo Zhu

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 introduce latent intuitive physics, a transfer learning framework for physics simulation that can infer hidden properties of fluids from a single 3D video and simulate the observed fluid in novel scenes. Our key insight is to use latent…

Artificial Intelligence · Computer Science 2024-08-06 Xiangming Zhu , Huayu Deng , Haochen Yuan , Yunbo Wang , Xiaokang Yang

The ever increasing demands placed upon machine performance have resulted in the need for more comprehensive particle accelerator modeling. Computer simulations are key to the success of particle accelerators. Many aspects of particle…

In a world made of atoms, the computer simulation of molecular systems, such as proteins in water, plays an enormous role in science. Software packages that perform these computations have been developed for decades. In molecular…

Chemical Physics · Physics 2024-08-07 Philipp Hoellmer , A. C. Maggs , Werner Krauth

Physics-informed deep learning has drawn tremendous interest in recent years to solve computational physics problems, whose basic concept is to embed physical laws to constrain/inform neural networks, with the need of less data for training…

Fluid Dynamics · Physics 2020-11-24 Chengping Rao , Hao Sun , Yang Liu

Kinetic instabilities are one of the most challenging aspects in computational plasma physics. Accurately capturing their onset and evolution requires fine resolution of the high-dimensional distribution functions of each relevant species,…

Plasma Physics · Physics 2025-11-05 Rostislav-Paul Wilhelm , Manuel Torrilhon

In this note we analyze a model for a unidirectional unsteady flow of a viscous incompressible fluid with time dependent viscosity. A possible way to take into account such behaviour is to introduce a memory formalism, including thus the…

Analysis of PDEs · Mathematics 2013-04-04 Roberto Garra , Federico Polito

Turbulent fluid flows are among the most computationally demanding problems in science, requiring enormous computational resources that become prohibitive at high flow speeds. Physics-informed neural networks (PINNs) represent a radically…

Machine Learning · Computer Science 2025-10-14 Sifan Wang , Shyam Sankaran , Xiantao Fan , Panos Stinis , Paris Perdikaris

We study the settling of solid particles within a viscous incompressible fluid contained in a two-dimensional channel, where the mass density of the particles is slightly greater than that of the fluid. The fluid-structure interaction…

Fluid Dynamics · Physics 2015-09-07 Sudeshna Ghosh , John M. Stockie

A computer code or simulator is a mathematical representation of a physical system, for example a set of differential equations. Running the code with given values of the vector of inputs, x, leads to an output y(x) or several such outputs.…

Methodology · Statistics 2016-01-25 Derek Bingham , Pritam Ranjan , William Welch

In this study, we develop computational models and methodology for accurate multi-component-flow simulation in under-resolved multi-scale porous structures. It is generally impractical to fully resolve the flow in porous structures with…

Blood flow, dam or ship construction and numerous other problems in biomedical and general engineering involve incompressible flows interacting with elastic structures. Such interactions heavily influence the deformation and stress states…

Computational Engineering, Finance, and Science · Computer Science 2021-12-17 R. Schussnig , D. R. Q. Pacheco , T. -P. Fries

Inferring universal laws of the environment is an important ability of human intelligence as well as a symbol of general AI. In this paper, we take a step toward this goal such that we introduce a new challenging problem of inferring…

Artificial Intelligence · Computer Science 2018-11-30 Siyu Huang , Zhi-Qi Cheng , Xi Li , Xiao Wu , Zhongfei Zhang , Alexander Hauptmann