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Magnetic reconnection is a fundamental process that quickly releases magnetic energy stored in a plasma.Identifying, from simulation outputs, where reconnection is taking place is non-trivial and, in general, has to be performed by human…

Computational Physics · Physics 2020-09-09 A. Hu , M. Sisti , F. Finelli , F. Califano , J. Dargent , M. Faganello , E. Camporeale , J. Teunissen

Machine learning is applied to investigate the phase transition of two-dimensional complex plasmas. The Langevin dynamics simulation is employed to prepare particle suspensions in various thermodynamic states. Based on the resulted particle…

Plasma Physics · Physics 2023-07-25 He Huang , Vladimir Nosenko , Han-Xiao Huang-Fu , Hubertus M. Thomas , Cheng-Ran Du

Engineering and applied sciences use models of increasing complexity to simulate the behaviour of manufactured and physical systems. Propagation of uncertainties from the input to a response quantity of interest through such models may…

Computation · Statistics 2016-06-29 K. Konakli , B. Sudret

Modern techniques for physical simulations rely on numerical schemes and mesh-refinement methods to address trade-offs between precision and complexity, but these handcrafted solutions are tedious and require high computational power.…

Machine Learning · Computer Science 2024-02-21 Janny Steeven , Nadri Madiha , Digne Julie , Wolf Christian

Real-life control tasks involve matters of various substances---rigid or soft bodies, liquid, gas---each with distinct physical behaviors. This poses challenges to traditional rigid-body physics engines. Particle-based simulators have been…

Machine Learning · Computer Science 2019-04-19 Yunzhu Li , Jiajun Wu , Russ Tedrake , Joshua B. Tenenbaum , Antonio Torralba

We present novel coupling schemes for partitioned multi-physics simulation that combine four important aspects for strongly coupled problems: implicit coupling per time step, fast and robust acceleration of the corresponding iterative…

Numerical Analysis · Mathematics 2020-09-21 Benjamin Rüth , Benjamin Uekermann , Miriam Mehl , Philipp Birken , Azahar Monge , Hans-Joachim Bungartz

We introduce a closure model for coarse-grained kinetic theories of polar active fluids. Based on a quasi-equilibrium approximation of the particle distribution function, the model closely captures important analytical properties of the…

Soft Condensed Matter · Physics 2022-06-17 Scott Weady , David B. Stein , Michael J. Shelley

Gas-particle flows are commonly simulated through two-fluid model at industrial-scale. However, these simulations need very fine grid to have accurate flow predictions, which is prohibitively demanding in terms of computational resources.…

The local balance equations for the density, momentum, and energy of a dilute gas of elastic or inelastic hard spheres, strongly confined between two parallel hard plates are obtained. The starting point is a Boltzmann-like kinetic…

Statistical Mechanics · Physics 2020-04-22 J. Javier Brey , P. Maynar , M. I. García de Soria

This work presents a methodology to predict a near-optimal spacing function, which defines the element sizes, suitable to perform steady RANS turbulent viscous flow simulations. The strategy aims at utilising existing high fidelity…

Computational Engineering, Finance, and Science · Computer Science 2024-06-25 Sergi Sanchez-Gamero , Oubay Hassan , Ruben Sevilla

We propose a high-order stochastic-statistical moment closure model for efficient ensemble prediction of leading-order statistical moments and probability density functions in multiscale complex turbulent systems. The statistical moment…

Numerical Analysis · Mathematics 2023-06-21 Di Qi , Jian-Guo Liu

Quantum correlations can be used as a resource for quantum computing, eg for quantum state manipulation, and for quantum sensing, eg for creating non-classical states which allow to achieve the quantum advantage regime. This review collects…

Quantum Gases · Physics 2023-02-14 Anna Minguzzi , Patrizia Vignolo

In the present work, we first introduce a general framework for modelling complex multiscale fluids and then focus on the derivation and analysis of a new hybrid continuum-kinetic model. In particular, we combine conservation of mass and…

Numerical Analysis · Mathematics 2022-02-02 A. Chertock , P. Degond , G. Dimarco , M. Lukáčova-Medvid'ová , A. Ruhi

We analyze the dynamics of an algorithm for approximate inference with large Gaussian latent variable models in a student-teacher scenario. To model nontrivial dependencies between the latent variables, we assume random covariance matrices…

Machine Learning · Computer Science 2020-08-26 Burak Çakmak , Manfred Opper

Physics-based simulations are often used to model and understand complex physical systems and processes in domains like fluid dynamics. Such simulations, although used frequently, have many limitations which could arise either due to the…

Machine Learning · Computer Science 2019-11-12 Nikhil Muralidhar , Jie Bu , Ze Cao , Long He , Naren Ramakrishnan , Danesh Tafti , Anuj Karpatne

Even though compressible plasma turbulence is encountered in many astrophysical phenomena, its effect is often not well understood. Furthermore, direct numerical simulations are typically not able to reach the extreme parameters of these…

Fluid Dynamics · Physics 2016-07-27 P. Grete , D. G. Vlaykov , W. Schmidt , D. R. G. Schleicher

Stable partitioned techniques for simulating unsteady fluid-structure interaction (FSI) are known to be computationally expensive when high added-mass is involved. Multiple coupling strategies have been developed to accelerate these…

Computational Engineering, Finance, and Science · Computer Science 2025-02-18 Azzeddine Tiba , Thibault Dairay , Florian de Vuyst , Iraj Mortazavi , Juan-Pedro Berro Ramirez

Despite their well-known limitations, RANS models remain the most commonly employed tool for modeling turbulent flows in engineering practice. RANS models are predicated on the solution of the RANS equations, but these equations involve an…

Fluid Dynamics · Physics 2020-04-22 Eric L. Peters , Riccardo Balin , Kenneth E. Jansen , Alireza Doostan , John A. Evans

Planet formation simulations are capable of directly integrating the evolution of hundreds to thousands of planetary embryos and planetesimals, as they accrete pairwise to become planets. In principle such investigations allow us to better…

Earth and Planetary Astrophysics · Physics 2019-08-01 Saverio Cambioni , Erik Asphaug , Alexandre Emsenhuber , Travis S. J. Gabriel , Roberto Furfaro , Stephen R. Schwartz

Active- and transfer-learning are applied to polymer flows for the multiscale discovery of effective constitutive approximations required in viscoelastic flow simulation. The result is macroscopic rheology directly connected to a…

Computational Physics · Physics 2021-02-03 Lifei Zhao , Zhen Li , Zhicheng Wang , Bruce Caswell , Jie Ouyang , George Em Karniadakis
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