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The self-diffusion process in a dense liquid is influenced by collective particle movements. Extensive molecular dynamics simulations for liquid aluminium and rubidium evidence a crossover in the diffusion coefficient at about $1.4$ times…

Disordered Systems and Neural Networks · Physics 2024-12-03 Franz Demmel , Noel Jakse

Current induced forces are not only related with the discrete nature of electrons but also with its quantum character. It is natural then to wonder about the effect of decoherence. Here, we develop the theory of current induced forces…

Mesoscale and Nanoscale Physics · Physics 2015-08-12 Lucas J. Fernández-Alcázar , Raúl A. Bustos-Marún , Horacio M. Pastawski

Recent advances in real-world applications of reinforcement learning (RL) have relied on the ability to accurately simulate systems at scale. However, domains such as fluid dynamical systems exhibit complex dynamic phenomena that are hard…

The compression of a cylindrical gas bubble by an imploding molten lead (Pb) shell may be accompanied by the development of the Richtmyer-Meshkov (RM) instability at the liquid-gas interface due to the initial imperfection of the interface.…

Soft Condensed Matter · Physics 2013-11-13 Victoria Suponitsky , Sandra Barsky , Aaron Froese

Reservoir computing (RC) is a state-of-the-art machine learning method that makes use of the power of dynamical systems (the reservoir) for real-time inference. When using biological complex systems as reservoir substrates, it serves as a…

Adaptation and Self-Organizing Systems · Physics 2026-03-03 Mario U. Gaimann , Miriam Klopotek

The need for improved engine efficiencies has motivated the development of high-pressure combustion systems, in which operating conditions achieve and exceed critical conditions. Associated with these conditions are strong variations in…

Fluid Dynamics · Physics 2018-09-25 Matthias Ihme , Peter C. Ma , Luis Bravo

We present TTCF4LAMMPS, a toolkit for performing non-equilibrium molecular dynamics (NEMD) simulations to study fluid behaviour at low shear rates using the LAMMPS software. By combining direct NEMD simulations and the transient-time…

Soft Condensed Matter · Physics 2023-12-07 Luca Maffioli , James P. Ewen , Edward R. Smith , Sleeba Varghese , Peter J. Daivis , Daniele Dini , B. D. Todd

A reduced kinetic method (RKM) with a first-principle collision operator is introduced in a 1D2V planar geometry and implemented in a computationally inexpensive code to investigate non-local ion heat transport in multi-species plasmas. The…

Plasma Physics · Physics 2024-03-07 Nicholas Mitchell , David Chapman , Christopher McDevitt , Martin Read , Grigory Kagan

Adiabatic processes are important for studying the dynamics of a time-dependent system. Conventionally, the adiabatic processes can only be achieved by varying the system slowly. We speed up both classical and quantum adiabatic processes by…

Quantum Physics · Physics 2013-05-21 Jia-wen Deng , Qing-hai Wang , Jiangbin Gong

Autoignition experiments of stoichiometric mixtures of s-, t-, and i-butanol in air have been performed using a heated rapid compression machine (RCM). At compressed pressures of 15 and 30 bar and for compressed temperatures in the range of…

Chemical Physics · Physics 2017-06-12 Bryan W. Weber , Chih-Jen Sung

This work introduces a comprehensive approach utilizing data-driven methods to elucidate the deposition process regimes in Chemical Vapor Deposition (CVD) reactors and the interplay of physical mechanism that dominate in each one of them.…

Drift-reduced plasma fluid models are commonly used in plasma physics for analytics and simulations; however, the validity of such models must be verified for the regions of parameter space in which tokamak plasmas exist. By looking at the…

Plasma Physics · Physics 2016-11-04 Jarrod Leddy , Ben Dudson , Michele Romanelli

This contribution analyzes the widely used and well-known "intelligent driver model (briefly IDM), which is a second order car-following model governed by a system of ordinary differential equations. Although this model was intensively…

Self-propelled liquid metal-aluminum hybrid machines represent a promising class of autonomous motion systems capable of sustained movement without external power sources. While interactions between machines and their environment inevitably…

Applied Physics · Physics 2026-03-20 Jingyi Li , Minghui Guo , Ju Wang , Xi Zhao , Jing Liu

The fluid dynamics community has increasingly adopted machine learning to analyze, model, predict, and control a wide range of flows. These methods offer powerful computational capabilities for regression, compression, and optimization. In…

Fluid Dynamics · Physics 2025-08-26 Kunihiko Taira , Georgios Rigas , Kai Fukami

An important challenge in robotics is understanding the interactions between robots and deformable terrains that consist of granular material. Granular flows and their interactions with rigid bodies still pose several open questions. A…

Machine Learning · Computer Science 2021-11-22 Amin Haeri , Krzysztof Skonieczny

To reduce computation times of simulations involving gas fueled internal combustion engines (ICEs), a model is developed that determines non-ideal nozzle exit conditions to spare expensive simulations of internal injector flows. The model,…

Fluid Dynamics · Physics 2025-09-23 N. Diepstraten , L. M. T. Somers , J. A. van Oijen

Supercritical carbon dioxide is of interest in a wide range of engineering problems, including carbon capture, utilization, and storage as well as advanced cycles for power generation. Non-ideal variations in physical properties of…

Various biological system models have been proposed in systems biology, which are based on the complex biological reactions kinetic of various components. These models are not practical because we lack of kinetic information. In this paper,…

Quantitative Methods · Quantitative Biology 2011-02-19 Weidong Huang , Chundu Wu , Bingjia Xiao , Weidong Xia

The development of turbulent gas flows in the intra-cluster medium and in the core of a galaxy cluster is studied by means of adaptive mesh refinement (AMR) cosmological simulations. A series of six runs was performed, employing identical…

Astrophysics · Physics 2009-11-13 L. Iapichino , J. C. Niemeyer