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A simple and efficient one-dimensional discrete Boltzmann method is developed for compressible flows with tunable specific heat ratios by incorporating extra degrees of freedom. To guarantee Galilean invariance in numerical simulations, a…

Fluid Dynamics · Physics 2026-03-03 Yaofeng Li , Chuandong Lin

In the quest for advanced propulsion and power-generation systems, high-fidelity simulations are too computationally expensive to survey the desired design space, and a new design methodology is needed that combines engineering physics,…

The dynamic emulation of non-linear deterministic computer codes where the output is a time series, possibly multivariate, is examined. Such computer models simulate the evolution of some real-world phenomenon over time, for example models…

Machine Learning · Statistics 2022-03-22 Hossein Mohammadi , Peter Challenor , Marc Goodfellow

The increasing application of cardiorespiratory simulations for diagnosis and surgical planning necessitates the development of computational methods significantly faster than the current technology. To achieve this objective, we leverage…

Numerical Analysis · Mathematics 2024-03-21 Mahdi Esmaily , Dongjie Jia

We seek to extract a small number of representative scenarios from large panel data that are consistent with sample moments. Among two novel algorithms, the first identifies scenarios that have not been observed before, and comes with a…

Machine Learning · Statistics 2024-11-06 Michael Multerer , Paul Schneider , Rohan Sen

We present a hybrid continuum-atomistic scheme which combines molecular dynamics (MD) simulations with on-the-fly machine learning techniques for the accurate and efficient prediction of multiscale fluidic systems. By using a Gaussian…

Fluid Dynamics · Physics 2016-03-16 David Stephenson , James R Kermode , Duncan A Lockerby

Modern control-command systems often include controllers that perform nonlinear computations to control a physical system, which can typically be described by an hybrid automaton containing high-dimensional systems of nonlinear differential…

Optimization and Control · Mathematics 2013-06-12 Olivier Bouissou , Alexandre Chapoutot , Samuel Mimram

This article is the complement to [quant-ph/0611284], which proves that flows (as introduced by [quant-ph/0506062]) can be found efficiently for patterns in the one-way measurement model which have non-empty input and output subsystems of…

Quantum Physics · Physics 2007-05-23 Niel de Beaudrap

Numerous algorithms and parallelisations have been developed for short-range particle simulations; however, none are optimally performant for all scenarios. Such a concept led to the prior development of the particle simulation library…

Computational Engineering, Finance, and Science · Computer Science 2025-05-07 Samuel James Newcome , Fabio Alexander Gratl , Manuel Lerchner , Abdulkadir Pazar , Manish Kumar Mishra , Hans-Joachim Bungartz

This paper introduces a new methodology for designing and optimizing the performance of hydraulic Cross-Flow turbines for a wide range of operating conditions. The methodology is based on a one-step approach for the system-level design…

Fluid Dynamics · Physics 2021-02-22 Goodarz Mehr , Mohammad Durali , Mohammad Hadi Khakrand , Hadi Hoghooghi

In this work, we propose a numerical approach for simulations of large deformations of interfaces in a level set framework. To obtain a fast and viable numerical solution in both time and space, temporal discretization is based on the…

General Mathematics · Mathematics 2023-05-30 Aymen Laadhari , Ahmad Deeb

We propose a neural physics system for real-time, interactive fluid simulations. Traditional physics-based methods, while accurate, are computationally intensive and suffer from latency issues. Recent machine-learning methods reduce…

Machine Learning · Computer Science 2025-05-27 Jingxuan Xu , Hong Huang , Chuhang Zou , Manolis Savva , Yunchao Wei , Wuyang Chen

We present two modifications of the standard cell list algorithm for nonequilibrium molecular dynamics simulations of homogeneous, linear flows. When such a flow is modeled with periodic boundary conditions, the simulation box deforms with…

Numerical Analysis · Mathematics 2014-12-12 Matthew Dobson , Ian Fox , Alexandra Saracino

We propose an algorithm to actively estimate the parameters of a linear dynamical system. Given complete control over the system's input, our algorithm adaptively chooses the inputs to accelerate estimation. We show a finite time bound…

Machine Learning · Computer Science 2020-06-23 Andrew Wagenmaker , Kevin Jamieson

We present a novel, generally applicable Monte Carlo algorithm for the simulation of fluid systems. Geometric transformations are used to identify clusters of particles in such a manner that every cluster move is accepted, irrespective of…

Statistical Mechanics · Physics 2016-08-31 Jiwen Liu , Erik Luijten

Recent work has shown that leveraging learned predictions can improve the running time of algorithms for bipartite matching and similar combinatorial problems. In this work, we build on this idea to improve the performance of the widely…

Data Structures and Algorithms · Computer Science 2023-03-03 Sami Davies , Benjamin Moseley , Sergei Vassilvitskii , Yuyan Wang

This paper synthesizes anytime algorithms, in the form of continuous-time dynamical systems, to solve monotone variational inequalities. We introduce three algorithms that solve this problem: the projected monotone flow, the safe monotone…

Optimization and Control · Mathematics 2025-02-18 Ahmed Allibhoy , Jorge Cortés

Functional integral representations for solutions of the motion equations for wall-bounded incompressible viscous flows, expressed (implicitly) in terms of distributions of solutions to stochastic differential equations of McKean-Vlasov…

Numerical Analysis · Mathematics 2024-03-26 Vladislav Cherepanov , Sebastian W. Ertel , Zhongmin Qian , Jiang-Lun Wu

This article provides a computational evaluation of the popular high resolution upwind WACEB, CUBISTA and ADBQUICKEST schemes for solving non-linear fluid dynamics problems. By using the finite difference methodology, the schemes are…

The linked cell list algorithm is an essential part of molecular simulation software, both molecular dynamics and Monte Carlo. Though it scales linearly with the number of particles, there has been a constant interest in increasing its…

Computational Physics · Physics 2013-03-19 Ulrich Welling , Guido Germano
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