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The accuracy of meshless methods like Smoothed Particle Hydrodynamics (SPH) is highly dependent on the quality of the particle distribution. Existing particle initialization techniques often struggle to simultaneously achieve adaptive…

Computational Physics · Physics 2026-01-01 Navaneet Villodi , Prabhu Ramachandran

For conventional smoothed particle hydrodynamics (SPH), obtaining the static solution of a problem is time-consuming. To address this drawback, we propose an efficient dynamic relaxation method by adding large artificial-viscosity-based…

Computational Engineering, Finance, and Science · Computer Science 2021-03-17 Yujie Zhu , Chi Zhang , Xiangyu Hu

Varieties of energy-stable numerical methods have been developed for incompressible two-phase flows based on the Navier-Stokes-Cahn-Hilliard (NSCH) model in the Eulerian framework, while few investigations have been made in the Lagrangian…

Fluid Dynamics · Physics 2023-03-22 Xiaoyu Feng , Zhonghua Qiao , Shuyu Sun , Xiuping Wang

First, a meshless simulation method is presented for multiphase fluid-particle flows with a two-way coupled Smoothed Particle Hydrodynamics (SPH) for the fluid and the Discrete Element Method (DEM) for the solid phase. The unresolved fluid…

Fluid Dynamics · Physics 2014-02-28 Martin Robinson , Stefan Luding , Marco Ramaioli

HII regions powered by ionizing radiation from massive stars drive the dynamical evolution of the interstellar medium. Fast radiative transfer methods for incorporating photoionization effects are thus essential in astrophysical…

Instrumentation and Methods for Astrophysics · Physics 2025-02-25 Cheryl S. C. Lau , Maya A. Petkova , Ian A. Bonnell

Federated Learning (FL) has emerged as a promising technique for edge devices to collaboratively learn a shared machine learning model while keeping training data locally on the device, thereby removing the need to store and access the full…

Machine Learning · Computer Science 2022-07-19 Konstantin Burlachenko , Samuel Horváth , Peter Richtárik

The smoothed particle hydrodynamics (SPH) technique is a purely Lagrangian method, used in numerical simulations of fluids in astrophysics and computational fluid dynamics, among many other fields. SPH simulations with detailed physics…

A new means of incorporating radiative transfer into smoothed particle hydrodynamics (SPH) is introduced, which builds on the success of two previous methods - the polytropic cooling approximation as devised by Stamatellos et al (2007), and…

Astrophysics · Physics 2009-11-13 Duncan Forgan , Ken Rice , Dimitris Stamatellos , Anthony Whitworth

Simulations based on particle methods, such as Smoothed Particle Hydrodynamics (SPH), are known to be computationally demanding. While such methods have for long been executed in parallel on multi-core CPUs, in recent years the increasing…

Computational Engineering, Finance, and Science · Computer Science 2026-03-18 Xiangyu Hu , Alberto Guarnieri

Isothermal and adiabatic shocks, which are produced from fast expansion of the gas, is simulated with smoothed particle hydrodynamics (SPH). The results are compared with the analytic solutions. The algorithm of the program is explained and…

Astrophysics · Physics 2007-05-23 Mohsen Nejad-Asghar

Implementing particle-interaction configuration and time integration are performance intensive essentials of particle-based methods. In this paper, a dual-criteria time-stepping method is proposed to improve the computational efficiency of…

Computational Physics · Physics 2020-02-28 Chi Zhang , Massoud Rezavand , Xiangyu Hu

The incompressible smoothed particle hydrodynamics method (ISPH) is a numerical method widely used for accurately and efficiently solving flow problems with free surface effects. However, to date there has been little mathematical…

Numerical Analysis · Mathematics 2019-07-03 Y. Imoto

We present a new formulation of the equations of motion used in smoothed particle hydrodynamics (SPH). The spatial resolution in SPH is determined by the smoothing length, $h$, and it has become common practice for each particle to be given…

Astrophysics · Physics 2015-06-24 Richard P. Nelson , John C. B. Papaloizou

Shampoo is an online and stochastic optimization algorithm belonging to the AdaGrad family of methods for training neural networks. It constructs a block-diagonal preconditioner where each block consists of a coarse Kronecker product…

The smoothed particle hydrodynamics (SPH) method is a useful numerical tool for the study of a variety of astrophysical and planetlogical problems. However, it turned out that the standard SPH algorithm has problems in dealing with…

Instrumentation and Methods for Astrophysics · Physics 2015-06-16 Natsuki Hosono , Takayuki R. Saitoh , Junichiro Makino

We describe and demonstrate a method for increasing the resolution locally in a Smoothed Particle Hydrodynamic (SPH) simulation, by splitting particles. We show that in simulations of self-gravitating collapse (of the sort which are…

Astrophysics · Physics 2009-11-07 S. Kitsionas , A. P. Whitworth

Smoothed dissipative particle dynamics (SDPD) is a widely used particle-based method for modelling soft matter systems at mesoscopic and macroscopic scales, offering thermodynamic consistency and direct control over the fluid's transport…

Fluid Dynamics · Physics 2025-10-22 Marina Echeverria Ferrero , Nicolas Moreno , Marco Ellero

In this work we will identify a novel relation between Smoothed Particle Hydrodynamics (SPH) and explicit Large Eddy Simulation (LES) using a coarse-graining method from Non-Equilibrium Molecular Dynamics (NEMD). While the current…

Fluid Dynamics · Physics 2022-11-24 Max Okraschevski , Niklas Bürkle , Rainer Koch , Hans-Jörg Bauer

We present the extension of the differentiable hydrodynamics code, diffhydro, enabling scalable PDE-constrained inference and integrated hybrid physics-ML models for a wide range of astrophysical applications. New physics additions include…

Instrumentation and Methods for Astrophysics · Physics 2025-12-16 Benjamin Horowitz , Zarija Lukić , Kentaro Nagamine , Yuri Oku

This paper proposes DiffPF, a differentiable particle filter that leverages diffusion models for state estimation in dynamic systems. Unlike conventional differentiable particle filters, which require importance weighting and typically rely…

Robotics · Computer Science 2026-01-13 Ziyu Wan , Lin Zhao
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