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In two papers we proposed a continuum model for the dynamics of systems of self propelling particles with kinematic constraints on the velocities and discussed some of its properties. The model aims to be analogous to a discrete algorithm…

Fluid Dynamics · Physics 2009-11-13 V. I. Ratushnaya , D. Bedeaux , V. L. Kulinskii , A. V. Zvelindovsky

We present a method to construct reduced-order models for duct flows of Bingham media. Our method is based on proper orthogonal decomposition (POD) to find a low-dimensional approximation to the velocity and artificial neural network to…

Numerical Analysis · Mathematics 2018-11-14 E. Muravleva , I. Oseledets , D. Koroteev

In this chapter we examine reduced order techniques for geometrical parametrized heat exchange systems, Poisson, and flows based on Stokes, steady and unsteady incompressible Navier-Stokes and Cahn-Hilliard problems. The full order finite…

Numerical Analysis · Mathematics 2023-01-31 Efthymios N. Karatzas , Giovanni Stabile , Francesco Ballarin , Gianluigi Rozza

The paper presents a Projection-Based Reduced-Order Model for simulations of high Reynolds turbulent flows. The PBROM are enhanced by incorporating various models of turbulent viscosity and residual closures to model the effects of…

Computational Engineering, Finance, and Science · Computer Science 2021-05-25 My Ha Dao , Hoang Huy Nguyen

We present a systematic procedure for the construction of relativistic lattice Boltzmann models (R-SLB) appropriate for the simulation of flows of massless particles. Quadrature rules are used for the discretization of the momentum space in…

Fluid Dynamics · Physics 2018-09-24 Victor E. Ambrus , Robert Blaga

Predicting particle-laden flows requires accurate fluid force models. However, a reliable particle force model for finite-size particles in turbulent flows remains lacking. In the present work, a fluid force model for a finite-size…

Fluid Dynamics · Physics 2025-05-29 Yuqi Wang , Ruifeng Hu

Diffusion models are powerful tools for sampling from high-dimensional distributions by progressively transforming pure noise into structured data through a denoising process. When equipped with a guidance mechanism, these models can also…

Machine Learning · Computer Science 2026-05-04 Saeed Mohseni-Sehdeh , Walid Saad , Kei Sakaguchi , Tao Yu

In this contribution we present a survey of concepts in localized model order reduction methods for parameterized partial differential equations. The key concept of localized model order reduction is to construct local reduced spaces that…

Numerical Analysis · Mathematics 2019-10-29 Andreas Buhr , Laura Iapichino , Mario Ohlberger , Stephan Rave , Felix Schindler , Kathrin Smetana

A simple model accounting for the ejection of heavy particles from the vortical structures of a turbulent flow is introduced. This model involves a space and time discretization of the dynamics and depends on only two parameters: the…

Chaotic Dynamics · Physics 2009-11-13 Jeremie Bec , Raphael Chetrite

Over the last two decades, lattice Boltzmann methods have become an increasingly popular tool to compute the flow in complex geometries such as porous media. In addition to single phase simulations allowing, for example, a precise…

We conduct a numerical study of relativistic viscous fluid dynamics in the Density Frame for one-dimensional fluid flows. The Density Frame is a formulation of relativistic viscous hydrodynamics that is first-order in time, requires no…

A new and very general technique for simulating solid-fluid suspensions has been described in a previous paper (Part I); the most important feature of the new method is that the computational cost scales with the number of particles. In…

comp-gas · Physics 2009-10-22 Anthony J. C. Ladd

A substantial number of algorithms exists for the simulation of moving particles suspended in fluids. However, finding the best method to address a particular physical problem is often highly non-trivial and depends on the properties of the…

Soft Condensed Matter · Physics 2015-02-10 Jens Harting , Stefan Frijters , Marco Ramaioli , Martin Robinson , Dietrich E. Wolf , Stefan Luding

Over the past few decades, tremendous progress has been made in the development of particle-based discrete simulation methods versus the conventional continuum-based methods. In particular, the lattice Boltzmann (LB) method has evolved from…

Computational Physics · Physics 2015-12-08 Qing Li , K. H. Luo , Q. J. Kang , Y. L. He , Q. Chen , Q. Liu

We use a lattice Boltzmann method to study pattern formation in chemically reactive binary fluids in the regime where hydrodynamic effects are important. The coupled equations solved by the method are a Cahn-Hilliard equation, modified by…

Soft Condensed Matter · Physics 2009-11-11 K. Furtado , J. M. Yeomans

Procedural material models have been gaining traction in many applications thanks to their flexibility, compactness, and easy editability. We explore the inverse rendering problem of procedural material parameter estimation from…

Graphics · Computer Science 2025-04-22 Yu Guo , Milos Hasan , Lingqi Yan , Shuang Zhao

The deformability of soft condensed matter often requires modelling of hydrodynamical aspects to gain quantitative understanding. This, however, requires specialised methods that can resolve the multiscale nature of soft matter systems. We…

Soft Condensed Matter · Physics 2017-12-22 Ulf D. Schiller , Timm Krüger , Oliver Henrich

We revisit force evaluation methodologies on rigid solid particles suspended in a viscous fluid and simulated via lattice Boltzmann method (LBM). We point out the non-commutativity of streaming and collision operators in the force…

Fluid Dynamics · Physics 2022-10-20 Shaurya Kaushal , Sauro Succi , Santosh Ansumali

The particle-in-cell (PIC) method is a well-established and widely used kinetic plasma modelling approach that provides a hybrid Lagrangian-Eulerian approach to solve the plasma kinetic equation. Despite its power in capturing details of…

Plasma Physics · Physics 2024-11-11 Maryam Reza , Farbod Faraji , Aaron Knoll

To close the moment model deduced from kinetic equations, the canonical approach is to provide an approximation to the flux function not able to be depicted by the moments in the reduced model. In this paper, we propose a brand new closure…

Computational Physics · Physics 2021-02-16 Ruo Li , Weiming Li , Lingchao Zheng