English
Related papers

Related papers: Particles on Demand method: theoretical analysis, …

200 papers

The recent advent of advanced microfabrication capabilities of microfluidic devices has driven attention towards the behavior of particles in inertial flows within microchannels for applications related to the separation and concentration…

Fluid Dynamics · Physics 2018-12-03 Mike Garcia , Sumita Pennathur

Entropic lattice Boltzmann methods have been developed to alleviate intrinsic stability issues of lattice Boltzmann models for under-resolved simulations. Its reliability in combination with moving objects was established for various…

Fluid Dynamics · Physics 2017-06-21 B. Dorschner , S. S. Chikatamarla , I. V. Karlin

Incompressibility is a fundamental condition in most fluid models. Accumulation of simulation errors violates it and causes volume loss. Past work suggested correction methods to battle it. These methods, however, are imperfect and in some…

Graphics · Computer Science 2026-01-21 Zohar Levi

We present a simple modification of the direct-forcing immersed boundary method (IBM) proposed by Uhlmann [J. Comput. Phys, 2005] in order to enable it to be applied to particulate flows with solid-to-fluid density ratios around unity. The…

Fluid Dynamics · Physics 2023-06-21 Manuel Garcia-Villalba , Blanca Fuentes , Jan Dusek , Manuel Moriche , Markus Uhlmann

Estimating parameters of a diffusion process given continuous-time observations of the process via maximum likelihood approaches or, online, via stochastic gradient descent or Kalman filter formulations constitutes a well-established…

Methodology · Statistics 2025-03-17 Jan Albrecht , Sebastian Reich

We derive mixed finite element discretizations of a cold relativistics fluid model from approximations of the Poisson bracket that preserve mass, energy and the divergence constraints. For time-discretization we derive an implicit…

Numerical Analysis · Mathematics 2025-10-14 Tileuzhan Mukhamet , Katharina Kormann

Demand forecasting is a crucial component of demand management. While shortening the forecasting horizon allows for more recent data and less uncertainty, this frequently means lower data aggregation levels and a more significant data…

Machine Learning · Computer Science 2021-03-26 Jože M. Rožanec , Dunja Mladenić

Lattice Boltzmann method (LBM) has been applied to predict flow properties of porous media including intrinsic permeability, where it is implicitly assumed that the LBM is equivalent to the incompressible (or near incompressible)…

Fluid Dynamics · Physics 2016-10-03 Jun Li , Minh Tuan Ho , Lei Wu , Yonghao Zhang

We treat the accurate simulation of the calcination reaction in particles, where the particles are large and, thus, the inner-particle processes must be resolved. Because these processes need to be described with coupled partial…

Fluid Dynamics · Physics 2023-11-28 Lucas Reineking , Torben Bergold , Enric Illana , Viktor Scherer , Martin Mönnigmann

This paper is concerned with probabilistic techniques for forecasting dynamical systems described by partial differential equations (such as, for example, the Navier-Stokes equations). In particular, it is investigating and comparing…

Machine Learning · Computer Science 2025-11-07 Hans Harder , Abhijeet Vishwasrao , Luca Guastoni , Ricardo Vinuesa , Sebastian Peitz

Suspensions with fiber-like particles in the low Reynolds number regime are modeled by two different approaches that both use a Lagrangian representation of individual particles. The first method is the well-established formulation based on…

Computational Engineering, Finance, and Science · Computer Science 2015-03-25 Dominik Bartuschat , Ellen Fischermeier , Katarina Gustavsson , Ulrich Rüde

We propose a new class of finite element approximations to ideal compressible magnetohydrodynamic equations in smooth regime. Following variational approximations developed for fluid models in the last decade, our discretizations are built…

Numerical Analysis · Mathematics 2024-02-29 Valentin Carlier , Martin Campos-Pinto

Most approaches in Lagrangian fluid dynamics simulations proceed from the definition of particle volumes, from which discrete versions of the spatial differential operators are derived. Recently, Gallou\"et and M\'erigot [1] simultaneously…

Fluid Dynamics · Physics 2023-01-25 Daniel Duque

A novel description of kinetic theory dynamics is proposed in terms of resummed moments that embed information of both hydrodynamic and non-hydrodynamic modes. The resulting expansion can be used to extend hydrodynamics to higher orders in…

Nuclear Theory · Physics 2019-01-16 L. Tinti , G. Vujanovic , J. Noronha , U. Heinz

Generally, reduced order models of fluid flows are obtained by projecting the Navier-Stokes equations onto a reduced subspace spanned by vector functions that carry the meaningful information of the dynamics. A common method to generate…

Fluid Dynamics · Physics 2023-09-22 M. Oulghelou , A. Ammar , R. Ayoub

This work presents a finite element method for a modified Poisson-Nernst-Planck/Navier-Stokes (PNP/NS) model under the mechanical equilibrium, developed for compressible electrolytes. Another key contribution of this work is the reduction…

Numerical Analysis · Mathematics 2026-01-27 Ankur , Ram Jiwari , Satyvir Singh

In the present chapter we focus on the fundamentals of non-grid-conforming numerical approaches to simulating particulate flows, implementation issues and grid convergence vs. available reference data. The main idea is to avoid adapting the…

Fluid Dynamics · Physics 2024-12-11 Markus Uhlmann , Jos Derksen , Anthony Wachs , Lian-Ping Wang , Manuel Moriche

A theoretical formulation of lattice Boltzmann models on a general curvilinear coordinate system is presented. It is based on a volumetric representation so that mass and momentum are exactly conserved as in the conventional lattice…

Fluid Dynamics · Physics 2024-01-31 Hudong Chen

In this paper we develop adaptive numerical schemes for certain nonlinear variational problems. The discretization of the variational problems is done by representing the solution as a suitable frame decomposition, i.e., a complete, stable,…

Numerical Analysis · Mathematics 2007-05-23 M. Charina , C. Conti , M. Fornasier

Parametric model order reduction using reduced basis methods can be an effective tool for obtaining quickly solvable reduced order models of parametrized partial differential equation problems. With speedups that can reach several orders of…

Numerical Analysis · Mathematics 2022-01-26 Mario Ohlberger , Stephan Rave