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This article provides a reduced-order modelling framework for turbulent compressible flows discretized by the use of finite volume approaches. The basic idea behind this work is the construction of a reduced-order model capable of providing…

Fluid Dynamics · Physics 2024-05-31 Matteo Zancanaro , Valentin Nkana Ngan , Giovanni Stabile , Gianluigi Rozza

Continuous normalizing flows (CNFs) are an attractive generative modeling technique, but they have been held back by limitations in their simulation-based maximum likelihood training. We introduce the generalized conditional flow matching…

Gaseous flows under an external force are intrinsically defined by their multi-scale nature due to the large variation of densities along the forcing direction. Devising a numerical method capable of accurately and efficiently solving…

Computational Physics · Physics 2025-07-15 Shuangqing Liu , Zuoxu Li , Yonghao Zhang , Tianbai Xiao

We consider in this paper a challenging problem of simulating fluid flows, in complex multiscale media possessing multi-continuum background. As an effort to handle this obstacle, model reduction is employed. In \cite{rh2}, homogenization…

Numerical Analysis · Mathematics 2022-05-31 Jun Sur Richard Park , Siu Wun Cheung , Tina Mai , Viet Ha Hoang

In this paper, a meshless Generalized Finite Difference Method (GFDM) is proposed to deal with the Stokes-Darcy coupled problem with the Beavers-Joseph-Saffman (BJS) interface conditions. Some high order GFDMs are proposed to show the…

Numerical Analysis · Mathematics 2025-06-24 Yanan Xing , Haibiao Zheng

Continuous normalizing flows (CNFs) can model data distributions with expressive infinite-length architectures. But this modeling involves computationally expensive process of solving an ordinary differential equation (ODE) during maximum…

Machine Learning · Computer Science 2024-10-15 Denis Gudovskiy , Tomoyuki Okuno , Yohei Nakata

The efficient resolution of Bayesian inverse problems remains challenging due to the high computational cost of traditional sampling methods. In this paper, we propose a novel framework that integrates Conditional Flow Matching (CFM) with a…

Machine Learning · Computer Science 2025-05-20 Daniil Sherki , Ivan Oseledets , Ekaterina Muravleva

In this work, we present a high-order finite volume framework for the numerical simulation of shallow water flows. The method is designed to accurately capture complex dynamics inherent in shallow water systems, particularly suited for…

Numerical Analysis · Mathematics 2025-05-14 Mirco Ciallella , Lorenzo Micalizzi , Victor Michel-Dansac , Philipp Öffner , Davide Torlo

A low-Mach-number flow, in the laminar regime, has intrinsically two characteristic spatial scales for a given time scale, or two characteristic temporal scales for a given spatial scale, and these dual scales are very different due to the…

Large-eddy simulation of incompressible turbulent flow has been extensively investigated; hence, a variety of models suited for different numerical schemes have been developed. In the case of compressible flow, the modeling is more…

Fluid Dynamics · Physics 2020-07-15 Ahmad Peyvan , Zia Ghiasi , Dongru Li , Jonathan Komperda , Farzad Mashayek

In the present study, a discrete forcing Immersed Boundary Method (IBM) is proposed for the numerical simulation of high-speed flow problems including heat exchange. The flow field is governed by the compressible Navier-Stokes equations,…

Fluid Dynamics · Physics 2023-01-24 Hamza Riahi , Eric Goncalves , Marcello Meldi

We consider coupled models for particulate flows, where the disperse phase is made of particles with distinct sizes. We are thus led to a system coupling the incompressible Navier-Stokes equations to the multi-component Vlasov-Fokker-Planck…

Numerical Analysis · Mathematics 2022-12-20 Shi Jin , Yiwen Lin

We present a fully conservative, skew-symmetric finite difference scheme on transformed grids. The skew-symmetry preserves the kinetic energy by first principles, simultaneously avoiding a central instability mechanism and numerical…

Fluid Dynamics · Physics 2013-09-02 Julius Reiss , Jörn Sesterhenn

Combining discrete and continuous data is an important capability for generative models. We present Discrete Flow Models (DFMs), a new flow-based model of discrete data that provides the missing link in enabling flow-based generative models…

Machine Learning · Statistics 2024-06-07 Andrew Campbell , Jason Yim , Regina Barzilay , Tom Rainforth , Tommi Jaakkola

Computational modeling of the melt pool dynamics in laser-based powder bed fusion metal additive manufacturing (PBF-LB/M) promises to shed light on fundamental mechanisms of defect generation. These processes are accompanied by rapid…

Computational Engineering, Finance, and Science · Computer Science 2026-03-05 Nils Much , Magdalena Schreter-Fleischhacker , Peter Munch , Martin Kronbichler , Wolfgang A. Wall , Christoph Meier

We introduce a finite-volume numerical scheme for solving stochastic gradient-flow equations. Such equations are of crucial importance within the framework of fluctuating hydrodynamics and dynamic density functional theory. Our proposed…

Forward-flux sampling (FFS) is a path sampling technique that has gained increased popularity in recent years, and has been used to compute rates of rare event phenomena such as crystallization, condensation, hydrophobic evaporation, DNA…

Statistical Mechanics · Physics 2018-05-01 Amir Haji-Akbari

This paper presents a novel mass-conservative mixed multiscale method for solving flow equations in heterogeneous porous media. The media properties (the permeability) contain multiple scales and high contrast. The proposed method solves…

Numerical Analysis · Mathematics 2019-04-01 Eric Chung , Yalchin Efendiev , Wing Tat Leung

The Direct Simulation Monte Carlo (DSMC) method was widely used to simulate low density gas flows with large Knudsen numbers. However, DSMC encounters limitations in the regime of lower Knudsen numbers (Kn<0.1). In such cases, approaches…

A new time discretization scheme for the numerical simulation of two-phase flow governed by a thermodynamically consistent diffuse interface model is presented. The scheme is consistent in the sense that it allows for a discrete in time…

Analysis of PDEs · Mathematics 2014-02-27 Harald Garcke , Michael Hinze , Christian Kahle