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A finite difference upwind discretization scheme in two dimensions is presented in detail for the transient simulation of the highly coupled non-linear partial differential equations of the full hydrodynamic model, providing thereby a…

Computational Physics · Physics 2007-05-23 Andreas Aste , Ruediger Vahldieck , Marcel Rohner

Cavitation in fluids can severely hinder the efficiency of the associated flows. This undesired phenomenon is strongly influenced by local flow conditions, flow orientation, proximity to boundaries and liquid/gas properties at saturation.…

This paper puts forth two new closure models for the proper orthogonal decomposition reduced-order modeling of structurally dominated turbulent flows: the dynamic subgrid-scale model and the variational multiscale model. These models, which…

Computational Physics · Physics 2015-05-28 Zhu Wang , Imran Akhtar , Jeff Borggaard , Traian Iliescu

We computationally study the flow of Newtonian fluids through sinusoidal expansion-contraction microchannels at low Reynolds number. We first use a perturbation method to analytically derive series solutions for the stream function and…

We present an ``equation-free'' multiscale approach to the simulation of unsteady diffusion in a random medium. The diffusivity of the medium is modeled as a random field with short correlation length, and the governing equations are cast…

Numerical Analysis · Mathematics 2007-05-23 Dongbin Xiu , Ioannis Kevrekidis

Studying the dynamics of open quantum systems can enable breakthroughs both in fundamental physics and applications to quantum engineering and quantum computation. Since the density matrix $\rho$, which is the fundamental description for…

Quantum Physics · Physics 2023-06-08 Owen Dugan , Peter Y. Lu , Rumen Dangovski , Di Luo , Marin Soljačić

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 this thesis, a variable speed heat conducting cylinder is positioned in the middle of a rectangular channel with an active flow modification system to demonstrate a numerical study of steady two-dimensional mixed convention heat transfer…

Fluid Dynamics · Physics 2022-10-25 Md Imran Khan , Md. Mamun Billah , Mohammed Mizanur Rahman

Strong generative models can accurately learn channel distributions. This could save recurring costs for physical measurements of the channel. Moreover, the resulting differentiable channel model supports training neural encoders by…

Information Theory · Computer Science 2024-06-12 Muah Kim , Rick Fritschek , Rafael F. Schaefer

In recent years, Rectified flow (RF) has gained considerable popularity largely due to its generation efficiency and state-of-the-art performance. In this paper, we investigate the degree to which RF automatically adapts to the intrinsic…

Machine Learning · Statistics 2026-02-24 Saptarshi Roy , Alessandro Rinaldo , Purnamrita Sarkar

This paper focuses on the numerical simulation of geothermal systems in complex geological settings. The physical model is based on two-phase Darcy flows coupling the mass conservation of the water component with the energy conservation and…

In this work we are interested in dealing with single-phase flows in fractured porous media for underground processes. We focus our attention on domains where the presence of faults, with thickness several orders of magnitude smaller than…

Numerical Analysis · Mathematics 2019-08-01 Alessio Fumagalli , Isabelle Faille

We model the evolution of the concentration field of macromolecules in a symmetric field-flow fractionation (FFF) channel by a one-dimensional advection-diffusion equation. The coefficients are precisely determined from the fluid dynamics.…

chao-dyn · Physics 2007-05-23 S. A. Suslov , A. J. Roberts

Entropy stable schemes can be constructed with a specific choice of the numerical flux function. First, an entropy conserving flux is constructed. Secondly, an entropy stable dissipation term is added to this flux to guarantee dissipation…

Computational Physics · Physics 2017-11-17 Dominik Derigs , Andrew R. Winters , Gregor J. Gassner , Stefanie Walch

Channel routing is important in flood forecasting and watershed modeling. The general constant-parameter Muskingum-Cunge (CPMC) method is second-order accurate and easy to implement. With specific discretizations such that the temporal and…

Fluid Dynamics · Physics 2018-02-14 Li Wang , Sergey Lapin , Joan Q. Wu , William J. Elliot , Fritz R. Fiedler

This article examines the use of characteristic methods in stratified two-phase pipe flow simulations for obtaining non-dissipative flow predictions. A Roe scheme and several methods based on the principle of characteristics are presented…

Computational Physics · Physics 2018-11-30 Andreas Holm Akselsen

Generative modeling over discrete data has recently seen numerous success stories, with applications spanning language modeling, biological sequence design, and graph-structured molecular data. The predominant generative modeling paradigm…

Machine Learning · Computer Science 2024-11-01 Oscar Davis , Samuel Kessler , Mircea Petrache , İsmail İlkan Ceylan , Michael Bronstein , Avishek Joey Bose

When modelling fluid flow in fractured reservoirs, it is common to represent the fracturesas lower-dimensional inclusions embedded in the host medium. Existing discretizationsof flow in porous media with thin inclusions assume that the…

Numerical Analysis · Mathematics 2021-01-22 Michele Starnoni , Inga Berre , Eirik Keilegavlen , Jan M. Nordbotten

Direct numerical simulations (DNS) indicate that at large values of the Rayleigh number ($Ra$) convection in porous media self-organizes into narrowly-spaced columnar flows, with more complex spatiotemporal features being confined to…

Fluid Dynamics · Physics 2018-08-01 Baole Wen , Gregory P. Chini

Flow Matching (FM) models achieve remarkable results in generative tasks. Building upon diffusion models, FM's simulation-free training paradigm enables simplicity and efficiency but introduces a train-inference gap: model outputs cannot be…

Machine Learning · Computer Science 2026-01-30 Zhaoyi Li , Jingtao Ding , Yong Li , Shihua Li