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The Active Flux scheme is a Finite Volume scheme with additional degrees of freedom. It makes use of a continuous reconstruction and does not require a Riemann solver. An evolution operator is used for the additional degrees of freedom on…

Computational Engineering, Finance, and Science · Computer Science 2023-03-14 Oliviu Şugar-Gabor

One of the prevailing challenges in Computational Fluid Dynamics is accurate simulation of two-phase flows involving heat and mass transfer across the fluid interface. This is currently an active field of research, which is to some extend…

Fluid Dynamics · Physics 2021-03-02 Henning Scheufler , Johan Roenby

In this paper, we first propose a filter-based continuous Ensemble Eddy Viscosity (EEV) model for stochastic turbulent flow problems. We then propose a generic algorithm for a family of fully discrete, grad-div regularized, efficient…

Numerical Analysis · Mathematics 2025-08-15 Brandiece N. Berry , Md Mahmudul Islam , Muhammad Mohebujjaman , Neethu Suma Raveendran

The analysis of the Reynolds Stress Transport Equation (RSTE) provides fundamental physical insights that are essential for the development and validation of advanced turbulence models. However, a comprehensive and validated tool for…

Fluid Dynamics · Physics 2025-11-07 Mario J. Rincón , Christoffer Hansen , Martino Reclari , Mahdi Abkar

We present a numerical method for Large Eddy Simulations (LES) of compressible two-phase flows. The method is validated for the flow in a micro channel with a step-like restriction. This setup is representative for typical cavitating…

Fluid Dynamics · Physics 2014-01-28 S Hickel , M. Mihatsch , S. J. Schmidt

The Exergetic Port-Hamiltonian Systems modeling language combines a graphical syntax inspired by bond graphs with a port-Hamiltonian semantics akin to the GENERIC formalism. The syntax enables the modular and hierarchical specification of…

Systems and Control · Electrical Eng. & Systems 2022-04-12 Markus Lohmayer , Sigrid Leyendecker

A conservative finite-volume framework, based on a collocated variable arrangement, for the simulation of flows at all speeds, applicable to incompressible, ideal-gas and real-gas fluids is proposed in conjunction with a fully-coupled…

Computational Physics · Physics 2020-03-03 Fabian Denner , Fabien Evrard , Berend van Wachem

Accurately depicting multiphysics interactions in interfacial systems requires computational frameworks capable of reconciling geometric adaptability with strict conservation fidelity. However, traditional spatiotemporal discretisation…

Computational Engineering, Finance, and Science · Computer Science 2025-11-18 Suhaib Ardah , Francisco J. Profito , Daniele Dini

We present a novel approach to define the filter and relax steps in the evolve-filter-relax (EFR) framework for simulating turbulent flows. The EFR main advantages are its ease of implementation and computational efficiency. However, as it…

The aim of this paper is to propose a new numerical model to simulate 2D vesicles interacting with a newtonian fluid. The inextensible membrane is modeled by a chain of circular rigid particles which are maintained in cohesion by using two…

Mathematical Physics · Physics 2012-02-15 Mourad Ismail , Aline Lefebvre-Lepot

This article focusses on the analysis of a conforming finite element method for the time-dependent incompressible Navier-Stokes equations. For divergence-free approximations, in a semi-discrete formulation, we prove error estimates for the…

Numerical Analysis · Mathematics 2018-03-20 Philipp W. Schroeder , Gert Lube

Understanding the fundamental mechanisms of sediment transport, particularly those during the formation and evolution of bedforms, is of critical scientific importance and has engineering relevance. Traditional approaches of sediment…

Fluid Dynamics · Physics 2016-06-22 Rui Sun , Heng Xiao

In this study, the ducted propeller has been numerically investigated under oblique flow, which is crucial and challenging for the design and safe operation of thruster driven vessel and dynamic positioning (DP) system. A Reynolds-Averaged…

Fluid Dynamics · Physics 2018-01-11 Qin Zhang , Rajeev K. Jaiman , Peifeng Ma , Jing Liu

A spectral element solver is developed for the high-fidelity simulation of the unsteady flow over an aerospike nozzle. The Navier-Stokes solver is a kinetic-energy-preserving, discontinuous Galerkin spectral element method (DGSEM) combined…

Fluid Dynamics · Physics 2025-11-20 Zachary Pyle , Gustaaf B. Jacobs

The Poisson--Nernst--Planck (PNP) equations have been widely applied to describe ionic transport in ion channels, nanofluidic devices, and many electrochemical systems. Despite their wide applications, the PNP equations fail in predicting…

Statistical Mechanics · Physics 2018-01-03 Farjana Siddiqua , Zhongming Wang , Shenggao Zhou

In this paper, a pore-scale network modeling method, based on the flow continuity residual in conjunction with a Newton-Raphson non-linear iterative solving technique, is proposed and used to obtain the pressure and flow fields in a network…

Fluid Dynamics · Physics 2014-12-02 Taha Sochi

This work explores the capability of simulating complex fluid flows by directly solving the Boltzmann equation. Due to the high-dimensionality of the governing equation, the substantial computational cost of solving the Boltzmann equation…

Fluid Dynamics · Physics 2023-12-05 Tarik Dzanic , Luigi Martinelli

We propose a new unfitted finite element method for simulation of two-phase flows in presence of insoluble surfactant. The key features of the method are 1) discrete conservation of surfactant mass; 2) the possibility of having meshes that…

Numerical Analysis · Mathematics 2022-11-30 Thomas Frachon , Sara Zahedi

A system of soft ellipsoid molecules confined between two planar walls is studied using classical Density Functional Theory (DFT). Both the isotropic and nematic phases are considered. The excess free energy is evaluated using two different…

Materials Science · Physics 2009-11-10 David Cheung , Friederike Schmid

Discrete flow-based models are a recently proposed class of generative models that learn invertible transformations for discrete random variables. Since they do not require data dequantization and maximize an exact likelihood objective,…

Machine Learning · Computer Science 2021-07-27 Alexandra Lindt , Emiel Hoogeboom
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