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An immersed boundary method for the fluid--structure--thermal interaction in rarefied gas flow is presented. In this method, the slip model is incorporated with the penalty immersed boundary method to address the velocity and temperature…

Fluid Dynamics · Physics 2023-05-22 Li Wang , Fang-Bao Tian , John Young

The simulation of hypersonic flows is computationally demanding due to large gradients of the flow variables caused by strong shock waves and thick boundary or shear layers. The resolution of those gradients imposes the use of extremely…

Computational Physics · Physics 2014-10-16 Sarah Frauholz , Arianna Bosco , Birgit U. Reinartz , Siegfried Müller , Marek Behr

Modeling of wall-bounded turbulent flows is still an open problem in classical physics, with only modest progress made in the last few decades beyond the so-called `log law', which describes only the intermediate region in wall-bounded…

Fluid Dynamics · Physics 2018-08-31 Fangying Song , George Em Karniadakis

This paper presents a Weakly Compressible Smoothed Particle Hydrodynamics (WCSPH) method for solving the two-equation Reynolds-Averaged Navier-Stokes (RANS) model. The turbulent wall-bounded flow with or without mild flow separation, a…

Fluid Dynamics · Physics 2025-01-31 Feng Wang , Zhongguo Sun , Xiangyu Hu

Computational fluid dynamics (CFD) is a powerful tool for modeling turbulent flow and is commonly used for urban microclimate simulations. However, traditional CFD methods are computationally intensive, requiring substantial hardware…

In wall-modeled large-eddy simulations (WMLES), the near-wall model plays a significant role in predicting the skin friction, although the majority of the boundary layer is resolved by the outer large-eddy simulation (LES) solver. In this…

Fluid Dynamics · Physics 2020-10-09 Kevin Patrick Griffin , Lin Fu

Wall modelling in large-eddy simulation (LES) is necessary to overcome the prohibitive near-wall resolution requirements in high-Reynolds-number turbulent flows. Most existing wall models rely on assumptions about the state of the boundary…

Fluid Dynamics · Physics 2021-10-26 H. Jane Bae , Adrián Lozano-Durán , Sanjeeb T. Bose , Parviz Moin

We develop numerical multiscale methods for viscous boundary layer flow. The goal is to derive effective boundary conditions, or wall laws, through high resolution simulations localized to the boundary coupled to a coarser simulation in the…

Numerical Analysis · Mathematics 2021-10-14 Sean Carney , Björn Engquist

The hybrid wall-modeled large-eddy simulation (WMLES) and immersed boundary (IB) method offers significant flexibility for simulating high Reynolds number flows involving complex boundaries. However, the approximate boundary conditions…

Fluid Dynamics · Physics 2025-06-30 Zhideng Zhou , Fengshun Zhang , Xiaolei Yang

We present a novel technique for the imposition of non-linear entropy conservative and entropy stable solid wall boundary conditions for the compressible Navier-Stokes equations in the presence of an adiabatic wall, or a wall with a…

Understanding the long-term transport of hydrogen isotopes in plasma-facing materials, such as tungsten, is critical for the steady-state operation of magnetic confinement fusion reactors. However, dynamically updating the transition…

The numerical modeling of hydraulic jumps remains challenging due to complex interactions among free-surface deformation, air entrainment and detrainment, and turbulent bubble transport. Whereas accurate prediction of these flows is…

Fluid Dynamics · Physics 2026-05-08 L. D'Angelo , F. Zabaleta , G. E. Spadari , P. Consol-Lizzi , F. A. Bombardelli

For high-fidelity predictions of turbulent flows in complex practical engineering problems, the Wall-Modeled (WM) Large-Eddy Simulation (LES) has aroused great interest. In the present study, we prove that the conventional Wall-Stress…

Fluid Dynamics · Physics 2025-11-12 Mohammad Taghvaei , Ehsan Amani

Two models based on convolutional neural networks are trained to predict the two-dimensional velocity-fluctuation fields at different wall-normal locations in a turbulent open channel flow, using the wall-shear-stress components and the…

Fluid Dynamics · Physics 2020-06-23 L. Guastoni , A. Güemes , A. Ianiro , S. Discetti , P. Schlatter , H. Azizpour , R. Vinuesa

Hydrodynamic forces acting on a neutrally-buoyant spherical particle immersed in a wall-bounded axisymmetric stagnation point flow (Hiemenz-Homann flow) are predicted, based on a suitable form of the reciprocal theorem. An approximate…

Fluid Dynamics · Physics 2020-11-24 Jacques Magnaudet , Micheline Abbas

A machine learning method to predict steady external fluid flows using elliptic input features is introduced. Using data from as few as one high-fidelity simulation, the proposed method produces models generalizable under changes to…

Advancements in computational fluid mechanics have largely relied on Newtonian frameworks, particularly through the direct simulation of Navier-Stokes equations. In this work, we propose an alternative computational framework that employs…

Fluid Dynamics · Physics 2024-12-10 H. Sababha , A. Elmaradny , H. Taha , M. Daqaq

Fluid models offer crucial computational efficiency for plasma simulations, yet accurately capturing kinetic effects like Landau damping remains a fundamental challenge. While conventional closures (e.g., Hammett-Perkins and Hunana) are…

Plasma Physics · Physics 2026-04-30 Yong Sun , Shijia Chen , Minqing He , Sizhong Wu , Rui Cheng , Jie Yang , Lei Yang , Zhiyu Sun , Liangwen Chen , Hua Zhang

A promising and cost-effective method for numerical simulation of high Re wall-bounded flows is wall-modeled large-eddy simulation. Most wall models are formulated from the Reynolds-averaged Navier-Stokes equations (RANS). These RANS-based…

Fluid Dynamics · Physics 2021-01-08 Ahmed Elnahhas , Adrián Lozano-Durán , Parviz Moin

In this work, an efficient physics-constrained deep learning model is developed for solving multiphase flow in 3D heterogeneous porous media. The model fully leverages the spatial topology predictive capability of convolutional neural…

Geophysics · Physics 2021-05-21 Bicheng Yan , Dylan Robert Harp , Bailian Chen , Rajesh Pawar