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This paper presents a novel methodology for the direct numerical modeling and simulation of turbulent flows. The kinetic model equation is firstly extended to turbulent flow with the account of coupled evolution of kinetic, thermal, and…

Computational Physics · Physics 2025-03-11 Xiaojian Yang , Kun Xu

A systematic and automated framework for developing closed-loop flow control strategies is proposed, integrating suboptimal control theory [Lee et al., J. Fluid Mech. 358, 245 (1998)] with Bayesian optimization. The approach is demonstrated…

Fluid Dynamics · Physics 2025-07-08 Yusuke Yugeta , Yosuke Hasegawa

Integrating machine learning techniques in established numerical solvers represents a modern approach to enhancing computational fluid dynamics simulations. Within the lattice Boltzmann method (LBM), the collision operator serves as an…

Computational Physics · Physics 2024-12-12 Mario Christopher Bedrunka , Tobias Horstmann , Ben Picard , Dirk Reith , Holger Foysi

A combination of methods originating from non-stationary timeseries analysis is applied to two datasets of near surface turbulence in order to gain insights on the non-stationary enhancement mechanism of intermittent turbulence in the…

Atmospheric and Oceanic Physics · Physics 2019-09-04 Nikki Vercauteren , Vyacheslav Boyko , Amandine Kaiser , Danijel Belušić

Direct numerical simulation (DNS) of a turbulent boundary layer over the Gaussian (Boeing) bump is performed. This boundary layer exhibits a series of adverse and favorable pressure gradients and convex and concave curvature effects before…

Fluid Dynamics · Physics 2023-06-12 Aviral Prakash , Riccardo Balin , John A. Evans , Kenneth E. Jansen

Results of numerical simulations obtained by a staggered finite difference scheme together with an efficient immersed boundary method are presented to understand the effects of the shape of three-dimensional obstacles on the transition of a…

Fluid Dynamics · Physics 2015-03-31 Paolo Orlandi , Sergio Pirozzoli , Matteo Bernardini

In the present study, the capabilities of a new Convolutional Neural Network (CNN) model are explored with the paramount objective of reconstructing the temperature field of wall-bounded flows based on a limited set of measurement points…

Fluid Dynamics · Physics 2022-02-02 Victor Coppo Leite , Elia Merzari , Roberto Ponciroli , Lander Ibarra

The interpolated bounce-back scheme and the immersed boundary method are the two most popular algorithms in treating a no-slip boundary on curved surfaces in the lattice Boltzmann method. While those algorithms are frequently implemented in…

Computational Physics · Physics 2020-11-25 Cheng Peng , Orlando M. Ayala , Lian-Ping Wang

The application machine learning (ML) algorithms to turbulence modeling has shown promise over the last few years, but their application has been restricted to eddy viscosity based closure approaches. In this article we discuss rationale…

Fluid Dynamics · Physics 2021-05-31 J. P. Panda , H. V. Warrior

We present a new Eulerian framework for the computation of turbulent compressible multiphase channel flows, specifically to assess turbulence modulation by dispersed particulate matter in dilute concentrations but with significant mass…

Fluid Dynamics · Physics 2025-08-12 Ajay Dhankarghare , Yuval Dagan

We present a two-level (fluid-kinetic) coupling procedure for the simulation of wall-bounded flows at Reynolds numbers up to thousands. The method combines a kinetic Direct Simulation Monte Carlo (DSMC) treatment of the near-wall layer,…

A scale resolving hybrid RANS-LES technique is applied to an aircraft-nacelle configuration under transonic flow conditions using the unstructured, compressible TAU solver. Therefore, a wall modelled LES methodology is locally applied to…

Fluid Dynamics · Physics 2024-04-03 Marius Herr , Axel Probst , Rolf Radespiel

We investigate three-dimensional turbulence in a stably stratified fluid driven by a vertically sheared Kolmogorov flow using direct numerical simulations of the Boussinesq equations. As stratification increases, mean profiles evolve toward…

Fluid Dynamics · Physics 2025-12-16 Alessandro Sozza , Andrea Maffioli

This study aims to enhance the generalizability of Reynolds-averaged Navier-Stokes (RANS) turbulence models, which are crucial for engineering applications. Classic RANS turbulence models often struggle to predict separated flows…

Fluid Dynamics · Physics 2025-09-03 Chenyu Wu , Shaoguang Zhang , Changxin Guo , Yufei Zhang

We propose a 3D meshless method to compute mean pressure fields in turbulent flows from image velocimetry. The method is an extension of the constrained Radial Basis Function (RBF) formulation by \citet{Sperotto2022} to a Reynolds Averaged…

Fluid Dynamics · Physics 2022-07-12 Pietro Sperotto , Sandra Pieraccini , Miguel A. Mendez

This paper addresses the issue of predicting separated flows with Reynolds-averaged Navier-Stokes (RANS) turbulence models, which are essential for many engineering tasks. Traditional RANS models usually struggle with this task, so recent…

Fluid Dynamics · Physics 2024-11-15 Chenyu Wu , Shaoguang Zhang , Yufei Zhang

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

Low Reynolds number turbulence in wall-bounded shear flows \emph{en route} to laminar flow takes the form of oblique, spatially-intermittent turbulent structures. In plane Couette flow, these emerge from uniform turbulence via a…

Fluid Dynamics · Physics 2023-06-08 S. Gomé , L. S. Tuckerman , D. Barkley

Immersed boundary methods for computing confined fluid and plasma flows in complex geometries are reviewed. The mathematical principle of the volume penalization technique is described and simple examples for imposing Dirichlet and Neumann…

Plasma Physics · Physics 2015-10-07 Kai Schneider

In the present paper a new data-driven model is proposed to close and increase accuracy of RANS equations. The divergence of the Reynolds Stress Tensor (RST) is obtained through a Neural Network (NN) whose architecture and input choice…

Fluid Dynamics · Physics 2022-10-19 Stefano Berrone , Davide Oberto
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