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We perform direct numerical simulations of shock-wave/boundary-layer interactions (SBLI) at Mach number M = 1.7 to investigate the influence of the state of the incoming boundary layer on the interaction properties. We reproduce and extend…

流体动力学 · 物理学 2017-09-18 Russell Quadros , Matteo Bernardini

Turbulent flows are fundamental in engineering and the environment, but their chaotic and three-dimensional (3-D) nature makes them computationally expensive to simulate. In this work, a dimensionality reduction technique is investigated to…

流体动力学 · 物理学 2020-12-16 Bernat Font

Deep learning provides a versatile suite of methods for extracting structured information from complex datasets, enabling deeper understanding of underlying fluid dynamic phenomena. The field of turbulence modeling, in particular, benefits…

机器学习 · 计算机科学 2025-07-31 Anuraj Maurya

The Bayesian uncertainty quantification technique has become well established in turbulence modeling over the past few years. However, it is computationally expensive to construct a globally accurate surrogate model for Bayesian inference…

数据分析、统计与概率 · 物理学 2022-03-16 Fanzhi Zeng , Wei Zhang , Jinping Li , Tianxin Zhang , Chao Yan

The influence of surface roughness on transition to turbulence in a Mach 4.5 boundary layer is studied using direct numerical simulations. Transition is initiated by the nonlinearly most dangerous inflow disturbance, which causes the…

流体动力学 · 物理学 2023-07-19 Reza Jahanbakhshi , Tamer A. Zaki

In this paper the capabilities of the turbulence-resolving Eulerian-Eulerian two-phase flow model to predict the suspension of mono-dispersed finite-sized solid particles in a boundary layer flow are investigated. For heavier-than-fluid…

流体动力学 · 物理学 2021-03-08 Antoine Mathieu , Julien Chauchat , Cyrille Bonamy , Guillaume Balarac , Tian-Jian Hsu

Hypersonic flow conditions pose exceptional challenges for Reynolds-Averaged Navier-Stokes (RANS) turbulence modeling. Critical phenomena include compressibility effects, shock/turbulent boundary layer interactions, turbulence-chemistry…

流体动力学 · 物理学 2025-04-30 Pratikkumar Raje , Eric Parish , Jean-Pierre Hickey , Paola Cinnella , Karthik Duraisamy

Laminar-turbulent transition in shock wave-boundary-layer interactions (SWBLI) remains a major challenge for hypersonic vehicle design, with implications for drag, heat transfer, and structural loads. Linear optimal perturbation analyses…

流体动力学 · 物理学 2026-05-12 Flavio Savarino , Denis Sipp , Georgios Rigas

The present numerical investigation uses well-resolved large-eddy simulations to study the low-frequency unsteady motions observed in shock-wave/turbulent-boundary-layer interactions. Details about the numerical aspects of the simulations…

流体动力学 · 物理学 2010-10-12 Emile Touber , Neil D. Sandham

We propose a framework for developing wall models for large-eddy simulation that is able to capture pressure-gradient effects using multi-agent reinforcement learning. Within this framework, the distributed reinforcement learning agents…

流体动力学 · 物理学 2024-07-29 Di Zhou , H. Jane Bae

The transition to turbulence in conduits is among the longest-standing problems in fluid mechanics. Challenges in producing or saving energy hinge on understanding promotion or suppression of turbulence. While a global picture based on an…

流体动力学 · 物理学 2023-05-23 Christopher J. Camobreco , Alban Pothérat , Gregory J. Sheard

Classic turbulence models often struggle to accurately predict complex flows. Although data-driven techniques have addressed these shortcomings, most existing research has concentrated on two-dimensional (2D) cases. This study bridges this…

流体动力学 · 物理学 2025-12-19 Chenyu Wu , Shaoguang Zhang , Yufei Zhang

Simulations of turbulent flows in 3D are one of the most expensive simulations in computational fluid dynamics (CFD). Many works have been written on surrogate models to replace numerical solvers for fluid flows with faster, learned,…

流体动力学 · 物理学 2024-03-18 Marten Lienen , David Lüdke , Jan Hansen-Palmus , Stephan Günnemann

Fluid models that approximate kinetic effects have received attention recently in the modelling of large scale plasmas such as planetary magnetospheres. In three-dimensional reconnection, both reconnection itself and current sheet…

等离子体物理 · 物理学 2021-03-03 F. Allmann-Rahn , S. Lautenbach , R. Grauer , R. D. Sydora

Site-specific flow and turbulence information are needed for various practical applications, ranging from aerodynamic/aeroelastic modeling for wind turbine design to optical diffraction calculations. Even though highly desirable, collecting…

大气与海洋物理 · 物理学 2013-07-10 Yao Wang , Sukanta Basu , Lance Manuel

This paper investigates wall boundary condition schemes for the simulation of turbulent flows using the Lattice Boltzmann method (LBM) coupled to turbulence models with wall functions. The analysis focuses on two schemes: a regularized…

流体动力学 · 物理学 2025-09-03 Jorge Ponsin , Carlos Lozano

Non-equilibrium wall turbulence with mean-flow three-dimensionality is ubiquitous in geophysical and engineering flows. Under these conditions, turbulence may experience a counter-intuitive depletion of the turbulent stresses, which has…

流体动力学 · 物理学 2020-01-08 Adrián Lozano-Durán , Marco Giometto , George I. Park , Parviz Moin

We propose an enhanced wall-boundary treatment for the lattice Boltzmann method (LBM), designed for high-Reynolds-number turbulent flows on adaptively refined Cartesian grids. The method improves the slip-velocity bounce-back scheme by…

流体动力学 · 物理学 2026-01-27 Jorge Ponsin , Carlos Lozano

Direct numerical simulations of turbulent flow in a channel with one rigid and one viscoelastic wall are performed. An Eulerian-Eulerian model is adopted with a level-set approach to identify the fluid-compliant material interface. Focus is…

流体动力学 · 物理学 2021-11-03 Amir Esteghamatian , Joseph Katz , Tamer A. Zaki

A hybrid lattice Boltzmann/finite-difference solver for low Mach thermo-compressible flows developed in earlier works is extended to more realistic and challenging configurations involving turbulence and complex geometries in the present…

流体动力学 · 物理学 2022-07-26 S. A. Hosseini , N. Darabiha , D. Thevenin
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