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Direct numerical simulations were performed to characterize fully developed supersonic turbulent channel flows over isothermal rough walls. The effect of roughness was incorporated using a level-set/volume-of-fluid immersed boundary method.…

To aid in prediction of turbulent boundary layer flows over rough surfaces, a new model is proposed to estimate hydrodynamic roughness based solely on geometric surface information. The model is based on a fluid-mechanics motivated…

Fluid Dynamics · Physics 2024-12-18 Charles Meneveau , Nicholas Hutchins , Daniel Chung

A surprising similarity is found between the distribution of hydrodynamic stress on the wall of an irregular channel and the distribution of flux from a purely Laplacian field on the same geometry. This finding is a direct outcome from…

Disordered Systems and Neural Networks · Physics 2009-11-11 J. S. Andrade , A. D. Araújo , M. Filoche , B. Sapoval

We introduce a wall model (WM) for large-eddy simulation (LES) applicable to rough surfaces with Gaussian and non-Gaussian distributions for both transitionally and fully rough regimes. The model is applicable to arbitrary complex…

Fluid Dynamics · Physics 2025-03-19 Rong Ma , Adrian Lozano-Duran

Pore-resolved direct numerical simulations of turbulent open channel flow are performed comparing the structure and dynamics of turbulence over impermeable rough and smooth walls to a porous sediment bed at permeability Reynolds number…

Fluid Dynamics · Physics 2022-05-02 Shashank K. Karra , Sourabh V. Apte , Xiaoliang He , Timothy D. Scheibe

Surface roughness elements are commonly used in wind tunnel testing to hasten the laminar-turbulent transition of the boundary layer in model tests to mimic the aerodynamic effects present in the full-scale application. These devices can…

When measuring the roughness of rough surfaces, the limited sizes of scanned areas lead to its systematic underestimation. Levelling by polynomials and other filtering used in real-world processing of atomic force microscopy data increases…

Data Analysis, Statistics and Probability · Physics 2020-04-28 David Nečas , Petr Klapetek , Miroslav Valtr

The failure of roughness parameters to predict surface properties stems from their inherent scale-dependence; in other words, the measured value depends on the way it was measured. Here we take advantage of this scale-dependence to develop…

Materials Science · Physics 2021-12-14 Antoine Sanner , Wolfram G. Nöhring , Luke A. Thimons , Tevis D. B. Jacobs , Lars Pastewka

We conducted direct numerical simulations (DNSs) of turbulent flow over three-dimensional sinusoidal roughness in a channel. A passive scalar is present in the flow with Prandtl number $Pr=0.7$, to study heat transfer by forced convection…

Fluid Dynamics · Physics 2019-02-20 M. MacDonald , N. Hutchins , D. Chung

Pore-resolved direct numerical simulations (DNS) are performed to investigate the interactions between streamflow turbulence and groundwater flow through a randomly packed porous sediment bed for three permeability Reynolds numbers, $Re_K$,…

Fluid Dynamics · Physics 2025-07-22 Shashank K. Karra , Sourabh V. Apte , Xiaoliang He , Timothy Scheibe

Many wind wave spectrum models provide excellent wave height prediction given the input of wind speed and wave age. Their quantification of the surface roughness, on the other hand, varies considerably. The ocean surface roughness is…

Geophysics · Physics 2022-09-14 Paul A. Hwang

In compressible turbulent boundary layers (TBLs), roughness drag is typically characterised by first applying a velocity transformation to account for compressibility, after which the momentum deficit $\Delta U^+$ (Hama, 1954) and the…

Surface roughness is an important quantity to many engineering and precision manufacturing disciplines. In this paper we investigate the problem of estimating the root-mean-square roughness of a sample by passive linear optical methods. By…

Direct numerical simulations of turbulent channels with rough walls are conducted in the transitionally rough regime. The effect that roughness produces on the overlying turbulence is studied using a modified triple decomposition of the…

Fluid Dynamics · Physics 2020-07-21 Nabil Abderrahaman-Elena , Chris T. Fairhall , Ricardo García-Mayoral

Surface roughness is a key factor when it comes to friction and wear, as well as to other physical properties. These phenomena are controlled by mechanisms acting at small scales, in which the topography of apparently-flat surfaces is…

Materials Science · Physics 2024-11-05 Joaquin Garcia-Suarez , Tobias Brink , Jean-François Molinari

We describe a fast direct numerical simulation (DNS) method that promises to directly characterise the hydraulic roughness of any given rough surface, from the hydraulically smooth to the fully rough regime. The method circumvents the…

Fluid Dynamics · Physics 2015-05-28 Daniel Chung , Leon Chan , Michael MacDonald , Nicholas Hutchins , Andrew Ooi

Direct Numerical Simulations (DNSs) are one of the most powerful tools for studying turbulent flows. Even if achievable Reynolds numbers are lower than those obtained with experimental means, there is a clear advantage since the entire…

Fluid Dynamics · Physics 2024-06-03 Sergio Hoyas , Ricardo Vinuesa , Peter Schmid , Hassan Nagib

This study compares turbulent channel flows over elastic walls with those over rough walls, to explore the role of the dynamic change of shape of the wall on turbulence. The comparison is made meaningful by generating rough walls from…

Fluid Dynamics · Physics 2025-09-16 M. Koseki , M. S. Aswathy , M. E. Rosti

Efficient tools for predicting the drag of rough walls in turbulent flows would have a tremendous impact. However, methods for drag prediction rely on experiments or numerical simulations which are costly and time-consuming. Data-driven…

Using event-driven molecular dynamics simulations, we quantify how the self diffusivity of confined hard-sphere fluids depends on the nature of the confining boundaries. We explore systems with featureless confining boundaries that treat…

Soft Condensed Matter · Physics 2015-05-30 William P. Krekelberg , Vincent K. Shen , Jeffrey R. Errington , Thomas M. Truskett