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This work presents a feature-rich open-source library for wall-modelled large-eddy simulation (WMLES), which is a turbulence modelling approach that reduces the computational cost of traditional (wall-resolved) LES by introducing special…

Fluid Dynamics · Physics 2019-04-01 Timofey Mukha , Saleh Rezaeiravesh , Mattias Liefvendahl

Wall-bounded turbulence is relevant for many engineering and natural science applications, yet there are still aspects of its underlying physics that are not fully understood, particularly at high Reynolds numbers. In this study, we…

Fluid Dynamics · Physics 2024-04-04 Himani Garg , Lei Wang , Martin Andersson , Christer Fureby

Turbulent flow has been extensively studied using computational fluid dynamics (CFD) simulations since turbulent flow regime is so frequently encountered in both academic and engineering applications. The high-fidelity simulation of the…

Fluid Dynamics · Physics 2024-05-21 Minghan Chu

Triboelectric charging in particle-laden flows is a complex interplay of fluid and particle dynamics, collision mechanics, and electrostatics. In this study, we introduce triboFoam, an open-source solver built on the OpenFOAM framework,…

Fluid Dynamics · Physics 2026-02-12 Christoph Wilms , Holger Grosshans

Direct numerical simulations (DNS) are one of the main ab initio tools to study turbulent flows. However, due to their considerable computational cost, DNS are primarily restricted to canonical flows at moderate Reynolds numbers, in which…

Fluid Dynamics · Physics 2024-09-17 Arnab Moitro , Sai Sandeep Dammati , Alexei Y. Poludnenko

A new approach to turbulence simulation, based on a combination of large-eddy simulation (LES) for the whole flow and an array of non-space-filling quasi-direct numerical simulations (QDNS), which sample the response of near-wall turbulence…

Fluid Dynamics · Physics 2017-10-20 Neil D. Sandham , Roderick Johnstone , Christian T. Jacobs

Computational fluid dynamics (CFD) is a useful tool for prediction of turbulence in aerodynamic and biomedical applications. The choice of appropriate turbulence models is key to reaching accurate predictions. The present investigation…

Fluid Dynamics · Physics 2018-03-13 Fardin Khalili , Peshala P. T. Gamage , Hansen A. Mansy

Prediction of two-phase boiling flows using the computational fluid dynamics (CFD) approach is very challenging since several sub-models for interfacial mass, momentum and energy transfer in such flows are still not well established and…

Fluid Dynamics · Physics 2017-09-07 Kai Fu , Henryk Anglart

Reynolds-averaged Navier-Stokes (RANS) turbulence models (such as k-\epsilon models) are still widely used for engineering applications because of their relatively simplicity and robustness. In fully developed plane channel flow (i.e. the…

Fluid Dynamics · Physics 2010-12-01 Najla El Gharbi , Rafik Absi , Ahmed Benzaoui

We study the error scaling properties of large-eddy simulation (LES) in the outer region of wall-bounded turbulence at moderately high Reynolds numbers. In order to avoid the additional complexity of wall-modeling, we perform LES of…

Fluid Dynamics · Physics 2021-10-26 Adrián Lozano-Durán , Hyunji Jane Bae

In many engineering and industrial applications, the investigation of rotating turbulent flow is of great interest. In rotor-stator cavities, the centrifugal and Coriolis forces have a strong influence on the turbulence by producing a…

Symbolic regression (SR) methods have been extensively investigated to explore explicit algebraic Reynolds stress models (EARSM) for turbulence closure of Reynolds-averaged Navier-Stokes (RANS) equations. The deduced EARSM can be readily…

Fluid Dynamics · Physics 2024-10-15 Yu Zhang , Kefeng Zheng , Fei Liu , Qingfu Zhang , Zhenkun Wang

Aerospace design is increasingly incorporating Design Under Uncertainty based approaches to lead to more robust and reliable optimal designs. These approaches require dependable estimates of uncertainty in simulations for their success. The…

Fluid Dynamics · Physics 2024-02-28 Marcel Matha , Christian Morsbach

Detailed chemistry-based computational fluid dynamics (CFD) simulations are computationally expensive due to the solution of the underlying chemical kinetics system of ordinary differential equations (ODEs). Here, we introduce a novel…

The physical fidelity of turbulence models can benefit from a partial resolution of fluctuations, but doing so often comes with an increase in computational cost. To explore this trade-off in the context of wall-bounded flows, this paper…

Fluid Dynamics · Physics 2025-07-16 Tanner Ragan , Mark Warnecke , Samuel T. Stout , Perry L. Johnson

Our work is motivated by the analysis of ash plume dynamics, arising in the study of volcanic eruptions. Such phenomena are characterized by large Reynolds number (exceeding $10^7$) and a large number of polydispersed particles~[1]. Thus,…

A part of non-Newtonian fluids are yield stress fluids. They require a minimum stress to flow. Below this minimum value, yield stress fluids remain solid. To date, 1D and 2D numerical models have been used predominantly to study free…

Fluid Dynamics · Physics 2018-08-03 N Schaer , J. Vazquez , M. Dufresne , G Isenmann , J. Wertel

In this report we briefly summarize the set-up and results for direct numerical simulations (DNS) of turbulent channel flows with riblets. The DNS are carried out with OpenFOAM which allows the use of an unstructured mesh. The present…

Fluid Dynamics · Physics 2017-07-27 Verena Fink , Bettina Frohnapfel

The integration of interpretability and generalisability in data-driven turbulence modelling remains a fundamental challenge for computational fluid dynamics applications. This study yields a generalisable advancement of the $k$-$\omega$…

Fluid Dynamics · Physics 2025-07-02 Mario J. Rincón , Martino Reclari , Xiang I. A. Yang , Mahdi Abkar

The weights of a deep neural network model are optimized in conjunction with the governing flow equations to provide a model for sub-grid-scale stresses in a temporally developing plane turbulent jet at Reynolds number $Re_0=6\,000$. The…

Fluid Dynamics · Physics 2023-03-23 Jonathan F. MacArt , Justin Sirignano , Jonathan B. Freund
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