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We revisit the grid-point requirement estimates in Choi and Moin [Phys. Fluid, 24, 011702 (2012)] and establish more general grid-point requirements for direct numerical simulations (DNS) and large-eddy simulations (LES) of a spatially…

Fluid Dynamics · Physics 2021-06-16 Xiang I. A. Yang , Kevin Patrick Griffin

High-fidelity flow simulations are indispensable when analyzing systems exhibiting multiphase flow phenomena. The accuracy of multiphase flow simulations is strongly contingent upon the finest mesh resolution used to represent the…

Computational Physics · Physics 2023-04-05 Kumar Saurabh , Masado Ishii , Makrand A. Khanwale , Hari Sundar , Baskar Ganapathysubramanian

One issue associated with the use of Large-Eddy Simulation (LES) to investigate the dispersion of small inertial particles in turbulent flows is the accuracy with which particle statistics and concentration can be reproduced. The motion of…

High-fidelity wall-resolved large-eddy simulations (LES) are utilized to investigate the flow-physics of small-amplitude pitch oscillations of an airfoil at Re = 100,000. The investigation of the unsteady phenomenon is done in the context…

In large-eddy simulations (LES) a computational-domain translation velocity can be used to improve performance by allowing longer time-step intervals. The continuous equations are Galilean invariant, however, standard…

Atmospheric and Oceanic Physics · Physics 2021-02-03 Oumaima Lamaakel , Georgios Matheou

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

Multi-element wings are popular in the aerospace community due to their high lift performance. Turbulent flow simulations of these configurations require very fine mesh spacings especially near the walls, thereby making use of a boundary…

Fluid Dynamics · Physics 2014-02-28 Kedar C. Chitale , Michel Rasquin , Onkar Sahni , Mark S. Shephard , Kenneth E. Jansen

Accurate prediction of wake dynamics behind hydrofoils is critical for mitigating vortex-induced vibrations and improving the performance of hydraulic machinery. Conventional turbulence modeling approaches often struggle to capture the…

Fluid Dynamics · Physics 2026-01-30 Gabriele Gaiti , Chirag Trivedi , Kristian F. Sagmo

This study shows that the turbulent velocities most strongly correlated with outer-scaled ($\delta$-scaled) wall-pressure fluctuations beneath a zero-pressure-gradient boundary layer reside within the logarithmic region. Even though…

Fluid Dynamics · Physics 2026-05-05 Rahul Deshpande , Abdelrahman Hassanein , Woutijn J. Baars

In this paper, we discuss the incorporation of dynamic subgrid scale (SGS) models in the lattice-Boltzmann method (LBM) for large-eddy simulation (LES) of turbulent flows. The use of a dynamic procedure, which involves sampling or…

Computational Physics · Physics 2015-05-13 Kannan N. Premnath , Martin J. Pattison , Sanjoy Banerjee

Insights gained from modal analysis are invoked for predictive large-eddy simulation (LES) wall modeling. Specifically, we augment the law of the wall (LoW) by an additional mode based on a one-dimensional proper orthogonal decomposition…

Fluid Dynamics · Physics 2023-12-05 Christoffer Hansen , Xiang IA Yang , Mahdi Abkar

This study proposes a multiscale convolutional neural network subgrid-scale (MSC-SGS) model for large-eddy simulation (LES). This model incorporates multiscale representations obtained via filtering to capture turbulent vortices…

Fluid Dynamics · Physics 2025-02-18 Bahrul Jalaali , Kie Okabayashi

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

While direct numerical simulations (DNS) are the most accurate method for studying turbulence, their large computational cost restricts their use to idealized configurations and to Reynolds numbers well below those found in practical…

Fluid Dynamics · Physics 2025-12-09 Chang Hsin Chen , Arnab Moitro , Alexei Y. Poludnenko

In aerodynamic design, the use of Computational Fluid Dynamics (CFD) tools has long relied on Reynolds-Averaged Navier-Stokes (RANS) and Unsteady RANS (URANS) turbulence models. However, these methods face limitations in predicting…

Fluid Dynamics · Physics 2024-10-15 Francesco Mario D'Afiero , Renato Tognaccini , Gianluca Iaccarino

We carried out high-resolution large-eddy simulations (LESs) to investigate the effects of several separation-control approaches on a NACA4412 wing section with spanwise width of $L_z = 0.6$ at an angle of attack of $AoA=11^{\circ}$ at a…

Fluid Dynamics · Physics 2025-04-25 Yuning Wang , Fermin Mallor , Carlos Guardiola , Raffaello Mariani , Ricardo Vinuesa

We study the sensitivity of wall model input variables to the modeling choices of the outer LES. This work is motivated by sensitivities observed in dynamic slip wall models. These dynamic wall models use variables from the near-wall LES…

Fluid Dynamics · Physics 2022-02-10 Michael Whitmore , Adrián Lozano-Durán , Parviz Moin

This work presents a review and perspectives on recent developments in the use of machine learning (ML) to augment Reynolds-averaged Navier--Stokes (RANS) and Large Eddy Simulation (LES) models of turbulent flows. Different approaches of…

Fluid Dynamics · Physics 2021-05-19 Karthik Duraisamy

Icing on three-dimensional wings causes severe flow separation near stall. Standard improved delayed detached eddy simulation (IDDES) is unable to correctly predict the separating reattaching flow due to its inability to accurately resolve…

Fluid Dynamics · Physics 2022-10-19 Maochao Xiao , Yufei Zhang , Feng Zhou

Accurate emulation of multi-scale physical systems governed by PDEs demands models that remain stable over long autoregressive rollouts while preserving fine-scale structures. Deterministic emulators produce overly-smoothed predictions,…