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Computational fluid dynamics using the Reynolds-averaged Navier-Stokes (RANS) remains the most cost-effective approach to study wake flows and power losses in wind farms. The underlying assumptions associated with turbulence closures are…

流体动力学 · 物理学 2022-08-03 Ali Eidi , Navid Zehtabiyan-Rezaie , Reza Ghiassi , Xiang Yang , Mahdi Abkar

A priori tests of turbulence models for the compressible Reynolds-Averaged Navier--Stokes (RANS) are performed by using Direct Numerical Simulations (DNS) data of zero-pressure-gradient flat-plate turbulent boundary layers. The DNS database…

流体动力学 · 物理学 2023-10-17 Sciacovelli L. , Cannici A. , Passiatore D. , Cinnella P

Reynolds-averaged Navier-Stokes (RANS)-based transition modeling is widely used in aerospace applications but suffers inaccuracies due to the Boussinesq turbulent viscosity hypothesis. The eigenspace perturbation method can estimate the…

流体动力学 · 物理学 2022-11-08 Minghan Chu , Weicheng Qian

Despite the increasing availability of high-performance computational resources, Reynolds-Averaged Navier-Stokes (RANS) simulations remain the workhorse for the analysis of turbulent flows in real-world applications. Linear eddy viscosity…

流体动力学 · 物理学 2023-11-27 Leon Riccius , Atul Agrawal , Phaedon-Stelios Koutsourelakis

We use approximate Bayesian computation (ABC) to estimate unknown parameter values, as well as their uncertainties, in Reynolds-averaged Navier-Stokes (RANS) simulations of turbulent flows. The ABC method approximates posterior…

流体动力学 · 物理学 2020-11-04 Olga A. Doronina , Scott M. Murman , Peter E. Hamlington

Reynolds-Averaged Navier-Stokes (RANS) models are widely used for turbulent flow simulations due to their computational efficiency, but their accuracy strongly depends on the selected turbulence closure and may vary across the flow domain.…

数值分析 · 数学 2026-03-18 Piero Zappi , Anna Ivagnes , Niccolò Tonicello , Gianluigi Rozza

We introduce a novel approach to derive compressibility corrections for Reynolds-averaged Navier-Stokes (RANS) models. Using this approach, we derive variable-property corrections for wall-bounded flows that take into account the distinct…

流体动力学 · 物理学 2025-09-17 Asif Manzoor Hasan , Alex Jose Elias , Florian Menter , Rene Pecnik

In typical nature and engineering scenarios, such as supernova explosion and inertial confinement fusion, mixing flows induced by hydrodynamics interfacial instabilities are essentially compressible. Despite their significance, accurate…

流体动力学 · 物理学 2025-06-23 Hansong Xie , Tengfei Luo , Yaomin Zhao , Yousheng Zhang , Jianchun Wang

In the turbulence modeling community, significant efforts have been made to quantify the uncertainties in the Reynolds-Averaged Navier--Stokes (RANS) models and to improve their predictive capabilities. Of crucial importance in these…

流体动力学 · 物理学 2017-10-11 Heng Xiao , Jin-Long Wu , Jian-xun Wang , Eric G. Paterson

We present results of implicit large eddy simulation (LES) and different Reynolds-averaged Navier-Stokes (RANS) models of the MTU 161 low pressure turbine at an exit Reynolds number of 90,000 and exit Mach number of 0.6. The LES results are…

Turbulence modeling is a classical approach to address the multiscale nature of fluid turbulence. Instead of resolving all scales of motion, which is currently mathematically and numerically intractable, reduced models that capture the…

流体动力学 · 物理学 2018-12-10 Rui Fang , David Sondak , Pavlos Protopapas , Sauro Succi

Despite their well-known limitations, RANS models remain the most commonly employed tool for modeling turbulent flows in engineering practice. RANS models are predicated on the solution of the RANS equations, but these equations involve an…

流体动力学 · 物理学 2020-04-22 Eric L. Peters , Riccardo Balin , Kenneth E. Jansen , Alireza Doostan , John A. Evans

The development of advanced simulation tools is essential, both presently and in the future, for improving wind-energy design strategies, paving the way for a complete transition to sustainable solutions. The Reynolds-averaged Navier-Stokes…

流体动力学 · 物理学 2024-11-19 Ali Amarloo , Navid Zehtabiyan-Rezaie , Mahdi Abkar

In computational fluid dynamics simulations of industrial flows, models based on the Reynolds-averaged Navier--Stokes (RANS) equations are expected to play an important role in decades to come. However, model uncertainties are still a major…

流体动力学 · 物理学 2018-10-01 Heng Xiao , Paola Cinnella

Predictive simulation of many complex flows requires moving beyond Reynolds-averaged Navier-Stokes (RANS) based models to representations resolving at least some scales of turbulence in at least some regions of the flow. To resolve…

流体动力学 · 物理学 2018-12-11 Sigfried Haering , Todd A. Oliver , Robert D. Moser

Turbulence is ubiquitous in engineering and science, yet direct simulation is prohibitively expensive. The Reynolds-averaged Navier-Stokes (RANS) equations provide savings exceeding ten orders of magnitude but introduce unclosed terms (the…

流体动力学 · 物理学 2026-05-27 Daniel Dehtyriov , Jonathan F. MacArt , Justin Sirignano

The constants and functions in Reynolds-averaged Navier Stokes (RANS) turbulence models are coupled. Consequently, modifications of a RANS model often negatively impact its basic calibrations, which is why machine-learned augmentations are…

流体动力学 · 物理学 2023-10-17 Yuanwei Bin , George Huang , Robert Kunz , Xiang I A Yang

It has previously been shown that by increasing the Reynolds number across a channel by spatially varying the viscosity does not cause an immediate change in the size of turbulent structures and a delay is in fact observed in both wall…

流体动力学 · 物理学 2021-06-11 Victor Coppo Leite , Elia Merzari

Turbulence modeling is a critical component in numerical simulations of industrial flows based on Reynolds-averaged Navier-Stokes (RANS) equations. However, after decades of efforts in the turbulence modeling community, universally…

流体动力学 · 物理学 2017-03-22 Jian-Xun Wang , Jin-Long Wu , Heng Xiao

We introduce a field-wide benchmark challenge for machine learning in Reynolds-averaged Navier-Stokes (RANS) turbulence modelling. Though open-source datasets exist for training data-driven turbulence closure models, the field has been…

流体动力学 · 物理学 2026-04-01 Ryley McConkey , Tyler Buchanan , Tess Smidt , Abigail Bodner , Richard Dwight , Paola Cinnella