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The goal of this dissertation is to investigate the PANS model capabilities in providing significant improvement over RANS predictions at slightly higher computational expense and producing LES quality results at significantly lower…

流体动力学 · 物理学 2017-12-12 Pooyan Razi

To fully evaluate a turbulent flow, Direct Numerical Simulation (DNS) is the most accurate method by far and requires considerable computational power and time; not optimum for industry standards. Developing an alternative model, providing…

流体动力学 · 物理学 2022-07-04 Indrajit Nandi , Saikat Saha , Sabir Subedi , Sumon Saha

A data-driven framework for formulation of closures of the Reynolds-Average Navier--Stokes (RANS) equations is presented. In recent years, the scientific community has turned to machine learning techniques to distill a wealth of highly…

流体动力学 · 物理学 2020-09-02 S. Beetham , J. Capecelatro

Turbulent problems in industrial applications are predominantly solved using Reynolds Averaged Navier Stokes (RANS) turbulence models. The accuracy of the RANS models is limited due to closure assumptions that induce uncertainty into the…

流体动力学 · 物理学 2018-02-20 Atieh Alizadeh Moghaddam , Amir Sadaghiyani

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

Solving the Reynolds-averaged Navier-Stokes equations (RANS) closed with an eddy viscosity computed through a turbulence model is still the leading approach for Computational Fluid Dynamics simulations. Unfortunately, universal models with…

流体动力学 · 物理学 2025-09-18 Marco Castelletti , Maurizio Quadrio

Traditional Reynolds-averaged Navier-Stokes (RANS) closures, based on the Boussinesq eddy viscosity hypothesis and calibrated on canonical flows, often yield inaccurate predictions of both mean flow and turbulence statistics. Here, we…

Reynolds-averaged Navier-Stokes (RANS) equations are presently one of the most popular models for simulating turbulence. Performing RANS simulation requires additional modeling for the anisotropic Reynolds stress tensor, but traditional…

流体动力学 · 物理学 2020-12-02 Rui Fang , David Sondak , Pavlos Protopapas , Sauro Succi

The transitional boundary layer flow over a flat plate is investigated. The boundary layer flow is known to develop unstable Tollmien-Schlichting waves above a critical value of the Reynolds number. However, it is also known that this…

流体动力学 · 物理学 2013-02-15 Damien Biau

The Reynolds-averaged Navier-Stokes (RANS) equations for steady-state assessment of incompressible turbulent flows remain the workhorse for practical computational fluid dynamics (CFD) applications. Consequently, improvements in speed or…

流体动力学 · 物理学 2020-12-04 Romit Maulik , Himanshu Sharma , Saumil Patel , Bethany Lusch , Elise Jennings

Turbulence models attempt to account for unresolved dynamics and diffusion in hydrodynamical simulations. We develop a common framework for two-equation Reynolds-Averaged Navier-Stokes (RANS) turbulence models, and we implement six models…

星系天体物理 · 物理学 2017-03-28 Matthew D. Goodson , Fabian Heitsch , Karl Eklund , Virginia A. Williams

Reynolds-Averaged Navier-Stokes(RANS) method will still play a vital role in the following several decade in aerospace engineering. Although RANS models are widely used, empiricism and large discrepancies between models reduce the…

流体动力学 · 物理学 2018-07-05 Weiwei Zhang , Linyang Zhu , Yilang Liu , Jiaqing Kou

This work introduces a novel data-driven framework to formulate explicit algebraic Reynolds-averaged Navier-Stokes (RANS) turbulence closures. Recent years have witnessed a blossom in applying machine learning (ML) methods to revolutionize…

流体动力学 · 物理学 2023-01-24 Hongwei Tang , Yan Wang , Tongguang Wang , Linlin Tian

This work determines the inaccuracy of using Reynolds averaged Navier Stokes (RANS) turbulence models in transition to turbulent flow regimes by predicting the model-based discrepancies between RANS and large eddy simulation (LES) models…

流体动力学 · 物理学 2019-01-21 Mustafa Usta , Ali Tosyali

Despite their well-known limitations, Reynolds-Averaged Navier-Stokes (RANS) models are still the workhorse tools for turbulent flow simulations in today's engineering application. For many practical flows, the turbulence models are by far…

计算物理 · 物理学 2018-09-11 H. Xiao , J. -L. Wu , J. -X. Wang , R. Sun , C. J. Roy

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

We present direct numerical simulations (DNSs) of bypass transition over a flat plate with inlet freestream turbulence intensity levels of 0.75%, 1.5%, 2.25%, 3.0%, and 6.0%, respectively. A new definition of the transition intermittency is…

流体动力学 · 物理学 2025-02-28 Carlos A. Gonzalez , Rahul Agrawal , Xiaohua Wu

The Reynolds Averaged Navier Stokes (RANS) models are the most common form of model in turbulence simulations. They are used to calculate Reynolds stress tensor and give robust results for engineering flows. But RANS model predictions have…

机器学习 · 计算机科学 2022-03-17 Khashayar Nobarani , Seyed Esmaeil Razavi

Accurate prediction of mixing transition induced by interfacial instabilities is vital for engineering applications, but has remained a great challenge for decades. For engineering practices, Reynolds-averaged Navier-Stokes simulation…

流体动力学 · 物理学 2023-10-02 Hansong Xie , Mengjuan Xiao , Yousheng Zhang , Yaomin Zhao

We propose a data-driven, closure model for Reynolds-averaged Navier-Stokes (RANS) simulations that incorporates aleatoric, model uncertainty. The proposed closure consists of two parts. A parametric one, which utilizes previously proposed,…

流体动力学 · 物理学 2024-04-16 Atul Agrawal , Phaedon-Stelios Koutsourelakis
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