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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…

Fluid Dynamics · Physics 2018-02-20 Atieh Alizadeh Moghaddam , Amir Sadaghiyani

A promising and cost-effective method for numerical simulation of high Re wall-bounded flows is wall-modeled large-eddy simulation. Most wall models are formulated from the Reynolds-averaged Navier-Stokes equations (RANS). These RANS-based…

Fluid Dynamics · Physics 2021-01-08 Ahmed Elnahhas , Adrián Lozano-Durán , Parviz Moin

Deep learning (DL)-based Reynolds stress with its capability to leverage values of large data can be used to close Reynolds-averaged Navier-Stoke (RANS) equations. Type I and Type II machine learning (ML) frameworks are studied to…

Fluid Dynamics · Physics 2022-07-28 Chih-Wei Chang , Nam T. Dinh

This chapter provides an introduction to data-driven techniques for the development and calibration of closure models for the Reynolds-Averaged Navier--Stokes (RANS) equations. RANS models are the workhorse for engineering applications of…

Fluid Dynamics · Physics 2024-04-16 Paola Cinnella

For helical isotropic turbulence, an improved two-term helical subgrid-scale (SGS) model is proposed and four types of dynamic methods are given to do large-eddy simulation (LES), which include the standard dynamic procedure, the least…

Fluid Dynamics · Physics 2014-08-13 changping Yu

Simulating massively separated turbulent flows over bodies is one of the major applications for large-eddy simulation (LES). In the current work, we propose a machine-learning-based LES framework for the rapid simulation of turbulent flows…

Fluid Dynamics · Physics 2026-03-17 Yunpeng Wang , Huiyu Yang , Zelong Yuan , Zhijie Li , Wenhui Peng , Jianchun Wang

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…

Fluid Dynamics · Physics 2020-04-22 Eric L. Peters , Riccardo Balin , Kenneth E. Jansen , Alireza Doostan , John A. Evans

Direct numerical simulation (DNS), mostly used in fundamental turbulence research, is limited to low turbulent intensities due the current and future computer resources. Standard turbulence models, like RaNS (Reynolds averaged…

Fluid Dynamics · Physics 2015-06-17 Christoph Glawe , Heiko Schmidt , Alan R. Kerstein , Rupert Klein

Although an increased availability of computational resources has enabled high-fidelity simulations of turbulent flows, the RANS models are still the dominant tools for industrial applications. However, the predictive capabilities of RANS…

Fluid Dynamics · Physics 2018-11-19 Jian-Xun Wang , Jinlong Wu , Julia Ling , Gianluca Iaccarino , Heng Xiao

This paper addresses the issue of predicting separated flows with Reynolds-averaged Navier-Stokes (RANS) turbulence models, which are essential for many engineering tasks. Traditional RANS models usually struggle with this task, so recent…

Fluid Dynamics · Physics 2024-11-15 Chenyu Wu , Shaoguang Zhang , Yufei Zhang

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

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…

Fluid Dynamics · Physics 2018-07-05 Weiwei Zhang , Linyang Zhu , Yilang Liu , Jiaqing Kou

The recent surge in machine learning augmented turbulence modelling is a promising approach for addressing the limitations of Reynolds-averaged Navier-Stokes (RANS) models. This work presents the development of the first open-source…

Fluid Dynamics · Physics 2021-10-01 Ryley McConkey , Eugene Yee , Fue-Sang Lien

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…

Astrophysics of Galaxies · Physics 2017-03-28 Matthew D. Goodson , Fabian Heitsch , Karl Eklund , Virginia A. Williams

With the rising of modern data science, data--driven turbulence modeling with the aid of machine learning algorithms is becoming a new promising field. Many approaches are able to achieve better Reynolds stress prediction, with much lower…

Fluid Dynamics · Physics 2020-06-19 Xianwen Guo , Zhenhua Xia , Heng Xiao , Jinlong Wu , Shiyi Chen

We examine and benchmark the emerging idea of applying the large-eddy simulation (LES) formalism to unconventionally coarse grids where RANS would be considered more appropriate at first glance. We distinguish this idea from…

Fluid Dynamics · Physics 2023-10-17 Yuanwei Bin , George I. Park , Yu Lv , Xiang I. A. Yang

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…

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…

Machine Learning · Computer Science 2022-03-17 Khashayar Nobarani , Seyed Esmaeil Razavi

In this study, realizable algebraic Reynolds stress modeling based on the square root tensor [Phys. Rev. E \textbf{92}, 053010 (2015)] is further developed for extending its applicability to more complex flows. In conventional methods, it…

Fluid Dynamics · Physics 2019-11-13 Kazuhiro Inagaki , Taketo Ariki , Fujihiro Hamba

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