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The use of emergent constraints to quantify uncertainty for key policy relevant quantities such as Equilibrium Climate Sensitivity (ECS) has become increasingly widespread in recent years. Many researchers, however, claim that emergent…

Applications · Statistics 2020-02-19 Daniel B. Williamson , Philip G. Sansom

This study presents a novel approach for enhancing Reynolds-averaged Navier-Stokes (RANS) turbulence modeling through the application of a Relative Importance Term Analysis (RITA) methodology to develop a new zonally-augmented $k-\omega$…

Fluid Dynamics · Physics 2025-11-26 Tyler Buchanan , Monica Lăcătuş , Alastair West , Richard P. Dwight

Turbulence is a complex, irregular flow phenomenon ubiquitous in natural processes and engineering applications. The Reynolds-averaged Navier-Stokes (RANS) method, owing to its low computational cost, has become the primary approach for…

Fluid Dynamics · Physics 2026-02-10 Ziqi Ji , Penghao Duan , Gang Du

Surrogate models are necessary to optimize meaningful quantities in physical dynamics as their recursive numerical resolutions are often prohibitively expensive. It is mainly the case for fluid dynamics and the resolution of Navier-Stokes…

Machine Learning · Computer Science 2023-06-02 Florent Bonnet , Ahmed Jocelyn Mazari , Paola Cinnella , Patrick Gallinari

A hybrid RANS/LES framework is developed based on a recently proposed Improved Delayed Detached Eddy Simulation (IDDES) model combined with a variant of recycling and rescaling method of generating inflow turbulence. This framework was…

Fluid Dynamics · Physics 2014-08-06 Sunil K. Arolla

The influence of turbulent effects on a fluid flow through a (pseudo) porous media is studied by numerically solving the set of Reynolds-averaged Navier-Stokes equations with the $\kappa$-$\epsilon$ model for turbulence. The spatial domains…

Statistical Mechanics · Physics 2009-11-07 H. H. M. Vasconcelos , U. M. S. Costa , M. P. Almeida

A machine-learned (ML) model is developed to enhance the accuracy of turbulence transport equations of Reynolds Averaged Navier Stokes (RANS) solver and applied for periodic hill test case, which involves complex flow regimes, such as…

Fluid Dynamics · Physics 2023-05-24 Shanti Bhushan , Greg W. Burgreen , Wesley Brewer , Ian D. Dettwiller

To study the Reynolds stresses which describe turbulent momentum transport from turbulence affected by large-scale shear and rotation. Three-dimensional numerical simulations are used to study turbulent transport under the influences of…

Solar and Stellar Astrophysics · Physics 2009-11-19 J. E. Snellman , P. J. Käpylä , M. J. Korpi , A. J. Liljeström

In this letter, a physics-based data-driven strategy is developed to predict vortex-induced drag on a circular cylinder under non-uniform inflow conditions - a prevalent issue for engineering applications at moderate Reynolds numbers.…

Fluid Dynamics · Physics 2026-04-20 Jiashun Guan , Haoyang Hu , Tianfang Hao , Huimin Wang , Yunxiao Ren , Dixia Fan

We consider a test problem for Navier-Stokes solvers based on the flow around a cylinder that exhibits chaotic behavior, to examine the behavior of various numerical methods. We choose a range of Reynolds numbers for which the flow is…

Numerical Analysis · Mathematics 2024-08-19 Henry von Wahl , L. Ridgway Scott

In-cylinder flow structures and turbulence characteristics are investigated using direct numerical simulations (DNS) in a laboratory-scale engine at technically relevant engine speeds (1500 and 2500 rpm at full load). The data is computed…

Fluid Dynamics · Physics 2025-06-05 Bogdan A. Danciu , George K. Giannakopoulos , Mathis Bode , Christos E. Frouzakis

A key factor in ensuring the accuracy of computer simulations that model physical systems is the proper calibration of their parameters based on real-world observations or experimental data. Inevitably, uncertainties arise, and Bayesian…

Computational Engineering, Finance, and Science · Computer Science 2026-02-25 Daniel Andrés Arcones , Martin Weiser , Phaedon-Stelios Koutsourelakis , Jörg F. Unger

The paper introduces a novel approach to global sensitivity analysis, grounded in the variance-covariance structure of random variables derived from random measures. The proposed methodology facilitates the application of…

Methodology · Statistics 2025-10-20 Caleb Deen Bastian , Herschel Rabitz , Grzegorz A Rempala

Several Tensor Basis Neural Network (TBNN) frameworks aimed at enhancing turbulence RANS modeling have recently been proposed in the literature as data-driven constitutive models for systems with known invariance properties. However,…

In this paper, we propose normalizing flows (NF) as a novel probability density function (PDF) turbulence model (NF-PDF model) for the Reynolds-averaged Navier-Stokes (RANS) equations. We propose to use normalizing flows in two different…

Fluid Dynamics · Physics 2021-01-12 Deniz A. Bezgin , Nikolaus A. Adams

With the rapid advancement of machine learning techniques, the development and study of machine learning turbulence models have become increasingly prevalent. As a critical component of turbulence modeling, the constitutive relationship…

Fluid Dynamics · Physics 2025-05-28 Ziqi Ji , Penghao Duan , Gang Du

Variational multiscale (VMS) methods offer a robust framework for handling under-resolved flow scales without resorting to problem-specific turbulence models. Here, we propose and assess a dynamic, term-by-term VMS stabilized formulation…

Fluid Dynamics · Physics 2026-02-06 Diego Escobar , Douglas Pacheco , Alejando Aguirre , Ernesto Castillo

In transonic turbine stages, complex interactions between trailing edge shocks from nozzle guide vanes and rotor blades generate unsteady wall pressure fields, impacting rotor aerodynamic performance and structural integrity. While…

Using the Lagrangian transport of momentum, the Reynolds shear stress can be expressed in terms of basic turbulence parameters. In this view, the Reynolds stress gradient represents the lateral transport of streamwise momentum, balanced by…

Fluid Dynamics · Physics 2020-07-28 T. -W. Lee

This work suggests several methods of uncertainty treatment in multiscale modelling and describes their application to a system of coupled turbulent transport simulations of a tokamak plasma. We propose a method to quantify the usually…

Plasma Physics · Physics 2023-07-10 Yehor Yudin , David Coster , Udo von Toussaint , Frank Jenko