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A framework for deriving probabilistic data-driven closure models is proposed for coarse-grained numerical simulations of turbulence in statistically stationary state. The approach unites the ideal large-eddy simulation model and data…

Fluid Dynamics · Physics 2025-03-25 Sagy Ephrati

A combined convolutional autoencoder-recurrent neural network machine learning model is presented to analyse and forecast the dynamics and low-order statistics of the local convective heat flux field in a two-dimensional turbulent…

Fluid Dynamics · Physics 2022-04-13 Sandeep Pandey , Philipp Teutsch , Patrick Mäder , Jörg Schumacher

Rayleigh-B\'enard convection in the turbulent regime is studied using statistical methods. Exact evolution equations for the probability density function of temperature and velocity are derived from first principles within the framework of…

Fluid Dynamics · Physics 2011-03-04 J. Lülff , M. Wilczek , R. Friedrich

Reservoir computing is applied to model the large-scale evolution and the resulting low-order turbulence statistics of a two-dimensional turbulent Rayleigh-B\'{e}nard convection flow at a Rayleigh number ${\rm Ra}=10^7$ and a Prandtl number…

Fluid Dynamics · Physics 2020-11-25 Sandeep Pandey , Jörg Schumacher

Turbulent thermal convection governs heat transport in systems ranging from stellar interiors to industrial heat exchangers. Two-dimensional Rayleigh-B\'enard convection serves as a paradigm for these flows, reproducing key features such as…

Data-driven flow control has significant potential for industry, energy systems, and climate science. In this work, we study the effectiveness of Reinforcement Learning (RL) for reducing convective heat transfer in the 2D Rayleigh-B\'enard…

Fluid Dynamics · Physics 2025-09-01 Thorben Markmann , Michiel Straat , Sebastian Peitz , Barbara Hammer

If a fluid flow is driven by a weak Gaussian random force, the nonlinearity in the Navier-Stokes equations is negligibly small and the resulting velocity field obeys Gaussian statistics. Nonlinear effects become important as the driving…

Fluid Dynamics · Physics 2018-10-01 Jörg Schumacher , Ambrish Pandey , Victor Yakhot , Katepalli R. Sreenivasan

Rayleigh-B\'enard convection, i.e. the flow of a fluid between two parallel plates that is driven by a temperature gradient, is an idealised setup to study thermal convection. Of special interest are the statistics of the turbulent…

Data-driven turbulence modeling is a newly emerged research area in thermal hydraulics simulation of nuclear power plant (NPP). The most common CFD method used in NPP thermal hydraulics simulation is Reynolds-averaged Navier-Stokes (RANS)…

Fluid Dynamics · Physics 2020-05-04 Yangmo Zhu , Nam Dinh

The aspect ratio (\Gamma) dependence of the heat transfer (Nusselt number Nu in dimensionless form) in turbulent (two-dimensional) Rayleigh-B\'enard convection is numerically studied in the regime $0.4 \le \Gamma \le 1.25$ for Rayleigh…

Fluid Dynamics · Physics 2011-12-05 Erwin P. van der Poel , Richard J. A. M. Stevens , Detlef Lohse

Rayleigh-B\'enard convection is numerically simulated in two- and three-dimensions using a recently developed two-component lattice Boltzmann equation (LBE) method. The density field of the second component, which evolves according to the…

comp-gas · Physics 2016-08-31 Xiaowen Shan

The central open question about Rayleigh--B\'enard convection -- buoyancy-driven flow in a fluid layer heated from below and cooled from above -- is how vertical heat flux depends on the imposed temperature gradient in the strongly…

Fluid Dynamics · Physics 2022-01-10 Baole Wen , David Goluskin , Charles R. Doering

Nudging is a data assimilation technique that has proved to be capable of reconstructing several highly turbulent flows from a set of partial spatiotemporal measurements. In this study we apply the nudging protocol on the temperature field…

Fluid Dynamics · Physics 2022-05-04 Lokahith Agasthya , Patricio Clark Di Leoni , Luca Biferale

This paper introduces a novel data driven framework for constructing accurate and general equivariant models of multiscale phenomena which does not rely on specific assumptions about the underlying physics. This framework is illustrated…

Fluid Dynamics · Physics 2026-04-15 Brandon Choi , Matteo Ugliotti , Mateo Reynoso , Daniel R. Gurevich , Roman O. Grigoriev

The representation of buoyancy-driven turbulence in Reynolds-averaged Navier--Stokes (RANS) models remains unresolved, with no widely accepted standard formulation. A key difficulty is the lack of analytical guidance for incorporating…

Fluid Dynamics · Physics 2026-04-29 Da-Sol Joo

The Rayleigh number $Ra$ dependence of the Nusselt number $Nu$ in turbulent Rayleigh--B\'enard convection is numerically investigated for a moderate and low Prandtl number, $Pr=0.7$ and $0.021$, respectively. Here we specifically address…

Fluid Dynamics · Physics 2019-06-18 Marten Klein , Heiko Schmidt

In this dissertation two-dimensional buoyancy-driven flows are investigated. While usually the Navier-Stokes equations are equipped with no-slip boundary conditions here we focus on the Navier-slip conditions that, depending on the system…

Analysis of PDEs · Mathematics 2024-09-25 Fabian Bleitner

We present a numerical study of Rayleigh-B\'enard convection disturbed by a longitudinal wind. Our results show that under the action of the wind, the vertical heat flux through the cell initially decreases, due to the mechanism of…

Fluid Dynamics · Physics 2015-06-17 Andrea Scagliarini , Armann Gylfason , Federico Toschi

This study explores heat and turbulent modulation in three-dimensional multiphase Rayleigh-B\'enard convection using direct numerical simulations. Two immiscible fluids with identical reference density undergo systematic variations in…

Fluid Dynamics · Physics 2024-08-26 Abbas Moradi Bilondi , Nicolò Scapin , Luca Brandt , Parisa Mirbod

To understand how internal flow structures manifest themselves in the global heat transfer, we study the correlation between different flow modes and the instantaneous Nusselt number ($Nu$) in a two-dimensional square Rayleigh-B\'enard…

Fluid Dynamics · Physics 2020-10-09 Ao Xu , Xin Chen , Feng Wang , Heng-Dong Xi
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