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We introduce a data-driven learning framework that assimilates two powerful ideas: ideal large eddy simulation (LES) from turbulence closure modeling and neural stochastic differential equations (SDE) for stochastic modeling. The ideal LES…

A mechanistic theory of wind-wave interaction must rely on verifiable assumptions and offer reproducible observable predictions. For decades, the limited mechanistic grasp on the problem has motivated RANS and LES modeling and has driven a…

流体动力学 · 物理学 2018-02-15 Tihomir Hristov

We introduce an analytical model that describes the vertical structure of Ekman boundary layer flows coupled to the Monin-Obukhov Similarity Theory (MOST) surface layer representation, which is valid for conventionally neutral (CNBL) and…

流体动力学 · 物理学 2024-12-04 Ghanesh Narasimhan , Dennice F. Gayme , Charles Meneveau

This study presents key enhancements in hydrodynamic modeling using the strip-based Morison's equation approach to enable rapid simulations of Floating Offshore Wind Turbines (FOWT). The modeling framework employs the relative form of the…

大气与海洋物理 · 物理学 2025-08-05 Doyal Sarker , Md Sakif , Tri Ngo , Tuhin Das

Molecular dynamics (MD) simulations represent a powerful investigation tool in the field of soft matter. By using shear flows, one can probe the bulk rheology of complex fluids, also beyond the linear response regime, in a way that imitates…

软凝聚态物质 · 物理学 2021-09-30 Sebastian Bindgen , Florian Weik , Rudolf Weeber , Erin Koos , Pierre de Buyl

We apply the proper orthogonal decomposition (POD) to large eddy simulation data of a wind turbine wake in a turbulent atmospheric boundary layer. The turbine is modeled as an actuator disk. Our analyis mainly focuses on the question…

流体动力学 · 物理学 2015-03-11 David Bastine , Björn Witha , Matthias Wächter , Joachim Peinke

The coupling between wind-waves and atmospheric surface layer turbulence sets surface drag. This coupling is however usually represented through a roughness length. Originally suggested on purely dimensional grounds, this roughness length…

流体动力学 · 物理学 2021-03-12 Alex Ayet , Bertrand Chapron , Peter Sutherland , Gabriel G. Katul

A version of model is proposed, which is aimed for getting parameters of the atmospheric layer and upper water layer with account of the wind-wave state. The dynamics of the atmospheric boundary layer is realized in version of papers [1,…

大气与海洋物理 · 物理学 2011-08-12 Vladislav Polnikov , Iliya Kabatchenko

Wind waves are considered as an intermediate small-scale dynamic process at the air-sea interface,which modulates radically middle-scale dynamic processes of the boundary layers in water and air. It is shown that with the aim of a…

大气与海洋物理 · 物理学 2010-06-22 Vladislav G. Polnikov

Vertical mixing parameterizations in ocean models are formulated on the basis of the physical principles that govern turbulent mixing. However, many parameterizations include ad hoc components that are not well constrained by theory or…

大气与海洋物理 · 物理学 2024-01-23 Aakash Sane , Brandon G. Reichl , Alistair Adcroft , Laure Zanna

In high Reynolds number turbulent flows, energy dissipation refers to the process of energy transfer from kinetic energy to internal energy due to molecular viscosity. In large eddy simulation (LES) with one-equation turbulence models, the…

流体动力学 · 物理学 2020-01-22 Hongjiang Li , Christopher J. Rutland , Francisco E. Hernandez Perez , Hong G. Im

The impact of anisotropic dynamic models for applications to LES of compressible flows is assessed in the framework of a numerical model based on high order discontinuous finite elements. The projections onto lower dimensional subspaces…

数值分析 · 数学 2014-07-25 Antonella Abbà , Luca Bonaventura , Michele Nini , Marco Restelli

Large eddy simulations (LES) are a powerful tool in understanding processes that are inaccessible by direct simulations due to their complexity, for example, in the highly turbulent regime. However, their accuracy and success depends on a…

流体动力学 · 物理学 2017-03-27 Philipp Grete , Dimitar G Vlaykov , Wolfram Schmidt , Dominik R G Schleicher

Wall modelling in large-eddy simulation (LES) is necessary to overcome the prohibitive near-wall resolution requirements in high-Reynolds-number turbulent flows. Most existing wall models rely on assumptions about the state of the boundary…

流体动力学 · 物理学 2021-10-26 H. Jane Bae , Adrián Lozano-Durán , Sanjeeb T. Bose , Parviz Moin

Wind forcing injects energy into the mesoscale eddies and near-inertial waves (NIWs) in the ocean, and the NIW is believed to solve the puzzle of mesoscale energy budget by absorbing energy from mesoscale eddies followed by a forward…

流体动力学 · 物理学 2020-06-05 Jin-Han Xie

High Reynolds Homogeneous Isotropic Turbulence is fully described within the Navier-Stokes (NS) equations, which are notoriously difficult to solve numerically. Engineers, interested primarily in describing turbulence at a reduced range of…

'Data' plays a central role in data-driven methods, but is not often the subject of focus in investigations of machine learning algorithms as applied to Earth System Modeling related problems. Here we consider the case of eddy-mean…

大气与海洋物理 · 物理学 2023-07-04 F. E. Yan , J. Mak , Y. Wang

A simple analytical model is developed for the current induced by the wind and modified by surface wind-waves in the oceanic surface layer, based on a first-order turbulence closure and including the effect of a vortex force representing…

大气与海洋物理 · 物理学 2018-12-05 Miguel A. C. Teixeira

The transport and deposition of heavy particles over complex surface topography by turbulent fluid flow is an important problem in a number of disciplines, including sediment and snow transport, ecology and plant pathology, aeolian…

大气与海洋物理 · 物理学 2019-03-11 Scott T. Salesky , Marco G. Giometto , Marcelo Chamecki , Michael Lehning , Marc B. Parlange

This work proposes a data-driven explicit algebraic stress-based detached-eddy simulation (DES) method. Despite the widespread use of data-driven methods in model development for both Reynolds-averaged Navier-Stokes (RANS) and large-eddy…

流体动力学 · 物理学 2026-01-14 Hao-Chen Liu , Zifei Yin , Xin-Lei Zhang , Guowei He