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An adjoint-based variational optimal mixed model (VOMM) is proposed for subgrid-scale (SGS) closure in large-eddy simulation (LES) of turbulence. The stabilized adjoint LES equations are formulated by introducing a minimal regularization to…

流体动力学 · 物理学 2023-07-19 Zelong Yuan , Yunpeng Wang , Xiaoning Wang , Jianchun Wang

The seasonal and spatial evolution of mixed layers (MLs) in the Red Sea (RS) is analyzed for the 2001-2015 period using the results of a high resolution (~1km horizontal, 50 vertical layers) ocean circulation model forced by a novel…

大气与海洋物理 · 物理学 2021-12-17 G. Krokos , I. Cerovečki , P. Zhan , M. C. Hendershott , I. Hoteit

Fluid turbulence is an important problem for physics and engineering. Turbulence modeling deals with the development of simplified models that can act as surrogates for representing the effects of turbulence on flow evolution. Such models…

流体动力学 · 物理学 2021-11-16 J P Panda

We propose a new model of turbulence for use in large-eddy simulations (LES). The turbulent force, represented here by the turbulent Lamb vector, is divided in two contributions. The contribution including only subfilter fields is…

流体动力学 · 物理学 2009-11-11 Jean-Philippe Laval , Berengere Dubrulle

The increasingly congested near earth environment requires accurate orbital modelling to prevent collision events that threaten access to space infrastructure. Ionospheric aerodynamics are the largest non-conservative source of orbital…

等离子体物理 · 物理学 2022-09-26 Faun Watson

Regional dynamics of Bay of Bengal is studied using Open Boundary Condition (OBC) in Modular Ocean Model (MOM) to understand the effect of primary and secondary mesoscale features on various bulk ocean products and turbulent fluxes. A…

大气与海洋物理 · 物理学 2021-05-07 Siddhesh Tirodkar , Mousumi Sarkar , Rajesh Chauhan , Manasa R. Behera , Sridhar Balasubramanian

Data-driven approaches offer novel opportunities for improving the performance of turbulent flow simulations, which are critical to wide-ranging applications from wind farms and aerodynamic designs to weather and climate forecasting. While…

流体动力学 · 物理学 2024-02-14 Xiao Xue , Shuo Wang , Hua-Dong Yao , Lars Davidson , Peter V. Coveney

Machine-learning (ML) models, such as the AIFS at the ECMWF, have revolutionised weather forecasting in recent years. We present an extension of the AIFS that jointly models the atmosphere and surface ocean, including ocean waves and sea…

Active wake control (AWC) has emerged as a promising strategy for enhancing wind turbine wake recovery, but accurately modelling its underlying fluid mechanisms remains challenging. This study presents a computationally efficient wake model…

流体动力学 · 物理学 2025-06-25 Zhaobin Li , Xiaolei Yang

Recent laboratory experiments have revealed that important insights into the physical processes involved in the wind-driven generation of surface waves may be obtained by varying the viscosity of the carrying liquid over several orders of…

流体动力学 · 物理学 2023-04-12 Florent Burdairon , Jacques Magnaudet

Data-driven, deep-learning modeling frameworks have been recently developed for forecasting time series data. Such machine learning models may be useful in multiple domains including the atmospheric and oceanic ones, and in general, the…

The shock induced mixing of two gases separated by a perturbed interface is investigated through Large Eddy Simulation (LES) and Direct Numerical Simulation (DNS). In a simulation, physical dissipation of the velocity field and species mass…

流体动力学 · 物理学 2015-06-18 Britton J. Olson , Jeffrey A. Greenough

The dune morphodynamics study is under highly focused recently, due to aeolian process induced nonlinear correlation to sediment modification over bedform. Surface stress, inflicted by aloft upcoming wind, impacts, crucially, the sediment…

流体动力学 · 物理学 2020-04-13 Chao Wang

From a direct numerical simulation of the MHD equations we show, for the first time, that velocity and magnetic-field structure functions exhibit multiscaling, extended self similarity (ESS), and generalized extended self similarity (GESS).…

chao-dyn · 物理学 2009-10-30 Abhik Basu , Anirban Sain , Sujan K. Dhar , Rahul Pandit

A stochastic approach based on generalized Polynomial Chaos (gPC) is used to quantify the error in Large-Eddy Simulation (LES) of a spatially-evolving mixing layer flow and its sensitivity to different simulation parameters, viz. the grid…

流体动力学 · 物理学 2013-09-27 Marcello Meldi , Maria Vittoria Salvetti , Pierre Sagaut

Numerical simulation of fluids plays an essential role in modeling many physical phenomena, such as weather, climate, aerodynamics and plasma physics. Fluids are well described by the Navier-Stokes equations, but solving these equations at…

流体动力学 · 物理学 2022-04-27 Dmitrii Kochkov , Jamie A. Smith , Ayya Alieva , Qing Wang , Michael P. Brenner , Stephan Hoyer

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…

流体动力学 · 物理学 2024-05-21 Minghan Chu

Recent extreme tropical cyclones caused extensive damages to critical civil infrastructure globally. To better capture the unique hurricane wind characteristics, a large eddy simulation (LES) Hurricane Boundary Layer (HBL) model is…

流体动力学 · 物理学 2023-10-06 Tianqi Ma , Chao Sun , Paul Miller

The precise simulation of turbulent flows holds immense significance across various scientific and engineering domains, including climate science, freshwater science, and energy-efficient manufacturing. Within the realm of simulating…

流体动力学 · 物理学 2024-12-31 Shengyu Chen , Peyman Givi , Can Zheng , Xiaowei Jia

Compressible magnetohydrodynamic (MHD) turbulence is ubiquitous in astrophysical phenomena ranging from the intergalactic to the stellar scales. In studying them, numerical simulations are nearly inescapable, due to the large degree of…

流体动力学 · 物理学 2016-07-27 Dimitar G Vlaykov , Philipp Grete , Wolfram Schmidt , Dominik R G Schleicher