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A new modeling approach for large-eddy simulation (LES) is obtained by combining a `regularization principle' with an explicit filter and its inversion. This regularization approach allows a systematic derivation of the implied…

混沌动力学 · 物理学 2009-11-07 Bernard J. Geurts , Darryl D. Holm

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 use of extended surfaces find wide range of applications in heat transfer devices for achieving heat transfer augmentation like gas turbine blade cooling and nuclear reactor core since the last few decades. So, understanding the…

流体动力学 · 物理学 2022-09-01 Auronil Mukherjee , Arnab Chakraborty

The complexity of the topological and combinatorial configuration space of MXenes can give rise to gigantic design challenges that cannot be addressed through traditional experimental or routine theoretical approaches. To this end, we…

材料科学 · 物理学 2022-12-13 B. Moses Abraham , Priyanka Sinha , Prosun Halder , Jayant K. Singh

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…

Hypersonic flight poses unique propulsion challenges, requiring engines that maintain thrust, efficiency, and stability across a wide range of operating conditions. These engines must transition smoothly between flight regimes and…

流体动力学 · 物理学 2025-11-25 Nick Plewacki , Benjamin Kale , Manu Kamin , Luis Bravo

This article utilizes the Large-Eddy Simulation (LES) paradigm with a physics-based turbulence modeling approach, including a dynamic subgrid-scale model and an equilibrium wall model, to examine the flow over the NASA transonic Common…

流体动力学 · 物理学 2024-07-11 Konrad A. Goc , Rahul Agrawal , Sanjeeb T. Bose , Parviz Moin

The Large Eddy Simulation (LES) approach is adapted to the study of plasma microturbulence in a fully three-dimensional gyrokinetic system. Ion temperature gradient driven turbulence is studied with the {\sc GENE} code for both a standard…

等离子体物理 · 物理学 2015-03-19 P. Morel , A. Bañón Navarro , M. Albrecht-Marc , D. Carati , F. Merz , T. Görler , F. Jenko

The need to burn 100% H2 in high efficient gas turbines featuring low NOx combustion in premix mode require the complete redesign of the combustion system to ensure stable operation without any flashback. Since all engine frames featuring a…

人工智能 · 计算机科学 2026-04-28 Patrick Krüger , Hanno Gottschalk , Werner Krebs , Bastian Werdelmann

Large-eddy simulations (LES) are widely-used for computing high Reynolds number turbulent flows. Spatial filtering theory for LES is not without its shortcomings, including how to define filtering for wall-bounded flows, commutation errors…

流体动力学 · 物理学 2022-02-02 Perry L. Johnson

We present a variant of the immersed boundary method integrated with octree meshes for highly efficient and accurate Large-Eddy Simulations (LES) of flows around complex geometries. We demonstrate the scalability of the proposed method up…

This work presents predictive hydrodynamic simulations empowered by artificial intelligence (AI) for laser driven implosion experiments, taking the double-cone ignition (DCI) scheme as an example. A Transformer-based deep learning model…

等离子体物理 · 物理学 2025-07-23 Zixu Wang , Yuhan Wang , Junfei Ma , Fuyuan Wu , Junchi Yan , Xiaohui Yuan , Zhe Zhang , Jie Zhang

This work presents, to the best of the authors' knowledge, the first generalizable and fully data-driven adaptive framework designed to stabilize deep learning (DL) autoregressive forecasting models over long time horizons, with the goal of…

流体动力学 · 物理学 2025-05-06 Rodrigo Abadía-Heredia , Manuel Lopez-Martin , Soledad Le Clainche

Large-eddy simulation developments and validations are presented for an improved simulation of turbulent internal flows. Numerical methods are proposed according to two competing criteria: numerical qualities (precision and spectral…

流体动力学 · 物理学 2008-01-15 Jérôme Boudet , Joëlle Caro , L. Shao , Emmanuel Lévêque

Two widely used sub-grid scale models, the standard and the dynamic Smagorinsky models were tested in a simulation of the flow in a thermally driven 3D cavity at Rayleigh number of Ra=1E9. The main focus of the research is the response of…

流体动力学 · 物理学 2021-10-04 M. A. Sayed , A. Dehbi , M. Hadžiabić , B. Ničeno , K. Mikityuk

In this work, we use ML techniques to develop presumed PDF models for large eddy simulations of reacting flows. The joint sub-filter PDF of mixture fraction and progress variable is modeled using various ML algorithms and commonly used…

计算物理 · 物理学 2019-09-04 Marc T. Henry de Frahan , Shashank Yellapantula , Ryan King , Marc S. Day , Ray W. Grout

The ability to rapidly detect hydrogen gas upon occurrence of a leak is critical for the safe large-scale implementation of hydrogen (energy) technologies. However, to date, no technically viable sensor solution exists that meets the…

The LES/PDF methodology is applied to the Cambridge/Sandia turbulent stratified flame series under swirling conditions. The methane/air chemistry is represented by a 16-species reduced ARM1 mechanism, and the in situ adaptive tabulation…

流体动力学 · 物理学 2020-12-04 Hasret Turkeri , Xinyu Zhao , Metin Muradgolu

A deep learning (DL) closure model for large-eddy simulation (LES) is developed and evaluated for incompressible flows around a rectangular cylinder at moderate Reynolds numbers. Near-wall flow simulation remains a central challenge in…

流体动力学 · 物理学 2023-07-19 Justin Sirignano , Jonathan F. MacArt

The present work focuses on the large eddy simulation (LES) and the study of turbulent dilute methanol spray flames in vitiated coflow using the secondary oxidizer Flamelet Generated Model (FGM). The modified FGM model uses an additional…

流体动力学 · 物理学 2022-08-25 Bharat Bhatia , Ashoke De , Dirk Roekaerts , Assaad R. Masri