中文
相关论文

相关论文: Modeling and Simulation of Transitional Taylor-Gre…

200 篇论文

This work focuses on the accuracy and stability of high-order nodal discontinuous Galerkin (DG) methods for under-resolved turbulence computations. In particular we consider the inviscid Taylor-Green vortex (TGV) flow to analyse the…

We propose a data-driven, closure model for Reynolds-averaged Navier-Stokes (RANS) simulations that incorporates aleatoric, model uncertainty. The proposed closure consists of two parts. A parametric one, which utilizes previously proposed,…

流体动力学 · 物理学 2024-04-16 Atul Agrawal , Phaedon-Stelios Koutsourelakis

Predictive simulation of many complex flows requires moving beyond Reynolds-averaged Navier-Stokes (RANS) based models to representations resolving at least some scales of turbulence in at least some regions of the flow. To resolve…

流体动力学 · 物理学 2018-12-11 Sigfried Haering , Todd A. Oliver , Robert D. Moser

This paper proposes a phenomenological Reynolds Averaged Navier-Stokes (RANS) calculation model based on physical constraints. In this model part of the source terms in the e equation was replaced with the deep learning model, using the…

流体动力学 · 物理学 2021-12-28 Shuming Zhang , Haiwang Li , Ruquan You , Tinglin Kong , Zhi Tao

Turbulent flows consist of a wide range of interacting scales. Since the scale range increases as some power of the flow Reynolds number, a faithful simulation of the entire scale range is prohibitively expensive at high Reynolds numbers.…

流体动力学 · 物理学 2023-07-24 Dhawal Buaria , Katepalli R. Sreenivasan

A local artificial neural network (LANN) framework is developed for turbulence modeling. The Reynolds-averaged Navier-Stokes (RANS) unclosed terms are reconstructed by artificial neural network (ANN) based on the local coordinate system…

流体动力学 · 物理学 2021-09-08 Chenyue Xie , Xiangming Xiong , Jianchun Wang

Turbulence in fluids is an ubiquitous phenomenon, characterized by spontaneous transition of a smooth, laminar flow to rapidly changing, chaotic dynamics. In 1883, Reynolds experimentally demonstrated that, in an initially laminar flow of…

流体动力学 · 物理学 2022-05-03 Rafail V. Abramov

Cavitation is a complex multiphase phenomenon characterised by vapour bubbles forming due to a sudden pressure drop and is often accompanied by increased hull vibrations, increased radiated noise and decrease in propeller and impeller…

流体动力学 · 物理学 2024-05-02 Dhruv Apte , Mingming Ge , Olivier Coutier-Delgosha

In this investigation, we outline an enveloping models methodology for estimating structural uncertainty bounds on RANS closures. This methodology incorporates both eigenvalue and eigenvector perturbations in the spectral representation of…

流体动力学 · 物理学 2017-04-07 A. A. Mishra , G. Iaccarino

We propose a new turbulence closure model based on the budget equations for the key second moments: turbulent kinetic and potential energies: TKE and TPE (comprising the turbulent total energy: TTE = TKE + TPE) and vertical turbulent fluxes…

大气与海洋物理 · 物理学 2013-07-18 S. S. Zilitinkevich , T. Elperin , N. Kleeorin , I. Rogachevskii

This study proposes a newly-developed deep-learning-based method to generate turbulent inflow conditions for spatially-developing turbulent boundary layer (TBL) simulations. A combination of a transformer and a multiscale-enhanced…

流体动力学 · 物理学 2023-03-22 Mustafa Z. Yousif , Meng Zhang , Linqi Yu , Ricardo Vinuesa , HeeChang Lim

We present an algebraic model for turbulent scalar-flux vector that stems from tensor representation theory. The resulting closure contains direct dependence on mean velocity gradients and on frame rotation tensor that accounts for Coriolis…

Turbulent problems in industrial applications are predominantly solved using Reynolds Averaged Navier Stokes (RANS) turbulence models. The accuracy of the RANS models is limited due to closure assumptions that induce uncertainty into the…

流体动力学 · 物理学 2018-02-20 Atieh Alizadeh Moghaddam , Amir Sadaghiyani

Despite well-known limitations of Reynolds-averaged Navier-Stokes (RANS) simulations, this methodology remains the most widely used tool for predicting many turbulent flows, due to computational efficiency. Machine learning is a promising…

流体动力学 · 物理学 2022-03-14 Ryley McConkey , Eugene Yee , Fue-Sang Lien

Reliably predictive simulation of complex flows requires a level of model sophistication and robustness exceeding the capabilities of current Reynolds-averaged Navier-Stokes (RANS) models. The necessary capability can often be provided by…

流体动力学 · 物理学 2022-01-20 Sigfried W. Haering , Todd A. Oliver , Robert D. Moser

Vortex induced vibration (VIV) occurs when vortex shedding frequency falls close to the natural frequency of a structure. Investigation on VIV is of great value in disaster mitigation, energy extraction and other applications. Following…

流体动力学 · 物理学 2021-03-11 Xiaodong Bai , Wei Zhang

This study employs three-dimensional particle-resolved simulations of planar shocks passing through a suspension of stationary solid particles to study wake-induced gas-phase velocity fluctuations, termed pseudo-turbulence. Strong coupling…

流体动力学 · 物理学 2025-04-07 Archana Sridhar , Rodney O. Fox , Jesse Capecelatro

Reynolds Averaged Navier Stokes (RANS) models represent the workhorse for studying turbulent flows in industrial applications. Such single-point turbulence models have limitations in accounting for the influence of the non-local physics and…

流体动力学 · 物理学 2017-04-19 K. Duraisamy , Anand A. , G. Iaccarino

Turbulence modeling within the Lattice Boltzmann Method (LBM) framework has long relied on traditional algebraic sub-grid scale (SGS) models, which often suffer from over-dissipation and lack of spatial selectivity near solid boundaries. In…

流体动力学 · 物理学 2026-05-12 Yujie Fu , Yihan Zhang , Wanru Deng , Yuanjun Dai

The transition to turbulence in a plane Poiseuille flow of dilute polymer solutions is studied by direct numerical simulations of a FENE-P fluid. A range of Reynolds number ($Re$) in $2000 \le Re \le 5000$ is studied but with the same level…

流体动力学 · 物理学 2023-11-07 Alexia Martinez Ibarra , Jae Sung Park