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A scale-resolving simulation methodology that includes stochastic energy backscatter is incorporated into a proprietary block-structured compressible flow solver. Particular attention is devoted to the discretisation of the convective terms…

流体动力学 · 物理学 2025-11-12 Angelo Passariello , Pietro Catalano , Carmine De Lucia , Renato Tognaccini

In typical nature and engineering scenarios, such as supernova explosion and inertial confinement fusion, mixing flows induced by hydrodynamics interfacial instabilities are essentially compressible. Despite their significance, accurate…

流体动力学 · 物理学 2025-06-23 Hansong Xie , Tengfei Luo , Yaomin Zhao , Yousheng Zhang , Jianchun Wang

This chapter provides an introduction to data-driven techniques for the development and calibration of closure models for the Reynolds-Averaged Navier--Stokes (RANS) equations. RANS models are the workhorse for engineering applications of…

流体动力学 · 物理学 2024-04-16 Paola Cinnella

This paper presents numerical simulations of a bichromatic wave group propagating and breaking over a fixed breaker bar. The simulations are performed using a newly stabilized Reynolds-averaged Navier Stokes (RANS) two-equation turbulence…

流体动力学 · 物理学 2020-10-29 B. E. Larsen , D. A. van der A. , J. van der Zanden , G. Ruessink , D. R. Fuhrman

To fully evaluate a turbulent flow, Direct Numerical Simulation (DNS) is the most accurate method by far and requires considerable computational power and time; not optimum for industry standards. Developing an alternative model, providing…

流体动力学 · 物理学 2022-07-04 Indrajit Nandi , Saikat Saha , Sabir Subedi , Sumon Saha

Traditional Reynolds-averaged Navier-Stokes (RANS) closures, based on the Boussinesq eddy viscosity hypothesis and calibrated on canonical flows, often yield inaccurate predictions of both mean flow and turbulence statistics. Here, we…

Accurate prediction of mixing transition induced by interfacial instabilities is vital for engineering applications, but has remained a great challenge for decades. For engineering practices, Reynolds-averaged Navier-Stokes simulation…

流体动力学 · 物理学 2023-10-02 Hansong Xie , Mengjuan Xiao , Yousheng Zhang , Yaomin Zhao

This paper presents a robust, adaptive numerical scheme for simulating high density ratio and high shear multiphase flows on locally refined Cartesian grids that adapt to the evolving interfaces and track regions of high vorticity. The…

This article provides a reduced-order modelling framework for turbulent compressible flows discretized by the use of finite volume approaches. The basic idea behind this work is the construction of a reduced-order model capable of providing…

流体动力学 · 物理学 2024-05-31 Matteo Zancanaro , Valentin Nkana Ngan , Giovanni Stabile , Gianluigi Rozza

We investigate generalized Navier-Stokes (GNS) equations that couple nonlinear advection with a generic linear instability. This analytically tractable minimal model for fluid flows driven by internal active stresses has recently been shown…

流体动力学 · 物理学 2020-04-10 Rohit Supekar , Vili Heinonen , Keaton J. Burns , Jörn Dunkel

We present a unified variational mechanics framework for cavitating turbulent flows and structural motions via a stabilized finite element formulation. To model the finite mass transfer rate in cavitation phenomena, we employ the homogenous…

流体动力学 · 物理学 2021-02-22 Suraj R. Kashyap , Rajeev K. Jaiman

In the turbulence modeling community, significant efforts have been made to quantify the uncertainties in the Reynolds-Averaged Navier--Stokes (RANS) models and to improve their predictive capabilities. Of crucial importance in these…

流体动力学 · 物理学 2017-10-11 Heng Xiao , Jin-Long Wu , Jian-xun Wang , Eric G. Paterson

The present work studied various models for predicting turbulence in the problem of injecting a fluid microjet into the boundary layer of a turbulent flow. For this purpose, the one-equation Spalart-Allmaras (SA), two-equation k-$\epsilon$…

Continuum fluid dynamic models based on the Navier-Stokes equations have previously been used to simulate granular media undergoing fluid-like shearing. These models, however, typically fail to predict the flow behaviour in confined…

流体动力学 · 物理学 2024-03-05 Duncan Dockar , M. H. Lakshminarayana Reddy , Matthew K. Borg , S. Kokou Dadzie

This work determines the inaccuracy of using Reynolds averaged Navier Stokes (RANS) turbulence models in transition to turbulent flow regimes by predicting the model-based discrepancies between RANS and large eddy simulation (LES) models…

流体动力学 · 物理学 2019-01-21 Mustafa Usta , Ali Tosyali

The present study assesses RANS-based turbulence models to simulate isothermal flow in a combustor representing a constituent can combustor of can-annular configuration used in jet engines. Two-equation models (standard $k-\epsilon$,…

流体动力学 · 物理学 2024-06-25 Aishvarya Kumar , Ram Prakash Bharti

Reynolds-averaged Navier-Stokes (RANS) equations are widely used in engineering turbulent flow simulations. However, RANS predictions may have large discrepancies due to the uncertainties in modeled Reynolds stresses. Recently, Wang et al.…

流体动力学 · 物理学 2018-09-11 Jin-Long Wu , Heng Xiao , Eric Paterson

Turbulence models attempt to account for unresolved dynamics and diffusion in hydrodynamical simulations. We develop a common framework for two-equation Reynolds-Averaged Navier-Stokes (RANS) turbulence models, and we implement six models…

星系天体物理 · 物理学 2017-03-28 Matthew D. Goodson , Fabian Heitsch , Karl Eklund , Virginia A. Williams

Reynolds-averaged Navier-Stokes (RANS) is one of the most cost-efficient approaches to simulate wind-farm-atmosphere interactions. However, the applicability of RANS-based methods is always limited by the accuracy of turbulence closure…

流体动力学 · 物理学 2021-12-08 Ali Eidi , Reza Ghiassi , Xiang Yang , Mahdi Abkar

We introduce a novel approach to derive compressibility corrections for Reynolds-averaged Navier-Stokes (RANS) models. Using this approach, we derive variable-property corrections for wall-bounded flows that take into account the distinct…

流体动力学 · 物理学 2025-09-17 Asif Manzoor Hasan , Alex Jose Elias , Florian Menter , Rene Pecnik