An ODE-based wall model for turbulent flow simulations

Marsha Berger, Michael J. Aftosmis

Research output: Contribution to journalArticle

Abstract

This paper presents a new wall model to compute turbulent boundary layers using the Reynolds-averaged Navier- Stokes equations in high Reynolds number flows. The model solves a two-point boundary value problem for a coupled set of equations for the streamwise velocity and the turbulent viscosity. Since it includes both the pressure gradient and the momentum balance of the full Navier-Stokes system, the ordinary differential equation is valid farther from the wall. We implement the model within a Cartesian cut-cell method and use one-dimensional linelets in each cut cell to avoid the excessive mesh refinement that would otherwise be needed. The linelets are coupled to the outer Cartesian grid in a fully conservative manner, with two-way interaction between the linelets and the background grid. Detailed comparisons of velocity and eddy viscosity with three well-studied examples from the Turbulence Modeling Resource website are presented to demonstrate the model's performance in two space dimensions, including an example with smooth-body separation. The results show the new model gives excellent results even when the y-value of the first point is in the wake layer.

Original languageEnglish (US)
Pages (from-to)700-714
Number of pages15
JournalAIAA Journal
Volume56
Issue number2
DOIs
StatePublished - Jan 1 2018

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Flow simulation
Turbulent flow
Viscosity
Pressure gradient
Ordinary differential equations
Navier Stokes equations
Boundary value problems
Websites
Momentum
Boundary layers
Reynolds number
Turbulence

ASJC Scopus subject areas

  • Aerospace Engineering

Cite this

An ODE-based wall model for turbulent flow simulations. / Berger, Marsha; Aftosmis, Michael J.

In: AIAA Journal, Vol. 56, No. 2, 01.01.2018, p. 700-714.

Research output: Contribution to journalArticle

Berger, Marsha ; Aftosmis, Michael J. / An ODE-based wall model for turbulent flow simulations. In: AIAA Journal. 2018 ; Vol. 56, No. 2. pp. 700-714.
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