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NASA NTRS1993

Workshop on Computational Turbulence Modeling

This document contains presentations given at Workshop on Computational Turbulence Modeling held 15-16 Sep. 1993. The purpose of the meeting was to discuss the current status and future development of turbulence modeling in computational fluid dynamics for aerospace propulsion systems. Papers cover the following topics: turbulence modeling activities at the Center for Modeling of Turbulence and Transition (CMOTT); heat transfer and turbomachinery flow physics; aerothermochemistry and computational methods for space systems; computational fluid dynamics and the k-epsilon turbulence model; propulsion systems; and inlet, duct, and nozzle flow.

Source record↗

NASA NTRS1986

Impact of turbulence modeling on numerical accuracy and efficiency of compressible flow simulations

Discussed is the numerical implementation of turbulence models used in viscous compressible flow simulations and their performance described with respect to numerical accuracy, efficiency and stability. The basic approach utilizes the Reynolds-averaged compressible Navier-Stokes equations in which the Reynolds stresses and heat fluxes are mathematically modeled by suitable turbulence models. The turbulence models investigated include zero-, one-, and two-equation eddy viscosity models. The flow fields investigated include theoretical and supersonic flows about two-dimensional and axisymmetric bodies. Discussions concerning the numerical implementation of models include differencing procedures and boundary conditions used to assume numerical stability and accuracy. Numerical performance is also evaluated by comparing computations with experimental results.

Coakley, Thomas J.↗

NASA NTRS1992

A comparative study of turbulence models for overset grids

The implementation of two different types of turbulence models for a flow solver using the Chimera overset grid method is examined. Various turbulence model characteristics, such as length scale determination and transition modeling, are found to have a significant impact on the computed pressure distribution for a multielement airfoil case. No inherent problem is found with using either algebraic or one-equation turbulence models with an overset grid scheme, but simulation of turbulence for multiple-body or complex geometry flows is very difficult regardless of the gridding method. For complex geometry flowfields, modification of the Baldwin-Lomax turbulence model is necessary to select the appropriate length scale in wall-bounded regions. The overset grid approach presents no obstacle to use of a one- or two-equation turbulence model. Both Baldwin-Lomax and Baldwin-Barth models have problems providing accurate eddy viscosity levels for complex multiple-body flowfields such as those involving the Space Shuttle.

Renze, Kevin J.↗

NASA NTRS1995

The applicability of turbulence models to aerodynamic and propulsion flowfields at McDonnell-Douglas Aerospace

The objective of this viewgraph presentation is to evaluate turbulence models for integrated aircraft components such as the forebody, wing, inlet, diffuser, nozzle, and afterbody. The one-equation models have replaced the algebraic models as the baseline turbulence models. The Spalart-Allmaras one-equation model consistently performs better than the Baldwin-Barth model, particularly in the log-layer and free shear layers. Also, the Sparlart-Allmaras model is not grid dependent like the Baldwin-Barth model. No general turbulence model exists for all engineering applications. The Spalart-Allmaras one-equation model and the Chien k-epsilon models are the preferred turbulence models. Although the two-equation models often better predict the flow field, they may take from two to five times the CPU time. Future directions are in further benchmarking the Menter blended k-w/k-epsilon and algorithmic improvements to reduce CPU time of the two-equation model.

Kral, Linda D.↗

NASA NTRS1991

Calculation of a circular jet in crossflow with a multiple-time-scale turbulence model

Numerical calculation of a three dimensional turbulent flow of a jet in a crossflow using a multiple time scale turbulence model is presented. The turbulence in the forward region of the jet is in a stronger inequilibrium state than that in the wake region of the jet, while the turbulence level in the wake region is higher than that in the front region. The calculated flow and the concentration fields are in very good agreement with the measured data, and it indicated that the turbulent transport of mass, concentration, and momentum is strongly governed by the inequilibrium turbulence. The capability of the multiple time scale turbulence model to resolve the inequilibrium turbulence field is also discussed.

Kim, S.-W.↗

NASA NTRS1992

Calculation of a circular jet in crossflow with a multiple-time-scale turbulence model

Kim, S.-W.↗

NASA NTRS1991

Multigrid acceleration and turbulence models for computations of 3D turbulent jets in crossflow

A multigrid method is presented for the calculation of three-dimensional turbulent jets in crossflow. Turbulence closure is achieved with either the standard k-epsilon model or a Reynolds Stress Model (RSM). Multigrid acceleration enables convergence rates which are far superior to that for a single grid method. With the k-epsilon model the rate approaches that for laminar flow, but with RSM it is somewhat slower. The increased stiffness of the system of equations in the latter may be responsible. Computed results with both turbulence models are compared with experimental data for a pair of opposed jets in crossflow. Both models yield reasonable agreement with mean flow velocity but RSM yields better prediction of the Reynolds stresses.

Demuren, A. O.↗

NASA NTRS2015

Recent Developments on the Turbulence Modeling Resource Website (Invited)

The NASA Langley Turbulence Model Resource (TMR) website has been active for over five years. Its main goal of providing a one-stop, easily accessible internet site for up-to-date information on Reynolds-averaged Navier-Stokes turbulence models remains unchanged. In particular, the site strives to provide an easy way for users to verify their own implementations of widely-used turbulence models, and to compare the results from different models for a variety of simple unit problems covering a range of flow physics. Some new features have been recently added to the website. This paper documents the site's features, including recent developments, future plans, and open questions.

Rumssey, Christopher L.↗

NASA NTRS1976

Development and application of an atmospheric turbulence model for use in flight simulators in flight simulators

The influence of simulated turbulence on aircraft handling qualities was investigated. Pilot opinion of the handling qualities of a light general aviation aircraft were evaluated in a motion-base simulator using a simulated turbulence environment. A realistic representation of turbulence disturbances is described in terms of rms intensity and scale length and their random variations with time. The time histories generated by the proposed turbulence models showed characteristics which appear to be more similar to real turbulence than the frequently-used Gaussian turbulence model. In addition, the proposed turbulence models can flexibly accommodate changes in atmospheric conditions and be easily implemented in flight simulator studies. Six turbulence time histories, including the conventional Gaussian model, were used in an IFR-tracking task. The realism of each of the turbulence models and the handling qualities of the simulated airplane were evaluated. Analysis of pilot opinions shows that at approximately the same rms intensities of turbulence, the handling quality ratings transit from the satisfactory level, for the simple Gaussian model, to an unacceptable level for more realistic and compositely structured turbulence models.

Jacobson, I. D.↗

NASA NTRS1994

Computation of Separated and Unsteady Flows with One- and Two-Equation Turbulence Models

The ability of one- and two-equation turbulence models to predict unsteady separated flows over airfoils is evaluated. An implicit, factorized, upwind-biased numerical scheme is used for the integration of the compressible, Reynolds averaged Navier-Stokes equations. The turbulent eddy viscosity is obtained from the computed mean flowfield by integration of the turbulent field equations. The two-equation turbulence models are discretized in space with an upwind-biased, second order accurate total variation diminishing scheme. One and two-equation turbulence models are first tested for a separated airfoil flow at fixed angle of incidence. The same models are then applied to compute the unsteady flowfields about airfoils undergoing oscillatory motion at low subsonic Mach numbers. Experimental cases where the flow has been tripped at the leading edge and where natural transition was allowed to occur naturally are considered. The more recently developed field-equation turbulence models capture the physics of unsteady separated flow significantly better than the standard kappa-epsilon and kappa-omega models. However, certain differences in the hysteresis effects are obtained. For an untripped high-Reynolds-number flow, it was found necessary to take into account the leading edge transitional flow region in order to capture the correct physical mechanism that leads to dynamic stall.

Ekaterinaris, John A.↗

NASA NTRS1985

Confined swirling jet predictions using a multiple-scale turbulence model

A recently developed multiple scale turbulence model is used for the numerical prediction of isothermal, confined turbulent swirling flows. Because of the streamline curvature and nonequilibrium spectral energy transfer nature of the swirling flow, the utilized multiple scale turbulence model includes a different set of response equations for each of the large scale energetic eddies and the small scale transfer eddies. Predictions are made of a confined coaxial swirling jet in a sudden expansion and comparisons are made with experimental data and with the conventional single scale two equation model. The multiple scale model shows significant improvement of predictions of swirling flows over the single scale k epsilon model. The sensitivity study of the effect of prescribed inlet turbulence levels on the flow fields is also included.

Chen, C. P.↗

NASA NTRS2019

The Effect of Turbulence Modeling on the Mixing Characteristics of Several Fuel Injectors at Hypervelocity Flow Conditions

CFD analysis is presented on the effects of turbulence modeling choices on the mixing characteristics and performance of three fuel injectors at hypervelocity flow conditions. The analyses were carried out with the VULCAN-CFD solver using Reynolds-Averaged Simulations (RAS). The hypervelocity flow conditions match the high Mach number flow of the experiments conducted as a part of the Enhanced Injection and Mixing Project (EIMP) at the NASA Langley Research Center. The three injectors are the baseline configurations used in the experiments and represent three categories of injectors typically considered individually or in combination for fueling high-speed propulsive devices. The current work discusses the impact of the turbulence model and the turbulent Schmidt number on the mixing flow field behavior and the mixing performance as described by the one-dimensional values of the Mach number, total pressure recovery, and the mixing efficiency. Because planar laser induced fluorescence (PLIF) images are available from the EIMP experiments, the sensitivity of the synthetic LIF signal to turbulence modeling choices is also examined to determine whether PLIF can be extended beyond its intended qualitative visualization purpose and used to guide CFD turbulence model and parameter selections. It is found that the mixing performance, as quantified using mixing efficiency, exhibits a strong sensitivity to both turbulence model choice and turbulent Schmidt number value. However, the synthetic LIF signal only demonstrates a modest level of sensitivity, which suggests that PLIF is of limited use for guiding CFD turbulence model and parameter selections.

Drozda, Tomasz G.↗

NASA NTRS1989

Turbulence modeling for aerodynamic flows

The state of statistical turbulence modeling is reviewed with emphasis on compressible aerodynamic flows. A three-stage modeling process is suggested to act as a frame-work for improving turbulence models for complex flows. This process is then used to guide assessments of the comparative performance of various levels of turbulence models for several examples of flow fields of aerodynamic interest. The examples cover flows in two and three dimensions and with a broad range of Mach numbers. In addition to considerations of individual flow fields, some generalizations are drawn from the aggregate behavior of the comparisons.

Rubesin, Morris W.↗

NASA NTRS1976

Turbulence model predictions for the inhomogeneous mixing layer

The plane mixing layer between two streams of different densities and velocities is studied using a complete, phenomenological model of turbulence. The model is an extension of that described by Saffman (1974). The properties of similarity solutions are computed, and compared with experimental data. The qualitative dependence on velocity ratio, density ratio, compressibility and adverse pressure gradient is predicted correctly. The quantitative agreement is satisfactory.

Milinazzo, F.↗

NASA NTRS2019

Turbulence Model Implementation and Verification in the SENSEI CFD Code

This paper outlines the implementation and verification of the negative Spalart-Allmaras turbulence model into the SENSEI CFD code. The SA-neg turbulence model is implemented in a flexible, object-oriented framework where additional turbulence models can be easily added. In addition to outlining the new turbulence modeling framework in SENSEI, an overview of the other general improvements to SENSEI is provided. The results for four 2D test cases are compared to results from CFL3D and FUN3D to verify that the turbulence models are implemented properly. Several differences in the results from SENSEI, CFL3D, and FUN3D are identified and are attributed to differences in the implementation and discretization order of the boundary conditions as well as the order of discretization of the turbulence model. When a solid surface is located near or intersects an inflow or outflow boundary, higher order boundary conditions should be used to limit their effect on the forces on the surface. When the turbulence equations are discretized using second order spatial accuracy, the edge of the eddy viscosity profile seems to be sharper than when a first order discretization is used. However, the discretization order of the turbulence equation does not have a significant impact on output quantities of interest, such as pressure and viscous drag, for the cases studied.

Jackson, Charles W.↗

NASA NTRS1992

Workshop on Engineering Turbulence Modeling

Discussed here is the future direction of various levels of engineering turbulence modeling related to computational fluid dynamics (CFD) computations for propulsion. For each level of computation, there are a few turbulence models which represent the state-of-the-art for that level. However, it is important to know their capabilities as well as their deficiencies in order to help engineers select and implement the appropriate models in their real world engineering calculations. This will also help turbulence modelers perceive the future directions for improving turbulence models. The focus is on one-point closure models (i.e., from algebraic models to higher order moment closure schemes and partial differential equation methods) which can be applied to CFD computations. However, other schemes helpful in developing one-point closure models, are also discussed.

Povinelli, Louis A.↗

NASA NTRS1994

Workshop on Computational Turbulence Modeling

The purpose of this meeting was to discuss the current status and future development of turbulence modeling in computational fluid dynamics for aerospace propulsion systems. Various turbulence models have been developed and applied to different turbulent flows over the past several decades and it is becoming more and more urgent to assess their performance in various complex situations. In order to help users in selecting and implementing appropriate models in their engineering calculations, it is important to identify the capabilities as well as the deficiencies of these models. This also benefits turbulence modelers by permitting them to further improve upon the existing models. This workshop was designed for exchanging ideas and enhancing collaboration between different groups in the Lewis community who are using turbulence models in propulsion related CFD. In this respect this workshop will help the Lewis goal of excelling in propulsion related research. This meeting had seven sessions for presentations and one panel discussion over a period of two days. Each presentation session was assigned to one or two branches (or groups) to present their turbulence related research work. Each group was asked to address at least the following points: current status of turbulence model applications and developments in the research; progress and existing problems; and requests about turbulence modeling. The panel discussion session was designed for organizing committee members to answer management and technical questions from the audience and to make concluding remarks.

Shabbir, A.↗

NASA NTRS2014

Turbulence Modeling Verification and Validation

Computational fluid dynamics (CFD) software that solves the Reynolds-averaged Navier-Stokes (RANS) equations has been in routine use for more than a quarter of a century. It is currently employed not only for basic research in fluid dynamics, but also for the analysis and design processes in many industries worldwide, including aerospace, automotive, power generation, chemical manufacturing, polymer processing, and petroleum exploration. A key feature of RANS CFD is the turbulence model. Because the RANS equations are unclosed, a model is necessary to describe the effects of the turbulence on the mean flow, through the Reynolds stress terms. The turbulence model is one of the largest sources of uncertainty in RANS CFD, and most models are known to be flawed in one way or another. Alternative methods such as direct numerical simulations (DNS) and large eddy simulations (LES) rely less on modeling and hence include more physics than RANS. In DNS all turbulent scales are resolved, and in LES the large scales are resolved and the effects of the smallest turbulence scales are modeled. However, both DNS and LES are too expensive for most routine industrial usage on today's computers. Hybrid RANS-LES, which blends RANS near walls with LES away from walls, helps to moderate the cost while still retaining some of the scale-resolving capability of LES, but for some applications it can still be too expensive. Even considering its associated uncertainties, RANS turbulence modeling has proved to be very useful for a wide variety of applications. For example, in the aerospace field, many RANS models are considered to be reliable for computing attached flows. However, existing turbulence models are known to be inaccurate for many flows involving separation. Research has been ongoing for decades in an attempt to improve turbulence models for separated and other nonequilibrium flows. When developing or improving turbulence models, both verification and validation are important steps in the process. Verification insures that the CFD code is solving the equations as intended (no errors in the implementation). This is typically done either through the method of manufactured solutions (MMS) or through careful step-by-step comparisons with other verified codes. After the verification step is concluded, validation is performed to document the ability of the turbulence model to represent different types of flow physics. Validation can involve a large number of test case comparisons with experiments, theory, or DNS. Organized workshops have proved to be valuable resources for the turbulence modeling community in its pursuit of turbulence modeling verification and validation. Workshop contributors using different CFD codes run the same cases, often according to strict guidelines, and compare results. Through these comparisons, it is often possible to (1) identify codes that have likely implementation errors, and (2) gain insight into the capabilities and shortcomings of different turbulence models to predict the flow physics associated with particular types of flows. These are valuable lessons because they help bring consistency to CFD codes by encouraging the correction of faulty programming and facilitating the adoption of better models. They also sometimes point to specific areas needed for improvement in the models. In this paper, several recent workshops are summarized primarily from the point of view of turbulence modeling verification and validation. Furthermore, the NASA Langley Turbulence Modeling Resource website is described. The purpose of this site is to provide a central location where RANS turbulence models are documented, and test cases, grids, and data are provided. The goal of this paper is to provide an abbreviated survey of turbulence modeling verification and validation efforts, summarize some of the outcomes, and give some ideas for future endeavors in this area.

Rumsey, Christopher L.↗