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At least 55 records · Page 3
All sourcesNASA NTRSDOE OSTI
NASA NTRS2003

Turbulent Simulation of the Dynamics of the Magnetotail

In situ observations indicate that the dynamical processes in the geoplasma environment generally entail localized intermittent processes and anomalous global transports. It was suggested by T. Chang that instead of considering the turbulence as a mixture of interacting waves, such type of patchy intermittency could be more easily understood in terms of the development, interaction, merging, preferential acceleration and evolution of coherent magnetic structures. In this three-year project, we have used direct numerical MHD simulations to study some aspects of the MHD dynamics in Chang's model. Our large-scale numerical calculations and simulations have been supplemented by and coordinated with theoretical studies conducted by Chang and his colleagues.

Wu, Cheng-Chin↗
NASA NTRSDate not supplied

Turbulence Simulations of Transonic Flows over NACA-0012 and OAT15A Airfoils

Three different simulation approaches, namely unsteady Reynolds-averaged Navier-Stokes (URANS), delayed detached-eddy simulation (DDES), and wall-modeled large-eddy simulation (WMLES) are employed to simulate transonic flow over an NACA-0012, OAT15A airfoils at different angles of attack covering pre- and post-buffet-onset regimes. The freestream Mach number is 0.75, and the Reynolds number based on the chord length is 10 and 3million, respectively. The NASA FUN3D solver is used for the simulations, which is an unstructured, compressible flow solver. The URANS simulations are performed using the Spalart-Allmaras (SA) model with the compressibility correction, the DDES predictions are based on the SA model, and the WMLES are performed using an equilibrium wall-model. The unsteady RANS simulations, only with the compressibility correction, predict the pre- and post- buffet characteristics, which compare well with the experimental results. DDES results predicted a lower buffet onset angle compared to experiment. The predicted shock locations are upstream of the locations predicted by URANS. Using a fine grid in the spanwise direction, WMLES predictions show buffeting consistent with the experiment.

Computational Fluid Dynamics↗
NASA NTRSDate not supplied

Turbulence Simulations of Transonic Flows over NACA-0012 and OAT15A Airfoils

Three different simulation approaches, namely unsteady Reynolds-averaged Navier-Stokes (URANS), delayed detached-eddy simulation (DDES), and wall-modeled large-eddy simulation (WMLES) are employed to simulate transonic flow over an NACA-0012, OAT15A airfoils at different angles of attack covering pre- and post-buffet-onset regimes. The freestream Mach number is 0.75, and the Reynolds number based on the chord length is 10 and 3million, respectively. The NASA FUN3D solver is used for the simulations, which is an unstructured, compressible flow solver. The URANS simulations are performed using the Spalart-Allmaras (SA) model with the compressibility correction, the DDES predictions are based on the SA model, and the WMLES are performed using an equilibrium wall-model. The unsteady RANS simulations, only with the compressibility correction, predict the pre- and post- buffet characteristics, which compare well with the experimental results. DDES results predicted a lower buffet onset angle compared to experiment. The predicted shock locations are upstream of the locations predicted by URANS. Using a fine grid in the spanwise direction, WMLES predictions show buffeting consistent with the experiment.

Computational Fluid Dynamics↗
NASA NTRS1992

High-resolution turbulent simulations using the Connection Machine-2

The spectral method provides an efficient algorithm for solving the 3D incompressible Navier-Stokes equations in periodic boundaries. Most people, so far, have used vectorized machines, such as the CRAY-2, to implement fast Fourier transformations and time integrations in the spectral calculations. In this paper, new results are presented using the spectral calculations on the Connection Machine-2 with a parallel algorithm. The large memory of the Connection Machine-2 and the parallel algorithm allows, of the first time, to implement a 512-cubed mesh resolution for high Reynolds number flows. The computational speed of the present code is about 30 percent faster than the fastest CRAY-2 simulations with four processors. Parallel machines, such as the Connection Machine-2, will possibly provide new computational power for understanding the intermittency and cascade mechanism in fluid turbulence.

Chen, Shiyi↗
NASA NTRS1993

Tensoral: A system for post-processing turbulence simulation data

Many computer simulations in engineering and science -- and especially in computational fluid dynamics (CFD) -- produce huge quantities of numerical data. These data are often so large as to make even relatively simple post-processing of this data unwieldy. The data, once computed and quality-assured, is most likely analyzed by only a few people. As a result, much useful numerical data is under-utilized. Since future state-of-the-art simulations will produce even larger datasets, will use more complex flow geometries, and will be performed on more complex supercomputers, data management issues will become increasingly cumbersome. My goal is to provide software which will automate the present and future task of managing and post-processing large turbulence datasets. My research has focused on the development of these software tools -- specifically, through the development of a very high-level language called 'Tensoral'. The ultimate goal of Tensoral is to convert high-level mathematical expressions (tensor algebra, calculus, and statistics) into efficient low-level programs which numerically calculate these expressions given simulation datasets. This approach to the database and post-processing problem has several advantages. Using Tensoral the numerical and data management details of a simulation are shielded from the concerns of the end user. This shielding is carried out without sacrificing post-processor efficiency and robustness. Another advantage of Tensoral is that its very high-level nature lends itself to portability across a wide variety of computing (and supercomputing) platforms. This is especially important considering the rapidity of changes in supercomputing hardware.

Dresselhaus, Eliot↗
NASA NTRS2011

Enhanced Spectral Anisotropies Near the Proton-Cyclotron Scale: Possible Two-Component Structure in Hall-FLR MHD Turbulence Simulations

Recent analysis of the magnetic correlation function of solar wind fluctuations at 1 AU suggests the existence of two-component structure near the proton-cyclotron scale. Here we use two-and-one-half dimensional and three-dimensional compressible MHD models to look for two-component structure adjacent the proton-cyclotron scale. Our MHD system incorporates both Hall and Finite Larmor Radius (FLR) terms. We find that strong spectral anisotropies appear adjacent the proton-cyclotron scales depending on selections of initial condition and plasma beta. These anisotropies are enhancements on top of related anisotropies that appear in standard MHD turbulence in the presence of a mean magnetic field and are suggestive of one turbulence component along the inertial scales and another component adjacent the dissipative scales. We compute the relative strengths of linear and nonlinear accelerations on the velocity and magnetic fields to gauge the relative influence of terms that drive the system with wave-like (linear) versus turbulent (nonlinear) dynamics.

Ghosh, Sanjoy↗
NASA NTRS1980

Verification of interim simulated atmospheric turbulence

During horizontal and near-horizontal flight of the space shuttle orbiter, the effects of atmospheric turbulence on the vehicle are crucial in establishing the space shuttle design, control, and human pilot effects. The effects of both turbulent gusts and gust gradients (shears) must be taken into account. By means of a nonrecursive turbulence simulation model, twelve simulated turbulence time series for gusts and gust gradients were generated as part of a previous investigation. The current investigation was concerned with the spectral analysis of the time series based on the use of Fourier transform theory. A comparison between the computed spectra and the corresponding von Karman theoretical spectra is also included. A basic difference is explained between the computed and theoretical spectra which was identified as a result of the comparison. Conclusions and recommendations are presented.

Tatom, F. B.↗
NASA NTRS1987

Wind shear and turbulence simulation

The aviation community is increasing its reliance on flight simulators. This is true both in pilot training and in research and development. In moving research concepts through the development pipeline, there is a sequence of events which take place: analysis, ground based simulation, inflight simulation, and flight testing. Increasing fidelity as progress toward the flight testing arena is accompanied by increasing cost. The question that seems to be posed in relation to the meteorological aspects of flight simulation is, How much fidelity is enough and can it be quantified. As a part of the Langley Simulation Technology Program, there are three principal areas of focus, one being improved simulation of weather hazards. A close liaison with the JAWS project was established because of the Langley Simulation Technology interests regarding reliable simulation of severe convective weather phenomena and their impact on aviation systems. Simulation offers the only feasible approach for examining the utility of new technology and new procedures for coping with severe convective weather phenomena such as wind shear. These simulation concepts are discussed in detail.

Bowles, Roland L.↗
NASA NTRS2020

Verification of Anisotropic Mesh Adaptation for Turbulent Simulations over ONERA M6 Wing

Unstructured anisotropic mesh adaptation is known to be an efficient way to control discretization errors in Computational Fluid Dynamics (CFD) simulations. Method verification is required to provide the confidence for routine use in production analysis. The current work aims at verification of anisotropic mesh adaptation for RANS simulations over the ONERA M6 wing. The present verification study is performed using four different flow solvers, three different implementations of the metric field, and three mesh mechanics packages. Two of the flow solvers use stabilized finite-element discretizations (FUN3D-SFE and GGNS), one uses finite-volume discretization (FUN3D-FV), and the last one uses mixed finite-volume and finite element discretizations (Wolf). The mesh adaptation is based on an error estimator that aims to control the quadratic error term in the linear interpolation of Mach number. Two sets of adaptations were performed; the first one controls the interpolation error in L2 norm and the second one controls the interpolation error in L4 norm. Convergence studies were performed on the forces and the pitching moment using all four solvers, and the results are compared with previously verified convergence studies on fixed (nonadapted) meshes. Both forces and pitching moment on adapted meshes are found to be converging to the fine mesh values faster than those on fixed meshes. In addition to forces and moments, convergence of surface pressure and skin friction coefficients at various measurement locations on the wing are also presented. Adapted-mesh surface pressure distributions agree with the fine fixed mesh pressure distributions. Adapted-mesh skin friction distributions contain high frequency noise with mean values approaching the fixed mesh pressure skin friction distributions.

Aravind Balan↗
NASA NTRSDate not supplied

Turbulence Simulations of Transonic Flows over an NACA-0012 Airfoil

Three different simulation approaches, namely unsteady Reynolds-averaged Navier-Stokes (URANS), delayed detached-eddy simulation (DDES), and wall-modeled large-eddy simulation (WMLES) are employed to simulate transonic flow over an NACA-0012 airfoil at different angles of attack covering pre- and post-buffet-onset regimes. The freestream Mach number is 0.75, and the Reynolds number based on the chord length is 10 million. These conditions are the same as the wind-tunnel experimental conditions of McDevitt and Okuno (1985). The NASA FUN3D solver is used for the simulations, which is an unstructured, compressible flow solver. The URANS simulations are performed using the Spalart-Allmaras (SA) model with the compressibility correction, the DDES predictions are based on the SA model, and the WMLES are performed using an equilibrium wall-model. The unsteady RANS simulations, only with the compressibility correction, predict the pre- and post- buffet characteristics, which compare well with the experimental results. DDES results predicted a lower buffet onset angle compared to experiment. The predicted shock locations are upstream of the locations predicted by URANS. Using a fine grid in the spanwise direction, WMLES predictions show buffeting consistent with the experiment.

Transonic Buffet↗
NASA NTRSDate not supplied

Turbulence Simulations of Transonic Flows over an NACA-0012 Airfoil

Three different simulation approaches, namely unsteady Reynolds-averaged Navier-Stokes (URANS), delayed detached-eddy simulation (DDES), and wall-modeled large-eddy simulation (WMLES) are employed to simulate transonic flow over an NACA-0012 airfoil at different angles of attack covering pre-and post-buffet-onset regimes. The freestream Mach number is 0.75,and the Reynolds number based on the chord length is 10million. These conditions are the same as the wind-tunnel experimental conditions of McDevitt and Okuno (1985). The NASA FUN3D solver is used for the simulations, which is an unstructured, compressible flow solver. The URANS simulations are performed using the Spalart-Allmaras (SA) model with the compressibility correction, the DDES predictions are based on the SA model, and the WMLES are performed using an equilibrium wall-model. The unsteady RANS simulations, only with the compressibility correction, predict the pre-and post-buffet characteristics, which compare well with the experimental results. DDES results predicted a lower buffet onset angle compared to experiment. The predicted shock locations are upstream of the locations predicted by URANS. Using a fine grid in the span wise direction, WMLES predictions show buffeting consistent with the experiment.

Transonic Buffet↗