29 research outputs found
Modeling of an Atmospheric-Boundary-Layer Profile in Support of Experiments in the NASA Langley Transonic Dynamics Tunnel
This paper presents the results of the Computational Fluid Dynamics (CFD) analyses to model two atmospheric-boundary-layer (ABL) profiles inside the NASA Langley Research Center Transonic Dynamics Tunnel (TDT). The CFD models include tunnel walls and all additional hardware needed to simulate the ABL profiles. This hardware includes Irwin spires and floor-mounted roughness elements. The numerical simulations show that the application of higher-fidelity numerical methods is necessary to compute boundary-layer and turbulenceintensity profiles that match experimental data. The ABL profiles are computed both inside the numerical model of the TDT and in a classical free-air model. Both Unsteady Reynolds Averaged Navier-Stokes (URANS) with Spalart-Allmaras (SA) turbulence model and Modified Delayed Detached Eddy (MDDES) simulation methods are used. The results show that the MDDES-simulation results match the experimental data very well while URANS-SA does not. The results also show that the wind-tunnel walls have a significant effect on ABL prediction
Computational Aeroelastic Analysis of Ares Crew Launch Vehicle Bi-Modal Loading
A Reynolds averaged Navier-Stokes analysis, with and without dynamic aeroelastic effects, is presented for the Ares I-X launch vehicle at transonic Mach numbers and flight Reynolds numbers for two grid resolutions and two angles of attack. The purpose of the study is to quantify the force and moment increment imparted by the sudden transition from fully separated flow around the crew module - service module junction to that of the bi-modal flow state in which only part of the flow reattaches. The bi-modal flow phenomenon is of interest to the guidance, navigation and control community because it causes a discontinuous jump in forces and moments. Computations with a rigid structure at zero zero angle of attack indicate significant increases in normal force and pitching moment. Dynamic aeroelastic computations indicate the bi-modal flow state is insensitive to vehicle flexibility due to the resulting deflections imparting only very small changes in local angle of attack. At an angle of attack of 2.5deg, the magnitude of the pitching moment increment resulting from the bi-modal state nearly triples, while occurring at a slightly lower Mach number. Significant grid induced variations between the solutions indicate that further grid refinement is warranted
Overview of the Aeroelastic Prediction Workshop
The AIAA Aeroelastic Prediction Workshop (AePW) was held in April, 2012, bringing together communities of aeroelasticians and computational fluid dynamicists. The objective in conducting this workshop on aeroelastic prediction was to assess state-of-the-art computational aeroelasticity methods as practical tools for the prediction of static and dynamic aeroelastic phenomena. No comprehensive aeroelastic benchmarking validation standard currently exists, greatly hindering validation and state-of-the-art assessment objectives. The workshop was a step towards assessing the state of the art in computational aeroelasticity. This was an opportunity to discuss and evaluate the effectiveness of existing computer codes and modeling techniques for unsteady flow, and to identify computational and experimental areas needing additional research and development. Three configurations served as the basis for the workshop, providing different levels of geometric and flow field complexity. All cases considered involved supercritical airfoils at transonic conditions. The flow fields contained oscillating shocks and in some cases, regions of separation. The computational tools principally employed Reynolds-Averaged Navier Stokes solutions. The successes and failures of the computations and the experiments are examined in this paper
Computational Analysis of the Transonic Dynamics Tunnel Using FUN3D
This paper presents results from an exploratory two-year effort of applying Computational Fluid Dynamics (CFD) to analyze the empty-tunnel flow in the NASA Langley Research Center Transonic Dynamics Tunnel (TDT). The TDT is a continuous-flow, closed circuit, 16- x 16-foot slotted-test-section wind tunnel, with capabilities to use air or heavy gas as a working fluid. In this study, experimental data acquired in the empty tunnel using the R-134a test medium was used to calibrate the computational data. The experimental calibration data includes wall pressures, boundary-layer profiles, and the tunnel centerline Mach number profiles. Subsonic and supersonic flow regimes were considered, focusing on Mach 0.5, 0.7 and Mach 1.1 in the TDT test section. This study discusses the computational domain, boundary conditions, and initial conditions selected and the resulting steady-state analyses using NASA's FUN3D CFD software
Aeroelasticity Benchmark Assessment: Subsonic Fixed Wing Program
The fundamental technical challenge in computational aeroelasticity is the accurate prediction of unsteady aerodynamic phenomena and the effect on the aeroelastic response of a vehicle. Currently, a benchmarking standard for use in validating the accuracy of computational aeroelasticity codes does not exist. Many aeroelastic data sets have been obtained in wind-tunnel and flight testing throughout the world; however, none have been globally presented or accepted as an ideal data set. There are numerous reasons for this. One reason is that often, such aeroelastic data sets focus on the aeroelastic phenomena alone (flutter, for example) and do not contain associated information such as unsteady pressures and time-correlated structural dynamic deflections. Other available data sets focus solely on the unsteady pressures and do not address the aeroelastic phenomena. Other discrepancies can include omission of relevant data, such as flutter frequency and / or the acquisition of only qualitative deflection data. In addition to these content deficiencies, all of the available data sets present both experimental and computational technical challenges. Experimental issues include facility influences, nonlinearities beyond those being modeled, and data processing. From the computational perspective, technical challenges include modeling geometric complexities, coupling between the flow and the structure, grid issues, and boundary conditions. The Aeroelasticity Benchmark Assessment task seeks to examine the existing potential experimental data sets and ultimately choose the one that is viewed as the most suitable for computational benchmarking. An initial computational evaluation of that configuration will then be performed using the Langley-developed computational fluid dynamics (CFD) software FUN3D1 as part of its code validation process. In addition to the benchmarking activity, this task also includes an examination of future research directions. Researchers within the Aeroelasticity Branch will examine other experimental efforts within the Subsonic Fixed Wing (SFW) program (such as testing of the NASA Common Research Model (CRM)) and other NASA programs and assess aeroelasticity issues and research topics
Analysis of Test Case Computations and Experiments for the First Aeroelastic Prediction Workshop
This paper compares computational and experimental data from the Aeroelastic Prediction Workshop (AePW) held in April 2012. This workshop was designed as a series of technical interchange meetings to assess the state of the art of computational methods for predicting unsteady flowfields and static and dynamic aeroelastic response. The goals are to provide an impartial forum to evaluate the effectiveness of existing computer codes and modeling techniques to simulate aeroelastic problems and to identify computational and experimental areas needing additional research and development. Three subject configurations were chosen from existing wind-tunnel data sets where there is pertinent experimental data available for comparison. Participant researchers analyzed one or more of the subject configurations, and results from all of these computations were compared at the workshop
Computational Aeroelastic Analyses of a Low-Boom Supersonic Configuration
An overview of NASA's Commercial Supersonic Technology (CST) Aeroservoelasticity (ASE) element is provided with a focus on recent computational aeroelastic analyses of a low-boom supersonic configuration developed by Lockheed-Martin and referred to as the N+2 configuration. The overview includes details of the computational models developed to date including a linear finite element model (FEM), linear unsteady aerodynamic models, unstructured CFD grids, and CFD-based aeroelastic analyses. In addition, a summary of the work involving the development of aeroelastic reduced-order models (ROMs) and the development of an aero-propulso-servo-elastic (APSE) model is provided
Structural Dynamics Modeling of HIRENASD in Support of the Aeroelastic Prediction Workshop
An Aeroelastic Prediction Workshop (AePW) was held in April 2012 using three aeroelasticity case study wind tunnel tests for assessing the capabilities of various codes in making aeroelasticity predictions. One of these case studies was known as the HIRENASD model that was tested in the European Transonic Wind Tunnel (ETW). This paper summarizes the development of a standardized enhanced analytical HIRENASD structural model for use in the AePW effort. The modifications to the HIRENASD finite element model were validated by comparing modal frequencies, evaluating modal assurance criteria, comparing leading edge, trailing edge and twist of the wing with experiment and by performing steady and unsteady CFD analyses for one of the test conditions on the same grid, and identical processing of results
A Summary of Data and Findings from the First Aeroelastic Prediction Workshop
This paper summarizes data and findings from the first Aeroelastic Prediction Workshop (AePW) held in April, 2012. The workshop has been designed as a series of technical interchange meetings to assess the state of the art of computational methods for predicting unsteady flowfields and static and dynamic aeroelastic response. The goals are to provide an impartial forum to evaluate the effectiveness of existing computer codes and modeling techniques to simulate aeroelastic problems, and to identify computational and experimental areas needing additional research and development. For this initial workshop, three subject configurations have been chosen from existing wind tunnel data sets where there is pertinent experimental data available for comparison. Participant researchers analyzed one or more of the subject configurations and results from all of these computations were compared at the workshop. Keywords: Unsteady Aerodynamics, Aeroelasticity, Computational Fluid Dynamics, Transonic Flow, Separated Flow
FUN3D Analyses in Support of the First Aeroelastic Prediction Workshop
This paper presents the computational aeroelastic results generated in support of the first Aeroelastic Prediction Workshop for the Benchmark Supercritical Wing (BSCW) and the HIgh REynolds Number AeroStructural Dynamics (HIRENASD) configurations and compares them to the experimental data. The computational results are obtained using FUN3D, an unstructured grid Reynolds-averaged Navier-Stokes solver developed at NASA Langley Research Center. The analysis results for both configurations include aerodynamic coefficients and surface pressures obtained for steady-state or static aeroelastic equilibrium (BSCW and HIRENASD, respectively) and for unsteady flow due to a pitching wing (BSCW) or modally-excited wing (HIRENASD). Frequency response functions of the pressure coefficients with respect to displacement are computed and compared with the experimental data. For the BSCW, the shock location is computed aft of the experimentally-located shock position. The pressure distribution upstream of this shock is in excellent agreement with the experimental data, but the pressure downstream of the shock in the separated flow region does not match as well. For HIRENASD, very good agreement between the numerical results and the experimental data is observed at the mid-span wing locations