Engineering topics

Florance, Jennifer P.

Publications and source records attributed to Florance, Jennifer P..

9 records

NASA NTRS2013

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.

Chwalowski, Pawel↗

NASA NTRS2013

Overview of the Aeroelastic Prediction Workshop

The Aeroelastic Prediction Workshop brought together an international community of computational fluid dynamicists as a step in defining the state of the art in computational aeroelasticity. This workshop's technical focus was prediction of unsteady pressure distributions resulting from forced motion, benchmarking the results first using unforced system data. The most challenging aspects of the physics were identified as capturing oscillatory shock behavior, dynamic shock-induced separated flow and tunnel wall boundary layer influences. The majority of the participants used unsteady Reynolds-averaged Navier Stokes codes. These codes were exercised at transonic Mach numbers for three configurations and comparisons were made with existing experimental data. Substantial variations were observed among the computational solutions as well as differences relative to the experimental data. Contributing issues to these differences include wall effects and wall modeling, non-standardized convergence criteria, inclusion of static aeroelastic deflection, methodology for oscillatory solutions, post-processing methods. Contributing issues pertaining principally to the experimental data sets include the position of the model relative to the tunnel wall, splitter plate size, wind tunnel expansion slot configuration, spacing and location of pressure instrumentation, and data processing methods.

Heeg, Jennifer↗

NASA NTRS2013

Lessons Learned in the Selection and Development of Test Cases for the Aeroelastic Prediction Workshop: Rectangular Supercritical Wing

The Aeroelastic Prediction Workshop brought together an international community of computational fluid dynamicists as a step in defining the state of the art in computational aeroelasticity. The Rectangular Supercritical Wing (RSW) was chosen as the first configuration to study due to its geometric simplicity, perceived simple flow field at transonic conditions and availability of an experimental data set containing forced oscillation response data. Six teams performed analyses of the RSW; they used Reynolds-Averaged Navier-Stokes flow solvers exercised assuming that the wing had a rigid structure. Both steady-state and forced oscillation computations were performed by each team. The results of these calculations were compared with each other and with the experimental data. The steady-state results from the computations capture many of the flow features of a classical supercritical airfoil pressure distribution. The most dominant feature of the oscillatory results is the upper surface shock dynamics. Substantial variations were observed among the computational solutions as well as differences relative to the experimental data. Contributing issues to these differences include substantial wind tunnel wall effects and diverse choices in the analysis parameters.

Heeg, Jennifer↗

NASA NTRS2011

Plans for Aeroelastic Prediction Workshop

This paper summarizes the plans for the first Aeroelastic Prediction Workshop. The workshop is designed to assess the state of the art of computational methods for predicting unsteady flow fields and aeroelastic response. The goals are to provide an impartial forum to evaluate the effectiveness of existing computer codes and modeling techniques, and to identify computational and experimental areas needing additional research and development. Three subject configurations have been chosen from existing wind tunnel data sets where there is pertinent experimental data available for comparison. For each case chosen, the wind tunnel testing was conducted using forced oscillation of the model at specified frequencies

Heeg, Jennifer↗

NASA NTRS2011

Preliminary Computational Analysis of the (HIRENASD) Configuration in Preparation for the Aeroelastic Prediction Workshop

This paper presents preliminary computational aeroelastic analysis results generated in preparation for the first Aeroelastic Prediction Workshop (AePW). These results were produced using FUN3D software developed at NASA Langley and are compared against the experimental data generated during the HIgh REynolds Number Aero- Structural Dynamics (HIRENASD) Project. The HIRENASD wind-tunnel model was tested in the European Transonic Windtunnel in 2006 by Aachen University0s Department of Mechanics with funding from the German Research Foundation. The computational effort discussed here was performed (1) to obtain a preliminary assessment of the ability of the FUN3D code to accurately compute physical quantities experimentally measured on the HIRENASD model and (2) to translate the lessons learned from the FUN3D analysis of HIRENASD into a set of initial guidelines for the first AePW, which includes test cases for the HIRENASD model and its experimental data set. This paper compares the computational and experimental results obtained at Mach 0.8 for a Reynolds number of 7 million based on chord, corresponding to the HIRENASD test conditions No. 132 and No. 159. Aerodynamic loads and static aeroelastic displacements are compared at two levels of the grid resolution. Harmonic perturbation numerical results are compared with the experimental data using the magnitude and phase relationship between pressure coefficients and displacement. A dynamic aeroelastic numerical calculation is presented at one wind-tunnel condition in the form of the time history of the generalized displacements. Additional FUN3D validation results are also presented for the AGARD 445.6 wing data set. This wing was tested in the Transonic Dynamics Tunnel and is commonly used in the preliminary benchmarking of computational aeroelastic software.

Chwalowski, Pawel↗

NASA NTRS2010

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.

Florance, Jennifer P.↗

NASA NTRS2005

Trailing Edge Blowing on a Two-Dimensional Six-Percent Thick Elliptical Circulation Control Airfoil Up to Transonic Conditions

A wind tunnel test was conducted in the NASA Langley Transonic Dynamics Tunnel (TDT) on a six percent thick slightly cambered elliptical circulation control airfoil with both upper and lower surface blowing capability. Parametric evaluations of jet slot heights and Coanda surface shapes were conducted at momentum coefficients (Cm) from 0.0 to 0.12. Test data were acquired at Mach numbers of 0.3, 0.5, 0.7, 0.8, and 0.84 at Reynolds numbers per foot of 2.43 x 105 to 1.05 x 106. For a transonic condition, (Mach = 0.8 at alpha = 3 degrees), it was generally found the smaller slot and larger Coanda surface combination was overall more effective than other slot/Coanda surface combinations. Lower surface blowing was not as effective as the upper surface blowing over the same range of momentum coefficients. No appreciable Coanda surface, slot height, or slot blowing position preference was indicated transonically with the dual slot blowing.

Alexander, Michael G.↗

NASA NTRS2003

Test Activities in the Langley Transonic Dynamics Tunnel and a Summary of Recent Facility Improvements

The Langley Transonic Dynamics Tunnel (TDT) has provided a unique capability for aeroelastic testing for over forty years. The facility has a rich history of significant contributions to the design of many United States commercial transports, military aircraft, launch vehicles, and spacecraft. The facility has many features that contribute to its uniqueness for aeroelasticity testing, perhaps the most important feature being the use of a heavy gas test medium to achieve higher test densities compared to testing in air. Higher test medium densities substantially improve model-building requirements and therefore simplify the fabrication process for building aeroelastically scaled wind tunnel models. This paper describes TDT capabilities that make it particularly suited for aeroelasticity testing. The paper also discusses the nature of recent test activities in the TDT, including summaries of several specific tests. Finally, the paper documents recent facility improvement projects and the continuous statistical quality assessment effort for the TDT.

Cole, Stanley R.↗

NASA NTRS2003

Contributions of the NASA Langley Research Center to the DARPA/AFRL/NASA/ Northrop Grumman Smart Wing Program

An overview of the contributions of the NASA Langley Research Center (LaRC) to the DARPA/AFRL/NASA/ Northrop Grumman Corporation (NGC) Smart Wing program is presented. The overall objective of the Smart Wing program was to develop smart** technologies and demonstrate near-flight-scale actuation systems to improve the aerodynamic performance of military aircraft. NASA LaRC s roles were to provide technical guidance, wind-tunnel testing time and support, and Computational Fluid Dynamics (CFD) analyses. The program was divided into two phases, with each phase having two wind-tunnel entries in the Langley Transonic Dynamics Tunnel (TDT). This paper focuses on the fourth and final wind-tunnel test: Phase 2, Test 2. During this test, a model based on the NGC Unmanned Combat Air Vehicle (UCAV) concept was tested at Mach numbers up to 0.8 and dynamic pressures up to 150 psf to determine the aerodynamic performance benefits that could be achieved using hingeless, smoothly-contoured control surfaces actuated with smart materials technologies. The UCAV-based model was a 30% geometric scale, full-span, sting-mounted model with the smart control surfaces on the starboard wing and conventional, hinged control surfaces on the port wing. Two LaRC-developed instrumentation systems were used during the test to externally measure the shapes of the smart control surface and quantify the effects of aerodynamic loading on the deflections: Videogrammetric Model Deformation (VMD) and Projection Moire Interferometry (PMI). VMD is an optical technique that uses single-camera photogrammetric tracking of discrete targets to determine deflections at specific points. PMI provides spatially continuous measurements of model deformation by computationally analyzing images of a grid projected onto the model surface. Both the VMD and PMI measurements served well to validate the use of on-board (internal) rotary potentiometers to measure the smart control surface deflection angles. Prior to the final entry, NASA LaRC also performed three-dimensional unstructured Navier Stokes CFD analyses in an attempt to predict the potential aerodynamic impact of the smart control surface on overall model forces and moments. Eight different control surface shapes were selected for study at Mach = 0.6, Reynolds number = 3.25 x 10(exp 6), and + 2 deg., 3 deg., 8 deg., and 10 deg.model angles-of-attack. For the baseline, undeflected control surface geometry, the CFD predictions and wind-tunnel results matched well. The agreement was not as good for the more complex aero-loaded control surface shapes, though, because of the inability to accurately predict those shapes. Despite these results, the NASA CFD study served as an important step in studying advanced control effectors.

Florance, Jennifer P.↗