Analysis of Factors Affecting Net Lift Increment Attainable with Trailing-Edge Split Flaps on Tailless Airplanes
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WINGS, TAPERED↗
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Results for “Lift coefficient”
Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.
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Lift Tests of a 0.1536c Thick Douglas Airfoil Section of NACA 7-Series Type Equipped with a Lateral-Control Device for Use with a Full-Span Double-Slotted Flap on the C-74 Airplane
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AIRPLANES - RANGE, LONG↗
Some Effects of Reynolds and Mach Numbers on the Lift of an NACA 0012 Rectangular Wing in the NACA 19-Foot Pressure Tunnel
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MACH NUMBER↗
Investigation of Effects of Various Camouflage Paints and Painting Procedures on the Drag Characteristics of an NACA 65(sub 421)-420, a = 1.0 Airfoil Section
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REYNOLDS NUMBER↗
A longitudinal aerodynamic data repeatability study for a commercial transport model test in the National Transonic Facility
A high Reynolds number investigation of a commercial transport model was conducted in the National Transonic Facility (NTF) at Langley Research Center. This investigation was part of a cooperative effort to test a 0.03-scale model of a Boeing 767 airplane in the NTF over a Mach number range of 0.70 to 0.86 and a Reynolds number range of 2.38 to 40.0 x 10(exp 6) based on the mean aerodynamic chord. One of several specific objectives of the current investigation was to evaluate the level of data repeatability attainable in the NTF. Data repeatability studies were performed at a Mach number of 0.80 with Reynolds numbers of 2.38, 4.45, and 40.0 x 10(exp 6) and also at a Mach number of 0.70 with a Reynolds number of 40.0 x 10(exp 6). Many test procedures and data corrections are addressed in this report, but the data presented do not include corrections for wall interference, model support interference, or model aeroelastic effects. Application of corrections for these three effects would not affect the results of this study because the corrections are systematic in nature and are more appropriately classified as sources of bias error. The repeatability of the longitudinal stability-axis force and moment data has been accessed. Coefficients of lift, drag, and pitching moment are shown to repeat well within the pretest goals of plus or minus 0.005, plus or minus 0.0001, and plus or minus 0.001, respectively, at a 95-percent confidence level over both short- and near-term periods.
Wahls, R. A.↗
An Efficient Multiblock Method for Aerodynamic Analysis and Design on Distributed Memory Systems
The work presented in this paper describes the application of a multiblock gridding strategy to the solution of aerodynamic design optimization problems involving complex configurations. The design process is parallelized using the MPI (Message Passing Interface) Standard such that it can be efficiently run on a variety of distributed memory systems ranging from traditional parallel computers to networks of workstations. Substantial improvements to the parallel performance of the baseline method are presented, with particular attention to their impact on the scalability of the program as a function of the mesh size. Drag minimization calculations at a fixed coefficient of lift are presented for a business jet configuration that includes the wing, body, pylon, aft-mounted nacelle, and vertical and horizontal tails. An aerodynamic design optimization is performed with both the Euler and Reynolds Averaged Navier-Stokes (RANS) equations governing the flow solution and the results are compared. These sample calculations establish the feasibility of efficient aerodynamic optimization of complete aircraft configurations using the RANS equations as the flow model. There still exists, however, the need for detailed studies of the importance of a true viscous adjoint method which holds the promise of tackling the minimization of not only the wave and induced components of drag, but also the viscous drag.
Reuther, James↗
Neural Network Prediction of New Aircraft Design Coefficients
This paper discusses a neural network tool for more effective aircraft design evaluations during wind tunnel tests. Using a hybrid neural network optimization method, we have produced fast and reliable predictions of aerodynamical coefficients, found optimal flap settings, and flap schedules. For validation, the tool was tested on a 55% scale model of the USAF/NASA Subsonic High Alpha Research Concept aircraft (SHARC). Four different networks were trained to predict coefficients of lift, drag, moment of inertia, and lift drag ratio (C(sub L), C(sub D), C(sub M), and L/D) from angle of attack and flap settings. The latter network was then used to determine an overall optimal flap setting and for finding optimal flap schedules.
Norgaard, Magnus↗
Effects of Outboard Thickened and Blunted Leading Edges on the Wave Drag of a 45 Degree Swept-Wing and Body Combination
An investigation to evaluate the effects of thickened and blunted leading-edge modifications on the wave drag of a swept wing has been made at Mach numbers from 0.65 to 2.20 and at a Reynolds number of 2,580,000 based on the mean aerodynamic chord of the basic wing. Two leading-edge designs were investigated and they are referred to as the thickened and the blunted modifications although both sections had equally large leading-edge radii. The thickened leading edge was formed by increasing the thickness over the forward 40 percent of the basic wing section. The blunted modification was formed by reducing the wing chords about 1 percent and by increasing the section thickness slightly over the forward 6 percent of the basic section in a manner to keep the wing sweep and volume essentially equal to the respective values for the basic wing. The basic wing had an aspect ratio of 3, a leading-edge sweep of 45 deg., a taper ratio of 0.4, and NACA 64AO06 sections perpendicular to a line swept back 39.45 deg., the quarter-chord line of these sections. Test results indicated that the thickened modification resulted in an increase in zero-lift drag coefficient of from 0.0040 to 0.0060 over values for the basic model at Mach numbers at which the wing leading edge was sonic or supersonic. Although drag coefficients of both the basic and thickened models were reduced at all test Mach numbers by body indentations designed for the range of Mach numbers from 1.00 to 2.00, the greater drag of the thickened model relative to that of the basic model was not reduced. The blunted model, however, had less than one quarter of the drag penalty of the thickened model relative to the basic model at supersonic leading-edge conditions (M greater or equal to root-2).
Holdaway, George H.↗
Prediction of Aerodynamic Coefficients using Neural Networks for Sparse Data
Basic aerodynamic coefficients are modeled as functions of angles of attack and sideslip with vehicle lateral symmetry and compressibility effects. Most of the aerodynamic parameters can be well-fitted using polynomial functions. In this paper a fast, reliable way of predicting aerodynamic coefficients is produced using a neural network. The training data for the neural network is derived from wind tunnel test and numerical simulations. The coefficients of lift, drag, pitching moment are expressed as a function of alpha (angle of attack) and Mach number. The results produced from preliminary neural network analysis are very good.
Rajkumar, T.↗
Prediction of Aerodynamic Coefficients for Wind Tunnel Data using a Genetic Algorithm Optimized Neural Network
A fast, reliable way of predicting aerodynamic coefficients is produced using a neural network optimized by a genetic algorithm. Basic aerodynamic coefficients (e.g. lift, drag, pitching moment) are modelled as functions of angle of attack and Mach number. The neural network is first trained on a relatively rich set of data from wind tunnel tests of numerical simulations to learn an overall model. Most of the aerodynamic parameters can be well-fitted using polynomial functions. A new set of data, which can be relatively sparse, is then supplied to the network to produce a new model consistent with the previous model and the new data. Because the new model interpolates realistically between the sparse test data points, it is suitable for use in piloted simulations. The genetic algorithm is used to choose a neural network architecture to give best results, avoiding over-and under-fitting of the test data.
Rajkumar, T.↗
Navier-Stokes Solutions about the F/A-18 Forebody-LEX Configuration
Three-dimensional viscous flow computations are presented for the F/A-18 forebody-LEX geometry. Solutions are obtained from an algorithm for the compressible Navier-Stokes equations which incorporates an upwind-biased, flux-difference-splitting approach along with longitudinally-patched grids. Results are presented for both laminar and fully turbulent flow assumptions and include correlations with wind tunnel as well as flight-test results. A good quantitative agreement for the forebody surface pressure distribution is achieved between the turbulent computations and wind tunnel measurements at Mach number of 0.6. The computed turbulent surface flow patterns on the forebody qualitatively agree well with in-flight surface flow patterns obtained on an F/A-fS aircraft at Mach number of 0.34.
Transitional flow↗
Automated CFD for Generation of Airfoil Performance Tables
A method of automated computational fluid dynamics (CFD) has been invented for the generation of performance tables for an object subject to fluid flow. The method is applicable to the generation of tables that summarize the effects of two-dimensional flows about airfoils and that are in a format known in the art as C81. (A C81 airfoil performance table is a text file that lists coefficients of lift, drag, and pitching moment of an airfoil as functions of angle of attack for a range of Mach numbers.) The method makes it possible to efficiently generate and tabulate data from simulations of flows for parameter values spanning all operational ranges of actual or potential interest. In so doing, the method also enables filling of gaps and resolution of inconsistencies in C81 tables generated previously from incomplete experimental data or from theoretical calculations that involved questionable assumptions.
Strawn, Roger↗
Statistical Analysis of CFD Solutions from the Fourth AIAA Drag Prediction Workshop
A graphical framework is used for statistical analysis of the results from an extensive N-version test of a collection of Reynolds-averaged Navier-Stokes computational fluid dynamics codes. The solutions were obtained by code developers and users from the U.S., Europe, Asia, and Russia using a variety of grid systems and turbulence models for the June 2009 4th Drag Prediction Workshop sponsored by the AIAA Applied Aerodynamics Technical Committee. The aerodynamic configuration for this workshop was a new subsonic transport model, the Common Research Model, designed using a modern approach for the wing and included a horizontal tail. The fourth workshop focused on the prediction of both absolute and incremental drag levels for wing-body and wing-body-horizontal tail configurations. This work continues the statistical analysis begun in the earlier workshops and compares the results from the grid convergence study of the most recent workshop with earlier workshops using the statistical framework.
Statistical analysis↗
Statistical Analysis of CFD Solutions From the Fifth AIAA Drag Prediction Workshop
A graphical framework is used for statistical analysis of the results from an extensive N-version test of a collection of Reynolds-averaged Navier-Stokes computational fluid dynamics codes. The solutions were obtained by code developers and users from North America, Europe, Asia, and South America using a common grid sequence and multiple turbulence models for the June 2012 fifth Drag Prediction Workshop sponsored by the AIAA Applied Aerodynamics Technical Committee. The aerodynamic configuration for this workshop was the Common Research Model subsonic transport wing-body previously used for the 4th Drag Prediction Workshop. This work continues the statistical analysis begun in the earlier workshops and compares the results from the grid convergence study of the most recent workshop with previous workshops.
Statistical analysis↗
Observations on CFD Verification and Validation from the AIAA Drag Prediction Workshops
The authors provide observations from the AIAA Drag Prediction Workshops that have spanned over a decade and from a recent validation experiment at NASA Langley. These workshops provide an assessment of the predictive capability of forces and moments, focused on drag, for transonic transports. It is very difficult to manage the consistency of results in a workshop setting to perform verification and validation at the scientific level, but it may be sufficient to assess it at the level of practice. Observations thus far: 1) due to simplifications in the workshop test cases, wind tunnel data are not necessarily the “correct” results that CFD should match, 2) an average of core CFD data are not necessarily a better estimate of the true solution as it is merely an average of other solutions and has many coupled sources of variation, 3) outlier solutions should be investigated and understood, and 4) the DPW series does not have the systematic build up and definition on both the computational and experimental side that is required for detailed verification and validation. Several observations regarding the importance of the grid, effects of physical modeling, benefits of open forums, and guidance for validation experiments are discussed. The increased variation in results when predicting regions of flow separation and increased variation due to interaction effects, e.g., fuselage and horizontal tail, point out the need for validation data sets for these important flow phenomena. Experiences with a recent validation experiment at NASA Langley are included to provide guidance on validation experiments.
Computational Fluid Dynamics↗
Enabling Electric Propulsion for Flight
Description of current ARMD projects; Team Seedling project AFRC and LaRC 31ft distributed electric propulsion wing on truck bed up 75 miles per hour for coefficient of lift validation. Convergent Aeronautic Solutions project (new ARMD reorg), sub-project Convergent Electric Propulsion Technologies AFRC, LaRC and GRC, re-winging a 4 passenger Tecnam aircraft with a 31ft distributed electric propulsion wing. Advanced Air Transport Technologies (Fixed Wing), Hybrid Electric Research Theme, developing a series hybrid ironbird and flight sim to study integration and performance challenges in preparation for a 1-2 MW flight project.
flight research↗
Computational Aerodynamic Analysis of Three-Dimensional Ice Shapes on a NACA 23012 Airfoil
The present study identifies a process for performing computational fluid dynamic calculations of the flow over full three-dimensional (3D) representations of complex ice shapes deposited on aircraft surfaces. Rime and glaze icing geometries formed on a NACA23012 airfoil were obtained during testing in the NASA Glenn Research Center's Icing Research Tunnel (IRT). The ice shape geometries were scanned as a cloud of data points using a 3D laser scanner. The data point clouds were meshed using Geomagic software to create highly accurate models of the ice surface. The surface data was imported into Pointwise grid generation software to create the CFD surface and volume grids. It was determined that generating grids in Pointwise for complex 3D icing geometries was possible using various techniques that depended on the ice shape. Computations of the flow fields over these ice shapes were performed using the NASA National Combustion Code (NCC). Results for a rime ice shape for angle of attack conditions ranging from 0 to 10 degrees and for freestream Mach numbers of 0.10 and 0.18 are presented. For validation of the computational results, comparisons were made to test results from rapid-prototype models of the selected ice accretion shapes, obtained from a separate study in a subsonic wind tunnel at the University of Illinois at Urbana-Champaign. The computational and experimental results were compared for values of pressure coefficient and lift. Initial results show fairly good agreement for rime ice accretion simulations across the range of conditions examined. The glaze ice results are promising but require some further examination.
Aerodynamics↗
Computational Aerodynamic Analysis of Three-Dimensional Ice Shapes on a NACA 23012 Airfoil
The present study identifies a process for performing computational fluid dynamic calculations of the flow over full three-dimensional (3D) representations of complex ice shapes deposited on aircraft surfaces. Rime and glaze icing geometries formed on a NACA23012 airfoil were obtained during testing in the NASA Glenn Research Centers Icing Research Tunnel (IRT). The ice shape geometries were scanned as a cloud of data points using a 3D laser scanner. The data point clouds were meshed using Geomagic software to create highly accurate models of the ice surface. The surface data was imported into Pointwise grid generation software to create the CFD surface and volume grids. It was determined that generating grids in Pointwise for complex 3D icing geometries was possible using various techniques that depended on the ice shape. Computations of the flow fields over these ice shapes were performed using the NASA National Combustion Code (NCC). Results for a rime ice shape for angle of attack conditions ranging from 0 to 10 degrees and for freestream Mach numbers of 0.10 and 0.18 are presented. For validation of the computational results, comparisons were made to test results from rapid-prototype models of the selected ice accretion shapes, obtained from a separate study in a subsonic wind tunnel at the University of Illinois at Urbana-Champaign. The computational and experimental results were compared for values of pressure coefficient and lift. Initial results show fairly good agreement for rime ice accretion simulations across the range of conditions examined. The glaze ice results are promising but require some further examination.
Aerodynamics↗