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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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At least 253 records · Page 14
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NASA NTRS1996

User's Guide for MSAP2D: A Program for Unsteady Aerodynamic and Aeroelastic (Flutter and Forced Response) Analysis of Multistage Compressors and Turbines

This guide describes the input data required for using MSAP2D (Multi Stage Aeroelastic analysis Program - Two Dimensional) computer code. MSAP2D can be used for steady, unsteady aerodynamic, and aeroelastic (flutter and forced response) analysis of bladed disks arranged in multiple blade rows such as those found in compressors, turbines, counter rotating propellers or propfans. The code can also be run for single blade row. MSAP2D code is an extension of the original NPHASE code for multiblade row aerodynamic and aeroelastic analysis. Euler equations are used to obtain aerodynamic forces. The structural dynamic equations are written for a rigid typical section undergoing pitching (torsion) and plunging (bending) motion. The aeroelastic equations are solved in time domain. For single blade row analysis, frequency domain analysis is also provided to obtain unsteady aerodynamic coefficients required in an eigen analysis for flutter. In this manual, sample input and output are provided for a single blade row example, two blade row example with equal and unequal number of blades in the blade rows.

Reddy, T. S. R.↗
NASA NTRSDate not supplied

Flutter Prediction Report in Support of the High Angle Working Group at the Third Aeroelastic Prediction Workshop

This paper presents a summary of the computational flutter results associated with the AIAA third Aeroelastic Prediction Workshop (AePW-3) High Angle Working Group (HAWG). The computational results are compared against the experimental data collected during the Pitch and Plunge Apparatus (PAPA) Benchmark Supercritical Wing (BSCW) test campaign conducted in the Transonic Dynamics Tunnel (TDT) at NASA Langley Research Center thirty years ago. During that test several flutter points were identified at transonic conditions. One of these points, specifically near Mach 0.8 and 5° angle of attack, became a focal point of the computational challenge with in HAWG. Various fidelity time-domain, Reduced Order Model (ROM) and Linearized Frequency Domain (LFD) methods were used by seven participating teams. While there are encouraging trends in the computational results, the range of the predicted flutter dynamic pressure is still quite large due to the stall flutter mechanism. A description of each participating team’s software and methods is included.

Pawel Chwalowski↗
NASA NTRS1987

Computational methods for unsteady transonic flows

Computational methods for unsteady transonic flows are surveyed with emphasis upon applications to aeroelastic analysis and flutter prediction. Computational difficulty is discussed with respect to type of unsteady flow; attached, mixed (attached/separated) and separated. Significant early computations of shock motions, aileron buzz and periodic oscillations are discussed. The maturation of computational methods towards the capability of treating complete vehicles with reasonable computational resources is noted and a survey of recent comparisons with experimental results is compiled. The importance of mixed attached and separated flow modeling for aeroelastic analysis is discussed and recent calculations of periodic aerodynamic oscillations for an 18 percent thick circular arc airfoil are given.

Edwards, John W.↗
NASA NTRS1975

Static aeroelastic program

Set of programs computes geometric, mass, aerodynamic, and structural effects on fighter and transport type aircraft at subsonic and supersonic speeds.

Roskam, J.↗
NASA NTRS1997

Worst-Case Flutter Margins from F/A-18 Aircraft Aeroelastic Data

An approach for computing worst-case flutter margins has been formulated in a robust stability framework. Uncertainty operators are included with a linear model to describe modeling errors and flight variations. The structured singular value, micron, computes a stability margin which directly accounts for these uncertainties. This approach introduces a new method of computing flutter margins and an associated new parameter for describing these margins. The micron margins are robust margins which indicate worst-case stability estimates with respect to the defined uncertainty. Worst-case flutter margins are computed for the F/A-18 SRA using uncertainty sets generated by flight data analysis. The robust margins demonstrate flight conditions for flutter may lie closer to the flight envelope than previously estimated by p-k analysis.

Lind, Rick↗
NASA NTRS1997

Static Aeroelastic Analysis of Transonic Wind Tunnel Models Using Finite Element Methods

A computational method for accurately predicting the static aeroelastic deformations of typical transonic transport wind tunnel models is described. The method utilizes a finite element method (FEM) for predicting the deformations. Extensive calibration/validation of this method was carried out using a novel wind-off wind tunnel model static loading experiment and wind-on optical wing twist measurements obtained during a recent wind tunnel test in the National Transonic Facility (NTF) at NASA LaRC. Further validations were carried out using a Navier-Stokes computational fluid dynamics (CFD) flow solver to calculate wing pressure distributions about several aeroelastically deformed wings and comparing these predictions with NTF experimental data. Results from this aeroelastic deformation method are in good overall agreement with experimentally measured values. Including the predicted deformations significantly improves the correlation between CFD predicted and experimentally measured wing & pressures.

Hooker, John R.↗
NASA NTRS2012

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.

Schuster, David M.↗
NASA NTRS2006

Analyzing Aeroelastic Stability of a Tilt-Rotor Aircraft

Proprotor Aeroelastic Stability Analysis, now at version 4.5 (PASTA 4.5), is a FORTRAN computer program for analyzing the aeroelastic stability of a tiltrotor aircraft in the airplane mode of flight. The program employs a 10-degree- of-freedom (DOF), discrete-coordinate, linear mathematical model of a rotor with three or more blades and its drive system coupled to a 10-DOF modal model of an airframe. The user can select which DOFs are included in the analysis. Quasi-steady strip-theory aerodynamics is employed for the aerodynamic loads on the blades, a quasi-steady representation is employed for the aerodynamic loads acting on the vibrational modes of the airframe, and a stability-derivative approach is used for the aerodynamics associated with the rigid-body DOFs of the airframe. Blade parameters that vary with the blade collective pitch can be obtained by interpolation from a user-defined table. Stability is determined by examining the eigenvalues that are obtained by solving the coupled equations of motions as a matrix eigenvalue problem. Notwithstanding the relative simplicity of its mathematical foundation, PASTA 4.5 and its predecessors have played key roles in a number of engineering investigations over the years.

Kvaternil, Raymond G.↗
NASA NTRSDate not supplied

Sparse Linear Algebra Toolkit for Computational Aerodynamics

Finding solutions to sparse linear systems of equations is an essential step in Computational Engineering applications of interest to NASA. Linear systems of equations are composed and solved in almost every computational engineering application. The characteristics of linear systems vary greatly from one application to another. Accordingly, there are a wide variety of methods for the solution of linear systems of equations. The operations and methods prepared by the authors are focused on linear systems of interest to NASA, primarily those associated with Computational Fluid Dynamics (CFD), Aeroelasticity, and Aeroacoustics. The Sparse Linear Algebra Toolkit (SLAT) is a coordinated collection of software featuring operations, methods, and data structures that are useful when solving sparse linear systems of equations on modern computer architectures. The implemented operations and methods are designed and tuned for parallelism in shared memory, in distributed memory, and across the hybrid combination of distributed-shared memory. The toolkit includes novel methods and implementations for modern architectures and facilitates development of new approaches for meeting NASA’s evolving computational engineering challenges using evolving computer architectures that are not available in vendor libraries. In this paper, significant features and interfaces within SLAT are presented and verified for simulations performed with NASA’s CFD solver, FUN3D. The runtime and scaling performance of the Generalized Minimum Residual (GMRES) method implemented in SLAT is analyzed for the linear subproblems within the solution of turbulent Navier-Stokes equations employed in the simulation of high-lift configurations. Prior to this work, the SPARSKIT GMRES implementation was the only Krylov subspace method available within FUN3D. A strong scaling study shows the SLAT GMRES implementation facilitates accurate Reynolds-averaged Navier-Stokes CFD solutions between 15% and 56% faster than the SPARSKIT GMRES implementation.

Stephen L Wood↗
NASA NTRS2009

Fan Flutter Computations Using the Harmonic Balance Method

An experimental forward-swept fan encountered flutter at part-speed conditions during wind tunnel testing. A new propulsion aeroelasticity code, based on a computational fluid dynamics (CFD) approach, was used to model the aeroelastic behavior of this fan. This threedimensional code models the unsteady flowfield due to blade vibrations using a harmonic balance method to solve the Navier-Stokes equations. This paper describes the flutter calculations and compares the results to experimental measurements and previous results from a time-accurate propulsion aeroelasticity code.

Bakhle, Milind A.↗
NASA NTRSDate not supplied

Shock-Buffet Prediction Report in Support of the High Angle Working Group at the Third Aeroelastic Prediction Workshop

This paper presents a summary of the computational shock-buffet results associated with the third Aeroelastic Prediction Workshop (AePW-3) High-Angle Working Group. The computational results are compared against experimental data collected during the Oscillating Turn Table (OTT) Benchmark Supercritical Wing (BSCW) test campaign conducted in NASA Langley Research Center Transonic Dynamics Tunnel (TDT) in early 2000. In addition to experimental forced oscillation data, unsteady pressure data was collected at a single spanwise station at transonic Mach numbers, several values of dynamic pressure, and fixed angles of attack. It is acknowledged that the current experimental data are limited, but future experiments are planned to obtain pressure data at two wingspan stations in addition to unsteady Pressure Sensitive Paint (uPSP). With that, the computational results presented here are considered to be semi-blind. The results are presented in the form of time-varying pressure coefficients, running-mean values of the pressure coefficients, Power Spectral Density (PSD) and Strouhal number computations. The results are split into two parts. In the first part, the computational results obtained by each team using their flow solvers and grids are compared. In the second part, a single computational tool was used to compute unsteady pressure on participant-generated grids. In addition, a description of each participating team’s software and methods is included.

Pawel Chwalowski↗
NASA NTRS1981

A hybrid state vector approach to aeroelastic analysis with application to composite lifting surfaces

A computational technique has been developed for performing preliminary design aeroelastic analyses of large aspect ratio lifting surfaces. This technique, applicable to both fixed and rotating wing configurations, is based upon a formulation of the structural equilibrium equations in terms of a hybrid state vector containing generalized force and displacement variables. An integrating matrix is employed to solve these equations for divergence and flutter eigenvalues and steady aeroelastic deformation. Results are presented for simple examples which verify the technique and demonstrate how it can be applied to analyze lifting surfaces, including those constructed from composite materials.

Lehman, L. L.↗
NASA NTRS1991

ASTROP2 users manual: A program for aeroelastic stability analysis of propfans

A user's manual is presented for the aeroelastic stability and response of propulsion systems computer program called ASTROP2. The ASTROP2 code preforms aeroelastic stability analysis of rotating propfan blades. This analysis uses a two-dimensional, unsteady cascade aerodynamics model and a three-dimensional, normal-mode structural model. Analytical stability results from this code are compared with published experimental results of a rotating composite advanced turboprop model and of nonrotating metallic wing model.

Narayanan, G. V.↗
NASA NTRS2005

Twist Model Development and Results From the Active Aeroelastic Wing F/A-18 Aircraft

Understanding the wing twist of the active aeroelastic wing F/A-18 aircraft is a fundamental research objective for the program and offers numerous benefits. In order to clearly understand the wing flexibility characteristics, a model was created to predict real-time wing twist. A reliable twist model allows the prediction of twist for flight simulation, provides insight into aircraft performance uncertainties, and assists with computational fluid dynamic and aeroelastic issues. The left wing of the aircraft was heavily instrumented during the first phase of the active aeroelastic wing program allowing deflection data collection. Traditional data processing steps were taken to reduce flight data, and twist predictions were made using linear regression techniques. The model predictions determined a consistent linear relationship between the measured twist and aircraft parameters, such as surface positions and aircraft state variables. Error in the original model was reduced in some cases by using a dynamic pressure-based assumption and by using neural networks. These techniques produced excellent predictions for flight between the standard test points and accounted for nonlinearities in the data. This report discusses data processing techniques and twist prediction validation, and provides illustrative and quantitative results.

Lizotte, Andrew↗
NASA NTRS2007

Twist Model Development and Results from the Active Aeroelastic Wing F/A-18 Aircraft

Understanding the wing twist of the active aeroelastic wing (AAW) F/A-18 aircraft is a fundamental research objective for the program and offers numerous benefits. In order to clearly understand the wing flexibility characteristics, a model was created to predict real-time wing twist. A reliable twist model allows the prediction of twist for flight simulation, provides insight into aircraft performance uncertainties, and assists with computational fluid dynamic and aeroelastic issues. The left wing of the aircraft was heavily instrumented during the first phase of the active aeroelastic wing program allowing deflection data collection. Traditional data processing steps were taken to reduce flight data, and twist predictions were made using linear regression techniques. The model predictions determined a consistent linear relationship between the measured twist and aircraft parameters, such as surface positions and aircraft state variables. Error in the original model was reduced in some cases by using a dynamic pressure-based assumption. This technique produced excellent predictions for flight between the standard test points and accounted for nonlinearities in the data. This report discusses data processing techniques and twist prediction validation, and provides illustrative and quantitative results.

Lizotte, Andrew M.↗
NASA NTRS2015

Wing Shape Sensing from Measured Strain

A new two-step theory is investigated for predicting the deflection and slope of an entire structure using strain measurements at discrete locations. In the first step, a measured strain is fitted using a piecewise least-squares curve fitting method together with the cubic spline technique. These fitted strains are integrated twice to obtain deflection data along the fibers. In the second step, computed deflection along the fibers are combined with a finite element model of the structure in order to interpolate and extrapolate the deflection and slope of the entire structure through the use of the System Equivalent Reduction and Expansion Process. The theory is first validated on a computational model, a cantilevered rectangular plate wing. The theory is then applied to test data from a cantilevered swept-plate wing model. Computed results are compared with finite element results, results using another strainbased method, and photogrammetry data. For the computational model under an aeroelastic load, maximum deflection errors in the fore and aft, lateral, and vertical directions are -3.2%, 0.28%, and 0.09%, respectively; and maximum slope errors in roll and pitch directions are 0.28% and -3.2%, respectively. For the experimental model, deflection results at the tip are shown to be accurate to within 3.8% of the photogrammetry data and are accurate to within 2.2% in most cases. In general, excellent matching between target and computed values are accomplished in this study. Future refinement of this theory will allow it to monitor the deflection and health of an entire aircraft in real time, allowing for aerodynamic load computation, active flexible motion control, and active induced drag reduction.

shape sensing↗