Search NASA⌕ Search

SEARCH · Search NASA

Results for “flutter analysis”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 253 records · Page 14
All sourcesNASA NTRSDOE OSTI
NASA NTRS1990

Influence of structural and aerodynamic modeling on optimization with flutter constraint

The influences of structural and aerodynamic modeling on multidisciplinary optimization in an aeroelastic environment are not well understood. Therefore, optimizations with flutter and frequency constraints were performed to investigate the effects these modeling factors have on various representative wings. To this end, the Automated Structural Optimization System (ASTROS) was used as a tool to minimize the weight of various fully built-up finite element wing models in subsonic and supersonic flow under given flutter and frequency constraints. First, the performance of the optimization module was tested against results from other codes on a straight and uniform wing widely used for optimization with flutter constraints. Then, fully built-up finite element models of various wings with different aspect ratios were investigated for the influence on the structural optimization for minimum weight of the following modeling factors: finite element selection, structural grid refinement; number of selected modes, retention of breathing modes; selection of reduced frequencies to be used in flutter analysis; aerodynamic panel size and placement; splining of the aerodynamic grid to the structural grid selection of extra points of the structural wing box for splining; and number of constraints to be retained. Knowledge of these influences as well as of the program behavior is important, since optimization can be made more efficient by the selection of reasonable initial models. Also, it was shown previously that modeling has an impact on the results of modal and aeroelastic analyses. Thus, if modeling errors can negatively affect the analyses, a minimum weight optimization can be jeopardized and result in an optimal design that is rather unreliable. In the following, selected results are presented and the influences of some modeling parameters on optimization are pointed out.

Striz, Alfred G.↗
NASA NTRS1960

Flutter Research on Skin Panels

Representative experimental results are presented to show the current status of the panel flutter problem. Results are presented for unstiffened rectangular panels and for rectangular panels stiffened by corrugated backing. Flutter boundaries are established for all types of panels when considered on the basis of equivalent isotropic plates. The effects of Mach number, differential pressure, and aerodynamic heating on panel flutter are discussed. A flutter analysis of orthotropic panels is presented in the appendix.

Kordes, Eldon E.↗
NASA NTRS2000

Aerodynamic Lift and Moment Calculations Using a Closed-Form Solution of the Possio Equation

In this paper, we present closed-form formulas for the lift and moment coefficients of a lifting surface in two dimensional, unsteady, compressible, subsonic flow utilizing a newly developed explicit analytical solution of the Possio equation. Numerical calculations are consistent with previous numerical tables based on series expansions or ad hoc numerical schemes. More importantly, these formulas lend themselves readily to flutter analysis, compared with the tedious table-look-up schemes currently in use.

Lin, Jensen↗
NASA NTRS2007

Build-up Approach to Updating the Mock Quiet Spike(TradeMark) Beam Model

A crucial part of aircraft design is ensuring that the required margin for flutter is satisfied. A trustworthy flutter analysis, which begins by possessing an accurate dynamics model, is necessary for this task. Traditionally, a model was updated manually by fine tuning specific stiffness parameters until the analytical results matched test data. This is a time consuming iterative process. NASA Dryden Flight Research Center has developed a mode matching code to execute this process in a more efficient manner. Recently, this code was implemented in the F-15B/Quiet Spike(TradeMark) (Gulfstream Aerospace Corporation, Savannah, Georgia) model update. A build-up approach requiring several ground vibration test configurations and a series of model updates was implemented in order to determine the connection stiffness between aircraft and test article. The mode matching code successfully updated various models for the F-15B/Quiet Spike(TradeMark) project to within 1 percent error in frequency and the modal assurance criteria values ranged from 88.51-99.42 percent.

Herrera, Claudia Y.↗
NASA NTRS2007

Build-up Approach to Updating the Mock Quiet Spike(TM)Beam Model

A crucial part of aircraft design is ensuring that the required margin for flutter is satisfied. A trustworthy flutter analysis, which begins by possessing an accurate dynamics model, is necessary for this task. Traditionally, a model was updated manually by fine tuning specific stiffness parameters until the analytical results matched test data. This is a time consuming iterative process. The NASA Dryden Flight Research Center has developed a mode matching code to execute this process in a more efficient manner. Recently, this code was implemented in the F-15B/Quiet Spike (Gulfstream Aerospace Corporation, Savannah, Georgia) model update. A build-up approach requiring several ground vibration test configurations and a series of model updates was implemented to determine the connection stiffness between aircraft and test article. The mode matching code successfully updated various models for the F-15B/Quiet Spike project to within 1 percent error in frequency and the modal assurance criteria values ranged from 88.51-99.42 percent.

Herrera, Claudia Y.↗
NASA NTRS2007

Quiet Spike Build-Up Ground Vibration Testing Approach

NASA's Dryden Flight Research Center uses a modified F-15B (836) aircraft as a testbed for a variety of flight research:experiments mounted underneath the aircraft fuselage. The F-15B was selected to fly Gulfstream Aerospace Corporation's (GAC)QuietSpike(TM)(QS) project; however, this experiment is very unique and unlike any of the previous testbed experiments flown on the F-15B. It involves the addition of a relatively long quiet spike boom attached to the radar bulkhead of the aircraft. This QS experiment is a stepping stone to airframe structural morphing technologies designed to mitigate sonic born strength of business jets over land. The QS boom is a concept in Which an aircraft's front-end would be extended prior to supersonic acceleration. This morphing would effectively lengthen the aircraft, reducing peak sonic boom amplitude, but is also expected to partition the otherwise strong bow shock into a series of reduced-strength, non-coalescing shocklets. Prior to flying the Quietspike(TM) experiment on the F-15B aircraft several ground vibration tests (GVT) were required in order to understand the QS modal characteristics and coupling effects with the F-15B. However, due to the project's late hardware delivery of the QS and the intense schedule, a "traditional" GVT of the mated F-1513 Quietspike(tm) ready-for-flight configuration would not have left sufficient time available for the finite element model update and flutter analyses before flight testing. Therefore, a "nontraditional" ground vibration testing approach was taken. The objective of the QuietSpike (TM) build-up ground testing approach was to ultimately obtain confidence in the F-15B Quietspike(TM) finite element model (FEM) to be used for the flutter analysis. In order to obtain the F15B QS FEM with reliable foundation stiffness between the QS and the F-15B radar bulkhead as well as QS modal characteristics, several different GVT configurations were performed. EAch of the four GVT's performed had a specific objective. The overall intent was to provide adequate data which would replicate a "traditional" F-15B QS GVT with actual ready-for-flight hardware. NASA Dryden was tasked with the conduct of the 1st, 2nd and 4th GVT and the 3rd GVT was GAC's responsibility. In order for this build-up GVT approach to be feasible, it was absolutely critical that each GVT configuration matched as closely as possible the connection interface configuration between the and aircraft bulkhead.

Spivey, Natalie D.↗
NASA NTRS2009

Ground Vibration Test of the Aerostructure Test Wing 2

The Aerostructures Test Wing (ATW) was developed to test unique concepts for flutter prediction and control synthesis. A follow-on to the successful ATW, denoted ATW2, was fabricated as a test bed to validate a variety of instrumentation in flight and to collect data for development of advanced signal processing algorithms for flutter prediction and aviation safety. As a means to estimate flutter speed, a ground vibration test (GVT) was performed. The results of a GVT are typically utilized to update structural dynamics finite element (FE) models used for flutter analysis. In this study, two GVT methodologies were explored to determine which nodes provide the best sensor locations: (i) effective independence and (ii) kinetic energy sorting algorithms. For measurement, ten and twenty sensors were used for three and 10 target test modes. A total of six accelerometer configurations measured frequencies and mode shapes. This included locations used in the original ATW GVT. Moreover, an optical measurement system was used to acquire data without mass effects added by conventional sensors. A considerable frequency shift was observed in comparing the data from the accelerometers to the optical data. The optical data provided robust data for use of the ATW2 finite element model update.

Herrera, Claudia↗
NASA NTRS2014

Creating a Test Validated Structural Dynamic Finite Element Model of the Multi-Utility Technology Test Bed Aircraft

Small modeling errors in the finite element model will eventually induce errors in the structural flexibility and mass, thus propagating into unpredictable errors in the unsteady aerodynamics and the control law design. One of the primary objectives of Multi Utility Technology Test Bed, X-56A, aircraft is the flight demonstration of active flutter suppression, and therefore in this study, the identification of the primary and secondary modes for the structural model tuning based on the flutter analysis of X-56A. The ground vibration test validated structural dynamic finite element model of the X-56A is created in this study. The structural dynamic finite element model of the X-56A is improved using a model tuning tool. In this study, two different weight configurations of the X-56A have been improved in a single optimization run.

structural dynamic model tuning↗
NASA NTRS2013

Follow on Research for Multi-Utility Technology Test Bed Aircraft at NASA Dryden Flight Research Center (FY13 Progress Report)

Modern aircraft employ a significant fraction of their weight in composite materials to reduce weight and improve performance. Aircraft aeroservoelastic models are typically characterized by significant levels of model parameter uncertainty due to the composite manufacturing process. Small modeling errors in the finite element model will eventually induce errors in the structural flexibility and mass, thus propagating into unpredictable errors in the unsteady aerodynamics and the control law design. One of the primary objectives of Multi Utility Technology Test-bed (MUTT) aircraft is the flight demonstration of active flutter suppression, and therefore in this study, the identification of the primary and secondary modes for the structural model tuning based on the flutter analysis of MUTT aircraft. The ground vibration test-validated structural dynamic finite element model of the MUTT aircraft is created in this study. The structural dynamic finite element model of MUTT aircraft is improved using the in-house Multi-disciplinary Design, Analysis, and Optimization tool. In this study, two different weight configurations of MUTT aircraft have been improved simultaneously in a single model tuning procedure.

multi-utility technology test bed aircraft↗
NASA NTRS2016

Inertial Force Coupling to Nonlinear Aeroelasticity of Flexible Wing Aircraft

This paper investigates the inertial force effect on nonlinear aeroelasticity of flexible wing aircraft. The geometric are nonlinearity due to rotational and tension stiffening. The effect of large bending deflection will also be investigated. Flutter analysis will be conducted for a truss-braced wing aircraft concept with tension stiffening and inertial force coupling.

Aeroelasticity↗
NASA NTRS2017

Economical Unsteady High-Fidelity Aerodynamics for Structural Optimization with a Flutter Constraint

Structural optimization with a flutter constraint for a vehicle designed to fly in the transonic regime is a particularly difficult task. In this speed range, the flutter boundary is very sensitive to aerodynamic nonlinearities, typically requiring high-fidelity Navier-Stokes simulations. However, the repeated application of unsteady computational fluid dynamics to guide an aeroelastic optimization process is very computationally expensive. This expense has motivated the development of methods that incorporate aspects of the aerodynamic nonlinearity, classical tools of flutter analysis, and more recent methods of optimization. While it is possible to use doublet lattice method aerodynamics, this paper focuses on the use of an unsteady high-fidelity aerodynamic reduced order model combined with successive transformations that allows for an economical way of utilizing high-fidelity aerodynamics in the optimization process. This approach is applied to the common research model wing structural design. As might be expected, the high-fidelity aerodynamics produces a heavier wing than that optimized with doublet lattice aerodynamics. It is found that the optimized lower skin of the wing using high-fidelity aerodynamics differs significantly from that using doublet lattice aerodynamics.

Bartels, Robert E.↗
NASA NTRS2019

Aero-Structural Modeling of the Truss-Braced Wing Aircraft Using Potential Method with Correction Methods for Transonic Viscous Flow and Wing-Strut Interference Aerodynamics

This paper describes an aero-structural modeling method for the Transonic Truss-Braced Wing (TTBW) aircraft using VSPAERO. A vortex-lattice model of the TTBW aircraft is developed, and a transonic and viscous flow correction method is implemented in the VSPAERO models to account for transonic and viscous flow effects. A correction method for the wing-strut interference aerodynamics is developed and applied to the VSPAERO solver. Also, a structural dynamic finite-element model of the TTBW aircraft is developed. This finite-element model includes the geometric nonlinear effect due to the tension in the struts which cause a deflection dependent nonlinear stiffness. The VSPAERO models are coupled to the finite-element model to provide a rapid capability for aero-structural modeling and flutter analysis. A flight-optimized jig twist model is being developed and will be applied for the purpose of generating a full flight dynamic model of the TTBW aircraft.

Fugate, Jason↗
NASA NTRS2019

Investigation of Transonic Truss-Braced Wing Aircraft Transonic Wing-Strut Interference Effects Using FUN3D

This paper presents a computational study of transonic wing-strut interference effects of Transonic Truss-Braced Wing (TTBW) aircraft using the high-fidelity CFD (Computational Fluid Dynamics) code FUN3D (Fully Unstructured Navier-Stokes Three Dimensional). The study is conducted for the wing-strut and the wing-alone configurations at different Mach numbers and Reynolds numbers. The interference effects are calculated by comparing the wing aerodynamics along the spanwise direction between the wing-strut and the wing-alone configurations. The presence of the strut underneath the wing induces a suction peak on the lower surface of the wing, which causes changes in aerodynamic forces and moments, as well as the aerodynamic center location. The interference effects become more pronounced as the Mach number increases. The Reynolds number has less impact on the interference effects. A transonic wing-strut interference aerodynamic correction method is developed for use in a lower-fidelity tool, VSPAERO [a vortex lattice flow solver], coupled to a finite-element model for rapid flutter analysis.

Xiong, Juntao↗
NASA NTRSDate not supplied

NASA Armstrong State of Discipline

- AFRC’s Overview Statement - AFRC is NASA's primary center for high-risk, atmospheric flight research and ground testing on modified or unique research vehicles and test articles - AFRC’s L&D Facility - Flight Loads Lab (FLL): High-bay test area with flight line access for large-scale structural & thermal testing of aerospace structures for component and airframe qualification/airworthiness & research - AFRC’s L&D Expertise - Mainly supports projects in the Aeronautics Research Mission - Aeroelasticity, Model Tuning, FEM & Flutter Analysis Airworthiness Clearance support - Modal Testing, Mass Property Testing & Flight Testing

Natalie Spivey↗
NASA NTRS1976

Time Series Analysis in Flight Flutter Testing at the Air Force Flight Test Center: Concepts and Results

The Air Force Flight Test Center (AFFTC) flight flutter facility is described. Concepts of using a minicomputer-based time series analyzer and a modal analysis software package for flight flutter testing are examined. The results of several evaluations of the software package are given. The reasons for employing a minimum phase concept in analyzing response only signals are discussed. The use of a Laplace algorithm is shown to be effective for the modal analysis of time histories in flutter testing. Sample results from models and flight tests are provided. The limitations inherent in time series analysis methods are discussed, and the need for effective noise reduction techniques is noted. The use of digital time series analysis techniques in flutter testing is shown to be fast, accurate, and cost effective.

Lenz, R. W.↗
NASA NTRS1975

Stability analysis of nonlinear autonomous systems - General theory and application to flutter

The analysis makes use of a singular perturbation method, the multiple time scaling. Concepts of stable and unstable limit cycles are introduced. The solution is obtained in the form of an asymptotic expansion. Numerical results are presented for the nonlinear flutter of panels and airfoils in supersonic flow. The approach used is an extension of a method for analyzing nonlinear panel flutter reported by Morino (1969).

Smith, L. L.↗
NASA NTRS2000

Propulsion Aeroelastic Analysis Developed for Flutter and Forced Response

The NASA Glenn Research Center at Lewis Field develops new technologies to increase the fuel efficiency of aircraft engines, improve the safety of engine operation, reduce emissions, and reduce engine noise. With the development of new designs for fans, compressors, and turbines to achieve these goals, the basic aeroelastic requirements are that there should be no flutter (self-excited vibrations) or high resonant blade stresses (due to forced response) in the operating regime. Therefore, an accurate prediction and analysis capability is required to verify the aeroelastic soundness of the designs. Such a three-dimensional viscous propulsion aeroelastic analysis capability has been developed at Glenn with support from the Advanced Subsonic Technology (AST) program. This newly developed aeroelastic analysis capability is based on TURBO, a threedimensional unsteady aerodynamic Reynolds-averaged Navier-Stokes turbomachinery code developed previously under a grant from Glenn. TURBO can model the viscous flow effects that play an important role in certain aeroelastic problems such as flutter with flow separation, flutter at high loading conditions near the stall line (stall flutter), flutter in the presence of shock and boundary-layer interaction, and forced response due to wakes and shock impingement. In aeroelastic analysis, the structural dynamics representation of the blades is based on normal modes. A finite-element analysis code is used to calculate these in-vacuum vibration modes and the associated natural frequencies. In an aeroelastic analysis using the TURBO code, flutter and forced response are modeled as being uncoupled. To calculate if a blade row will flutter, one prescribes the motion of the blade to be a harmonic vibration in a specified in-vacuum normal mode. An aeroelastic analysis preprocessor is used to generate the displacement field required for the analysis. The work done by aerodynamic forces on the vibrating blade during a cycle of vibration is calculated. If this work is positive, the blade is dynamically unstable, since it will extract energy from the flow, leading to an increase in the blade s oscillation amplitude. The forced-response excitations on a blade row are calculated by modeling the flow through two adjacent blade rows using the TURBO code. The blades are assumed to be rigid. As an option, a single blade row can be modeled with the upstream blade row influence represented by a time-varying disturbance (gust) at the inlet boundary. The unsteady forces on a blade row from such analyses are used in a structural analysis along with the blade structural dynamics characteristics and aerodynamic damping associated with blade vibration to calculate the resulting dynamic stresses on the blade.

Bakhle, Milind A.↗
NASA NTRS1981

Application of a flight test and data analysis technique to flutter of a drone aircraft

Modal identification results presented were obtained from recent flight flutter tests of a drone vehicle with a research wing (DAST ARW-1 for Drones for Aerodynamic and Structural Testing, Aeroelastic Research Wing-1). This vehicle is equipped with an active flutter suppression system (FSS). Frequency and damping of several modes are determined by a time domain modal analysis of the impulse response function obtained by Fourier transformations of data from fast swept sine wave excitation by the FSS control surface on the wing. Flutter points are determined for two different altitudes with the FSS off. Data are given for near the flutter boundary with the FSS on.

Bennett, R. M.↗