Introduction to Aircraft Aeroelasticity and Loads

Total Page:16

File Type:pdf, Size:1020Kb

Introduction to Aircraft Aeroelasticity and Loads JWBK209-FM-I JWBK209-Wright November 14, 2007 2:58 Char Count= 0 Introduction to Aircraft Aeroelasticity and Loads Jan R. Wright University of Manchester and J2W Consulting Ltd, UK Jonathan E. Cooper University of Liverpool, UK iii JWBK209-FM-I JWBK209-Wright November 14, 2007 2:58 Char Count= 0 Introduction to Aircraft Aeroelasticity and Loads i JWBK209-FM-I JWBK209-Wright November 14, 2007 2:58 Char Count= 0 ii JWBK209-FM-I JWBK209-Wright November 14, 2007 2:58 Char Count= 0 Introduction to Aircraft Aeroelasticity and Loads Jan R. Wright University of Manchester and J2W Consulting Ltd, UK Jonathan E. Cooper University of Liverpool, UK iii JWBK209-FM-I JWBK209-Wright November 14, 2007 2:58 Char Count= 0 Copyright C 2007 John Wiley & Sons Ltd, The Atrium, Southern Gate, Chichester, West Sussex PO19 8SQ, England Telephone (+44) 1243 779777 Email (for orders and customer service enquiries): [email protected] Visit our Home Page on www.wileyeurope.com or www.wiley.com All Rights Reserved. No part of this publication may be reproduced, stored in a retrieval system or transmitted in any form or by any means, electronic, mechanical, photocopying, recording, scanning or otherwise, except under the terms of the Copyright, Designs and Patents Act 1988 or under the terms of a licence issued by the Copyright Licensing Agency Ltd, 90 Tottenham Court Road, London W1T 4LP, UK, without the permission in writing of the Publisher. Requests to the Publisher should be addressed to the Permissions Department, John Wiley & Sons Ltd, The Atrium, Southern Gate, Chichester, West Sussex PO19 8SQ, England, or emailed to [email protected], or faxed to (+44) 1243 770620. This publication is designed to provide accurate and authoritative information in regard to the subject matter covered. It is sold on the understanding that the Publisher is not engaged in rendering professional services. If professional advice or other expert assistance is required, the services of a competent professional should be sought. Other Wiley Editorial Offices John Wiley & Sons Inc., 111 River Street, Hoboken, NJ 07030, USA Jossey-Bass, 989 Market Street, San Francisco, CA 94103-1741, USA Wiley-VCH Verlag GmbH, Boschstr. 12, D-69469 Weinheim, Germany John Wiley & Sons Australia Ltd, 42 McDougall Street, Milton, Queensland 4064, Australia John Wiley & Sons (Asia) Pte Ltd, 2 Clementi Loop #02-01, Jin Xing Distripark, Singapore 129809 John Wiley & Sons Canada Ltd, 6045 Freemont Blvd, Mississauga, Ontario, Canada L5R 4J3 Wiley also publishes its books in a variety of electronic formats. Some content that appears in print may not be available in electronic books. Anniversary Logo Design: Richard J. Pacifico British Library Cataloguing in Publication Data A catalogue record for this book is available from the British Library ISBN 978-0470-85840-0 Typeset in 9/11pt Times by Aptara, New Delhi, India. Printed and bound in Great Britain by Antony Rowe Ltd, Chippenham, Wiltshire This book is printed on acid-free paper responsibly manufactured from sustainable forestry in which at least two trees are planted for each one used for paper production. iv JWBK209-FM-I JWBK209-Wright November 14, 2007 2:58 Char Count= 0 To our wives, Joy and Sarah v JWBK209-FM-I JWBK209-Wright November 14, 2007 2:58 Char Count= 0 vi JWBK209-FM-I JWBK209-Wright November 14, 2007 2:58 Char Count= 0 Contents Preface xv Introduction xix Abbreviations xxv Part I Background Material 1 1 Vibration of Single Degree of Freedom Systems 3 1.1 Setting up equations of motion for single DoF systems 3 1.2 Free vibration of single DoF systems 5 1.3 Forced vibration of single DoF systems 7 1.4 Harmonic forced vibration – frequency response functions 7 1.5 Transient/random forced vibration – time domain solution 10 1.6 Transient forced vibration – frequency domain solution 14 1.7 Random forced vibration – frequency domain solution 16 1.8 Examples 17 2 Vibration of Multiple Degree of Freedom Systems 19 2.1 Setting up equations of motion 19 2.2 Undamped free vibration 21 2.3 Damped free vibration 24 2.4 Transformation to modal coordinates 27 2.5 ‘Free–free’ systems 31 2.6 Harmonic forced vibration 31 2.7 Transient/random forced vibration – time domain solution 33 2.8 Transient forced vibration – frequency domain solution 34 2.9 Random forced vibration – frequency domain solution 34 2.10 Examples 35 3 Vibration of Continuous Systems – Assumed Shapes Approach 37 3.1 Rayleigh–Ritz ‘assumed shapes’ method 38 3.2 Generalized equations of motion – basic approach 39 3.3 Generalized equations of motion – matrix approach 44 3.4 Generating aircraft ‘free–free’ modes from ‘branch’ modes 46 3.5 Whole aircraft ‘free–free’ modes 49 3.6 Examples 50 vii JWBK209-FM-I JWBK209-Wright November 14, 2007 2:58 Char Count= 0 viii CONTENTS 4 Vibration of Continuous Systems – Discretization Approach 53 4.1 Introduction to the finite element (FE) approach 53 4.2 Formulation of the beam bending element 54 4.3 Assembly and solution for a structure with beam elements 58 4.4 Torsion element 63 4.5 Combined bending/torsion element 64 4.6 Comments on modelling 65 4.7 Examples 66 5 Introduction to Steady Aerodynamics 69 5.1 The standard atmosphere 69 5.2 Effect of air speed on aerodynamic characteristics 71 5.3 Flows and pressures around a symmetric aerofoil 72 5.4 Forces on an aerofoil 74 5.5 Variation of lift for an aerofoil at an angle of incidence 75 5.6 Pitching moment variation and the aerodynamic centre 76 5.7 Lift on a three-dimensional wing 77 5.8 Drag on a three-dimensional wing 81 5.9 Control surfaces 82 5.10 Supersonic aerodynamics – piston theory 83 5.11 Transonic flows 84 5.12 Examples 84 6 Introduction to Loads 87 6.1 Laws of motion 87 6.2 D’Alembert’s principle – inertia forces and couples 90 6.3 Externally applied/reactive loads 93 6.4 Free body diagrams 94 6.5 Internal loads 95 6.6 Internal loads for continuous representation of a structure 96 6.7 Internal loads for discretized representation of a structure 100 6.8 Intercomponent loads 102 6.9 Obtaining stresses from internal loads – structural members with simple load paths 103 6.10 Examples 103 7 Introduction to Control 107 7.1 Open and closed loop systems 107 7.2 Laplace transforms 108 7.3 Modelling of open and closed loop systems using Laplace and frequency domains 110 7.4 Stability of systems 111 7.5 PID control 118 7.6 Examples 119 Part II Introduction to Aeroelasticity and Loads 121 8 Static Aeroelasticity – Effect of Wing Flexibility on Lift Distribution and Divergence 123 8.1 Static aeroelastic behaviour of a two-dimensional rigid aerofoil with spring attachment 124 8.2 Static aeroelastic behaviour of a fixed root flexible wing 127 JWBK209-FM-I JWBK209-Wright November 14, 2007 2:58 Char Count= 0 CONTENTS ix 8.3 Effect of trim on static aeroelastic behaviour 129 8.4 Effect of wing sweep on static aeroelastic behaviour 134 8.5 Examples 139 9 Static Aeroelasticity – Effect of Wing Flexibility on Control Effectiveness 141 9.1 Rolling effectiveness of a flexible wing – the steady roll case 141 9.2 Rolling effectiveness of a flexible wing – the fixed wing root case 146 9.3 Effect of spanwise position of the control surface 149 9.4 Full aircraft model – control effectiveness 149 9.5 Effect of trim on reversal speed 151 9.6 Examples 151 10 Introduction to Unsteady Aerodynamics 153 10.1 Quasi-steady aerodynamics 153 10.2 Unsteady aerodynamics 154 10.3 Aerodynamic lift and moment for a harmonically oscillating aerofoil 157 10.4 Oscillatory aerodynamic derivatives 159 10.5 Aerodynamic damping and stiffness 160 10.6 Unsteady aerodynamics related to gusts 161 10.7 Examples 165 11 Dynamic Aeroelasticity – Flutter 167 11.1 Simplified unsteady aerodynamic model 167 11.2 Binary aeroelastic model 168 11.3 General form of the aeroelastic equations 171 11.4 Eigenvalue solution of flutter equations 171 11.5 Aeroelastic behaviour of the binary model 172 11.6 Aeroelastic behaviour of a flexible wing 180 11.7 Aeroelastic behaviour of a multiple mode system 182 11.8 Flutter speed prediction for binary systems 182 11.9 Flutter conic 184 11.10 Divergence of aeroelastic systems 186 11.11 Inclusion of unsteady reduced frequency effects 187 11.12 Control surface flutter 191 11.13 Whole aircraft model – inclusion of rigid body modes 193 11.14 Flutter in the transonic regime 194 11.15 Flutter in the supersonic regime – wing and panel flutter 194 11.16 Effect of nonlinearities – limit cycle oscillations 197 11.17 Examples 198 12 Aeroservoelasticity 201 12.1 Mathematical modelling of a simple aeroelastic system with a control surface 202 12.2 Inclusion of gust terms 203 12.3 Implementation of a control system 204 12.4 Determination of closed loop system stability 204 12.5 Gust response of the closed loop system 205 12.6 Inclusion of control law frequency dependency in stability calculations 206 12.7 Response determination via the frequency domain 208 12.8 State space modelling 208 12.9 Examples 209 JWBK209-FM-I JWBK209-Wright November 14, 2007 2:58 Char Count= 0 x CONTENTS 13 Equilibrium Manoeuvres 211 13.1 Equilibrium manoeuvre – rigid aircraft under normal acceleration 213 13.2 Manoeuvre envelope 217 13.3 Equilibrium manoeuvre – rigid aircraft pitching 218 13.4 Equilibrium manoeuvre – flexible aircraft pitching 225 13.5 Flexible corrections to rigid aircraft pitching derivatives 238 13.6 Equilibrium manoeuvres – aircraft rolling and yawing 239 13.7 Representation of the flight control system (FCS) 243 13.8 Examples 243 14 Flight Mechanics Model for Dynamic Manoeuvres 245 14.1 Aircraft axes 246 14.2 Motion variables 247 14.3
Recommended publications
  • 2.161 Signal Processing: Continuous and Discrete Fall 2008
    MIT OpenCourseWare http://ocw.mit.edu 2.161 Signal Processing: Continuous and Discrete Fall 2008 For information about citing these materials or our Terms of Use, visit: http://ocw.mit.edu/terms. Massachusetts Institute of Technology Department of Mechanical Engineering 2.161 Signal Processing - Continuous and Discrete Fall Term 2008 1 Lecture 1 Reading: • Class handout: The Dirac Delta and Unit-Step Functions 1 Introduction to Signal Processing In this class we will primarily deal with processing time-based functions, but the methods will also be applicable to spatial functions, for example image processing. We will deal with (a) Signal processing of continuous waveforms f(t), using continuous LTI systems (filters). a LTI dy nam ical system input ou t pu t f(t) Continuous Signal y(t) Processor and (b) Discrete-time (digital) signal processing of data sequences {fn} that might be samples of real continuous experimental data, such as recorded through an analog-digital converter (ADC), or implicitly discrete in nature. a LTI dis crete algorithm inp u t se q u e n c e ou t pu t seq u e n c e f Di screte Si gnal y { n } { n } Pr ocessor Some typical applications that we look at will include (a) Data analysis, for example estimation of spectral characteristics, delay estimation in echolocation systems, extraction of signal statistics. (b) Signal enhancement. Suppose a waveform has been contaminated by additive “noise”, for example 60Hz interference from the ac supply in the laboratory. 1copyright c D.Rowell 2008 1–1 inp u t ou t p u t ft + ( ) Fi lte r y( t) + n( t) ad d it ive no is e The task is to design a filter that will minimize the effect of the interference while not destroying information from the experiment.
    [Show full text]
  • Lecture 2 LSI Systems and Convolution in 1D
    Lecture 2 LSI systems and convolution in 1D 2.1 Learning Objectives Understand the concept of a linear system. • Understand the concept of a shift-invariant system. • Recognize that systems that are both linear and shift-invariant can be described • simply as a convolution with a certain “impulse response” function. 2.2 Linear Systems Figure 2.1: Example system H, which takes in an input signal f(x)andproducesan output g(x). AsystemH takes an input signal x and produces an output signal y,whichwecan express as H : f(x) g(x). This very general definition encompasses a vast array of di↵erent possible systems.! A subset of systems of particular relevance to signal processing are linear systems, where if f (x) g (x)andf (x) g (x), then: 1 ! 1 2 ! 2 a f + a f a g + a g 1 · 1 2 · 2 ! 1 · 1 2 · 2 for any input signals f1 and f2 and scalars a1 and a2. In other words, for a linear system, if we feed it a linear combination of inputs, we get the corresponding linear combination of outputs. Question: Why do we care about linear systems? 13 14 LECTURE 2. LSI SYSTEMS AND CONVOLUTION IN 1D Question: Can you think of examples of linear systems? Question: Can you think of examples of non-linear systems? 2.3 Shift-Invariant Systems Another subset of systems we care about are shift-invariant systems, where if f1 g1 and f (x)=f (x x )(ie:f is a shifted version of f ), then: ! 2 1 − 0 2 1 f (x) g (x)=g (x x ) 2 ! 2 1 − 0 for any input signals f1 and shift x0.
    [Show full text]
  • Linear System Theory
    Chapter 2 Linear System Theory In this course, we will be dealing primarily with linear systems, a special class of sys- tems for which a great deal is known. During the first half of the twentieth century, linear systems were analyzed using frequency domain (e.g., Laplace and z-transform) based approaches in an effort to deal with issues such as noise and bandwidth issues in communication systems. While they provided a great deal of intuition and were suf- ficient to establish some fundamental results, frequency domain approaches presented various drawbacks when control scientists started studying more complicated systems (containing multiple inputs and outputs, nonlinearities, noise, and so forth). Starting in the 1950’s (around the time of the space race), control engineers and scientists started turning to state-space models of control systems in order to address some of these issues. These time-domain approaches are able to effectively represent concepts such as the in- ternal state of the system, and also present a method to introduce optimality conditions into the controller design procedure. We will be using the state-space (or “modern”) approach to control almost exclusively in this course, and the purpose of this chapter is to review some of the essential concepts in this area. 2.1 Discrete-Time Signals Given a field F,asignal is a mapping from a set of numbers to F; in other words, signals are simply functions of the set of numbers that they operate on. More specifically: • A discrete-time signal f is a mapping from the set of integers Z to F, and is denoted by f[k]fork ∈ Z.Eachinstantk is also known as a time-step.
    [Show full text]
  • Digital Image Processing Lectures 3 & 4
    2-D Signals and Systems 2-D Fourier Transform Digital Image Processing Lectures 3 & 4 M.R. Azimi, Professor Department of Electrical and Computer Engineering Colorado State University Spring 2017 M.R. Azimi Digital Image Processing 2-D Signals and Systems 2-D Fourier Transform Definitions and Extensions: 2-D Signals: A continuous image is represented by a function of two variables e.g. x(u; v) where (u; v) are called spatial coordinates and x is the intensity. A sampled image is represented by x(m; n). If pixel intensity is also quantized (digital images) then each pixel is represented by B bits (typically B = 8 bits/pixel). 2-D Delta Functions: They are separable 2-D functions i.e. 1 (u; v) = (0; 0) Dirac: δ(u; v) = δ(u) δ(v) = 0 Otherwise 1 (m; n) = (0; 0) Kronecker: δ(m; n) = δ(m) δ(n) = 0 Otherwise M.R. Azimi Digital Image Processing 2-D Signals and Systems 2-D Fourier Transform Properties: For 2-D Dirac delta: 1 1- R R x(u0; v0)δ(u − u0; v − v0)du0dv0 = x(u; v) −∞ 2- R R δ(u; v)du dv = 1 8 > 0 − For 2-D Kronecker delta: 1 1 1- x(m; n) = P P x(m0; n0)δ(m − m0; n − n0) m0=−∞ n0=−∞ 1 2- P P δ(m; n) = 1 m;n=−∞ Periodic Signals: Consider an image x(m; n) which satisfies x(m; n + N) = x(m; n) x(m + M; n) = x(m; n) This signal is said to be doubly periodic with horizontal and vertical periods M and N, respectively.
    [Show full text]
  • CHAPTER TWO - Static Aeroelasticity – Unswept Wing Structural Loads and Performance 21 2.1 Background
    Static aeroelasticity – structural loads and performance CHAPTER TWO - Static Aeroelasticity – Unswept wing structural loads and performance 21 2.1 Background ........................................................................................................................... 21 2.1.2 Scope and purpose ....................................................................................................................... 21 2.1.2 The structures enterprise and its relation to aeroelasticity ............................................................ 22 2.1.3 The evolution of aircraft wing structures-form follows function ................................................ 24 2.2 Analytical modeling............................................................................................................... 30 2.2.1 The typical section, the flying door and Rayleigh-Ritz idealizations ................................................ 31 2.2.2 – Functional diagrams and operators – modeling the aeroelastic feedback process ....................... 33 2.3 Matrix structural analysis – stiffness matrices and strain energy .......................................... 34 2.4 An example - Construction of a structural stiffness matrix – the shear center concept ........ 38 2.5 Subsonic aerodynamics - fundamentals ................................................................................ 40 2.5.1 Reference points – the center of pressure..................................................................................... 44 2.5.2 A different
    [Show full text]
  • Introduction to Aeroelasticity.Pdf
    Aeroelasticity Dr. Ugur GUVEN Aerospace Engineer (P.hD) Nuclear Science and Technology Engineer (M.Sc) What is Aeroelasticity • Aeroelasticity is broadly defined as the interaction between the aerodynamic forces and the structural forces causing a deformation in the structure of the aerospace craft as well as in its control mechanism or in its propulsion systems. Importance of Aeroelasticity • Aeroelasticity has become a very important force especially after the 1950’s. • The interaction between aerodynamic loads and structural deformations have gained great importance in view of factors related to the design of aircraft as well as missiles. • Aeroelasticity plays at least some part on fuel sloshing as well as on the reentry of spacecraft in astronautics. Trends in Technology • Due to the advancements in technology, it has become quite common to see the slenderness ratio (ratio of length of wing span to thickness at the root) increase. • The wing span area as well as the length of aircrafts have increased causing aircraft to become much more susceptible to interaction between structural loads and aerodynamic loads Slenderness Ratio Effect of Aerodynamic Loads • The forces of lift and drag as well as torsion moment will have some sort of effect on the structural integrity of the spacecraft. • In many cases, some parts of aircraft or spacecraft may bend or ripple slightly due to these loads. • The frequency of these loads and effects can also cause the aircraft’s structure to suffer from metal fatigue in the long run. Scope of Aeroelasticity Vibration • One of the ways in which aerodynamic and structural forces collide with each other is through vibration.
    [Show full text]
  • AAE556-Aeroelasticity
    AIRCRAFT AEROELASTIC DESIGN AND ANALYSIS An introduction to fundamental concepts of static and dynamic aeroelasticity - with simple idealized models and mathematics to describe the essential features of aeroelastic problems. These notes are intended for the use of Purdue University students enrolled in AAE556. They are not for sale or intended for distribution to others, but may be used for educational purposes, with prior permission of the author. Terry A. Weisshaar Purdue University © 1995 (Second edition -2009) Introduction - page 1 Preface to Second Edition – The purpose and scope These notes are the result of three decades of experiences teaching a course in aeroelasticity to seniors and first or second year graduate students. During this time I have presented lectures and developed homework problems with the objective of introducing students to the complexities of a field in which several major disciplines intersect to produce major problems for high speed flight. These problems affect structural and flight stability problems, re-distribution of external aerodynamic loads and a host of other problems described in the notes. This three decade effort has been challenging, but more than anything, it has been fun. My students have had fun and have been contributors to this teaching effort. Some of them have even gone on to surpass my skills in this area and to be recognized practitioners in this area. First of all, let me emphasize what these notes are not. They are not notes on advanced methods of analysis. They are not a “how to” book describing advanced methods of analysis required to analyze complex configurations. If your job is to compute the flutter speed of a Boeing 787, you will have to learn that skill elsewhere.
    [Show full text]
  • Calculus and Differential Equations II
    Calculus and Differential Equations II MATH 250 B Linear systems of differential equations Linear systems of differential equations Calculus and Differential Equations II Second order autonomous linear systems We are mostly interested with2 × 2 first order autonomous systems of the form x0 = a x + b y y 0 = c x + d y where x and y are functions of t and a, b, c, and d are real constants. Such a system may be re-written in matrix form as d x x a b = M ; M = : dt y y c d The purpose of this section is to classify the dynamics of the solutions of the above system, in terms of the properties of the matrix M. Linear systems of differential equations Calculus and Differential Equations II Existence and uniqueness (general statement) Consider a linear system of the form dY = M(t)Y + F (t); dt where Y and F (t) are n × 1 column vectors, and M(t) is an n × n matrix whose entries may depend on t. Existence and uniqueness theorem: If the entries of the matrix M(t) and of the vector F (t) are continuous on some open interval I containing t0, then the initial value problem dY = M(t)Y + F (t); Y (t ) = Y dt 0 0 has a unique solution on I . In particular, this means that trajectories in the phase space do not cross. Linear systems of differential equations Calculus and Differential Equations II General solution The general solution to Y 0 = M(t)Y + F (t) reads Y (t) = C1 Y1(t) + C2 Y2(t) + ··· + Cn Yn(t) + Yp(t); = U(t) C + Yp(t); where 0 Yp(t) is a particular solution to Y = M(t)Y + F (t).
    [Show full text]
  • The Scientist and Engineer's Guide to Digital Signal Processing Properties of Convolution
    CHAPTER 7 Properties of Convolution A linear system's characteristics are completely specified by the system's impulse response, as governed by the mathematics of convolution. This is the basis of many signal processing techniques. For example: Digital filters are created by designing an appropriate impulse response. Enemy aircraft are detected with radar by analyzing a measured impulse response. Echo suppression in long distance telephone calls is accomplished by creating an impulse response that counteracts the impulse response of the reverberation. The list goes on and on. This chapter expands on the properties and usage of convolution in several areas. First, several common impulse responses are discussed. Second, methods are presented for dealing with cascade and parallel combinations of linear systems. Third, the technique of correlation is introduced. Fourth, a nasty problem with convolution is examined, the computation time can be unacceptably long using conventional algorithms and computers. Common Impulse Responses Delta Function The simplest impulse response is nothing more that a delta function, as shown in Fig. 7-1a. That is, an impulse on the input produces an identical impulse on the output. This means that all signals are passed through the system without change. Convolving any signal with a delta function results in exactly the same signal. Mathematically, this is written: EQUATION 7-1 The delta function is the identity for ( ' convolution. Any signal convolved with x[n] *[n] x[n] a delta function is left unchanged. This property makes the delta function the identity for convolution. This is analogous to zero being the identity for addition (a%0 ' a), and one being the identity for multiplication (a×1 ' a).
    [Show full text]
  • Linear Time Invariant Systems
    UNIT III LINEAR TIME INVARIANT CONTINUOUS TIME SYSTEMS CT systems – Linear Time invariant Systems – Basic properties of continuous time systems – Linearity, Causality, Time invariance, Stability – Frequency response of LTI systems – Analysis and characterization of LTI systems using Laplace transform – Computation of impulse response and transfer function using Laplace transform – Differential equation – Impulse response – Convolution integral and Frequency response. System A system may be defined as a set of elements or functional blocks which are connected together and produces an output in response to an input signal. The response or output of the system depends upon transfer function of the system. Mathematically, the functional relationship between input and output may be written as y(t)=f[x(t)] Types of system Like signals, systems may also be of two types as under: 1. Continuous-time system 2. Discrete time system Continuous time System Continuous time system may be defined as those systems in which the associated signals are also continuous. This means that input and output of continuous – time system are both continuous time signals. For example: Audio, video amplifiers, power supplies etc., are continuous time systems. Discrete time systems Discrete time system may be defined as a system in which the associated signals are also discrete time signals. This means that in a discrete time system, the input and output are both discrete time signals. For example, microprocessors, semiconductor memories, shift registers etc., are discrete time signals. LTI system:- Systems are broadly classified as continuous time systems and discrete time systems. Continuous time systems deal with continuous time signals and discrete time systems deal with discrete time system.
    [Show full text]
  • A Historical Overview of Flight Flutter Testing
    tV - "J -_ r -.,..3 NASA Technical Memorandum 4720 /_ _<--> A Historical Overview of Flight Flutter Testing Michael W. Kehoe October 1995 (NASA-TN-4?20) A HISTORICAL N96-14084 OVEnVIEW OF FLIGHT FLUTTER TESTING (NASA. Oryden Flight Research Center) ZO Unclas H1/05 0075823 NASA Technical Memorandum 4720 A Historical Overview of Flight Flutter Testing Michael W. Kehoe Dryden Flight Research Center Edwards, California National Aeronautics and Space Administration Office of Management Scientific and Technical Information Program 1995 SUMMARY m i This paper reviews the test techniques developed over the last several decades for flight flutter testing of aircraft. Structural excitation systems, instrumentation systems, Maximum digital data preprocessing, and parameter identification response algorithms (for frequency and damping estimates from the amplltude response data) are described. Practical experiences and example test programs illustrate the combined, integrated effectiveness of the various approaches used. Finally, com- i ments regarding the direction of future developments and Ii needs are presented. 0 Vflutte r Airspeed _c_7_ INTRODUCTION Figure 1. Von Schlippe's flight flutter test method. Aeroelastic flutter involves the unfavorable interaction of aerodynamic, elastic, and inertia forces on structures to and response data analysis. Flutter testing, however, is still produce an unstable oscillation that often results in struc- a hazardous test for several reasons. First, one still must fly tural failure. High-speed aircraft are most susceptible to close to actual flutter speeds before imminent instabilities flutter although flutter has occurred at speeds of 55 mph on can be detected. Second, subcritical damping trends can- home-built aircraft. In fact, no speed regime is truly not be accurately extrapolated to predict stability at higher immune from flutter.
    [Show full text]
  • Control Theory for Linear Systems
    Control theory for linear systems Harry L. Trentelman Research Institute of Mathematics and Computer Science University of Groningen P.O. Box 800, 9700 AV Groningen The Netherlands Tel. +31-50-3633998 Fax. +31-50-3633976 E-mail. [email protected] Anton A. Stoorvogel Dept. of Mathematics and Computing Science Eindhoven Univ. of Technology P.O. Box 513, 5600 MB Eindhoven The Netherlands Tel. +31-40-2472378 Fax. +31-40-2442489 E-mail. [email protected] Malo Hautus Dept. of Mathematics and Computing Science Eindhoven Univ. of Technology P.O. Box 513, 5600 MB Eindhoven The Netherlands Tel. +31-40-2472628 Fax. +31-40-2442489 E-mail. [email protected] May 15, 2002 2 Preface This book originates from several editions of lecture notes that were used as teach- ing material for the course ‘Control Theory for Linear Systems’, given within the framework of the national Dutch graduate school of systems and control, in the pe- riod from 1987 to 1999. The aim of this course is to provide an extensive treatment of the theory of feedback control design for linear, finite-dimensional, time-invariant state space systems with inputs and outputs. One of the important themes of control is the design of controllers that, while achieving an internally stable closed system, make the influence of certain exogenous disturbance inputs on given to-be-controlled output variables as small as possible. In- deed, in the appropriate sense this theme is covered by the classical linear quadratic regulator problem and the linear quadratic Gaussian problem, as well as, more re- cently, by the H2 and H∞ control problems.
    [Show full text]