Flutter Free FLight Envelope expansion for economical Performance improvement FLEXOP

Transcription

1 Flutter Free FLight Envelope expansion for economical Performance improvement FLEXOP Andrés Marcos Technology for AeroSpace Control (TASC) Aerospace Engineering Department University of Bristol, U.K.

2 Layout FLEXOP project University of Bristol Team, Tasks & Work 2

3 FLEXOP Project 3

4 State-of-Practice To remain competitive Europe must develop, consolidate and master advanced technologies for future flexible aircraft The Airbus A350 XWB is setting a new standard of efficiency, with 25% lower fuel consumption compared to current aluminum long-range competitors. It also integrates robust and efficient state-of-the-art systems, such as the fully-electrical flight control system (FCS). which supports the best level of comfort and reliability by controlling the flexible modes in the wings structurally optimized during the aircraft development program. 4

5 State-of-Art U.S. is mastering the technology through a philosophy of bring back the spirit of learning by flying LOCKHEED MARTIN BFF Program Body Freedom Flutter (BFF) IRA and X-56A UoF/NASA Flutterometer Program UMN PAAW Program Performance Adaptive Aeroelastic Wing 5

6 General Description European H2020 Call: MobilityForGrowth Competitiveness of European Aviation through cost efficiency and innovation Start Date: June 2015 Duration: 42 months Consortium: 6 European Countries, 9 Partners 2 Research Centers, 3 Universities and 3 Industrial partners Funding: 6,676,788 Euros 6

7 Consortium Frank Teurich Rafael Palacios Peter Seiler Dagfin Gangsaas 7

8 Aim & Research Objectives Develop multidisciplinary flexible aircraft design capabilities that will increase competitiveness in terms of aircraft development costs. FLEXOP aim will be achieved by development of: a. Aeroelastic tailoring methods and tools: to improve efficiency of currently existing wing and of redesign of derivative wing b. Flutter modelling, analysis and control methods and tools: to enable flying with modified wing at same airspeed as baseline aircraft c. Affordable flight testing platform for experimental validation, followed by a scale-up study demonstrating development cycle. 8

9 Technology Readiness Level (TRL) Goals Increasing the wingspan by a retrofit solution TRL 3/4 (proven using numeric models of the XRF1) Passive load alleviation by aeroelastic tailoring TRL 5 validated by shape and loads monitoring during flight test Flutter modelling, prediction and control methods & tools TRL 5 validated by pre & post flutter flight tests Interdisciplinary development cycle TRL 3 9

10 Approach Move towards methods and tools enabling multidisciplinary design, analysis and optimization in the aeroservoelastic domain 10

11 Work Breakdown Structure WP number Title Lead WP1 Wing design using aeroelastic tailoring methods FACC WP2 Flutter Prediction and Control Design Methods UOB WP3 Flutter Management Demonstrator TUM WP4 Assessment, Validation & Scale-Up Issues AGI-G WP5 Coordination, Exploitation and Dissemination Management SZTAKI 11

12 Demonstrators Examples Lockheed Martin MUTT demonstrator, 3 m span, Flutter speed 44KEAS TUM IMPULLS UAV, 5m span, MTOW = 25 kg 12

13 UoB Team & Tasks 13

14 WP2 Methods and tools for flutter modelling, prediction and control 14

15 WP2 tasks Task 2.1: Control Oriented Flexible Aircraft Modelling (DLR) Goal: develop LFT and LPV models for flight and flutter control Inputs: WP1 flutter models for -1/-2 wings (from CFD, FEM) Task 2.2: Flutter Analysis Methodologies (UoB) Goal: Develop techniques for flutter analysis and prediction to determine [i] flight envelop limits [2] predict flutter [3] analyze flutter suppression Methods: [1] Standard methods: P-K (linear) and UVLM (FEM-time) [2] Robust methods: Bifurcation (nonlinear) and (linear) Task 2.3: Flexible Aircraft Control Methodologies (AGI-G) Goal: Design the rigid and flexible control laws for 0/-1/-2 wings Methods: [1] Decoupled: rigid then flexible filters or flutter suppression [2] Integrated: architectures and methods combining above 15

16 FLEXOP UoB: Team Dr. Andrés Marcos Principal Investigator Prof. Mark Lowenberg Co-Investigator Dr. Nandor Terkovics Research Associate LFT/LPV modelling, On-board flutter analysis Dr. Iman S. Delshad Research Associate On-board flutter suppression Mr. Andrea Iannelli PhD candidate Off-board Mu + Bifurcation analysis 16

17 FLEXOP UoB: Tasks Task2.1 Rigid and flexible aircraft modelling Using linear fractional transformation (LFT) & linear parameter varying (LPV) methods Task2.2 Flutter analysis and prediction: Using nonlinear (bifurcation) and linear (mu+lft) methods Task2.3 Flutter control & suppression: Using robust linear methods: H-infinity, mu, LPV 17

18 Robust Flutter Analysis: Uncertainty Modelling A Linear Fractional Transformation (LFT) is a nonlinear system where the known linear component (M) is clearly separated from the uncertain/varying/nonlinear component ( ) in a very specific structure y FU ( M, ) u F U 1 22 M 21 ( I M11 ) ( M, ) M M 12 Uncertainty matrix : bounded, < 1 complex / real, LTI / LTV / NL param = parametric TV = time-varying NL = nonlinear = modelling 18

19 Robust Flutter Analysis: analysis Given an uncertainty system in LFT format, the Structured Singular Value ( )is defined as: # Note that it is a frequency domain analysis, ( ) LTI # Singular values ( ) are the multivariable generalization of eigenvalues # We look at the instability border, i.e. imaginary axis det(i- M)=0 # Size of uncertainty is =1 / (M) 19

20 Robust Flutter Analysis: analysis Difficult to calculate exactly (NP-hard) so we use bounds For pure real uncertainty Typically only used in binomial mode: > 1 violation of objective Sometimes in phase-plane mode: 20

21 Conclusions 21

22 Conclusion & Challenges FLEXOP aims to develop a multidisciplinary aircraft design process To increase EU competitiveness in terms of aircraft development costs Multidisciplinary aspects in many ways: Different disciplines (structural dynamics, aeroelastic tailoring, control) Different background (industry, universities, research labs) Very ambitious goals: Mature interdisciplinary tools and methods Build & flight test 3 versions of FLEXOP flight demonstrator Scale-up the results 22