1. Further Results of Soft-Inplane Tiltrotor Aeromechanics Investigation Using Two Multibody Analyses Pierangelo Masarati Assistant Professor Dipartimento di Ingegneria Aerospaziale Politecnico di Milano (Italy) AHS International 60th Annual Forum & Technology Display Baltimore, MD - Inner Harbor June 7-10, 2004

2. Authors and Contributors David J. Piatak NASA Langley Research Center David J. Piatak NASA Langley Research Center Jeffrey D. Singleton Army Research Laboratory Jeffrey D. Singleton Army Research Laboratory Giuseppe Quaranta Politecnico di Milano Giuseppe Quaranta Politecnico di Milano

3. Outline Objectives and Approach Objectives and Approach Experimental Model Description Experimental Model Description Multibody Dynamics Analyses Multibody Dynamics Analyses Key Analytical Results Key Analytical Results Isolated Blade & Hub Results Isolated Blade & Hub Results Control System Couplings Control System Couplings Hover Performance & Stability Hover Performance & Stability Forward Flight Stability Forward Flight Stability Selected Nonlinear Analysis Issues Selected Nonlinear Analysis Issues Concluding Remarks Concluding Remarks

4. Objectives Compare multibody analytical techniques Compare multibody analytical techniques Develop fundamental understanding of strengths, weaknesses, and capabilities of two different codes Develop fundamental understanding of strengths, weaknesses, and capabilities of two different codes Assess prediction capabilities Assess prediction capabilities Compare response, loads, and aeroelastic stability in Compare response, loads, and aeroelastic stability in hover & forward flight. hover & forward flight. Analysis vs. analysis Analysis vs. analysis Analysis vs. experiment Analysis vs. experiment Assess code/user fidelity Assess code/user fidelity Two different multibody codes Two different multibody codes Two different researchers Two different researchers Contrasting two codes helps eliminate errors in modeling Contrasting two codes helps eliminate errors in modeling

5. Experimental Model Wing & Rotor Aeroelastic Test System (WRATS) Tested in the Rotorcraft Hover Test Facility and the Transonic Dynamics Tunnel at NASA Langley Research Center Semi-Articulated Soft-Inplane Hub (SASIP) 4 blades 4 blades articulated articulated soft-inplane soft-inplane elastomeric lag damper elastomeric lag damper

6. Multibody Analyses Time domain - analyze via virtual experiments Time domain - analyze via virtual experiments Can model components and mechanical effects not typically included with comprehensive rotor analyses Can model components and mechanical effects not typically included with comprehensive rotor analyses Hydraulic components Hydraulic components Mechanical joints Mechanical joints Free-play in linkages Free-play in linkages No fixed-hub assumption No fixed-hub assumption

7. Analytical Models & Analysts MBDyn - MultiBody Dynamics MBDyn - MultiBody Dynamics Developed by (a team led by) Prof. Paolo Mantegazza, Politecnico di Milano Developed by (a team led by) Prof. Paolo Mantegazza, Politecnico di Milano WRATS-SASIP analyzed by Pierangelo Masarati and Giuseppe Quaranta WRATS-SASIP analyzed by Pierangelo Masarati and Giuseppe Quaranta DYMORE DYMORE Developed by (a team led by) Prof. Olivier Bauchau, Georgia Tech Developed by (a team led by) Prof. Olivier Bauchau, Georgia Tech WRATS-SASIP analyzed by Dave Piatak and Jinwei Shen WRATS-SASIP analyzed by Dave Piatak and Jinwei Shen

8. MBDyn - Analytical Model Swashplate mechanics Swashplate mechanics Hydraulic actuators Hydraulic actuators Blades as composite- ready beams, with blade element aerodynamics Blades as composite- ready beams, with blade element aerodynamics Wing as modal element, with state-space aerodynamics Wing as modal element, with state-space aerodynamics Analysis includes: Analysis includes: Conventional WRATS Model

9. DYMORE - Analytical Model Blade Model Blade Model 4 element FEM 4 element FEM Lifting line Lifting line 3D inflow model 3D inflow model Highly twisted: 34 degrees from root to tip Highly twisted: 34 degrees from root to tip Structural and geometrical properties tuned to match WRATS SASIP ground vibration test results Structural and geometrical properties tuned to match WRATS SASIP ground vibration test results

10. DYMORE Simulation Example

11. Blade Modal Analysis All analyses consistent All analyses consistent Results agree with experiment Results agree with experiment 108.49106.58103.50107.94T1 61.4562.4364.2061.15F3 18.5119.3720.0121.7F2 6.466.326.436.46L1 0.690.670.76-F1DYMOREMBDynUMARCMeasuredMode

12. Control System Couplings Typically difficult to model. Elastic deformation can have a significant contribution. Typically difficult to model. Elastic deformation can have a significant contribution. Non-linear modeling - classical analyses typically use constant or tabulated lookup coefficients. Non-linear modeling - classical analyses typically use constant or tabulated lookup coefficients. Multibody codes capture nonlinear effect. Multibody codes capture nonlinear effect.

13. Hover Run-up Current analytical model is a simple, constant stiffness equivalent spring hinge Current analytical model is a simple, constant stiffness equivalent spring hinge

14. Hover Performance Blade elasticity and geometrical cross-couplings greatly influence performance predictions Blade elasticity and geometrical cross-couplings greatly influence performance predictions

15. Hover Dynamics Transient time-series correlate with frequency analysis Linear wind-up

16. Forward Flight Stability Comparison of generic soft- stiff inplane wing mode damping, Windmillingconfiguration

17. Forward Flight Stability Comparison of generic soft-stiff inplane wing mode damping in powered and windmill. Windmilling case correlates well. Initial results for powered mode did not (no drive system dynamics)

18. Powered Flight Damping Bucket Experimental evidence of high damping in wing beam mode in powered flight, with low damping bucket around zero torque Experimental evidence of high damping in wing beam mode in powered flight, with low damping bucket around zero torque High damping found in coupling with drive train dynamics High damping found in coupling with drive train dynamics Possible bucket explanation found by considering deadband in drive train Possible bucket explanation found by considering deadband in drive train

19. Powered Flight Damping Bucket Stiff-inplane experimental results have generally show only small differences in wing damping between powered and wind- milling flight mode. Stiff-inplane experimental results have generally show only small differences in wing damping between powered and wind- milling flight mode. Soft-inplane experimental results have significant differences. Soft-inplane experimental results have significant differences. Reason is chance coupling of drive dynamics with wing: Reason is chance coupling of drive dynamics with wing:

20. Powered Flight Damping Bucket Deadband yields windmill- like damping Deadband yields windmill- like damping Soft mast slope controls bucket width Soft mast slope controls bucket width

21. Powered Flight Damping Bucket

22. Damping peaks at bucket borders may be explained with identification close to deadband transition Damping peaks at bucket borders may be explained with identification close to deadband transition

23. Concluding Remarks Multibody codes can: Multibody codes can: successfully model complex systems successfully model complex systems improve predictions of rotorcraft dynamic behavior improve predictions of rotorcraft dynamic behavior proficiently address nonlinearity issues proficiently address nonlinearity issues Next steps are: Next steps are: Conversion / maneuver simulations Conversion / maneuver simulations Hub/blade maneuver loads correlation Hub/blade maneuver loads correlation Parametric study of SASIP Parametric study of SASIP

24. Special Thanks To - Giampiero Bindolino (Politecnico di Milano, Dipartimento di Ingegneria Aerospaziale) Giampiero Bindolino (Politecnico di Milano, Dipartimento di Ingegneria Aerospaziale) Mark W. Nixon (ARL: Army Research Laboratory, Vehicle Technology Directorate) Mark W. Nixon (ARL: Army Research Laboratory, Vehicle Technology Directorate) Jinwei Shen (NIA: National Institute of Aerospace) Jinwei Shen (NIA: National Institute of Aerospace)