TECHNOLOGY AREAS: Air Platform

OBJECTIVE: Develop an experimentally validated high fidelity nonlinear lag damper model that accurately predicts behavior of passive and semi-active or active lag dampers for a range of temperatures, amplitudes, and frequency range, for implementation into a comprehensive rotorcraft analysis system for rotor loads prediction.

DESCRIPTION: The use of a Health and Usage Monitoring System (HUMS) facilitates the monitoring of critical systems on helicopters, including rotor system, drive train, engines and life-limited components [1]. Rotors and their associated dynamic components operate in high-cycle and environmentally challenging conditions. To maximize the benefits of HUMS for rotor and dynamic components, accurate load prediction via a comprehensive rotorcraft analysis tool are crucial to conduct fatigue analysis and determine Remaining Useful Life (RUL). The key challenge in effectively predicting the lead-lag motions and resulting rotor loads is the lack of a high fidelity lag damper model.

Lag dampers are typically passive [2], and incorporate elastomeric [3], hydraulic [4-6], or adaptive damping capabilities based on smart fluids [7-8]. These dampers are integrated into existing rotor heads to augment stability of in-plane rotor bending modes while the helicopter is on the ground (i.e. mitigation of ground resonance) or in high speed forward flight (i.e. air resonance). Because lag dampers must be implemented in the rotor hub to augment rotor stability, innovative analysis is critical for the coupling between dampers and rotor blade motion. The complex behavior of lag dampers provides significant challenges for modeling such devices even for passive configurations. Current analytical models oversimplify the complexity of the operational environment and make assumptions about operating parameters, thus hindering an accurate prediction of damping.

Recently, semi-active or active lag dampers have been introduced with a goal of improving rotor stability via a feedback control system to compensate for substantial losses in damping capacity in passive elastomeric dampers as the amplitude of lead-lag excitation increases [2, 5]. Such losses of damping capacity in the face of excitation amplitude increases, dual frequency excitation, and increases in temperature due to self-heating and ambient temperature, remain a challenge in lag damper development that could be aided by effective damper models.

A high fidelity lag damper model is sought that can predict stiffness and damping forces over a wide range of amplitudes, temperatures, and frequencies. Proposed models should successfully predict the onset of resonance phenomena, resulting fatigue loads arising from damper implementation and their impact on rotor and dynamic components. The required outcome for this topic is an innovative and comprehensive approach to the prediction of stiffness and damping forces introduced by lag dampers having different configurations (e.g. snubber vs. linear stroke), materials, and feedback control strategies.

The lag damper model should be able to:
1) Predict the stiffness and damping of lag dampers comprising of elastomeric and/or (smart) fluidic components using appropriate material test data;
2) Predict forces induced by stiffness and damping for an appropriate range of amplitudes, temperatures (-50 to 120 degrees Fahrenheit based on altitude-dependent temperature profile) and frequencies (up to 40 Hz or 5/rev) representative of full scale lag dampers;
3) Predict performance improvements in stability augmentation and vibration loads reduction when implementing passive or semi-active (e.g., elastomeric, hydraulic, and/or fluid-elastomeric) lag dampers with feedback control; and
4) Integrate damper modeling approach with existing and future comprehensive rotor analysis codes.

PHASE I: Using existing data from the literature, develop innovative concepts for accurately predicting the lag damper behavior in response to both single and multi-harmonic steady state sinusoidal excitation, as well as transient excitation, for dampers comprising elastomeric materials and/or (smart) fluidic components. Incorporate effects of temperature dependent behaviors into this framework. Demonstrate via rotor analysis the benefits that would be expected (both in performance and computational capability) when implementing this analysis framework in a comprehensive rotor analysis. Develop a plan to experimentally validate the analysis at the component and rotor level.

PHASE II: Implement the concepts developed under Phase I and develop a prototype predictive analysis tool. Initiate verification and validation of the analysis tool through a demonstration showing predictive simulations track damper loads, and damping capacity, and that the predictive analysis can be readily incorporated into a comprehensive rotor analysis. Assess the effects of damper behavior, with and without adaptive control, on rotor loads.

PHASE III: Refine and expand the simulation capability to handle specific lag damper configurations. Develop and execute technology transfer plan to enable comprehensive rotor analysis codes to exploit this new lag damper simulation capability across the industry.

PRIVATE SECTOR COMMERCIAL POTENTIAL/DUAL-USE APPLICATIONS: This lag damper analysis system will have broad application to both civilian and military helicopter systems.

REFERENCES:
1. Maley, S., Plets, J., Phan, N.D. "US Navy Roadmap to Structural Health and Usage Monitoring - The Present and Future" Presented at the American Helicopter Society 63rd Annual Forum, Virginia Beach, VA, May 1-3, 2007 (www.vtol.org)

2. Panda, B., Mychalowycz, E., & Tarzanin, F. (1996). Application of Passive Dampers to Modern Helicopters. "Smart Materials and Structures", 5(5), 509-516.

3. Hausmann, G., & Gergely, P. (1992). Proceedings from the 18th European Rotorcraft Forum: "Approximate Methods for Thermoviscoelastic Characterization and Analysis of Elastomeric Lead-lag Dampers." Avignon, France.

4. Jones, P., Russell, D., & McGuire, P. (2003). Proceedings from the American Helicopter Society 59th Annual Forum: "Latest Development in Fluidlastic® Lead-Lag Dampers for Vibration Control in Helicopters." Phoenix, Arizona.

5. Wereley, N.M., Snyder, R., Krishnan, R., Sieg, T. (2001). Helicopter Damping. "Encyclopedia of Vibration", Academic Press, London, UK, 2, 629-642.

6. Hu, W., and Wereley, N.M. (2007). A Distributed Rate-Dependent Elasto-Slide Model for Elastomeric Lag Dampers. "AIAA Journal of Aircraft", 44(6):1972-1984.

7. Kothera, C.S., Ngatu, G., & Wereley, N.M. (2009). Proceeding from 65th Annual Forum of the American Helicopter Society: "Control Evaluations of a Magneto-Rheological Fluid Elastomeric (MRFE) Lag Damper for Helicopter Rotor Blades." Grapevine, TX.

8. Ngatu, G.T., Wereley, N.M., & Kothera, C.S. (2009). Proceedings from 65th Annual Forum of the American Helicopter Society: "Hydromechanical Analysis of a Fluid-Elastomeric Lag Damper Incorporating Temperature Effects." Grapevine, TX.

KEYWORDS: Helicopter; Rotorcraft; Rotor Load; Lag Damper; Nonlinear; Analysis

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