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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.

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At least 181 records · Page 10
All sourcesNASA NTRSDOE OSTI
NASA NTRS1995

State Estimation of Main Rotor Flap and Lead-Lag Using Accelerometers and Laser Transducers on the RASCAL UH-60 Helicopter

Modern rotorcraft flight control system designs which promise to yield high vehicle response bandwidth and good gust rejection can benefit from the use of rotor-state feedbacks. The measurement of main rotor blade motions is also desirable to validate and improve rotorcraft simulation models, to identify high-order linear flight dynamics models, to provide rotor system health monitoring; during flight test, and to provide for correlation with acoustic measurements from wind tunnel and flight tests. However, few attempts have been made to instrument a flight vehicle in this manner, and no previous system has had the robustness and accuracy required for these diverse applications. A rotor blade motion measurement and estimation system has been developed by NASA and the U.S. Army for use on the Rotorcraft Aircrew Systems Concepts Airborne Laboratory (RASCAL) helicopter. RASCAL is a UH-60 Blackhawk which is being modified at Ames Research Center in a phased development program for use in flight dynamics and controls, navigation, airspace management, and rotorcraft human factors research. The aircraft will feature a full-authority, digital, fly-by-wire research flight control system; a coupled ring laser gyro, differential GPS based navigation system; a stereoscopic color wide field of view helmet, mounted display; programmable panel mounted displays; and advanced navigation sensors. The rotor blade motion system is currently installed for data acquisition only, but will be integrated with the research flight control system when it is installed later this year.

Fletcher, Jay W.↗
DOE OSTI2022

Cross-Layered Cyber-Physical Power System State Estimation towards a Secure Grid Operation

In the Smart Grid paradigm, this critical infrastructure operation is increasingly exposed to cyber-threats due to the increased dependency on communication networks. An adversary can launch an attack on a power grid operation through False Data Injection into system measurements and/or through attacks on the communication network, such as flooding the communication channels with unnecessary data or intercepting messages. A cross-layered strategy that combines power grid data, communication grid monitoring and Machine Learning based processing is a promising solution for detecting cyberthreats. In this paper, an implementation of an integrated solution of a cross-layer framework is presented. The advantage of such a framework is the augmentation of valuable data that enhances the detection of anomalies in the operation of power grid. IEEE 118-bus system is built in Simulink to provide a power grid testing environment and communication network data is emulated using SimComponents. The performance of the framework is investigated under various FDI and communication attacks.

cyber security, network security, cyber-physical s↗