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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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Hot, Cold, or Just Right? Model Predictive Controller (HCJR MPC) v0.1.0
The project seeks to develop new sensor and control technologies that will improve occupant thermal comfort and reduce cooling energy consumption in commercial buildings by minimizing overcooling.
Implementation of Model Predictive Control for Frequency Support in Real-time Digital Simulator.
Abstract not provided.
Model Predictive Control of Energy Storage Systems for Combined Energy Arbitrage and Voltage Regulation.
Abstract not provided.
Implementation of Model Predictive Control for Frequency Support in a Real-time Digital Simulator.
Abstract not provided.
Data-Driven Model Predictive Control for Fast Frequency Support
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Enhancing quantum algorithms through integration with model predictive control concepts
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Enhancing Quantum Algorithms Through Integration with Model Predictive Control Concepts
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Evaluating the Impacts of Weather Forecast Inaccuracy on Performance of Model Predictive Control for Dynamic Facades
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Data-driven subspace predictive control of adaptive optics for high-contrast imaging
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Noise control prediction for high-speed, propeller-driven aircraft
An analytical study is described which explores add-on treatments and advanced concepts for the reduction of noise levels in three high-speed aircraft driven by propellers. Noise reductions of 25 to 28 dB are required to achieve a goal of an A-weighted sound level not greater than 80 dB. It is found that only a double-wall system, with a limp inner wall or trim panel, can achieve the required noise reductions. Weight penalties are estimated for the double-wall treatments. These penalties are 0.75% to 1.51% of the aircraft takeoff weight for the particular baseline designs selected.
Investigation of Reduced-Order Modeling for Aircraft Stability and Control Prediction
High-fidelity computational fluid dynamics tools offer the potential to approximate increments for ground-to-flight scaling effects, as well as to augment the dynamic damping derivative data for motion-based flight simulators. Unfortunately, the computational expense is currently prohibitive for populating a complete simulator database. This work investigates an existing surrogate-based, indicial response reduced-order model methodology as a means to efficiently augment a flight simulator database with high-fidelity nonlinear aerodynamic damping derivatives. Creation of the reduced-order model is based on the superposition integrals of the step response with the derivative of its corresponding input signal. Step responses are calculated using a computational grid motion approach that separates the effects of angle of attack and sideslip angle from angular rates, and rates from angle of attack and sideslip. It is demonstrated that the transients produced during the start of a forced-oscillation motion are captured by the reduced-order model to the level of fidelity of a comparable computational solution. Aerodynamic coefficients computed within minutes by the reduced-order model for an aircraft undergoing an 18-second half Lazy-8 maneuver and a 25-second Immelmann turn maneuver are compared with those from full computational flight solutions that required days to complete. Finally, a cost-benefit assessment is included that demonstrates a compelling advantage for this approach. d for maneuvering, flexible vehicles.
Computational Fluid Dynamics Reduced-Order Modeling for Aircraft Stability & Control Prediction
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Wind-Tunnel Testing for the Second AIAA Stability and Control Prediction Workshop
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Summary of Results for the Second AIAA Stability and Control Prediction Workshop
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Stability and Control Prediction Workshop: STAR-CCM+
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