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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 NTRS1986

Mission Adaptive Wing test program

With the completion of the F-111 test-bed Mission Adaptive Wing (MAW) test program's manual flight control system, emphasis has been shifted to flight testing of MAW automatic control modes. These encompass (1) cruise camber control, (2) maneuver camber control, (3) maneuver load control, and (4) maneuver enhancement and load alleviation control. The aircraft is currently cleared to a 2.5-g maneuvering limit due to generally higher variable-incidence wing pivot loads than had been anticipated, especially at the higher wing-camber settings. Buffet is noted to be somewhat higher than expected at the higher camber settings.

Birk, Frank T.↗
NASA NTRS1974

Vehicle design considerations for active control application to subsonic transport aircraft

The state of the art in active control technology is summarized. How current design criteria and airworthiness regulations might restrict application of this emerging technology to subsonic CTOL transports of the 1980's are discussed. Facets of active control technology considered are: (1) augmentation of relaxed inherent stability; (2) center-of-gravity control; (3) ride quality control; (4) load control; (5) flutter control; (6) envelope limiting, and (7) pilot interface with the control system. A summary and appraisal of the current state of the art, design criteria, and recommended practices, as well as a projection of the risk in applying each of these facets of active control technology is given. A summary of pertinent literature and technical expansions is included.

Hofmann, L. G.↗
NASA NTRS1976

B-52 control configured vehicles: Flight test results

Recently completed B-52 Control Configured Vehicles (CCV) flight testing is summarized, and results are compared to analytical predictions. Results are presented for five CCV system concepts: ride control, maneuver load control, flutter mode control, augmented stability, and fatigue reduction. Test results confirm analytical predictions and show that CCV system concepts achieve performance goals when operated individually or collectively.

Arnold, J. I.↗
NASA NTRS1980

Multicyclic control of a helicopter rotor considering the influence of vibration, loads, and control motion

Weighted multiple linear regression is used to establish a transfer function matrix relationship between higher harmonic control inputs and transducer vibration outputs for a controllable twist rotor. Data used in the regression were taken from the test of a KAMAN controllable twist rotor conducted in the Ames Research Center's 40- by 80-Foot Wind Tunnel in June 1977. Optimal controls to minimize fixed system vibrational levels are calculated using linear quadratic regulatory theory with a control deflection penalty included in the performance criteria. Control sensitivity to changes in control travel, forward speed, and lift and propulsive forces is examined. It is found that the linear transfer matrix is a strong function of forward speed and a weak function of lift and propulsive force. An open-loop strategy is proposed for systems with limited control travel.

Brown, T. J.↗
NASA NTRSDate not supplied

Structural Design and Aeromechanical Analysis of Unconventional Blades for Future Mars Rotorcraft

The structural design for rotor blades with thin, unconventional airfoils for Earth-based testing is obtained using three-Dimensional (3D) aeromechanical analysis. This analysis is in support of the NASA ROAMX project. The outer mold was provided by NASA, but the internal structural design was developed at the University of Maryland and is presented here, along with a thorough aeromechanical analysis. The main objectives are to verify the structural integrity of the design and understand the unique aeroelastic behavior of the non-conventional airfoils designed for low-Reynolds number and high-Mach number flow. Six different blade models are considered, with the pitch axis varied from quarter-chord to mid-chord to determine the effect of C.G. offset on natural frequencies, blade deformations, root loads, and 3D stresses. All six blade designs are first studied under rotation in pure vacuum, and significant reductions in root loads and 3D stresses are achieved by moving the pitch axis closer to mid-chord to reduce the C.G. offset. Based on the vacuum analysis, the blade design with the pitch axis at 40% chord is selected for aerodynamic analysis. The blade control load, airloads, deformations, and 3D stresses are studied for steady hover. Dynamic control load and dynamic 3D stresses are studied for unsteady hover achieved using cyclic. Significant elastic twist is observed due to the trapeze effect and propeller moment, affecting the spanwise distribution of aerodynamic loads on the blades. However, the effect of aerodynamic loads on 3D stresses and the blade control load is found to be minimum. The dynamic control load is found to increase significantly due to inertial coupling from the C.G. offset. The dynamic stresses also increase, although still have factors of safety greater than two for both tensile and compressive stress.

Structural Design↗
DOE OSTI2018

Assessment of Optimal Flexibility in Ensemble of Frequency Responsive Loads

Potential of electrical loads in providing grid ancillary services is often limited due to the uncertainties associated with the load behavior. A knowledge of the expected uncertainties with a load control program would invariably yield to better informed control policies, opening up the possibility of extracting the maximal load control potential without affecting grid operations. In the context of frequency responsive load control, a probabilistic uncertainty analysis framework is presented to quantify the expected error between the target and actual load response, under uncertainties in the load dynamics. A closed-form expression of an optimal demand flexibility, minimizing the expected error in actual and committed flexibility, is provided. Analytical results are validated through Monte Carlo simulations of ensembles of electric water heaters.

Kundu, Soumya↗
DOE OSTI2023

Impact of Open Communication Networks on Load Frequency Control with Plug-In Electric Vehicles by Cyber-Physical Dynamic Co-Simulation

With the increasing electrification of the transportation sector to achieve the carbon neutrality objective, despite the challenges of charging electric vehicles (EV), there are also opportunities through smart charging EVs to improve system frequency stability; however, EV control technologies might require nontraditional communication support. This paper investigates the impacts of communication variations of EV on power system load frequency control through a cyber-physical dynamic system (CPDS) co-simulation. Here, the CPDS is built upon our previously developed transmission-and-distribution dynamic co-simulation model with the added communication variation functions (i.e., delay and packet loss). The case studies consider multiple communication variation scenarios when the system experiences an N-1 generation trip contingency. The scenarios include communication delays and packet loss using both homogeneous and heterogeneous assumptions. The outcomes of this work can help improve EV frequency regulation services and provide robust and effective tests for different load frequency control algorithms of the future power systems.

ADVANCED PROPULSION SYSTEMS,ENERGY PLANNING, POLIC↗
DOE OSTI2016

Aggregate modeling of fast-acting demand response and control under real-time pricing

This paper develops and assesses the performance of a short-term demand response (DR) model for utility load control with applications to resource planning and control design. Long term response models tend to underestimate short-term demand response when induced by prices. This has two important consequences. First, planning studies tend to undervalue DR and often overlook its benefits in utility demand management program development. Second, when DR is not overlooked, the open-loop DR control gain estimate may be too low. This can result in overuse of load resources, control instability and excessive price volatility. Our objective is therefore to develop a more accurate and better performing short-term demand response model. We construct the model from first principles about the nature of thermostatic load control and show that the resulting formulation corresponds exactly to the Random Utility Model employed in economics to study consumer choice. The model is tested against empirical data collected from field demonstration projects and is shown to perform better than alternative models commonly used to forecast demand in normal operating conditions. The results suggest that (1) existing utility tariffs appear to be inadequate to incentivize demand response, particularly in the presence of high renewables, and (2) existing load control systems run the risk of becoming unstable if utilities close the loop on real-time prices.

Aggregate Modeling↗
DOE OSTI2014

Fast DR: Controlling Small Loads over the Internet

Current state-of-the-art demand response systems are expensive due to extreme reliability constraints in telemetry, control, and metering. The typical cost of enabling a site for regulation services is between $50k and $80k. These costs are orders of magnitude too high for small loads to participate in high-value grid services. Traditional demand response (DR) schedules events in advance and provides basic on/off control. We developed fast DR measurement and communication technologies, which are scalable cost-effective demand response systems with sufficient reliability for real-time control and monitoring of loads over the internet, and we demonstrated an example system for under $100. We installed FastDR systems for lighting, motor, and thermostat control along with power metering at a total of 10 sites, including 6 commercial buildings and 4 residential buildings. This demonstration addressed the following important methodological questions: 1) Can we reliably control loads simultaneously and with low latency across multiple sites within a specified response time; 2) How reliable is using the internet or 4G cellular network as the mode of control and metering; and 3) Can existing Smart Meters provide data for real-time telemetry services. Testing shows fast DR is capable of control to response in 4 seconds and loads complete transition in seconds to less than one minute depending on load type. We demonstrated 4s regulation services and synchronized load control, and we successfully met specifications for ancillary services across the US. Telemetry via the 4G cellular network demonstrated 94.5% success rate, and residential Internet demonstrated a 98% success rate.

Kiliccote, Sila↗
NASA NTRS1993

SSF loads and controllability during assembly

The Orbiter Primary Reaction Control System (PRCS) pulse width and firing frequency is restricted to prevent excessive loads in the Space Station Freedom (SSF). The feasibility of using the SSF Control Moment Gyros (CMG) as a secondary controller for load relief is evaluated. The studies revealed the CMG not only reduced loads but were useful for other SSF functions: vibration suppression and modal excitation. Vibration suppression lowers the g level for the SSF micro-g experiments and damps the low frequency oscillations that cause crew sickness. Modal excitation could be used for the modal identification experiment and health monitoring. The CMG's reduced the peak loads and damped the vibrations. They were found to be an effective multi-purpose ancillary device for SSF operation.

Larson, Charles R.↗
DOE OSTI2017

Optimal Load-Side Control for Frequency Regulation in Smart Grids

Frequency control rebalances supply and demand while maintaining the network state within operational margins. It is implemented using fast ramping reserves that are expensive and wasteful, and which are expected to become increasingly necessary with the current acceleration of renewable penetration. The most promising solution to this problem is the use of demand response, i.e., load participation in frequency control. Yet it is still unclear how to efficiently integrate load participation without introducing instabilities and violating operational constraints. In this paper, we present a comprehensive load-side frequency control mechanism that can maintain the grid within operational constraints. In particular, our controllers can rebalance supply and demand after disturbances, restore the frequency to its nominal value, and preserve interarea power flows. Furthermore, our controllers are distributed (unlike the currently implemented frequency control), can allocate load updates optimally, and can maintain line flows within thermal limits. We prove that such a distributed load-side control is globally asymptotically stable and robust to unknown load parameters. We illustrate its effectiveness through simulations.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2014

Recovery Act: Advanced Load Identification and Management for Buildings

In response to the U.S. Department of Energy (DoE)’s goal of achieving market ready, net-zero energy residential and commercial buildings by 2020 and 2025, Eaton partnered with the Department of Energy’s National Renewable Energy Laboratory (NREL) and Georgia Institute of Technology to develop an intelligent load identification and management technology enabled by a novel “smart power strip” to provide critical intelligence and information to improve the capability and functionality of building load analysis and building power management systems. Buildings account for 41% of the energy consumption in the United States, significantly more than either transportation or industrial. Within the building sector, plug loads account for a significant portion of energy consumption. Plug load consumes 15-20% of building energy on average. As building managers implement aggressive energy conservation measures, the proportion of plug load energy can increase to as much as 50% of building energy leaving plug loads as the largest remaining single source of energy consumption. This project focused on addressing plug-in load control and management to further improve building energy efficiency accomplished through effective load identification. The execution of the project falls into the following three major aspects; An intelligent load modeling, identification and prediction technology was developed to automatically determine the type, energy consumption, power quality, operation status and performance status of plug-in loads, using electric waveforms at a power outlet level. This project demonstrated the effectiveness of the developed technology through a large set of plug-in loads measurements and testing; A novel “Smart Power Strip (SPS) / Receptacle” prototype was developed to act as a vehicle to demonstrate the feasibility of load identification technology as a low-cost, embedded solution; and Market environment for plug-in load control and management solutions, in particular, advanced power strips (APSs) was studied. The project evaluated the market potential for Smart Power Strips (SPSs) with load identification and the likely impact of a load identification feature on APS adoption and effectiveness. The project also identified other success factors required for widespread APS adoption and market acceptance. Even though the developed technology is applicable for both residential and commercial buildings, this project is focused on effective plug-in load control and management for commercial buildings, accomplished through effective load identification. The project has completed Smart Receptacle (SR) prototype development with integration of Load ID, Control/Management, WiFi communication, and Web Service. Twenty SR units were built, tested, and demonstrated in the Eaton lab; eight SR units were tested in the National Renewable Energy Lab (NREL) for one-month of field testing. Load ID algorithm testing for extended load sets was conducted within the Eaton facility and at local university campuses. This report is to summarize the major achievements, activities, and outcomes under the execution of the project.

24 POWER TRANSMISSION AND DISTRIBUTION↗