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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 1,297 records · Page 72
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

An evaluation of the demand response potential of integrated dynamic window and HVAC systems

Demand response (DR) increases the flexibility and reliability of the electricity grid as use of intermittent renewable energy sources increases. HVAC and envelope DR measures present the largest aggregate energy and peak demand savings potential of all commercial building end uses because their net demand savings occur during critical peak demand periods. Controllable envelope measures include switchable electrochromic windows, operable window attachments such as outdoor louvers, roller shades, and awnings, as well as other innovative facade technologies that can modulate both solar heat gain and daylight admission over a broad solar-optical range. This study evaluated the technical potential of DR-enabled dynamic windows to reduce critical peak demand for a prototypical medium office building situated in all 16 U.S. climates. Model predictive control (MPC) algorithms were designed to minimize electricity cost in daylit perimeter office zones through control of an electrochromic window with and without HVAC thermostat setpoint control. Conventional and time-of-use rates were used to shape the degree of DR. Median annual peak demand savings with window and thermostat control across all climate zones were 24.3 kW (4.4 W/m 2 ) per building or 15.9 W/m 2 for non-north perimeter zones. Resource adequacy at the whole building level was estimated to be 13.1 to 43.4 $/kW per year over the 30-year life of the installation. Co-benefits were increased energy efficiency, and reduced electricity cost and emissions. Visual and thermal comfort requirements were met at all times. Dynamic facades controlled by MPC have substantial technical potential for DR across all U.S. climates and warrant serious consideration for inclusion in DR portfolios.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
NASA NTRS1984

Optical systolic solutions of linear algebraic equations

The philosophy and data encoding possible in systolic array optical processor (SAOP) were reviewed. The multitude of linear algebraic operations achievable on this architecture is examined. These operations include such linear algebraic algorithms as: matrix-decomposition, direct and indirect solutions, implicit and explicit methods for partial differential equations, eigenvalue and eigenvector calculations, and singular value decomposition. This architecture can be utilized to realize general techniques for solving matrix linear and nonlinear algebraic equations, least mean square error solutions, FIR filters, and nested-loop algorithms for control engineering applications. The data flow and pipelining of operations, design of parallel algorithms and flexible architectures, application of these architectures to computationally intensive physical problems, error source modeling of optical processors, and matching of the computational needs of practical engineering problems to the capabilities of optical processors are emphasized.

Neuman, C. P.↗
NASA NTRS1986

Electronic controls and displays for a Space Station workstation

A workstation to serve as a man/machine interface for one of the test beds used in the NASA-Space Station development effort is described which will also serve as a demonstrator of the advanced technologies anticipated for the Space Station workstation. Thin-film electroluminescent flat-panels may replace the presently used CRTs for image generation, and the development of multifunctional controls, advanced graphic generators, and videodisc technology are considered. A generalized window management algorithm will control the large volume of information required, and conventional office automation tools such as spread sheets and database managers will be applied to workstation image management.

Busquets, A. M.↗
NASA NTRS1999

Active Control of Inlet Noise on the JT15D Turbofan Engine

This report presents the key results obtained by the Vibration and Acoustics Laboratories at Virginia Tech over the year from November 1997 to December 1998 on the Active Noise Control of Turbofan Engines research project funded by NASA Langley Research Center. The concept of implementing active noise control techniques with fuselage-mounted error sensors is investigated both analytically and experimentally. The analytical part of the project involves the continued development of an advanced modeling technique to provide prediction and design guidelines for application of active noise control techniques to large, realistic high bypass engines of the type on which active control methods are expected to be applied. Results from the advanced analytical model are presented that show the effectiveness of the control strategies, and the analytical results presented for fuselage error sensors show good agreement with the experimentally observed results and provide additional insight into the control phenomena. Additional analytical results are presented for active noise control used in conjunction with a wavenumber sensing technique. The experimental work is carried out on a running JT15D turbofan jet engine in a test stand at Virginia Tech. The control strategy used in these tests was the feedforward Filtered-X LMS algorithm. The control inputs were supplied by single and multiple circumferential arrays of acoustic sources equipped with neodymium iron cobalt magnets mounted upstream of the fan. The reference signal was obtained from an inlet mounted eddy current probe. The error signals were obtained from a number of pressure transducers flush-mounted in a simulated fuselage section mounted in the engine test cell. The active control methods are investigated when implemented with the control sources embedded within the acoustically absorptive material on a passively-lined inlet. The experimental results show that the combination of active control techniques with fuselage-mounted error sensors and passive control techniques is an effective means of reducing radiated noise from turbofan engines. Strategic selection of the location of the error transducers is shown to be effective for reducing the radiation towards particular directions in the farfield. An analytical model is used to predict the behavior of the control system and to guide the experimental design configurations, and the analytical results presented show good agreement with the experimentally observed results.

Smith, Jerome P.↗
NASA NTRS2017

Multi-Objective Reinforcement Learning-Based Deep Neural Networks for Cognitive Space Communications

Future communication subsystems of space exploration missions can potentially benefit from software-defined radios (SDRs) controlled by machine learning algorithms. In this paper, we propose a novel hybrid radio resource allocation management control algorithm that integrates multi-objective reinforcement learning and deep artificial neural networks. The objective is to efficiently manage communications system resources by monitoring performance functions with common dependent variables that result in conflicting goals. The uncertainty in the performance of thousands of different possible combinations of radio parameters makes the trade-off between exploration and exploitation in reinforcement learning (RL) much more challenging for future critical space-based missions. Thus, the system should spend as little time as possible on exploring actions, and whenever it explores an action, it should perform at acceptable levels most of the time. The proposed approach enables on-line learning by interactions with the environment and restricts poor resource allocation performance through virtual environment exploration. Improvements in the multiobjective performance can be achieved via transmitter parameter adaptation on a packet-basis, with poorly predicted performance promptly resulting in rejected decisions. Simulations presented in this work considered the DVB-S2 standard adaptive transmitter parameters and additional ones expected to be present in future adaptive radio systems. Performance results are provided by analysis of the proposed hybrid algorithm when operating across a satellite communication channel from Earth to GEO orbit during clear sky conditions. The proposed approach constitutes part of the core cognitive engine proof-of-concept to be delivered to the NASA Glenn Research Center SCaN Testbed located onboard the International Space Station.

space archtiecture↗
NASA NTRS2017

Multi-Objective Reinforcement Learning-based Deep Neural Networks for Cognitive Space Communications

Future communication subsystems of space exploration missions can potentially benefit from software-defined radios (SDRs) controlled by machine learning algorithms. In this paper, we propose a novel hybrid radio resource allocation management control algorithm that integrates multi-objective reinforcement learning and deep artificial neural networks. The objective is to efficiently manage communications system resources by monitoring performance functions with common dependent variables that result in conflicting goals. The uncertainty in the performance of thousands of different possible combinations of radio parameters makes the trade-off between exploration and exploitation in reinforcement learning (RL) much more challenging for future critical space-based missions. Thus, the system should spend as little time as possible on exploring actions, and whenever it explores an action, it should perform at acceptable levels most of the time. The proposed approach enables on-line learning by interactions with the environment and restricts poor resource allocation performance through virtual environment exploration. Improvements in the multiobjective performance can be achieved via transmitter parameter adaptation on a packet-basis, with poorly predicted performance promptly resulting in rejected decisions. Simulations presented in this work considered the DVB-S2 standard adaptive transmitter parameters and additional ones expected to be present in future adaptive radio systems. Performance results are provided by analysis of the proposed hybrid algorithm when operating across a satellite communication channel from Earth to GEO orbit during clear sky conditions. The proposed approach constitutes part of the core cognitive engine proof-of-concept to be delivered to the NASA Glenn Research Center SCaN Testbed located onboard the International Space Station.

space archtiecture↗
NASA NTRS1981

Test results of flight guidance for fuel conservative descents in a time-based metered air traffic environment

The NASA developed, implemented, and flight tested a flight management algorithm designed to improve the accuracy of delivering an airplane in a fuel-conservative manner to a metering fix at a time designated by air traffic control. This algorithm provides a 3D path with time control (4D) for the TCV B-737 airplane to make an idle-thrust, clean configured (landing gear up, flaps zero, and speed brakes retracted) descent to arrive at the metering fix at a predetermined time, altitude, and airspeed. The descent path is calculated for a constant Mach/airspeed schedule from linear approximations of airplane performance with considerations given for gross weight, wind, and nonstandard pressure and temperature effects. The flight management descent algorithms are described and flight test results are presented.

Knox, C. E.↗
DOE OSTI2024

Development of algorithms for augmenting and replacing conventional process control using reinforcement learning

Here, this work seeks to allow for the online operation and training of model-free reinforcement learning (RL) agents but limit the risk to system equipment and personnel. The parallel implementation of RL alongside more conventional process control (CPC) allows for the RL algorithm to learn from CPC. The past performance of both methods are assessed on a continuous basis allowing for a transition from CPC to RL and, if needed, transitioning back to CPC from RL. This allows for the RL algorithm to slowly and safely assume control of the process without significant degradation in control performance. It is shown that the RL can derive a near optimal policy even when coupled with a suboptimal CPC. It is also demonstrated that the coupled RL-CPC algorithm learns at a faster rate than traditional RL methods of exploration while the algorithm’s performance does not deteriorate below CPC, even when exposed to an unknown operating condition.

30 DIRECT ENERGY CONVERSION↗
NASA NTRS1975

An implementable digital adaptive flight controller designed using stabilized single stage algorithms

Simple mechanical linkages have not solved the many control problems associated with high performance aircraft maneuvering throughout a wide flight envelope. One procedure for retaining uniform handling qualities over such an envelope is to implement a digital adaptive controller. Towards such an implementation an explicit adaptive controller which makes direct use of on-line parameter identification, has been developed and applied to both linearized and nonlinear equations of motion for a typical fighter aircraft. This controller is composed of an on-line weighted least squares parameter identifier, a Kalman state filter, and a model following control law designed using single stage performance indices. Simulation experiments with realistic measurement noise indicate that the proposed adaptive system has the potential for on-board implementation.

Kaufman, H.↗
NASA NTRS1999

Fuzzy Control Hardware for Segmented Mirror Phasing Algorithm

This paper presents a possible implementation of a control model developed to phase a system of segmented mirrors, with a PAMELA configuration, using analog fuzzy hardware. Presently, the model is designed for piston control only, but with the foresight that the parameters of tip and tilt will be integrated eventually. The proposed controller uses analog circuits to exhibit a voltage-mode singleton fuzzifier, a mixed-mode inference engine, and a current-mode defuzzifier. The inference engine exhibits multiplication circuits that perform the algebraic product composition through the use of operational transconductance amplifiers rather than the typical min-max circuits. Additionally, the knowledge base, containing exemplar data gained a priori through simulation, interacts via a digital interface.

Roth, Elizabeth↗
DOE OSTI2024

Hybrid model predictive control techniques for safety factor profile and stored energy regulation while incorporating NBI constraints

Abstract A novel hybrid Model Predictive Control (MPC) algorithm has been designed for simultaneous safety factor ( q ) profile and stored energy ( w ) control while incorporating the pulse-width-modulation constraints associated with the neutral beam injection (NBI) system. Regulation of the q -profile has been extensively shown to be a key factor for improved confinement as well as non-inductive sustainment of the plasma current. Simultaneous control of w is necessary to prevent the triggering of pressure-driven magnetohydrodynamic instabilities as the controller shapes the q profile. Conventional MPC schemes proposed for q -profile control have considered the NBI powers as continuous-time signals, ignoring the discrete-time nature of these actuators and leading in some cases to performance loss. The hybrid MPC scheme in this work has the capability of incorporating the discrete-time actuator dynamics as additional constraints. In nonlinear simulations, the proposed hybrid MPC scheme demonstrates improved q -profile+ w control performance for NSTX-U operating scenarios.

Physics↗
DOE OSTI2020

Byte select cache compression

Techniques are disclosed for designing cache compression algorithms that control how data in caches are compressed. The techniques generate a custom “byte select algorithm” by applying repeated transforms applied to an initial compression algorithm until a set of suitability criteria is met. The suitability criteria include that the “cost” is below a threshold and that a metadata constraint is met. The “cost” is the number of blocks that can be compressed by an algorithm as compared with the “ideal” algorithm. The metadata constraint is the number of bits required for metadata.

Das, Shomit N.↗
NASA NTRS1989

A parallel row-based algorithm for standard cell placement with integrated error control

A new row-based parallel algorithm for standard-cell placement targeted for execution on a hypercube multiprocessor is presented. Key features of this implementation include a dynamic simulated-annealing schedule, row-partitioning of the VLSI chip image, and two novel approaches to control error in parallel cell-placement algorithms: (1) Heuristic Cell-Coloring; (2) Adaptive Sequence Length Control.

Sargent, Jeff S.↗
NASA NTRS1980

IUS guidance algorithm gamma guide assessment

The Gamma Guidance Algorithm which controls the inertial upper stage is described. The results of an independent assessment of the algorithm's performance in satisfying the NASA missions' targeting objectives are presented. The results of a launch window analysis for a Galileo mission, and suggested improvements are included.

Bray, R. E.↗
NASA NTRS1991

Kinematics of the six-degree-of-freedom force-reflecting Kraft Master

Presented here are kinematic equations for a six degree of freedom force-reflecting hand controller. The forward kinematics solution is developed and shown in simplified form. The Jacobian matrix, which uses terms from the forward kinematics solution, is derived. Both of these kinematic solutions require joint angle inputs. A calibration method is presented to determine the hand controller joint angles given the respective potentiometer readings. The kinematic relationship describing the mechanical coupling between the hand and controller shoulder and elbow joints is given. These kinematic equations may be used in an algorithm to control the hand controller as a telerobotic system component. The purpose of the hand controller is two-fold: operator commands to the telerobotic system are entered using the hand controller, and contact forces and moments from the task are reflected to the operator via the hand controller.

Williams, Robert L., II↗
NASA NTRS2002

Control Oriented Modeling and Validation of Aeroservoelastic Systems

Lightweight aircraft design emphasizes the reduction of structural weight to maximize aircraft efficiency and agility at the cost of increasing the likelihood of structural dynamic instabilities. To ensure flight safety, extensive flight testing and active structural servo control strategies are required to explore and expand the boundary of the flight envelope. Aeroservoelastic (ASE) models can provide online flight monitoring of dynamic instabilities to reduce flight time testing and increase flight safety. The success of ASE models is determined by the ability to take into account varying flight conditions and the possibility to perform flight monitoring under the presence of active structural servo control strategies. In this continued study, these aspects are addressed by developing specific methodologies and algorithms for control relevant robust identification and model validation of aeroservoelastic structures. The closed-loop model robust identification and model validation are based on a fractional model approach where the model uncertainties are characterized in a closed-loop relevant way.

Crowder, Marianne↗