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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 1,459 records · Page 81
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Keras2c: A library for converting Keras neural networks to real-time compatible C

With the growth of machine learning models and neural networks in measurement and control systems comes the need to deploy these models in a way that is compatible with existing systems. Existing options for deploying neural networks either introduce very high latency, require expensive and time consuming work to integrate into existing code bases, or only support a very limited subset of model types. We have therefore developed a new method called Keras2c, which is a simple library for converting Keras/TensorFlow neural network models into real-time compatible C code. It supports a wide range of Keras layers and model types including multidimensional convolutions, recurrent layers, multi-input/output models, and shared layers. Keras2c re-implements the core components of Keras/TensorFlow required for predictive forward passes through neural networks in pure C, relying only on standard library functions considered safe for real-time use. The core functionality consists of ~ 1500 lines of code, making it lightweight and easy to integrate into existing codebases. Keras2c has been successfully tested in experiments and is currently in use on the plasma control system at the DIII-D National Fusion Facility at General Atomics in San Diego.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2021

Branching Dueling Q-Network Based Online Scheduling of a Microgrid With Distributed Energy Storage Systems

This letter investigates a Branching Dueling Q-Network (BDQ) based online operation strategy for a microgrid with distributed battery energy storage systems (BESSs) operating under uncertainties. Additionally, the developed deep reinforcement learning (DRL) based microgrid online optimization strategy can achieve a linear increase in the number of neural network outputs with the number of distributed BESSs, which overcomes the curse of dimensionality caused by the charge and discharge decisions of multiple BESSs. Numerical simulations validate the effectiveness of the proposed method.

24 POWER TRANSMISSION AND DISTRIBUTION↗
NASA NTRS2003

Performance Evaluation Modeling of Network Sensors

Substantial benefits are promised by operating many spatially separated sensors collectively. Such systems are envisioned to consist of sensor nodes that are connected by a communications network. A simulation tool is being developed to evaluate the performance of networked sensor systems, incorporating such metrics as target detection probabilities, false alarms rates, and classification confusion probabilities. The tool will be used to determine configuration impacts associated with such aspects as spatial laydown, and mixture of different types of sensors (acoustic, seismic, imaging, magnetic, RF, etc.), and fusion architecture. The QualNet discrete-event simulation environment serves as the underlying basis for model development and execution. This platform is recognized for its capabilities in efficiently simulating networking among mobile entities that communicate via wireless media. We are extending QualNet's communications modeling constructs to capture the sensing aspects of multi-target sensing (analogous to multiple access communications), unimodal multi-sensing (broadcast), and multi-modal sensing (multiple channels and correlated transmissions). Methods are also being developed for modeling the sensor signal sources (transmitters), signal propagation through the media, and sensors (receivers) that are consistent with the discrete event paradigm needed for performance determination of sensor network systems. This work is supported under the Microsensors Technical Area of the Army Research Laboratory (ARL) Advanced Sensors Collaborative Technology Alliance.

probability of detection↗
NASA NTRS1985

Determining Availability Characteristics of DSN Data Systems Using Discrepancy Report Data

A reasonably economical way was developed to determine availability characteristics of Deep Space Network (DSN) data systems, subsystems, and assemblies using the DSN discrepancy report (DR) data base and DSN operating schedule and history data bases. Operating mean time between failures (OMTBF), operating mean time to restore service (OMTTRS), and operating functional availability (OFA) can be computed by year, by system, by subsystem, by assembly, and by station. The effort required to produce the desired reports is described, specific data on the telemetry, command, and tracking systems are presented, and major contributors to system outages are identified. Future improvements in preparing and analyzing DR data are also outlined to enhance their use in correcting conditions that lead to outages.

Ruskin, A. M.↗
DOE OSTI2023

Control development and sizing analysis for a 5th generation district heating and cooling network using Modelica

5th generation district heating and cooling system (5GDHC) are a relatively new concept. They use a single district loop near ambient temperature to provide heating and cooling. This paper improves on the modelling and control of a 5GDHC system called the reservoir network. The study updates the sewage heat exchanger plant model to more realistically represent seasonal changes, uses refined pump models with variable efficiency, introduces a ground coupled district pipe model to consider the inertia of the district network and implements a new control strategy for geothermal storage and sewage heat exchanger. The new approach reduced operating costs, mainly due to pumping cost for storage, sewage heat exchanger plant and distribution pump, while increasing the overall robustness of the approach in different sizing conditions. Thanks to the new controller, the pumping consumption was reduced by 21% with respect to the original baseline. Furthermore, the new control makes the system take better advantage of design changes, when reducing borehole field size and increasing the sewage heat exchanger size, the pumping energy savings become 29% with respect to the original baseline. Lastly, borehole field temperature stability was analyzed through 40 years of simulation.

Zanetti, Ettore↗
NASA NTRS1991

Precise time and time interval applications to electric power systems

There are many applications of precise time and time interval (frequency) in operating modern electric power systems. Many generators and customer loads are operated in parallel. The reliable transfer of electrical power to the consumer partly depends on measuring power system frequency consistently in many locations. The internal oscillators in the widely dispersed frequency measuring units must be syntonized. Elaborate protection and control systems guard the high voltage equipment from short and open circuits. For the highest reliability of electric service, engineers need to study all control system operations. Precise timekeeping networks aid in the analysis of power system operations by synchronizing the clocks on recording instruments. Utility engineers want to reproduce events that caused loss of service to customers. Precise timekeeping networks can synchronize protective relay test-sets. For dependable electrical service, all generators and large motors must remain close to speed synchronism. The stable response of a power system to perturbations is critical to continuity of electrical service. Research shows that measurement of the power system state vector can aid in the monitoring and control of system stability. If power system operators know that a lightning storm is approaching a critical transmission line or transformer, they can modify operating strategies. Knowledge of the location of a short circuit fault can speed the re-energizing of a transmission line. One fault location technique requires clocks synchronized to one microsecond. Current research seeks to find out if one microsecond timekeeping can aid and improve power system control and operation.

Robert E. Wilson↗
NASA NTRS2020

NASA’s Carbon Monitoring System (CMS) and Arctic-Boreal Vulnerability Experiment (ABoVE) Social Network and Community of Practice

The NASA Carbon Monitoring System (CMS) and Arctic-Boreal Vulnerability Experiment (ABoVE) have been planned and funded by the NASA Earth Science Division. Both programs have a focus on engaging stakeholders and developing science useful for decision making. The resulting programs have funded significant scientific output and advancements in understanding how satellite remote sensing observations can be used to not just study how the Earth is changing, but also create data products that are of high utility to stakeholders and decisions makers. In this paper we focus on documenting thematic diversity of research themes and methods used, and how the CMS and ABoVE themes are related. We do this through developing a Correlated Topic Model on the 521 papers produced by the two programs and plotting the results in a network diagram. Through analysis of the themes in these papers, we document the relationships between researchers and institutions participating in CMS and ABoVE programs and the benefits from sustained engagement with stakeholders due to recurring funding. We note an absence of policy engagement in the papers and conclude that funded researchers need to be more ambitious and explicit in drawing the connection between their research and carbon policy implications in order to meet the stated goals of the CMS and ABoVE programs.

Molly E Brown↗
DOE OSTI2022

QuCNN : A Quantum Convolutional Neural Network with Entanglement Based Backpropagation

Quantum Machine Learning continues to be a highly active area of interest within Quantum Computing. Many of these approaches have adapted classical approaches to the quantum settings, such as QuantumFlow, etc. We push forward this trend, and demonstrate an adaption of the Classical Convolutional Neural Networks to quantum systems - namely QuCNN. QuCNN is a parameterised multi-quantum-state based neural network layer computing similarities between each quantum filter state and each quantum data state. With QuCNN, back propagation can be achieved through a single-ancilla qubit quantum routine. QuCNN is validated by applying a convolutional layer with a data state and a filter state over a small subset of MNIST images, comparing the backpropagated gradients, and training a filter state against an ideal target state.

high performance computing, quantum computing↗
NASA NTRS1989

The NASA SETI sky survey: Recent developments

NASA's Search for Extraterrestrial Intelligence (SETI) project utilizes two complementary search strategies: a sky survey and a targeted search. The SETI team at the Jet Propulsion Laboratory (JPL) in Pasadena, California, has primary responsibility to develop and carry out the sky survey part. Described here is progress that has been made developing the major elements of the survey including a 2-million channel wideband spectrum analyzer system that is being designed and constructed by JPL for the Deep Space Network (DSN). The system will be a multiuser instrument; it will serve as a prototype for the SETI sky survey processor. This prototype system will be used to test the signal detection and observational strategies on DSN antennas in the near future.

Klein, M. J.↗
NASA NTRS1993

Efficiently modeling neural networks on massively parallel computers

Neural networks are a very useful tool for analyzing and modeling complex real world systems. Applying neural network simulations to real world problems generally involves large amounts of data and massive amounts of computation. To efficiently handle the computational requirements of large problems, we have implemented at Los Alamos a highly efficient neural network compiler for serial computers, vector computers, vector parallel computers, and fine grain SIMD computers such as the CM-2 connection machine. This paper describes the mapping used by the compiler to implement feed-forward backpropagation neural networks for a SIMD (Single Instruction Multiple Data) architecture parallel computer. Thinking Machines Corporation has benchmarked our code at 1.3 billion interconnects per second (approximately 3 gigaflops) on a 64,000 processor CM-2 connection machine (Singer 1990). This mapping is applicable to other SIMD computers and can be implemented on MIMD computers such as the CM-5 connection machine. Our mapping has virtually no communications overhead with the exception of the communications required for a global summation across the processors (which has a sub-linear runtime growth on the order of O(log(number of processors)). We can efficiently model very large neural networks which have many neurons and interconnects and our mapping can extend to arbitrarily large networks (within memory limitations) by merging the memory space of separate processors with fast adjacent processor interprocessor communications. This paper will consider the simulation of only feed forward neural network although this method is extendable to recurrent networks.

Farber, Robert M.↗
NASA NTRS1993

Modeling of the ground-to-SSFMB link networking features using SPW

This report describes the modeling and simulation of the networking features of the ground-to-Space Station Freedom manned base (SSFMB) link using COMDISCO signal processing work-system (SPW). The networking features modeled include the implementation of Consultative Committee for Space Data Systems (CCSDS) protocols in the multiplexing of digitized audio and core data into virtual channel data units (VCDU's) in the control center complex and the demultiplexing of VCDU's in the onboard baseband signal processor. The emphasis of this work has been placed on techniques for modeling the CCSDS networking features using SPW. The objectives for developing the SPW models are to test the suitability of SPW for modeling networking features and to develop SPW simulation models of the control center complex and space station baseband signal processor for use in end-to-end testing of the ground-to-SSFMB S-band single access forward (SSAF) link.

Watson, John C.↗
NASA NTRS1978

Ku-band signal design study

Analytical tools, methods and techniques for assessing the design and performance of the space shuttle orbiter data processing system (DPS) are provided. The computer data processing network is evaluated in the key areas of queueing behavior synchronization and network reliability. The structure of the data processing network is described as well as the system operation principles and the network configuration. The characteristics of the computer systems are indicated. System reliability measures are defined and studied. System and network invulnerability measures are computed. Communication path and network failure analysis techniques are included.

Rubin, I.↗
DOE OSTI2025

Fermionic Isometric Tensor Network States in Two Dimensions

We generalize isometric tensor network states to fermionic systems, paving the way for efficient adaptations of 1D tensor network algorithms to 2D fermionic systems. As the first application of this formalism, we developed and benchmarked a time-evolving block-decimation (TEBD) algorithm for real-time and imaginary-time evolution. The imaginary-time evolution produces ground-state energies for gapped systems, systems with a Dirac point, and systems with gapless edge modes to good accuracy. Here, the real-time TEBD captures the scattering of two fermions and the chiral edge dynamics on the boundary of a Chern insulator.

2-dimensional systems↗
NASA NTRS1989

DSN radio science system design and testing for Voyager-Neptune encounter

The Deep Space Network (DSN) Radio Science System presently implemented within the Deep Space Network was designed to meet stringent requirements imposed by the demands of the Voyager-Neptune encounter and future missions. One of the initial parameters related to frequency stability is discussed. The requirement, specification, design, and methodology for measuring this parameter are described. A description of special instrumentation that was developed for the test measurements and initial test data resulting from the system tests performed at Canberra, Australia and Usuda, Japan are given.

Ham, N. C.↗
NASA NTRS1986

Wide-area remote-sensing system of pollution and gas dispersal by near-infrared absorption based on low-loss optical fiber network

An all optical remote sensing system utilizing long distance, ultralow loss optical fiber networks is studied and discussed for near infrared absorption measurements of combustible and/or explosive gases such as CH4 and C3H8 in our environment, including experimental results achieved in a diameter more than 20 km. The use of a near infrared wavelength range is emphasized.

Inaba, H.↗
DOE OSTI2021

Modeling and Evaluation of Cyber-Attacks on Grid-Interactive Efficient Buildings

Grid-interactive efficient buildings (GEBs) are not only exposed to passive threats (e.g., physical faults) but also active threats such as cyber-attacks launched on the network-based control systems. The impact of cyber-attacks on GEB operation are not yet fully understood, especially as regards the performance of grid services. To quantify the consequences of cyber-attacks on GEBs, this paper proposes a modeling and simulation framework that includes different cyber-attack models and key performance indexes to quantify the performance of GEB operation under cyber-attacks. The framework is numerically demonstrated to model and evaluate cyber-attacks such as data intrusion attacks and Denial-of-Service attacks on a typical medium-sized office building that uses the BACnet/IP protocol for communication networks. Simulation results show that, while different types of attacks could compromise the building systems to different extents, attacks via the remote control of a chiller yield the most significant consequences on a building system’s operation, including both the building service and the grid service. It is also noted that a cyber-attack impacts the building systems during the attack period as well as the post-attack period, which suggests that both periods should be considered to fully evaluate the consequences of a cyber-attack.

Fu, Yanyang↗
NASA NTRS1977

Automation of the deep space network

Approaches to automating the radiofrequency system used in the deep space network (DSN) are discussed. The goal is to operate DSN, which communicates with U.S. space probes that travel beyond the moon, in an unattended mode in order to reduce operating costs. The philosophy of a hierachical automation plan, which emphasizes distributed control and the utilization of DSN hardware development engineers to develop automation software, is discussed, and software development as well as common software and common microcontroller hardware are considered. It is planned that a station controller will serve as the operator interface and control and coordinate the operation of three system controllers (RF system, digital system, and antenna system). These systems are described.

Crow, R. B.↗
NASA NTRS1981

DSN scheduling system

The Deep Space Network (DSN) Scheduling Group provides the operationally oriented administrative support necessary for the effective scheduling of the DSN. The scheduling system plus the levels of schedules are explained.

Dorham, R.↗