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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 145 records · Page 8

An Ensemble Approach to Computationally Efficient Radiological Anomaly Detection and Isotope Identification

Radiological source search is a challenging task involving detection and identification of weak sources in a constantly changing radiological background. As of now, many radiological source detection algorithms have been proposed; however, their computational complexity, and hence reliance on power intensive processing units inhibit low-power applications of radiological source search systems. In this work, we introduce the anomaly filter (AF) algorithm; a computationally light, yet effective time-series source detection algorithm based on exponential weighted moving average (EWMA) and Poisson deviance statistics. Then, we demonstrate that the proposed algorithm can be used in ensemble with other more computationally intensive source detection and identification algorithms to achieve both increased detection performance and reduced power consumption. The proposed AF algorithm and the ensemble algorithms were thoroughly benchmarked against several existing source detection and identification algorithms. The results show that the AF algorithm outperforms existing conventional source detection algorithms, and the ensemble approach improves the overall performance of existing source detection and isotope identification algorithms. Furthermore, the AF algorithm and the Non-negative Matrix Factorization approach based source identification (NMF-ID) algorithm were combined and implemented on a singleboard microcontroller and the power consumption was measured. This ensemble algorithm reduced the power consumption of the NMF-ID algorithm almost by a factor of 100, while improving the detection performance of the overall system.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Identification of the Space Shuttle Main Engine dynamic models from firing data

A multi-input multi-output system identification technique is used to obtain linearized point models of the Space Shuttle Main Engine (SSME) at five different operating conditions (power levels) from the engine firing data. This study demonstrates that the open-loop dynamics of the SSME can be successfully modeled from the engine firing data. The identified linear models may be used for fault detection studies and control system design and development.

Saravanan, N.↗

Protection Against Graph-Based False Data Injection Attacks on Power Systems

Graph signal processing (GSP) has emerged as a powerful tool for practical network applications, including power system monitoring. By representing power system voltages as smooth graph signals, recent research has focused on developing GSP-based methods for state estimation, attack detection, and topology identification. Included, efficient methods have been developed for detecting false data injection (FDI) attacks, which until now were perceived as non-smooth with respect to the graph Laplacian matrix. Consequently, these methods may not be effective against smooth FDI attacks. In this paper, we propose a graph FDI (GFDI) attack that minimizes the Laplacian-based graph total variation (TV) under practical constraints. In addition, we develop a low-complexity algorithm that solves the non-convex GDFI attack optimization problem using ell_1-norm relaxation, the projected gradient descent (PGD) algorithm, and the alternating direction method of multipliers (ADMM). We then propose a protection scheme that identifies the minimal set of measurements necessary to constrain the GFDI output to high graph TV, thereby enabling its detection by existing GSP-based detectors. Our numerical simulations on the IEEE-57 bus test case reveal the potential threat posed by well-designed GSP-based FDI attacks. Moreover, we demonstrate that integrating the proposed protection design with GSP-based detection can lead to significant hardware cost savings compared to previous designs of protection methods against FDI attacks.

Morgenstern, Gal↗

Magnetohydrodynamics (MHD) Engineering Test Facility (ETF) 200 MWe power plant. Conceptual Design Engineering Report (CDER). Volume 4: Supplementary engineering data

The reference conceptual design of the Magnetohydrodynamic Engineering Test Facility (ETF), a prototype 200 MWe coal-fired electric generating plant designed to demonstrate the commercial feasibility of open cycle MHD is summarized. Main elements of the design are identified and explained, and the rationale behind them is reviewed. Major systems and plant facilities are listed and discussed. Construction cost and schedule estimates, and identification of engineering issues that should be reexamined are also given. The latest (1980-1981) information from the MHD technology program are integrated with the elements of a conventional steam power electric generating plant. Supplementary Engineering Data (Issues, Background, Performance Assurance Plan, Design Details, System Design Descriptions and Related Drawings) is presented.

Source record↗

Synchro-Waveform-Based Event Identification Using Multi-Task Time-Frequency Transform Networks

Influenced by the transient dynamics and reduced inertia characteristics of high-penetration renewable energy systems, power system events frequently exhibit distinct characteristics such as high-frequency components including wide-band oscillations and hyper-harmonics. This makes standard systems face challenges including significant latency and reduced accuracy due to limited data resolution. However, current methods face significant limitations, including insufficient pattern capture ability, low noise immunity, limited feature learning, and restricted localization capabilities, thereby hindering real-time performance. To tackle this issue, this paper proposed a novel synchro-waveform-based event identification approach via a Multi-task Time-frequency Transform Network (MTTNet). Initially, a Time-frequency Transform Block (TTB) is developed to extract both local and global information. The TTB leverages both Fourier and S-transforms to derive comprehensive time-frequency information from synchro-waveforms. Subsequently, a multi-task learning strategy is employed to identify the type and distinguish localization of events. Integrating the TTB and multi-task learning, the MTTNet is designed for synchro-waveform-based event identification, incorporating an adaptive weighting strategy and simplified computation for the S-transform. Two different datasets, comprising simulated and actual synchro-waveforms, are collected from the IEEE 123 bus system and a real-world high-penetration renewable energy system using a universal grid analyzer. Extensive experiments on various conditions are carried out. In conclusion, results demonstrated that the MTTNet consistently surpasses both basic and advanced baselines, with maximum improvements of 13.24% and 9.86%, respectively, while reducing the calculation burden by 15-19 times to achieve real-time event identification.

Event identification↗

The Solar Power Satellite concept - Towards the future

An evolutionary program phasing with respect to the development of a Solar Power Satellite (SPS) is considered, taking into account concept identification, concept evaluation, exploratory research, space technology projects, system development, and commercial operations. At the present time the concept evaluation phase of the program is underway. This phase is scheduled for completion in 1980. It will result in a recommendation as to whether the concept should be explored further and if so, in what manner. The recommendation will be based on technical feasibility, economic and environmental considerations, and comparisons with other potential systems of the future. It is premature to speculate on the conclusions and recommendations from the evaluation program as to whether the program should proceed to the next phase.

Kraft, C. C., Jr.↗

Research developing closed loop roll control for magnetic balance systems

Computer inputs were interfaced to the magnetic balance outputs to provide computer position control and data acquisition. The use of parameter identification of a means of determining dynamic characteristics was investigated. The thyraton and motor generator power supplies for the pitch and yaw degrees of freedom were repaired. Topics covered include: choice of a method for handling dynamic system data; applications to the magnetic balance; the computer interface; and wind tunnel tests, results, and error analysis.

Covert, E. E.↗

Gas Composition Sensing Using Carbon Nanotube Arrays

This innovation is a lightweight, small sensor for inert gases that consumes a relatively small amount of power and provides measurements that are as accurate as conventional approaches. The sensing approach is based on generating an electrical discharge and measuring the specific gas breakdown voltage associated with each gas present in a sample. An array of carbon nanotubes (CNTs) in a substrate is connected to a variable-pulse voltage source. The CNT tips are spaced appropriately from the second electrode maintained at a constant voltage. A sequence of voltage pulses is applied and a pulse discharge breakdown threshold voltage is estimated for one or more gas components, from an analysis of the current-voltage characteristics. Each estimated pulse discharge breakdown threshold voltage is compared with known threshold voltages for candidate gas components to estimate whether at least one candidate gas component is present in the gas. The procedure can be repeated at higher pulse voltages to estimate a pulse discharge breakdown threshold voltage for a second component present in the gas. The CNTs in the gas sensor have a sharp (low radius of curvature) tip; they are preferably multi-wall carbon nanotubes (MWCNTs) or carbon nanofibers (CNFs), to generate high-strength electrical fields adjacent to the tips for breakdown of the gas components with lower voltage application and generation of high current. The sensor system can provide a high-sensitivity, low-power-consumption tool that is very specific for identification of one or more gas components. The sensor can be multiplexed to measure current from multiple CNT arrays for simultaneous detection of several gas components.

Li, Jing↗

Spacecraft Impacts with Advanced Power and Electric Propulsion

A study was performed to assess the benefits of advanced power and electric propulsion systems for various space missions. Advanced power technologies that were considered included multiband gap and thin-film solar arrays, lithium batteries, and flywheels. Electric propulsion options included Hall effect thrusters and Ion thrusters. Several mission case studies were selected as representative of future applications for advanced power and propulsion systems. These included a low altitude Earth science satellite, a LEO communications constellation, a GEO military surveillance satellite, and a Mercury planetary mission. The study process entailed identification of overall mission performance using state-of-the-art power and propulsion technology, enhancements made possible with either power or electric propulsion advances individually, and the collective benefits realized when advanced power and electric propulsion are combined. Impacts to the overall spacecraft included increased payload, longer operational life, expanded operations and launch vehicle class step-downs.

Mason, Lee S.↗

The NASA-Lewis program on fusion energy for space power and propulsion, 1958-1978

An historical synopsis is provided of the NASA-Lewis research program on fusion energy for space power and propulsion systems. It was initiated to explore the potential applications of fusion energy to space power and propulsion systems. Some fusion related accomplishments and program areas covered include: basic research on the Electric Field Bumpy Torus (EFBT) magnetoelectric fusion containment concept, including identification of its radial transport mechanism and confinement time scaling; operation of the Pilot Rig mirror machine, the first superconducting magnet facility to be used in plasma physics or fusion research; operation of the Superconducting Bumpy Torus magnet facility, first used to generate a toroidal magnetic field; steady state production of neutrons from DD reactions; studies of the direct conversion of plasma enthalpy to thrust by a direct fusion rocket via propellant addition and magnetic nozzles; power and propulsion system studies, including D(3)He power balance, neutron shielding, and refrigeration requirements; and development of large volume, high field superconducting and cryogenic magnet technology.

Schulze, Norman R.↗

Space-based solar power conversion and delivery systems study. Volume 1: Executive summary

The technical and economic aspects of satellite solar power systems are presented with a focus on the current configuration 5000 MW system. The technical studies include analyses of the orbital system structures, control and stationkeeping, and the formulation of program plans and costs for input to the economic analyses. The economic analyses centered about the development and use of a risk analysis model for a system cost assessment, identification of critical issues and technologies, and to provide information for programmatic decision making. A preliminary economic examination of some utility interface issues is included. Under the present state-of-knowledge, it is possible to formulate a program plan for the development of a satellite solar power system that can be economically justified. The key area of technological uncertainty is man's ability to fabricate and assemble large structures in space.

Hazelrigg, G. A., Jr.↗

Statistical Steady-State Stability Analysis for Transmission System Planning for Offshore Wind Power Plant Integration

This paper presents a statistical steady-state stability analysis for transmission system planning studies in order to identify operational issues inherent in the integration of offshore wind power plants. It includes normal and contingency operation. This study considers the integration of a 1000-MW offshore wind power plant into the FirstEnergy/PJM service territory in the U.S. Great Lakes region as a case study and uses a realistic computer model of the U.S. Eastern Interconnection, a 63,000-bus test system. The results show the utility of this statistical analysis tool and its effectiveness in identification of the operational impacts as a result of the integration of offshore wind power plant.

Sajadi, Amirhossein↗

Phase identification using co‐association matrix ensemble clustering

Calibrating distribution system models to aid in the accuracy of simulations such as hosting capacity analysis is increasingly important in the pursuit of the goal of integrating more distributed energy resources. The recent availability of smart meter data is enabling the use of machine learning tools to automatically achieve model calibration tasks. This research focuses on applying machine learning to the phase identification task, using a co‐association matrix‐based, ensemble spectral clustering approach. The proposed method leverages voltage time series from smart meters and does not require existing or accurate phase labels. This work demonstrates the success of the proposed method on both synthetic and real data, surpassing the accuracy of other phase identification research.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Certainty Equivalence M-MRAC for Systems with Unmatched Uncertainties

The paper presents a certainty equivalence state feedback indirect adaptive control design method for the systems of any relative degree with unmatched uncertainties. The approach is based on the parameter identification (estimation) model, which is completely separated from the control design and is capable of producing parameter estimates as fast as the computing power allows without generating high frequency oscillations. It is shown that the system's input and output tracking errors can be systematically decreased by the proper choice of the design parameters.

Unmatched uncertainties↗

The Upgrade of the SNS Extraction Kicker Power Supplies for the Proton Power Upgrade

The Proton Power Upgrade (PPU) project at the Spallation Neutron Source (SNS) aims to enhance the linear accelerator's power output from 1.4 to 2.8 megawatts. A critical focus lies on upgrading the Extraction Kicker Power Supplies to handle the amplified beam power. The existing capacitor charging power supplies lacked the capability to charge the Blumlein-type Pulse Forming Network (PFN) to the required 40 kV at a repetition rate of 60 Hz. To address this limitation, an initial solution involving the use of a resonant charging circuit was proposed. However, a challenge arose with a self-firing issue in the thyristor switch, which proved unsolvable within the given timeframe. Facing a critical decision point in the project, an alternative approach was explored: integrating a supplementary power supply to enhance the overall power capacity. This solution was tested and ultimately chosen as the path forward. To accommodate the additional power supply, the power distribution system had to undergo upgrades. Throughout this endeavor, a comprehensive examination of the system took place, with meticulous identification of key components. This paper delves into the technical challenges encountered during the process and the corresponding solutions that were implemented.

Tan, Yugang [ORNL] (ORCID:0000000155968252)↗

A virtual Frisch-grid geometry-based CZT gamma detector for in-field radioisotope identification

Here, we present a Virtual Frisch-Grid geometry-based CZT gamma detector developed for identifying different radioisotopes over an energy range from a few keV up to 2 MeV, and useful for efficient characterization of CZT crystals. The detector is built with a 3 x 3 matrix of CZT crystals, each measuring approximately 6 mm x 6 mm x 15 mm. The charge generated within the sensor’s active volume is read out via an anode connected directly to the AVG3_Dev integrated circuit. A current signal induced by charge drift is collected on side pads of the crystals, enabling reconstruction of a 3D interaction position. This paper discusses the design, development, and performance of the standalone, mobile detector system, which integrates the AVG3_Dev readout IC developed at Brookhaven National Laboratory, a high-speed FPGA-based with per-channel digital signal processing, and embedded system capabilities. The device is compact, battery-powered, and supports wireless data streaming, making it suitable for field operations for radioisotope identification.

47 OTHER INSTRUMENTATION↗

Towards Learning-Based Architectures for Sensor Impact Evaluation in Building Controls

Advanced control algorithms for building systems are known to have significant potential in reducing energy consumption while optimizing thermal comfort. The success of such algorithms is critically contingent on several different types of sensor systems, which are in turn, used for continuous monitoring, identification and estimation of several important building states, such as temperatures, humidity, air quality, power consumption and occupancy status. Nonidealities in any of these sensors can lead to significant performance degradation of the control functionalities, and may lead to unwanted sub-optimal building operation. In this paper, we provide a simulation example with a high-fidelity building model, for a particular use-case of advanced optimization-based control in buildings, i.e., occupancy-based controls. We show how imperfections in occupancy sensing can offset performance. Subsequently, we discuss a novel learning-based architecture to efficiently evaluate the impact of sensor nonidealities for building systems, in context of advanced control algorithms.

Bhattacharya, Saptarshi↗

Robust Matrix Completion State Estimation in Distribution Systems

Due to the insufficient measurements in the distribution system state estimation (DSSE), full observability and redundant measurements are difficult to achieve without using the pseudo measurements. The matrix completion state estimation (MCSE) combines the matrix completion and power system model to estimate voltage by exploring the low-rank characteristics of the matrix. This paper proposes a robust matrix completion state estimation (RMCSE) to estimate the voltage in a distribution system under a low-observability condition. Tradition state estimation weighted least squares (WLS) method requires full observability to calculate the states and needs redundant measurements to proceed a bad data detection. The proposed method improves the robustness of the MCSE to bad data by minimizing the rank of the matrix and measurements residual with different weights. It can estimate the system state in a low-observability system and has robust estimates without the bad data detection process in the face of multiple bad data. The method is numerically evaluated on the IEEE 33-node radial distribution system. The estimation performance and robustness of RMCSE are compared with the WLS with the largest normalized residual bad data identification (WLS-LNR), and the MCSE.

24 POWER TRANSMISSION AND DISTRIBUTION↗