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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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All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

A Voltage Inference Framework for Real-Time Observability in Active Distribution Grids

Active distribution grids are gaining traction to meet the growing environmental, socio-economic, and sustainability targets. Various advanced smart grid technologies facilitate the integration of Distributed Energy Resources (DERs) by supporting the bi-directional power flow. The limited observability of distribution grids, primarily related to their location at the very edge of power system infrastructure, brings challenges to optimal grid management. Moreover, only a limited number of measurements at regular intervals are usually available. This paper presents a novel inference framework, referred to as “Voltage Inference”, to overcome the observability issues. The proposed framework employs a prediction step based on the Multivariate Taylor series approximation, followed by a corrector step that minimizes the estimation error to infer the otherwise unknown voltages from the available measurements. Furthermore, numerical results on the IEEE 13-bus test feeder validate the accuracy and computational performance of the proposed framework.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2025

A distributed voltage inference framework for cyber-physical attacks detection and localization in active distribution grids

The transition to active distribution grids with real-time monitoring and control depends on the proliferation of advanced communication networks and devices. This paradigm shift towards a cyber-physical architecture also introduces new vulnerabilities for adversaries to exploit and launch sophisticated cyber-physical attacks targeting grid observability. Current research highlights the challenges in distinguishing attacks on voltage phasor or nodal injection measurements and isolating multi-source attack locations in a multiphase distribution grid. The attack detection and localization methods in literature face accuracy issues, applications across diverse attack scenarios, or scalability limits. Here, to bridge these gaps, this paper proposes a distributed Voltage Inference framework for real-time detection and localization of cyber-physical attacks, addressing scalability, adaptability, and accuracy challenges in state-of-the-art methods. The proposed methodology leverages the distributed nature of the Voltage Inference framework through a two-step process of prediction and correction, together with a tractable graph partitioning approach, providing a reliable solution to identify compromised measurement sources and facilitate isolation. Extensive testing on IEEE 13 and 123-node distribution feeders underscores the algorithm’s efficacy, enhancing the security and resilience of active distribution grids against evolving cyber threats. Additionally, Hardware-in-the-Loop (HIL) implementation validates the proposed strategy’s practical applicability in real-world scenarios.

active distribution grids↗
DOE OSTI2022

Artificial intelligence inferred microstructural properties from voltage–capacity curves

Abstract The quantification of microstructural properties to optimize battery design and performance, to maintain product quality, or to track the degradation of LIBs remains expensive and slow when performed through currently used characterization approaches. In this paper, a convolution neural network-based deep learning approach (CNN) is reported to infer electrode microstructural properties from the inexpensive, easy to measure cell voltage versus capacity data. The developed framework combines two CNN models to balance the bias and variance of the overall predictions. As an example application, the method was demonstrated against porous electrode theory-generated voltage versus capacity plots. For the graphite|LiMn $$_2$$ 2 O $$_4$$ 4 chemistry, each voltage curve was parameterized as a function of the cathode microstructure tortuosity and area density, delivering CNN predictions of Bruggeman’s exponent and shape factor with 0.97 $$R^2$$ R 2 score within 2 s each, enabling to distinguish between different types of particle morphologies, anisotropies, and particle alignments. The developed neural network model can readily accelerate the processing-properties-performance and degradation characteristics of the existing and emerging LIB chemistries.

25 ENERGY STORAGE↗
DOE OSTI2020

Optimization of DARHT Axis 1 Injector Voltage

The Dual-Axis Radiographic Hydrodynamic Test (DARHT) facility provides flash radiography capabilities using two electron Linear Induction Accelerators (LIA’s). Axis-1 of DARHT produces a 20- MeV, 2-kA, 80-ns-FWHM electron beam. The strict requirements for flash radiography require a detailed understanding of the LIA’s performance, including precision measurements of the injector electron beam energy. The technique for time resolved measurement of the electron beam energy using electron Permanent Magnet Spectrometer (ePMSpec) has been developed. The electron energy then is used to infer the voltage produced by the injector pulsed power. The injector pulsed power of DARHT I consists of a 1.5-MV, glycol-insulated Blumlein that is pulsecharged by a step-up transformer and switched by four, laser-triggered spark gaps. A series of increasing impedance transmission lines are used to transform the output voltage of the Blumlein to a maximum of 3.8MV at the diode. Figure 1a shows a graphic of the Axis-1 prime power tank, Blumlein and downstream transmission lines. The injector pulse power is designed to produce voltage on a velvet cathode located in the vacuum vessel. The specifications of the voltage-pulse flat-top over 60ns is +/-1%. A key element in the high-voltage circuit is the ethylene glycol Blumlein. The outer volume, adjacent to the laser triggered switches of the Blumlein, is a peaking capacitor. This is an independent volume that contains a mixture of ethylene glycol and water to make it an adjustable capacitor of 380 to 750 pF.

43 PARTICLE ACCELERATORS↗
NASA NTRS1990

Optical Arc-Length Sensor For TIG Welding

Proposed subsystem of tungsten/inert-gas (TIG) welding system measures length of welding arc optically. Viewed by video camera, in one of three alternative optical configurations. Length of arc measured instead of inferred from voltage.

Smith, Matthew A.↗
NASA NTRS2022

Lithium-ion Battery Strain Gauge Monitoring and Depth of Discharge Estimation

Lithium-ion battery diagnostics and prognostics rely on measurements of electrical impedance, capacity, and voltage to infer the internal state of the battery. Mechanical changes to the cell structure represent an additional measure of the battery’s state because these changes are related to the overall battery health. As lithium-ion batteries are charged and discharged, lithium ions are inserted or removed from the anode and cathode, a process called intercalation and de-intercalation. As lithium ions intercalate and de-intercalate, they can cause changes to the lattice of the electrode particles, resulting in volumetric changes. These volumetric changes cause mechanical stresses and strains on the lithium-ion battery electrodes, and subsequently, the whole cell’s thickness varies as it is charged and discharged. This paper presents a study on the use of surface-mounted strain gauges for in-situ measurement of structural changes to lithium-ion batteries, along with a characterization of the unit-to-unit differences in strain response. A neural network modeling structure is then used to predict the battery’s depth of discharge under dynamic discharge conditions.

Lithium-ion batteries, depth of discharge, strain ↗
NASA NTRS1978

Preliminary results on the conversion of laser energy into electricity

A preliminary experiment was performed to investigate conversion of 10.6 micron laser energy to electrical energy via a laser-sustained argon plasma. Short-circuit currents of 0.7 A were measured between a thoriated-tungsten emitter and collector electrodes immersed in the laser-sustained argon plasma. Open-circuit voltages of about 1.5 V were inferred from the current-voltage load characteristics. The dominant mechanism of laser energy conversion is uncertain at this time. Much higher output powers appear possible.

Thompson, R. W.↗
DOE OSTI2024

Analytic Neural Network Gaussian Process Enabled Chance-Constrained Voltage Regulation for Active Distribution Systems with PVs, Batteries and EVs

This paper proposes an analytic neural network Gaussian process (NNGP)-based chance-constrained real-time voltage regulation method for active distribution systems with photovoltaics (PVs), batteries, and electric vehicles (EVs). NNGP can utilize historical measurement data to achieve real-time probabilistic node voltage estimation through Bayesian inference. Then, NNGP is fully analytically embedded into the optimal power flow model to perform voltage regulation and adapt to various topological changes. The uncertainties of voltage estimations are easily considered via the chance constraint, and it has been shown that the adoption of this chance constraint can significantly improve the reliability of voltage regulation under various scenarios. The comparison results with other methods, carried out on a real 759-node distribution system located in western Colorado, U.S., show that the proposed method can achieve accurate voltage estimation across different topologies and reliably perform voltage regulation considering PVs, batteries, and EVs.

active distribution systems↗
DOE OSTI2021

Enhanced electro-osmosis in propylene carbonate salt solutions

Properties of solid–liquid interfaces and surface charge characteristics mediate ionic and molecular transport through porous systems, affecting many processes such as separations. Herein, we report experiments designed to probe the electrochemical properties of solid–liquid interfaces using a model system of a single polyethylene terephthalate (PET) pore in contact with aqueous and propylene carbonate solutions of LiClO 4 . First, the existence and polarity of surface charges were inferred from current–voltage curves recorded when a pore was placed in contact with a LiClO4 concentration gradient. Second, the electro-osmotic transport of uncharged polystyrene particles through the PET pore provided information on the polarity and the magnitude of the pore walls’ zeta potential. Our experiments show that the PET pores become effectively positively charged when in contact with LiClO 4 solutions in propylene carbonate, even though in aqueous LiClO 4 , the same pores are negatively charged. Additionally, the electro-osmotic velocity of the particles revealed a significantly higher magnitude of the positive zeta potential of the pores in propylene carbonate compared to the magnitude of the negative zeta potential in water. The presented methods of probing the properties of solid–liquid interfaces are expected to be applicable to a wide variety of solid and liquid systems.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
NASA NTRS1980

Initial comparison of SSPM ground test results and flight data to NASCAP simulations

The satellite surface potential monitor (SSPM) has been developed for the P78-2 SCATHA (Spacecraft Charging At The High Altitudes) satellite to determine the response of selected spacecraft materials to charged-particle environmental fluxes. Since the monitor infers total surface voltages from a single point on the interior side of insulators, a ground simulation program was undertaken to develop analytical techniques to model the monitors and to obtain an experimental calibration of the relationship between the flight measurement techniques and actual measurements. The experimental testing was conducted using monoenergetic electron beams irradiating samples in the dark. An analytical computer model was developed in the NASCAP (NASA Charging Analyzer Program) code. The analytical model material properties for Kapton that controlled backscatter and secondary yield were adjusted to obtain a single set of values that produced reasonable fits for both voltages and currents. The analytical techniques developed in the ground technology investigation have been applied to space flight conditions. Predictions were compared with limited flight data. The agreement is very good indicating that the technique, and NASCAP, can be used to predict spacecraft material charging behavior. Details of the testing, the analytical modelling technique and flight data comparisons are presented.

Stevens, N. J.↗
NASA NTRS1981

Thrust and efficiency of a self-field MPD thruster

Thrust and efficiency of a quasi-steady multi-MW argon MPD thruster are determined for one-millisecond current pulses. Terminal voltage and impulse bit per pulse are measured for a benchmark thruster geometry on a swinging gate thrust stand in a dielectric vacuum tank, at a background pressure of 0.0001 torr, for a range of argon flow rates and arc currents. The quasi-steady thrust data scale quadratically with arc current, and confirm previous estimates of the electromagnetic and electrothermal components of thrust from magnetic and pressure probe measurements. Thruster efficiency is found to increase monotonically with specific impulse, reaching a value of 25% for 4.5 to 6.0 g/sec at 2000 seconds. Results of further experiments show that the inferred specific impulse for voltage fluctuation onset can be increased to 3000 seconds, and the thrust efficiency to above 30%.

Burton, R. L.↗
DOE OSTI2024

AI Driven Experiment Calibration and Control

One critical step on the path from data taking to physics analysis is calibration. For many experiments this step is both time consuming and computationally expensive. The AI Experimental Calibration and Control project seeks to address these issues, starting first with the GlueX Central Drift Chamber (CDC). We demonstrate the ability of a Gaussian Process to estimate the gain correction factor (GCF) of the GlueX CDC accurately, and also the uncertainty of this estimate. Using the estimated GCF, the developed system infers a new high voltage (HV) setting that stabilizes the GCF in the face of changing environmental conditions. This happens in near real time during data taking and produces data which are already approximately gain-calibrated, eliminating the cost of performing those calibrations which vary ±15% with fixed HV. We also demonstrate an implementation of an uncertainty aware system which exploits a key feature of a Gaussian process.

Britton, Thomas↗
DOE OSTI2020

Basic factors for acquiring, correcting, and interpreting probe current-voltage characteristic in moderate-collisional plasma for determining electron energy distribution

Methods for inferring the electron distribution function (EDF) from a probe current–voltage trace are reviewed for moderate-collisional plasma. The explicit accounting of particle collisions, modeling sheath depletion, and electron refilling processes are rarely performed when analyzing probe measurements, yet they are critical for regime validity, EDF-profile accuracy, and space potential quantification precision. Furthermore, the advantages, limitations, and utilization of large-area wall probes in moderate-collisional plasma, capable of highly resolved indications of energetic electrons in plasma, are outlined.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
NASA NTRS1994

Toward an automated signature recognition toolkit for mission operations

Signature recognition is the problem of identifying an event or events from its time series. The generic problem has numerous applications to science and engineering. At NASA's Johnson Space Center, for example, mission control personnel, using electronic displays and strip chart recorders, monitor telemetry data from three-phase electrical buses on the Space Shuttle and maintain records of device activation and deactivation. Since few electrical devices have sensors to indicate their actual status, changes of state are inferred from characteristic current and voltage fluctuations. Controllers recognize these events both by examining the waveform signatures and by listening to audio channels between ground and crew. Recently the authors have developed a prototype system that identifies major electrical events from the telemetry and displays them on a workstation. Eventually the system will be able to identify accurately the signatures of over fifty distinct events in real time, while contending with noise, intermittent loss of signal, overlapping events, and other complications. This system is just one of many possible signature recognition applications in Mission Control. While much of the technology underlying these applications is the same, each application has unique data characteristics, and every control position has its own interface and performance requirements. There is a need, therefore, for CASE tools that can reduce the time to implement a running signature recognition application from months to weeks or days. This paper describes our work to date and our future plans.

Cleghorn, T.↗
NASA NTRS1986

The voltage threshold for arcing for solar cells in LEO: Flight and ground test results

Ground and flight results of solar cell arcing in low Earth orbit (LEO) conditions are compared and interpreted. It is shown that an apparent voltage threshold for arcing may be produced by a strong power law dependence of arc rate on voltage, combined with a limited observation time. The change in this apparent threshold with plasma density is a reflection of the density dependence of the arc rate. A nearly linear dependence of arc rate on density is inferred from the data. A real voltage threshold for arcing for 2 by 2 cm solar cells may exist however, independent of plasma density, near -230 V relative to the plasma. Here, arc rates may change by more than an order of magnitude for a change of only 30 V in array potential. For 5.9 by 5.9 solar cells, the voltage dependence of the arc rate is steeper, and the data are insufficient to indicate the existence of an arcing increased by an atomic oxygen plasma, as is found in LEO, and by arcing from the backs of welded-through substrates.

Ferguson, D. C.↗
NASA NTRS1986

The voltage threshold for arcing for solar cells in Leo - Flight and ground test results

Ground and flight results of solar cell arcing in low earth orbit (LEO) conditions are compared and interpreted. It is shown that an apparent voltage threshold for arcing may be produced by a storage power law dependence of arc rate on voltage, combined with a limited observation time. The change in this apparent threshold with plasma density is a reflection of the density dependence of the arc rate. A nearly linear dependence of arc rate on density is inferred from the data. A real voltage threshold for arcing for 2 by 2 cm solar cells may exist however, independent of plasma density, near -230 V relative to the plasma. Here, arc rates may change by more than an order of magnitude for a change of only 30 V in array potential. For 5.9 by 5.9 solar cells, the voltage dependence of the arc rate is steeper, and the data are insufficient to indicate the existence of an arcing increased by an atomic oxygen plasma, as is found in LEO, and by arcing from the backs of welded-through substrates.

Ferguson, Dale C.↗
DOE OSTI2023

Probabilistic Physics-Informed Graph Convolutional Network for Active Distribution System Voltage Prediction

Here this letter proposes a novel data-driven probabilistic physics-informed graph convolutional network (GCN) for active distribution system voltage prediction with PVs and EVs. It leverages both measurements and network topology to accurately and efficiently predict node voltages without the need for an accurate distribution system power flow model. The dropout-enabled Bayesian inference is developed to achieve uncertainty quantification of the voltage prediction. Thanks to the network model embedding, it also has robustness against topology changes, a key difference with existing machine learning-based approaches. Comparison results with other state-of-the-art machine learning methods on a realistic 759-node distribution system demonstrate that the proposed method can achieve better accuracy and robustness under different scenarios.

24 POWER TRANSMISSION AND DISTRIBUTION↗