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At least 631 records · Page 35

Progress on Machine Learning for the SNS High Voltage Converter Modulators

The High-Voltage Converter Modulators (HVCM) used to power the klystrons in the Spallation Neutron Source (SNS) linac were selected as one area to explore machine learning due to reliability issues in the past and the availability of large sets of archived waveforms. Progress in the past two years has resulted in generating a significant amount of simulated and measured data for training neural network models such as recurrent neural networks, convolutional neural networks, and variational autoencoders. Applications in anomaly detection, fault classification, and prognostics of capacitor degradation were pursued in collaboration with the Jefferson Laboratory, and early promising results were achieved. This paper will discuss the progress to date and present results from these efforts.

Pappas, Chris↗

Passive components for high temperature operation

The development of resistors, capacitors, and interconnect metalizations utilizing a low pressure chemical vapor deposition (LPCVD) process is described. The LPCVD process allows the passive components to be fabricated at temperatures higher than their highest operating temperatures. The deposition of thin films by LPCVD is accomplished by reacting one or more gases on the surface of a heated substrate. The substrates to be coated are placed on a graphite susceptor and then loaded into the center of a quartz reaction tube. The RF power is applied to the coil on the outside of the reaction tube which in turn is coupled into the graphite susceptor causing it to heat. Pressures of several torr or less are typical, with carrier flow rates of 0.1 to 2.0 liters/min. Nitrogen, hydrogen, and helium are typical carrier gases. These are controlled with mass flow controllers and the pressure is continuously monitored with a capacitive manometer. Materials selection and device testing are also discussed.

Raymond, L. S.↗

Silicon carbide power inverter/rectifier for electric machines

The present disclosure involves a two stage inverter, a system for electrical power conversation, and a method of converting electrical power using silicon carbide (SiC) metal-oxide-semiconductor field-effect transistors (MOSFETs). One example implementation includes using two or more SiC MOSFETs in series with each MOSFET having a gate terminal for triggering a state switch between an on (conducting) and off (non-conducting) state of the MOSFET. An AC terminal is connected between the series SiC MOSFETS, and the series SiC MOSFETs are connected across a DC bus and in parallel with one or more capacitors.

Shenoy, Suratkal P.↗

Insights from machine learning of carbon electrodes for electric double layer capacitors

Recent years have witnessed the broad use of carbon electrodes for electric double layer capacitors (EDLCs) because of large surface area, high porosity and low cost. Whereas experimental investigations are mostly focused on the device performance, computational studies have been rarely concerned with electrochemical properties at conditions remote from equilibrium, limiting their direct applications to materials design. Through a comprehensive analysis of extensive experimental data with various machine-learning methods, we report herein quantitative correlations between the structural features of carbon electrodes and the in-operando behavior of EDLCs including energy and power density. Machine learning allows us to identify important characteristics of activated carbons useful to optimize their efficiency in energy storage.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

A quasi-passive CMOS pipeline D/A converter

A novel pipeline digital-to-analog converter configuration, based on switched-capacitor techniques, is described. An n-bit D/A conversion can be implemented by cascading n + 1 unit cells. The device count of the circuit increases linearly, not exponentially, with the conversion accuracy. The new configuration can be pipelined. Hence, the conversion rate can be increased without requiring a higher clock rate. An experimental 10-bit DAC prototype has been fabricated using a 3-micron CMOS process. The results show that high-speed, high-accuracy, and low-power operation can be achieved without special process or postprocess trimming.

Wang, Fong-Jim↗

New Modulation and Impact of Transformer Leakage Inductance on Current-Source Solid-State Transformer

This article presents a novel modulation scheme for device voltage stress mitigation and comprehensive analysis of the impact of transformer leakage inductance in a current-source solid-state transformer (SST). Different from dual active bridge (DAB) SST, the operation of the current-source SST is similar to that of a flyback converter. The device bridge on only one side of the transformer is active to store energy into or release energy from the magnetizing inductance which acts as a current-source dc link. Such flyback operation with reverse-blocking switches can lead to additional device voltage stress and incomplete zero-voltage switching (ZVS) on the current-source soft-switching solid-state transformer (S4T) under conventional modulation. A new modulation scheme is proposed to address this issue. Moreover, different from the DAB, the leakage inductance of the medium-frequency transformer (MFT) in the S4T is a parasitic element similar to that in a matrix SST and can cause additional device voltage stress. Though the resonant capacitors, originally added to achieve ZVS, can absorb and recycle the leakage energy in the S4T, these capacitors need to be increased with larger leakage inductances to limit the voltage stress. However, large resonant capacitors can result in more lost duty cycles and reduced efficiency. The impact of such leakage inductance on device voltage stress is analyzed comprehensively, which is critical to guide future research and design of the S4T. Experimental results from S4T prototypes for DC-DC, multiport AC-DC, and AC-AC conversion with 1:1 and 4:1 MFT comprehensively verify the proposed concepts. Lastly, a case study of a three-phase AC-AC S4T over a power range from 1 kVA to 100 kVA each module reveals that the MFT leakage inductance should be less than 1% of the magnetizing inductance for safe operation.

14 SOLAR ENERGY↗

ASDTIC duty-cycle control for power converters.

The application of analog signal to discrete interval converter (ASDTIC), a hybrid micromodule, two-loop control subsystem, to a switching, stepdown dc-to-dc converter is described. The power circuitry, interface and ASDTIC subsystems used in this switching regulator were developed to exhibit the improved regulation, transient performance, regulator stability, and freedom from the effects of variations in parts characteristics due to environmental changes and aging. The circuitry and performance characteristics of a +10-V dc switching converter as well as that of the ASDTIC micromodule are described. Realization of the ASDTIC hybrid micromodule has been accomplished with hermetically sealed, beam-lead, bonded/deposited nichrome thin film resistors, discrete capacitors, and integrated circuits on dilithic, glazed alumina substrates, using 22 feed through terminals in an integrated package.

Lalli, V. R.↗

A Fast Monte Carlo Method for Model-Based Prognostics Based on Stochastic Calculus

This work proposes a fast Monte Carlo method to solve differential equations utilized in model-based prognostics. The methodology is derived from the theory of stochastic calculus, and the goal of such a method is to speed up the estimation of the probability density functions describing the independent variable evolution over time. In the prognostic scenarios presented in this paper, the stochastic differential equations describe variables directly or indirectly related to the degradation of a monitored system. The method allows the estimation of the probability density functions by solving the deterministic equation and approximating the stochastic integrals using samples of the model noise. By so doing, the prognostic problem is solved without the Monte Carlo simulation based on Euler's forward method, which is typically the most time consuming task of the prediction stage. Three different prognostic scenarios are presented as proof of concept: (i) life prediction of electrolytic capacitors, (ii) remaining time to discharge of Lithium-ion batteries, and (iii) prognostic of cracked structures under fatigue loading. The paper shows how the method produces probability density functions that are statistically indistinguishable from the distributions estimated with Euler's forward Monte Carlo simulation. However, the proposed solution is orders of magnitude faster when computing the time-to-failure distribution of the monitored system. The approach may enable complex real-time prognostics and health management solutions with limited computing power.

Corbetta, M.↗

A Fast Monte Carlo Method for Model-Based Prognostics Based on Stochastic Calculus

This work proposes a fast Monte Carlo method to solve differential equations utilized in model-based prognostics. The methodology is derived from the theory of stochastic calculus, and the goal of such a method is to speed up the estimation of the probability density functions describing the independent variable evolution over time. In the prognostic scenarios presented in this paper, the stochastic differential equations describe variables directly or indirectly related to the degradation of a monitored system. The method allows the estimation of the probability density functions by solving the deterministic equation and approximating the stochastic integrals using samples of the model noise. By so doing, the prognostic problem is solved without the Monte Carlo simulation based on Euler's forward method, which is typically the most time consuming task of the prediction stage. Three different prognostic scenarios are presented as proof of concept: (i) life prediction of electrolytic capacitors, (ii) remaining time to discharge of Lithium-ion batteries, and (iii) prognostic of cracked structures under fatigue loading. The paper shows how the method produces probability density functions that are statistically indistinguishable from the distributions estimated with Euler's forward Monte Carlo simulation. However, the proposed solution is orders of magnitude faster when computing the time-to-failure distribution of the monitored system. The approach may enable complex real-time prognostics and health management solutions with limited computing power.

stochastic calculus↗

Geothermal-integrated thermally anisotropic building envelope for energy and peak-demand reduction

Buildings consume large amounts of energy for heating and cooling, while peak electricity demand places significant stress on the power grid. This paper presents a reduced-order co-simulation framework and load-oriented supervisory control strategy for a geothermal-integrated thermally anisotropic building envelope with a ground loop (TABE+GL). In TABE+GL, a hydronic loop embedded in the building envelope is directly coupled with a geothermal ground loop, allowing for bidirectional heat exchange between the envelope, the ground, and the indoor environment. A hybrid co-simulation framework was established by coupling a reduced-order resistor–capacitor (RC) thermal network model with EnergyPlus augmented with GHEDesigner modules. The RC model generated feasible heat flux options under three operating modes, and EnergyPlus predicted sensible loads, energy use, and pump energy demand. At each simulation step, a supervisory control algorithm selected the optimal loop configuration and duty factor that maximizes useful TABE geothermal utilization without exceeding the predicted sensible load, thereby avoiding overheating or cooling. Case studies were conducted for Los Angeles, California, Charleston, South Carolina, and Denver, Colorado. Results showed that the proposed framework reduced HVAC electricity consumption by 43%–67%, natural gas use for space heating by 11%–38%, and peak electricity demand by 43%–88%. These results highlight the potential of combining reduced-order envelope modeling, direct geothermal coupling, and load-oriented supervisory control to improve whole building energy performance and reduce peak demand across diverse weather conditions.

Howard, Daniel [Southern Adventist University]↗

An updated technique to obtain explosive kinetics data on microsecond timescales

There are few techniques available for chemists to obtain time-to-explosion data with known temperature inputs at the early stages of the design and synthesis of new explosives. In the 1960s, a technique was developed to rapidly heat milligram-quantities of confined explosives to ~1000 K on microsecond timescales. Wenograd loaded explosives inside stainless steel hypodermic needles, connected them to a fireset and rapidly discharged a capacitor through the steel. He obtained the temperature by measuring the needle resistance in a Wheatstone bridge arrangement and the time to explosion from a needle rupture. However, owing to the narrow-gauge needles used in the original research, the experiment was only possible with melt-castable explosives; it was never replicated, and modern diagnostics are now available with advances beyond the 1960s. Here, we report the development of the High Explosives Initiation Time (HEIT) test, which utilizes a 250 J pulsed power system to heat the needles. This work extends the Wenograd approach by using optical diagnostics, computational modeling, and advanced techniques to measure needle resistance and needle rupture. Preliminary rate information for pentaerythritol tetranitrate (PETN) will be presented.

45 MILITARY TECHNOLOGY, WEAPONRY, AND NATIONAL DEF↗

The Computational Capacity of Mem-LRC Reservoirs

Reservoir computing has a emerged as a powerful tool in data-driven time series analysis. The possibility of utilizing hardware reservoirs as specialized co-processors has generated interest in the properties of electronic reservoirs, especially those based on memristors as the nonlinearity of these devices should translate to an improved nonlinear computational capacity of the reservoir. However, designing these reservoirs requires a detailed understanding of how memristive networks process information which has thus far been lacking. In this work, we derive an equation for general memristor-inductor-resistor-capacitor (MEM-LRC) reservoirs that includes all network and dynamical constraints explicitly. Utilizing this we undertake a study of the computational capacity of these reservoirs. We demonstrate that hardware reservoirs may be constructed with extensive memory capacity and that the presence of memristors enacts a tradeoff between memory capacity and nonlinear computational capacity. Here, using these principles, we design reservoirs to tackle problems in signal processing, paving the way for applying hardware reservoirs to high-dimensional spatiotemporal systems.

Circuits with memory↗

Ferroresonant flux coupled battery charger

A battery charger for incorporation into an electric-powered vehicle is disclosed. The charger includes a ferroresonant voltage-regulating circuit for providing an output voltage proportional to the frequency of an input AC voltage. A high frequency converter converts a DC voltage supplied, for example, from a rectifier connected to a standard AC outlet, to a controlled frequency AC voltage which is supplied to the input of the ferroresonant circuit. The ferroresonant circuit includes an output, a saturable core transformer connected across the output, and a first linear inductor and a capacitor connected in series across the saturable core transformer and tuned to resonate at the third harmonic of the AC voltage from the high frequency converter. The ferroresonant circuit further includes a second linear inductor connected between the input of the ferroresonant circuit and the saturable core transformer. The output voltage from the ferroresonant circuit is rectified and applied across a pair of output terminals adapted to be connected to the battery to be charged. A feedback circuit compares the voltage across the output terminals with a reference voltage and controls the frequency of the AC voltage produced by the high frequency converter to maintain the voltage across the output terminals at a predetermined value. The second linear inductor provides a highly reactive load in the event of a fault across the output terminals to render the charger short-circuit proof.

McLyman, Colonel W. T.↗

Fuel-Cell-Powered Vehicle with Hybrid Power Management

Figure 1 depicts a hybrid electric utility vehicle that is powered by hydrogenburning proton-exchange-membrane (PEM) fuel cells operating in conjunction with a metal hydride hydrogen-storage unit. Unlike conventional hybrid electric vehicles, this vehicle utilizes ultracapacitors, rather than batteries, for storing electric energy. This vehicle is a product of continuing efforts to develop the technological discipline known as hybrid power management (HPM), which is oriented toward integration of diverse electric energy-generating, energy-storing, and energy- consuming devices in optimal configurations. Instances of HPM were reported in five prior NASA Tech Briefs articles, though not explicitly labeled as HPM in the first three articles: "Ultracapacitors Store Energy in a Hybrid Electric Vehicle" (LEW-16876), Vol. 24, No. 4 (April 2000), page 63; "Photovoltaic Power Station With Ultracapacitors for Storage" (LEW- 17177), Vol. 27, No. 8 (August 2003), page 38; "Flasher Powered by Photovoltaic Cells and Ultracapacitors" (LEW-17246), Vol. 27, No. 10 (October 2003), page 37; "Hybrid Power Management" (LEW-17520), Vol. 29, No. 12 (December 2005), page 35; and "Ultracapacitor-Powered Cordless Drill" (LEW-18116-1), Vol. 31, No. 8 (August 2007), page 34. To recapitulate from the cited prior articles: The use of ultracapacitors as energy- storage devices lies at the heart of HPM. An ultracapacitor is an electrochemical energy-storage device, but unlike in a conventional rechargeable electrochemical cell or battery, chemical reactions do not take place during operation. Instead, energy is stored electrostatically at an electrode/electrolyte interface. The capacitance per unit volume of an ultracapacitor is much greater than that of a conventional capacitor because its electrodes have much greater surface area per unit volume and the separation between the electrodes is much smaller.

Eichenberg, Dennis J.↗

Fabrication of Phononic-Isolated Kinetic Inductance Detectors

Kinetic inductance detectors (KID) have received increased interest due to their relative ease of fabrication, low noise, and scalability to large format arrays required by next generation of astronomical telescopes. The development of KIDs has progressed rapidly, with very low noise equivalent power demonstrated by several groups and KIDs arrays implemented in several ground-based and air-borne instruments. In this paper, we describe a new fabrication process which consists of a membrane isolated KID incorporating a phononic bandgap structure tuned to block recombination phonons from escaping to the thermal bath. This architecture is designed to increase the quasi-particle lifetime and results in increased responsivity to signal photons and lower noise. These devices have been fabricated as lumped-element resonators with hafnium inductors and Nb capacitors on low stress silicon nitride and silicon-on-insulator membranes. We discuss the fabrication process, which uses a combination of sub-micron laser based direct write lithography and nanoscale electron beam lithography.

Denis, Kevin L.↗

Conservation Voltage Reduction with Distributed Energy Resource Management System, Grid-Edge, and Legacy Devices

Distribution utilities use conservation voltage reduction (CVR) to obtain energy savings and lower peak demand by reducing bus voltages. Traditionally, the CVR is accomplished by controlling the legacy assets such as load tap changers, voltage regulators, and capacitor banks. The deployment of the advanced distribution management system (ADMS) and distributed energy resource management system (DERMS) enables the integration of distributed energy resources into the distribution networks and provide the grid services including CVR. This paper studies the coordinated operation of an ADMS and a DERMS in achieving CVR and voltage regulation. A commercial ADMS uses legacy devices and Edge-of-Network Grid Optimization (ENGO) devices to obtain energy savings through CVR. A prototype DERMS dispatches the photovoltaic smart inverters based on real-time optimal power low to ensure voltage regulation across the feeder. The results show that the coordinated operation of ADMS and DERMS is effective in achieving CVR and voltage regulation. Specifically, energy savings of up to 4.7% are observed in the real utility distribution system used in this study.

advanced distribution management system↗

Conservation Voltage Reduction with Distributed Energy Resource Management System, Grid-Edge, and Legacy Devices: Preprint

Distribution utilities use conservation voltage reduction (CVR) to obtain energy savings and lower peak demand by reducing bus voltages. Traditionally, the CVR is accomplished by controlling the legacy assets such as load tap changers, voltage regulators, and capacitor banks. The deployment of the advanced distribution management system (ADMS) and distributed energy resource management system (DERMS) enables the integration of distributed energy resources into the distribution networks and provide the grid services including CVR. This paper studies the coordinated operation of an ADMS and a DERMS in achieving CVR and voltage regulation. A commercial ADMS uses legacy devices and Edge-of-Network Grid Optimization (ENGO) devices to obtain energy savings through CVR. A prototype DERMS dispatches the photovoltaic smart inverters based on real-time optimal power low to ensure voltage regulation across the feeder. The results show that the coordinated operation of ADMS and DERMS is effective in achieving CVR and voltage regulation. Specifically, energy savings of up to 4.7% are observed in the real utility distribution system used in this study.

advanced distribution management system↗

Conservation Voltage Reduction with Distributed Energy Resource Management System, Grid-Edge, and Legacy Devices

Distribution utilities use conservation voltage reduction (CVR) to obtain energy savings and lower peak demand by reducing bus voltages. Traditionally, the CVR is accomplished by controlling the legacy assets such as load tap changers, voltage regulators, and capacitor banks. The deployment of the advanced distribution management system (ADMS) and distributed energy resource management system (DERMS) enables the integration of distributed energy resources into the distribution networks and provide the grid services including CVR. This paper studies the coordinated operation of an ADMS and a DERMS in achieving CVR and voltage regulation. A commercial ADMS uses legacy devices and Edge-of-Network Grid Optimization (ENGO) devices to obtain energy savings through CVR. A prototype DERMS dispatches the photovoltaic smart inverters based on real-time optimal power low to ensure voltage regulation across the feeder. The results show that the coordinated operation of ADMS and DERMS is effective in achieving CVR and voltage regulation. Specifically, energy savings of up to 4.7% are observed in the real utility distribution system used in this study.

advanced distribution management system↗