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At least 1,657 records · Page 92
All sourcesNASA NTRSDOE OSTI
DOE OSTI2018

Development of Dynamic Model of a Ternary Pumped Storage Hydropower Plant

Hydropower is the largest source of renewable energy in the United States. Pumped storage hydropower (PSH) is a hydropower plant that can generate power when it operates as a hydro turbine, and it can absorb power from the electric grid when it is pumping water from the lower reservoir to the upper reservoir. The conventional role of PSH is as an energy arbitrage: it sells power when the price of electricity is high (i.e., during peak hours of energy demand), and it is operated as a pump during times when the price of electricity is low (e.g., midnight to dawn). PSH is an important part in hydropower generation. Currently, the total installed capacity is approximately 22 GW. Recently, a new type of PSH was developed, called ternary PSH (T-PSH). T-PSH is a type of advanced PSH that is different from conventional PSH and adjusted-speed PSH. T-PSH uses a single generator rotating in one direction with two different runners connected to the same shaft (i.e., one is for pumping water, and the other is for generating power as a turbine). This paper presents the development of a dynamic model of T-PSH for power system analysis. T-PSH can be operated in three different modes: generating mode, pumping mode, and hydraulic short-circuit (HSC) mode. The three modes of operation will be presented in this paper. A new combined governor is developed to represent the HSC operation mode, which is a special mode for T-PSH. The power command is divided into two parts, and a distribution coefficient is introduced to regulate the transitions from one mode to the other. Simulation and validation results are presented to verify the performance of the governor model and the characteristics of T-PSH.

15 GEOTHERMAL ENERGY↗
DOE OSTI2019

Effect of ZnS, iZnO, dZnO and Cu(In,Ga)Se{sub 2} thickness on the performance of simulated Mo/Cu(In,Ga)Se{sub 2}/ZnS/iZnO/dZnO solar cell

In this paper, Mo/Cu(In,Ga)Se{sub 2}/ZnS/iZnO/dZnO solar cell is simulated and optimized by studying the effect of layers thickness on solar cell efficiency using Silvaco ATLAS software. The input simulation parameters are: dielectric permittivity (ε), band gap energy (E{sub g}), electron affinity (χ), conduction band effective density of states (N{sub c}), valence band effective density of states (N{sub v}). The output parameters used to find the optimum values of the layers thickness are the short circuit current density (I{sub sc}), open circuit voltage (V{sub oc}), maximum power (P{sub max}), fill factor (FF), efficiency (η), Current–voltage (I–V) and power–voltage (P–V) characteristics.

14 SOLAR ENERGY↗
DOE OSTI2020

HEMP Testing of Substation Yard Circuit Breaker Control and Protective Relay Circuits

There are concerns about the effects of High-Altitude Electromagnetic Pulses (HEMP) on the electric power grid. Activities to date tested and analyzed vulnerability of digital protective relays (DPRs) used in power substations, but the effect of HEMP on the greater substation environment is not well known. This work establishes a method of testing the vulnerability of circuit breaker control and protective relay circuits to the radiated E1 pulse associated with HEMP based on coupling to the cables in a substation yard. Two DPRs from Schweitzer Engineering Laboratories, Inc. were independently tested. The test setup also included a typical cable in a substation yard with return plane to emulate the ground grid and other ground conductors near the yard cable, cabinetry housing the installed DPRs, station battery and battery charger, terminal block elements, and a breaker simulator to emulate a substation yard configuration. The DPRs were powered from the station battery and the transformer inputs energized with a three-phase source to maintain typical operating conditions during the tests. Vulnerability testing consisted of a conducted E1 pulse injected into the center of the yard cable of the DPR circuits. Current measurements on the yard cable and DPR inputs indicated significant attenuation of the conducted pulse arriving at the control house equipment from the emulated substation yard. This reduction was quantified with respect to the equivalent open-circuit voltage on the yard cable. No equipment damage or undesired operation occurred on the tested circuits for values below 180 kV, which is significantly higher than the anticipated coupling to a substation yard cable.

24 POWER TRANSMISSION AND DISTRIBUTION↗
NASA NTRS2012

The Ground Flash Fraction Retrieval Algorithm Employing Differential Evolution: Simulations and Applications

The ability to estimate the fraction of ground flashes in a set of flashes observed by a satellite lightning imager, such as the future GOES-R Geostationary Lightning Mapper (GLM), would likely improve operational and scientific applications (e.g., severe weather warnings, lightning nitrogen oxides studies, and global electric circuit analyses). A Bayesian inversion method, called the Ground Flash Fraction Retrieval Algorithm (GoFFRA), was recently developed for estimating the ground flash fraction. The method uses a constrained mixed exponential distribution model to describe a particular lightning optical measurement called the Maximum Group Area (MGA). To obtain the optimum model parameters (one of which is the desired ground flash fraction), a scalar function must be minimized. This minimization is difficult because of two problems: (1) Label Switching (LS), and (2) Parameter Identity Theft (PIT). The LS problem is well known in the literature on mixed exponential distributions, and the PIT problem was discovered in this study. Each problem occurs when one allows the numerical minimizer to freely roam through the parameter search space; this allows certain solution parameters to interchange roles which leads to fundamental ambiguities, and solution error. A major accomplishment of this study is that we have employed a state-of-the-art genetic-based global optimization algorithm called Differential Evolution (DE) that constrains the parameter search in such a way as to remove both the LS and PIT problems. To test the performance of the GoFFRA when DE is employed, we applied it to analyze simulated MGA datasets that we generated from known mixed exponential distributions. Moreover, we evaluated the GoFFRA/DE method by applying it to analyze actual MGAs derived from low-Earth orbiting lightning imaging sensor data; the actual MGA data were classified as either ground or cloud flash MGAs using National Lightning Detection Network[TM] (NLDN) data. Solution error plots are provided for both the simulations and actual data analyses.

Koshak, William↗
DOE OSTI2018

Current Loss in 0.1 - 100 Terawatt Vacuum Transmission Lines: Experiments and Simulations

Current loss in magnetically insulated transmission lines (MITLs) was investigated using data from experiments conducted on Z and Mykonos. Data from experiments conducted on Z were used to optimize an ion diode current loss model that has been implemented into the transmission line circuit model of Z. Details on the current loss model and comparisons to data from Z experiments have been previously published in a peer-reviewed journal [Hutsel, et al., Phys. Rev. Accel. Beams 21, 030401]. Dedicated power flow experiments conducted on Mykonos investigated current loss in a millimeter-scale anode-cathode gap MITL operated at lineal current densities greater than 410 kA/cm and with electric field stresses in excess of 240 kV/cm where it is expected that both anode and cathode plasmas are formed. The experiment MITLs were exposed to varying vacuum conditions; including vacuum pressure at shot time, time under vacuum, and vacuum storage protocols. The results indicate that the vacuum conditions have an effect on current loss in high lineal current density MITLs.

42 ENGINEERING↗
DOE OSTI2025

Quantum AI Based Enhanced Detection of Dementia

Quantum computing has the potential to significantly improve the early detection of Alzheimer's Disease and Related Dementias (ADRD). Quantum-enhanced machine learning can be used to perform an early screening of Alzheimer's disease using brain imaging data based on dataset of MRI scans from both healthy individuals and those diagnosed with Alzheimer's. This study aims to demonstrate the potential of quantum transfer learning to enhance the performance of the classical deep learning model for dementia detection. Using the MRI sagittal images available in the OASIS-2 (64 demented and 72 non-demented subjects between 60 and 96 years), we show how quantum techniques can transform a suboptimal classical model into a more effective solution for dementia detection, highlighting their potential impact on advancing healthcare technology. We begin with a simple classical deep learning model with a significantly smaller number of parameters, which gives suboptimal performance on the problem. Then, we apply different configurations of quantum transfer learning based on the pre-trained weak classifier (Figure 1). We fix the weak classifier's initial convolutional layers at their fixed pre-trained parameters and replace the last set of dense layers with a dressed quantum circuit (DQN), which we train to enhance performance. We performed 4-fold cross-validation for both the classical and the hybrid quantum models and trained them using Pennylane's `default.qubit' simulator and IonQ's Aria-1 simulator (noisy simulation). We showed that with significantly fewer parameters, the quantum transfer learning-based hybrid models showed significant performance enhancement over the base weak classical deep learning model for dementia detection. To classify between a demented and non-demented subject, the accuracy of quantum-based AI methods improved by 6 to 14% compared to classical methods. The sensitivity of the models improved by 4 to 17%. This shows that there are fewer chances of misclassifying demented patients. Figure 2 compares the performance of the hybrid quantum models and their base classical model, and Table 1 summarizes the results. We illustrated that with assistance from quantum machine learning, it is possible to enhance detection for dementia based on brain images. This shows the potential for practical utility of quantum computing in ADRD research.

Bhowmik, Sounak [University of Tennessee, Knoxvill↗
DOE OSTI2019

Series Resistance Measurements of Perovskite Solar Cells Using J sc – V oc Measurements

The fill factor (FF) of perovskite solar cells is considerably lower than that of gallium arsenide and silicon cells, though they have similar open–circuit voltage deficits. To probe the FF loss, which mainly comes from series resistance, the J sc –V oc characterization technique is applied to perovskite solar cells. A continuous–lamp solar simulator with an array of neutral density filters is used instead of the quasi–steady–state photoconductance technique commonly employed for silicon cells, which allows us to tune sweep parameters to accommodate the complex behavior of perovskites such as hysteresis. It is found that, for Cs 0.25 FA 0.75 Pb(Br 0.2 I 0.8 ) 3 (CsFA) perovskite cells, sweeping from positive to negative voltage yields the same series resistance regardless of sweep speed, whereas this is not the case if the sweep is reversed. However, for CH 3 NH 3 PbI 3 perovskite cells, the series resistance is independent of the sweep speed in both sweep directions. Furthermore, it is also found that, for a poly[bis(4–phenyl)(2,4,6–trimethylphenyl)amine] (PTAA) hole contact, increasing the PTAA thickness barely changes the recombination–limited pseudo–FF, but reduces the FF due to increased series resistance. A maximum FF of 80.9% was achieved with the PTAA hole contact on a CsFA perovskite absorber.

14 SOLAR ENERGY↗
DOE OSTI2021

Scalable semitransparent prototype organic photovoltaic module with minimal resistance loss

Semi-transparent organic photovoltaic (ST-OPV) cells are regarded as an attractive solution to building-integrated solar energy harvesting. Both the power conversion efficiency (PCE) and average photopic transmission (APT) of ST-OPVs have shown substantial increases in recent years. However, less attention has been paid to the area scaling of ST-OPV cells. In this work, we investigate the scalability of ST-OPV cells from 4 mm 2 to 1 cm 2 , as well as 9 cm 2 active area prototype module. By integrating both top and bottom metal grids onto the transparent electrodes, the series resistance loss of 1 cm 2 ST-OPV cell is significantly reduced, and is comparable to that of the grid-free 4 mm 2 cell. Nine 1 cm 2 cells are then connected in a series-parallel circuit to realize a prototype ST-OPV module. A 100% fabrication yield with only 5% PCE deviation among discrete cells is achieved. The semitransparent module shows PCE = 7.2 ± 0.1% under simulated AM 1.5G illumination at 1 sun intensity, which exhibits no connection resistance loss compared to that of the individual cells. The ST-OPV module exhibits an APT = 38.1 ± 1.1%, which enables a light utilization efficiency, LUE = 2.74 ± 0.09%. Here, the method demonstrates a promising way for ST-OPV modules to scale without compromising performance.

14 SOLAR ENERGY↗
DOE OSTI2021

Fast digital lossy compression for X-ray ptychographic data

Increases in X-ray brightness from synchrotron light sources lead to a requirement for higher frame rates from hybrid pixel array detectors (HPADs), while also favoring charge integration over photon counting. However, transfer of the full uncompressed data will begin to constrain detector design, as well as limit the achievable continuous frame rate. Here a data compression scheme that is easy to implement in a HPAD's application-specific integrated circuit (ASIC) is described, and how different degrees of compression affect image quality in ptychography, a commonly employed coherent imaging method, is examined. Using adaptive encoding quantization, it is shown in simulations that one can digitize signals up to 16383 photons per pixel (corresponding to 14 bits of information) using only 8 or 9 bits for data transfer, with negligible effect on the reconstructed image.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2025

Visual Analytics of Crosstalk in Quantum Hardware

Crosstalk remains a major obstacle to building scalable and fault-tolerant quantum computers. Conventional diagnostic techniques-often based on numerical simulation or statistical modeling-struggle to scale with hardware complexity and offer limited interpretability. In this work, we present a visual analytics framework for diagnosing qubit crosstalk using lightweight, circuit-based models integrated with an interactive user interface. Our approach quantifies correlations between active and idle qubits under parameterized single- and twoqubit operations, enabling detection of both spatial and gateinduced crosstalk. The system incorporates qubit topology and gate performance data to support sector-based exploration and correlation mapping. This tool assists users in identifying correlated error sources, informing qubit placement strategies, and guiding noise-aware circuit design.

Chae, Junghoon [ORNL] (ORCID:0000000206016746)↗
DOE OSTI2019

A brain-plausible neuromorphic on-the-fly learning system implemented with magnetic domain wall analog memristors

Neuromorphic computing is an approach to efficiently solve complicated learning and cognition problems like the human brain using electronics. To efficiently implement the functionality of biological neurons, nanodevices and their implementations in circuits are exploited. Here, we describe a general-purpose spiking neuromorphic system that can solve on-the-fly learning problems, based on magnetic domain wall analog memristors (MAMs) that exhibit many different states with persistence over the lifetime of the device. The research includes micromagnetic and SPICE modeling of the MAM, CMOS neuromorphic analog circuit design of synapses incorporating the MAM, and the design of hybrid CMOS/MAM spiking neuronal networks in which the MAM provides variable synapse strength with persistence. Using this neuronal neuromorphic system, simulations show that the MAM-boosted neuromorphic system can achieve persistence, can demonstrate deterministic fast on-the-fly learning with the potential for reduced circuitry complexity, and can provide increased capabilities over an all-CMOS implementation.

42 ENGINEERING↗
DOE OSTI2023

Rational design of Lewis base molecules for stable and efficient inverted perovskite solar cells

Lewis base molecules that bind undercoordinated lead atoms at interfaces and grain boundaries (GBs) are known to enhance the durability of metal halide perovskite solar cells (PSCs). Using density functional theory calculations, we found that phosphine-containing molecules have the strongest binding energy among members of a library of Lewis base molecules studied herein. Experimentally, we found that the best inverted PSC treated with 1,3-bis(diphenylphosphino)propane (DPPP), a diphosphine Lewis base that passivates, binds, and bridges interfaces and GBs, retained a power conversion efficiency (PCE) slightly higher than its initial PCE of ~23% after continuous operation under simulated AM1.5 illumination at the maximum power point and at ~40°C for >3500 hours. DPPP-treated devices showed a similar increase in PCE after being kept under open-circuit conditions at 85°C for >1500 hours.

14 SOLAR ENERGY↗
DOE OSTI2013

Development of Compact Gamma Camera for Detection of Prostate Carcinoma

BNL and Hybridyne will jointly develop a compact gamma camera capable of localizing cancerous tumors within the prostate gland. The new gamma-ray camera will consist of a pixilated cadmium-zinc-telluride (CZT) detector array, which would be flip-chip bonded to a suitable substrate. Application specific integrated circuits would also be developed to read out the electronic signals from the pixels, and the detector/ASIC would be integrated into a small probe capable of imaging shaped radioactive phantoms to simulate the detection of cancerous tumors within the prostate gland.

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2018

Formulas For Plane Wave Coupling To A Transmission Line Above Ground With Terminating Loads

This report considers plane wave coupling to a transmission line consisting of a wire above a conducting ground. Comparisons are made for the two types of available source models, along with a discussion about the decomposition of the line currents. Simple circuit models are constructed for the terminating impedances at the ends of the line including radiation effects. Results from the transmission line with these loads show good agreement with full wave simulations.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2026

Upgrading Biogas through in situ Conversion of Carbon Dioxide to Biomethane in Anaerobic Digesters

Organic waste streams generated by wastewater treatment plants, agricultural operations, and food processing industries represent an important yet underutilized opportunity for renewable energy production in the United States. Through anaerobic digestion, these waste streams can produce biogas, a mixture primarily composed of methane (CH4) and carbon dioxide (CO2), that can be upgraded to pipeline-quality natural gas. However, most existing upgrading technologies remove CO2 from biogas rather than utilizing it, leaving a significant portion of the potential energy unused. This project investigates a novel biological upgrading approach that converts CO2 into additional CH4 by supplying hydrogen (H2) to specialized microorganisms capable of performing hydrogenotrophic methanation. The main challenges associated with biological biogas upgrading are related to hydrogen supply, gas-liquid mass transfer, and process stability. First, due to the high cost of hydrogen gas, it is preferable that H2 be produced on-site using renewable energy sources such as wind or solar power. Second, hydrogen has low solubility in liquids, which limits its availability to microorganisms and requires strategies to improve gas dissolution and transfer within the reactor. Third, process inhibition may occur as a result of increased pH caused by CO2 consumption or elevated H2 partial pressure, both of which can negatively affect methanogenic activity. Although research in these areas has advanced during the course of this project, these challenges have not yet been fully resolved. To date, the biological systems that have achieved the highest methane concentrations are typically ex-situ reactors, where operational conditions can be more easily controlled. For this reason, the findings of the present project remain highly relevant. The project goal was to develop an innovative system that can accomplish biogas upgrading via biological conversion of CO2 to CH4, in a novel hybrid approach that combines the advantages of both in-situ and ex-situ systems. The proposed system employs a three-phase upflow anaerobic bioreactor with H2 delivery through a gas-permeable membrane, enabling efficient hydrogen transfer and microbial conversion. Under optimized operating conditions, the system achieved 99% H2 consumption and 90% CO2 conversion. A subsequent gas cleaning stage was implemented to further improve gas quality and meet target purity standards. The upgraded gas composition reached 97.7% CH4, 2.2% CO2, and 0.97% O2, while H2S concentrations remained below detection limits. In addition, a flue gas-driven inorganic thermoelectric generator (TEG) system was designed and experimentally validated as a potential source of electricity for H2 production. The system consisted of six TEG modules connected in series and achieved an open-circuit voltage of 4.5 V and a maximum power output of 224 mW at a temperature difference of approximately 53.5 °C, demonstrating effective conversion of waste heat into electrical power under simulated flue gas conditions. Finally, a comprehensive techno-economic analysis was completed to evaluate the capital and operating costs associated with the proposed system. The results provide important insights to guide future scale-up, optimization, and potential deployment of integrated biological biogas upgrading technologies.

09 BIOMASS FUELS↗
NASA NTRS1991

Power electronics for low power arcjets

In anticipation of the needs of future light-weight, low-power spacecraft, arcjet power electronics in the 100 to 400 W operating range were developed. Limited spacecraft power and thermal control capacity of these small spacecraft emphasized the need for high efficiency. Power topologies similar to those in the higher 2 kW and 5 to 30 kW power range were implemented, including a four transistor bridge switching circuit, current mode pulse-width modulated control, and an output current averaging inductor with an integral pulse generation winding. Reduction of switching transients was accomplished using a low inductance power distribution network, and no passive snubber circuits were necessary for power switch protection. Phase shift control of the power bridge was accomplished using an improved pulse width modulation to phase shift converter circuit. These features, along with conservative magnetics designs allowed power conversion efficiencies of greater than 92.5 percent to be achieved into resistive loads over the entire operating range of the converter. Electromagnetic compatibility requirements were not considered in this work, and control power for the converter was derived from AC mains. Addition of input filters and control power converters would result in an efficiency of on the order of 90 percent for a flight unit. Due to the developmental nature of arcjet systems at this power level, the exact nature of the thruster/power processor interface was not quantified. Output regulation and current ripple requirements of 1 and 20 percent respectively, as well as starting techniques, were derived from the characteristics of the 2 kW system but an open circuit voltage in excess of 175 V was specified. Arcjet integration tests were performed, resulting in successful starts and stable arcjet operation at power levels as low as 240 W with simulated hydrazine propellants.

Hamley, John A.↗
NASA NTRS1992

Content addressable memory project

A parameterized version of the tree processor was designed and tested (by simulation). The leaf processor design is 90 percent complete. We expect to complete and test a combination of tree and leaf cell designs in the next period. Work is proceeding on algorithms for the computer aided manufacturing (CAM), and once the design is complete we will begin simulating algorithms for large problems. The following topics are covered: (1) the practical implementation of content addressable memory; (2) design of a LEAF cell for the Rutgers CAM architecture; (3) a circuit design tool user's manual; and (4) design and analysis of efficient hierarchical interconnection networks.

Hall, J. Storrs↗
DOE OSTI2015

Temperature coefficients for GaInP/GaAs/GaInNAsSb solar cells

We report the temperature coefficients for MBE-grown GaInP/GaAs/GaInNAsSb multijunction solar cells and the corresponding single junction sub-cells. Temperature-dependent current-voltage measurements were carried out using a solar simulator equipped with a 1000 W Xenon lamp and a three-band AM1.5D simulator. The triple-junction cell exhibited an efficiency of 31% at AM1.5G illumination and an efficiency of 37–39% at 70x real sun concentration. The external quantum efficiency was also measured at different temperatures. The temperature coefficients up to 80°C, for the open circuit voltage, the short circuit current density, and the conversion efficiency were determined to be −7.5 mV/°C, 0.040 mA/cm{sup 2}/°C, and −0.09%/°C, respectively.

14 SOLAR ENERGY↗