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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 91 records · Page 5

Implications of the GSFC Q3 model for trapped particle motion

The Uranus magnetic field model of Connerney et al. (1987), designated GSFC Q3, is used to compute field geometric invariant parameters that determine the adiabatic motion of energetic charged particles trapped in the Uranian magnetosphere, performing computations only for points located along the Voyager 2 flyby trajectory. The L-shell values computed along the Voyager-2 trajectory were compared with L shell values corresponding to the orbital positions for the Uranian satellites Ariel, Umbriel, Miranda, and Titania for a time period centered on the time of the Voyager 2 closest approach to the planet. Bimodal distributions of L minima asociated with the orbital motion of the moons are obtained, thus complicating the model predictions and correlations with charged particle data. The location of charged particle absorption signatures associated with the sweeping effects of the Uranian satellites is reasonably predicted, but significant discrepancies remain which cannot be explained by Q3 model uncertainties.

Acuna, M. H.↗

Io and its plasma environment

The interaction of Io with its plasma torus and the Jovian magnetic field is described and examined in the context of several currently popular models. Three specific matters are addressed. First, features implied by sub-Alfvenic flow which must be common to all models are discussed. Next, the magnetic signature observed near Io by the Goddard Space Flight Center Voyager 1 magnetometer is examined and it is pointed out that the preliminary estimate of 5,000,000 A current may be an overestimate. Good fits are obtained with alternative current distributions which yield currents as small as 700,000 A through Io. The best fits are obtained for an Alfven Mach number of 0.15, but good fits are also found for Alfven Mach numbers between 0.1 and 0.25. Lastly, the crucial role of charged particle data for probing the near Io interaction is pointed out. Published data from the low energy charged particle (LECP) detector are made to suggest that Io has an intrinsic magnetic field of magnitude comparable with earlier estimates. Predictions are made which can test this picture as further data become available.

Southwood, D. J.↗

Parallelizing the Unpacking and Clustering of Detector Data for Reconstruction of Charged Particle Tracks on Multi-core CPUs and Many-core GPUs

We present results from parallelizing the unpacking and clustering steps of the raw data from the silicon strip modules for reconstruction of charged particle tracks. Throughput is further improved by concurrently processing multiple events using nested OpenMP parallelism on CPU or CUDA streams on GPU. The new implementation along with earlier work in developing a parallelized and vectorized implementation of the combinatoric Kalman filter algorithm has enabled efficient global reconstruction of the entire event on modern computer architectures. We demonstrate the performance of the new implementation on Intel Xeon and NVIDIA GPU architectures.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Short-Term Load Forecasting Considering EV Charging Loads with Prediction Interval Evaluation

Short-term load forecasting plays a critical role in power system planning and operation. Along with the electrification of various loads, electricity demands are becoming increasingly hard to predict. Notably, the recent rise in electric vehicles (EVs) has further contributed to this unpredictability. To address this issue, this paper proposes a probabilistic load forecasting strategy utilizing Gaussian process regression, structured in a day-ahead manner. While many works focus on deterministic prediction, probabilistic forecasting offers additional insights into variability and uncertainty, enabling more flexible and reliable operation for power systems. To enhance the accuracy of the load forecasting model, the inputs include features related to EV charging habits as well as commonly used weather information. The load forecasting results are evaluated using various metrics, including conventional ones that assess the accuracy of point forecasts, as well as additional metrics that test the reliability of prediction intervals. The proposed load forecasting method is finally tested on real residential power consumption data and EV charging data sampled from real-world sources. The results prove that the new features can greatly improve the performance of the load forecasting method.

electrical vehicle↗

Evaluation of electrostatic charge effects on the data processing system and the orbiter communication and tracking receivers

An analysis of radiated interference test results obtained from frictionally charged Orbiter TPS tile was presented. The tests included the measurement of noise pick-up by Orbiter S-band, L-band, C-band, and Ku-band antennas located beneath the tiles in a manner simulating their installation on Orbiter. In addition, the radiated field characteristics resulting from the static discharge was determined. The results are analyzed as to their effect on data bus equipment and on Orbiter Communications and Tracking (C&T) receivers. It was concluded that the radiated interference should have no effect on MDM's. However the CPU, IOP and PMU enclosures require some minor modification to assure immunity from P-static interference. Orbiter antenna tests indicate that the S-band receiver should not be affected by P-static noise. The TACAN and Radar Altimeter performance appears to be adequate but with a small margin. MSBLS performance is uncertain because laboratory instrumentation cannot approach the MSBLS sensitivity.

Lawton, R. M.↗

EV Profile Capture

NextGen Profiles' EV profile capture efforts aimed to explore the variance in performance and evaluate how different operational conditions influence production EV charging behavior. Data were collected at a frequency of 10 Hz from both the EV and EVSE during each charge session. These charge session parameters were then entered into a time-series database for further analysis. The data were gathered under different operational conditions to examine the effects of various factors such as battery state of charge, battery temperature, vehicle condition, smart charge management, and EVSE limitations. The EV profile capture dataset includes extensive high-power charging data from 16 different EVs—comprising light-, medium-, and heavy-duty vehicles—along with EVSE from various suppliers. To protect confidentiality, the EV and EVSE metadata are anonymized, and the publicly released datasets are aggregated to 0.1-Hz frequency.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Reduction and scientific analysis of data from the charge-energy-mass (CHEM) spectrometer on the AMPTE/CCE spacecraft

The Charge-Energy-Mass (CHEM) spectrometer instrument on the AMPTE/Charge Composition Explorer (CCE) spacecraft is designed to measure the mass and charge-state abundance of magnetospheric and magnetosheath ions between 0.3 and 315 keV/e, an energy range that includes the bulk of the ring current and the dynamically important portion of the plasma sheet population. Continuing research is being conducted using the AMPTE mission data set, and in particular, that of the CHEM spectrometer which has operated flawlessly since launch and still provides excellent quality data. The requirted routine data processing and reduction, and software develpment continues to be performed. Scientific analysis of composition data in a number of magnetospheric regions including the ring current region, near-earth plasma sheet and subsolar magnetosheath continues to be undertaken. Correlative studies using data from the sister instrument SULEICA, which determines the mass and charge states of ions in the energy range of approximately 10 to 250 keV/e on the IRM, as well as other data from the CCE and IRM spacecraft, particularly in the upstream region and plasma sheet have also been undertaken.

Gloeckler, G.↗

Evaluating system responses to electric vehicle charging infrastructure expansion through data-driven simulation

Understanding the system responses to electric vehicle (EV) charging infrastructure expansion, including vehicle charging needs, station utilization, and energy consumption, is critical for effective planning to meet growing charging demand without unnecessary resource investment. This study evaluates the system responses to EV charging infrastructure expansion, focusing on charging needs, station utilization, and energy consumption. Using trip data from the National Household Travel Survey and origin–destination patterns, we simulated trip chains in downtown Atlanta with 10 % EV penetration. We assessed 32 scenarios involving different charging port power levels and siting strategies. Furthermore, we found that higher-power ports were more sensitive to placement, with concentrated expansion boosting station utilization more than uniform expansion. Adding high-power ports did not always increase peak energy consumption; in some cases, a few 400 kW ports reduced overall consumption compared to 150 kW ports by enabling faster charging and higher vehicle turnover.

Electric vehicle↗

Analyzing Residential Charging Demand for Light-Duty Electric Vehicles in Colorado

The past decade has witnessed a remarkable surge in adoption of electric vehicles (EVs). The momentum is expected to continue with strong support from governments and industry. Rapid EV adoption will add significant electricity demand, making it critical to plan for and manage EV charging to avoid causing additional stress and non-negligible risks to the already-aging power grid. To help power grid operators understand the impacts of residential EV charging and identify risk factors, this study presents a data-driven charging demand analysis for light-duty vehicles. This study considers two real-world grid service regions in Colorado and merges multiple data sources and state-of-the-art tools that characterize EV adoption projections, vehicle travel patterns, seasonal variations, residential charging accessibility, ambient temperature impact, EV charging behaviors, grid utility customers, vehicle registration, and household-level EV charging demand distribution. We characterize potential residential charging demand in 2030 for two regions within the state of Colorado: Boulder and Aurora regions. We project that EVs will be 26% of the light-duty vehicle population in Boulder and 16% in Aurora areas. Charging demand is characterized for ten power grid feeders (five for each study region). Across the ten feeders, peak total EV charging powers during wintertime range from less than 1 MW to more than 4 MW.

ADVANCED PROPULSION SYSTEMS↗

Irradiated stainless steel 347 and irradiated, welded, and hydrogen charged Zircaloy-4 property data for the target solution vessel and support lines of SHINE

In support of the reactor-vessel development effort of SHINE medical technologies, irradiation of its structural materials and post-irradiation testing have been performed in the High Flux Isotope Reactor at Oak Ridge National Laboratory. This irradiation was performed on welded and unwelded AISI 347 steel and Zircaloy-4 samples at low temperature (~60°C) in contact with the reactor coolant. Hardness, Charpy, and tensile data have been taken from all cases of unirradiated specimens, while post-irradiation tensile and hardness data have been taken from AISI 347 base metal and Zircaloy-4 base metal and weld specimens so far. Additionally, 3-point bend data have been taken from explosion-welded specimens. The expected changes to hardness, yield strength, ultimate tensile strength, uniform elongation, and total elongation as a result of the low temperature and low dose neutron irradiation are reported here.

36 MATERIALS SCIENCE↗

NEWTS EPA Gasification Dataset and Case Studies

Data from the US EPA Gasification Database containing gasification effluent data from selected U.S. coal power plants. Original data from: Nguyen, Dan-Tam, Eastern Research Group. Sep 29, 2015. Analytical Database for the Steam Electric Rulemaking - DCN SE05359. https://www.regulations.gov/document/EPA-HQ-OW-2009-0819-5640 Files include: Original data tab, processed data and charge balance information in "NEWTS_EPA_Gasification_Effluent_Dataset_all_tabs.xlsx" Individual .csv files for data in format for input into aqueous chemistry modeling software (OLI Systems and Geochemist's Workbench) Data input templates for modeling streams in OLI Systems and Geochemist's Workbench Case studies for selected solved streams modeled in OLI Systems and Geochemist's Workbench

gasification↗

Western Smart Regional EV Adoption and Infrastructure at Scale- WestSmartEV@Scale (Budget Period 2 – Milestone Report – TNC EV Study)

WestSmartEV@Scale is a comprehensive research project addressing key opportunities to decarbonize transportation throughout the Rocky Mountain West. Building upon the framework established in the original WestSmart project, unique subprojects are scoped targeting transportation emissions across light-, medium-, and heavy-duty vehicles with consideration of equity and access. This report summarizes the progress to date on Subproject 6, TNC EV Study (Urban Mobility). It is comprised of three sections: • Outreach and participant recruitment; • Survey data collection and analysis; and • BEV driver driving and charging behavior data collection and analysis.

33 ADVANCED PROPULSION SYSTEMS↗

Validation of the NASCAP model using spaceflight data

The NASA Charging Analyzer Program (NASCAP) has been validated in a space environment. Data collected by the SCATHA (Spacecraft Charging at High Altitude) spacecraft has been used with NASCAP to simulate the charging response of the spacecraft ground conductor and dielectric surfaces with considerable success. Charging of the spacecraft ground observed in eclipse, during moderate and severe substorm environments, and in sunlight has been reproduced using the code. Close agreement between both the currents and potentials measured by the SSPM's, and the NASCAP simulated response, has been obtained for differential charging. It is concluded that NASCAP is able to predict spacecraft charging behavior in a space environment.

Stannard, P. R.↗

Correlation of Resonance Charge Exchange Cross-Section Data in the Low-Energy Range

During the course of a literature survey concerning resonance charge exchange, an unusual degree of agreement was noted between an extrapolation of the data reported by Kushnir, Palyukh, and Sena and the data reported by Ziegler. The data of Kushnir et al. are for ion-atom relative energies from 10 to 1000 ev, while the data of Ziegler are for a relative energy of about 1 ev. Extrapolation of the data of Kushnir et al. was made in accordance with Holstein's theory, 3 which is a combination of time-dependent perturbation methods and classical orbit theory. The results of this theory may be discussed in terms of a critical impact parameter b(sub c).

Sheldon, John W.↗