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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

Demonstration of INCC6 for advanced list-mode data acquisition and analysis using ALMM

The International Neutron Coincidence Counting (INCC) software plays an important role in nuclear safeguards and nuclear material control and accounting (NMC&A) measurements. While the current version, INCC5, represents the traditional standard utilized by inspectorates as well as facilities and practitioners alongside shift register hardware, LANL has recently developed an upgraded version of the software, INCC6. INCC6 offers the same analysis tools as INCC5 while adding new capabilities including acquisition and analysis of list-mode data, recording and storage of list-mode data files, and an expanded set of advanced analysis tools that make use of the additional information available from list-mode data. Here, this paper presents the first demonstration of data acquisition and analysis using INCC6 and the Advanced List Mode Multiplicity Module (ALMM). The capability of INCC6 to perform live list-mode data acquisition and analysis is demonstrated for a variety of neutron sources with a range of neutron emission rates relevant for practical applications and validated against the results obtained with INCC5 and traditional shift register hardware. Advanced list-mode analysis tools introduced by INCC6, such as time-interval and coincidence matrix analysis, are also demonstrated. Finally, the capability of INCC6 to analyze list-mode data files is tested and validated against traditional shift register results using INCC5.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2021

GAMA/DEVILS: constraining the cosmic star formation history from improved measurements of the 0.3–2.2 μm extragalactic background light

We present a revised measurement of the optical extragalactic background light (EBL), based on the contribution of resolved galaxies to the integrated galaxy light (IGL). The cosmic optical background radiation (COB), encodes the light generated by star formation, and provides a wealth of information about the cosmic star formation history (CSFH). We combine wide and deep galaxy number counts from the Galaxy And Mass Assembly survey (GAMA) and Deep Extragalactic VIsible Legacy Survey (DEVILS), along with the Hubble Space Telescope (HST) archive and other deep survey data sets, in nine multiwavelength filters to measure the COB in the range from 0.35 μm to 2.2 μm. We derive the luminosity density in each band independently and show good agreement with recent and complementary estimates of the optical-EBL from very high-energy (VHE) experiments. Our error analysis suggests that the IGL and γ-ray measurements are now fully consistent to within $\sim 10{{\ \rm per\ cent}}$, suggesting little need for any additional source of diffuse light beyond the known galaxy population. We use our revised IGL measurements to constrain the CSFH, and place amplitude constraints on a number of recent estimates. As a consistency check, we can now demonstrate convincingly, that the CSFH, stellar mass growth, and the optical-EBL provide a fully consistent picture of galaxy evolution. Here, we conclude that the peak of star formation rate lies in the range 0.066–0.076 M ⊙ yr -1 Mpc -3 at a lookback time of 9.1 to 10.9 Gyr.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2020

“Third-body” collision parameters for hydrocarbons, alcohols, and hydroperoxides and an effective internal rotor approach for estimating them

Collision rate constants and third-body collision efficiencies are calculated for more than 300 alkanes, alcohols, and hydroperoxides, for the bath gases He, Ar, H 2 , and N 2 , and from 300 to 2000 K. The data set includes highly branched species and species with as many as 16 nonhydrogen atoms N , and it is analyzed to develop strategies for estimating collision properties more generally. Simple analytic formulas describing the Lennard-Jones collision parameters $σ$ and $ε$ are obtained for each of the three classes of systems as a function of N . Trends in the collision efficiency range parameter $α$ = $\langle$Δ E d $\rangle$ are more complicated, and a method is developed and validated for estimating $α$ based on the numbers and types of internal rotors and oxygen-containing groups. Specifically, the approach maps the expected value of $α$ for a branched alkane, alcohol, or hydroperoxide onto those for the corresponding normal (linear) series via an effective number of nonhydrogen atoms N eff . The prescription for N eff is based on counting internal rotor types and is shown to be insensitive to temperature and fairly insensitive to the identity of the bath gas. Together, these strategies allow for the ready estimation of the collision parameters $σ$, $ε$, and $α$ so long as results for the associated linear series are available.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

Statistical Significance Testing for Mixed Priors: A Combined Bayesian and Frequentist Analysis

In many hypothesis testing applications, we have mixed priors, with well-motivated informative priors for some parameters but not for others. The Bayesian methodology uses the Bayes factor and is helpful for the informative priors, as it incorporates Occam’s razor via the multiplicity or trials factor in the look-elsewhere effect. However, if the prior is not known completely, the frequentist hypothesis test via the false-positive rate is a better approach, as it is less sensitive to the prior choice. We argue that when only partial prior information is available, it is best to combine the two methodologies by using the Bayes factor as a test statistic in the frequentist analysis. We show that the standard frequentist maximum likelihood-ratio test statistic corresponds to the Bayes factor with a non-informative Jeffrey’s prior. We also show that mixed priors increase the statistical power in frequentist analyses over the maximum likelihood test statistic. We develop an analytic formalism that does not require expensive simulations and generalize Wilks’ theorem beyond its usual regime of validity. In specific limits, the formalism reproduces existing expressions, such as the p-value of linear models and periodograms. We apply the formalism to an example of exoplanet transits, where multiplicity can be more than 10 7 . We show that our analytic expressions reproduce the $p$-values derived from numerical simulations. We offer an interpretation of our formalism based on the statistical mechanics. We introduce the counting of states in a continuous parameter space using the uncertainty volume as the quantum of the state. We show that both the $p$-value and Bayes factor can be expressed as an energy versus entropy competition.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

Predicting U.S. federal fleet electric vehicle charging patterns using internal combustion engine vehicle fueling transaction statistics

Utilizing fueling transactions from internal combustion engine vehicles (ICEVs), the authors estimated how frequently midday public charging would be required for U.S. federal fleet battery electric vehicles (BEVs). Fueling transaction summary statistics are more widely available than trip-level telematics data, making this methodology more accessible and transferable to other researchers and fleet managers considering BEV replacements. For example, readers can easily apply a linear model using only the count of back-to-back fueling events at gas stations over 57 straight-line miles apart to predict days exceeding range. This linear regression predicted binned days exceeding 250 miles at 80% accuracy on a hold-out test set from the same fleet as the training data and 66 % accuracy on a new fleet displaying different driving behaviors. The authors additionally provide linear equations for days exceeding 200 and 300 miles as alternative range estimates to account for differences in BEV range and temperature impacts. Beyond the single-feature linear models which readers can apply, the authors tuned and trained other machine learning models on a variety of fueling transaction statistics including consecutive transaction distances, transaction distance from garage, estimated miles traveled from fuel economy and fuel quantity, and transaction periodicity. Utilizing a subset of 1678 light-duty federal fleet vehicles which contained daily vehicle miles traveled (VMT) in addition to fueling statistics, the authors determined which fueling transaction statistics were most relevant in predicting driving days exceeding 250 miles (an approximation of BEV rated driving range). In support of the U.S. federal fleet transition to zero-emission vehicles (ZEVs), the authors used these statistics and machine learning models to predict the frequency of BEV midday charging. After training models on the subset with VMT, the authors predicted days exceeding rated range for 112,902 light-duty vehicles operating in similar circumstances in the federal fleet using a Support Vector Regressor (SVR). In conclusion, they then used the projections as part of the ZEV Planning and Charging (ZPAC) tool to identify optimal candidates for BEVs for the federal fleet. An anonymized version of ZPAC is included in the supplementary materials.

25 ENERGY STORAGE↗
DOE OSTI2021

Extremely Slow Trap-Mediated Hole Relaxation in Room-Temperature InP/ZnSe/ZnS Quantum Dots

Time-resolved photoluminescence (PL) and transient absorption (TA) spectroscopy have been used to elucidate the hole relaxation dynamics in high-quality InP/ZnSe/ZnS quantum dots (QDs) at room temperature. In QDs having an In/P ratio close to 1:1, hole cooling is fast compared to the ~40 ps time-correlated photon-counting instrument response. However, in QDs that luminesce at wavelengths greater than around 600 nm and have excess indium, a significant fraction of the PL exhibits a slower rise time. In this case, the PL rises over a range of timescales varying from close to the instrument response to approximately 300–400 ps. The time constant of the slowest component increases with increasing InP core size and the fraction of the PL that has the slow rise time increases with excess indium in the particle. In all cases, a slow rise time and any spectral evolution on that timescale are absent in the TA results, indicating that the slow dynamics may be assigned to relaxation in the valence band. QDs emitting at wavelengths below 560 nm show very different dynamics, exhibiting a barely detectable <50 ps rise time. Based on these results and measured elemental compositions, the slow hole relaxation is assigned to the transient population of indium-based traps in the ZnSe shell that are above the valence band edge only for the larger, red-emitting QDs. Here, the relative trap to band edge relaxation rates can be understood in terms of effective mass approximation hole wave function calculations, which show that the relaxation rate is largely determined by the extent to which the hole wave function in the lowest exciton penetrates into the ZnSe shell, overlapping the trapped-hole wave functions.

77 NANOSCIENCE AND NANOTECHNOLOGY↗
DOE OSTI2023

Supporting data for "Frozen flume experiments indicate rapid permafrost riverbank erosion depends on bank roughness"

This dataset contains supporting files detailing five frozen flume experiments conducted at the Caltech Earth Surface Dynamics Laboratory to investigate rates of ablation-limited permafrost riverbank erosion under controlled conditions. Water flowed past a bank of saturated, frozen sand and ice and gradually eroded the bank by thawing pore ice and immediately entraining sand and washing it downstream. Experiments were scaled for flow hydraulics and heat transfer allowing comparisons between our results and natural permafrost riverbanks. For each experiment, we measured the initial and final sand bank topography using a Keyence laser scanner, water surface slope at 3-min intervals throughout the experiment using a Massa sonar scanner, bank erosion using 10-sec overhead timelapse imagery taken by an overhead camera, water and bank temperature using thermistors frozen into the sand bank and sampling at 2 Hz, and water discharge using an in-line flow meter. We include calibration data for the carriage (engineered by the Saint Anthony Falls Laboratory) used to make sonar and laser topography measurements. We also include calibration data for temperature sensors, water discharge measurements, and images of a regular grid placed in the flume to align overhead camera images with the carriage datum. Grain size analysis for the channel bed (gravel) was produced using a pebble count and bank sand was measured using a Camsizer X2. In addition to the five frozen experiments, we include sonar scans of water surface slope and Keyence scans of bed and bank topography for calibration experiments ran with an immobile gravel bank and bed.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Industry Partnerships & Their Role In Reducing Natural Gas Supply Chain Greenhouse Gas Emissions – Phase 2

This analysis is the product of collaboration between Our Nation’s Energy Future (ONE Future) and the United States (U.S.) Department of Energy (DOE) National Energy Technology Laboratory (NETL). This analysis is an update to Phase 1 of the collaboration between ONE Future and NETL. Phase 1 had three objectives: 1. Calculate a greenhouse gas (GHG) emission profile representative of ONE Future’s supply chain, including methane (CH 4 ) emission rates. 2. Compare ONE Future’s emission profile to the emission profile for the U.S. natural gas supply chain. 3. Evaluate specific emission reduction opportunities. Phase 2 has two key enhancements over Phase 1: 1. The reporting year of the data is updated from 2016 to 2017. 2. The emission profiles and the specific emission reduction opportunities are regionalized for the ONE Future supply chain. The ONE Future supply chain is based on data provided by ONE Future members for all their U.S. onshore assets. ONE Future’s data are mostly representative of their participation in the Greenhouse Gas Reporting Program (GHGRP) administered by the Environmental Protection Agency (EPA) and is supplemented by ONE Future facilities that are not required to report to GHGRP. The U.S. scenario is based on NETL’s life cycle analysis (LCA) of natural gas extraction and power generation, which also uses data from the GHGRP (but does not include non-GHGRP facilities). In addition to the data from these sources, NETL accounted for uncertainty due to data variability, data limitations, and variability in liquids unloading frequency and event duration. This report is a re-issue of the 2020 study (published on July 28, 2020). It revises the device count in the mitigation strategy “pipeline pump-down before maintenance” in the Marginal Abatement Cost (MAC) Analysis section of the report (Section 7). Please see the addendum for more details on this revision and resultant changes. This revision does not change most of our conclusions and recommendations. It only changes the total methane reduced from all the mitigation opportunities (low cost and high cost) from 6.5 Bcf CH 4 /yr to 4.8 Bcf CH 4 /yr.

03 NATURAL GAS↗
DOE OSTI2021

Leveraging lifetime information to perform real-time 3D single-particle tracking in noisy environments

A microscopy platform that leverages the arrival time of individual photons to enable 3D single-particle tracking of fast-moving (translational diffusion coefficient of ≃ 3.3 µm 2 /s) particles in high-background environments is reported here. It combines a hardware-based time-gating module, which enables the rate of photon processing to be as high as 100 MHz, with a two-photon excited 3D single-particle tracking confocal microscope to enable high sample penetration depth. Proof-of-principle experiments where single quantum dots are tracked in solutions containing dye-stained cellulose are shown, with tracking performance markedly improved using the hardware-based time-gating module. Furthermore, such a microscope design is anticipated to be of use to a variety of communities who wish to track single-particles in cellular environments, which commonly have high fluorescence and scattering background.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

Artificial intelligence models, photos, and data associated with the manuscript “Quantifying Streambed Grain Size, Uncertainty, and Hydrobiogeochemical Parameters Using Machine Learning Model YOLO” (v2)

This data package is associated with the manuscript “Quantifying Streambed Grain Size, Uncertainty, and Hydrobiogeochemical Parameters Using Machine Learning Model YOLO” published in Water Resources Research (Chen et al., 2024). This data package includes the training, validation, testing, and prediction data used by the artificial intelligence (AI) model for automated grain size and hydro-biogeochemistry quantification using streambed photos. The grain size data are extracted for each photo using You Look Only Once (YOLO), a pre-trained object detection model. This data package was originally published in October 2023. It was updated August 2025 (v2; new and modified files). File and folder names were not revised to indicate changes. See the change history section in the readme for more details. Please see flmd.csv for a list of all files contained in this data package and descriptions for each. Please see dd.csv for a data dictionary that defines the column headers of .csv files in the data package. This dataset is comprised of one data folder containing (1) file-level metadata; (2) data dictionary; (3) readme; and (4) six subfolders. Subfolders 1 to 4 include the training, validation, testing, and prediction data. Subfolder 5_Summary includes the summary results of different combinations of training, validation, testing, and prediction data. Subfolder 6_SupplementalData includes additional data downloaded from public sources (Kaufman et al., 2023a; Kaufman et al., 2023b; Garefalakis et al., 2023; Mair et al., 2024; https://github.com/river-corridors-sfa/Geospatial_variables). In total, the data package includes 110 folders and 44,283 files. These files include 9,047 .jpg photos, 1 .png photo, 3 .tif photos; 26,639 photo labels and individual grain sizes and probability from AI (.txt); 8,447 grain size distribution data (.dat); and 126 CSV files for results summary, and 14 required metadata files (.xlsx). The summary CSV files contain 68 columns and approximately 2,200 rows that represent photo names, site locations, recording time, GPS coordinates, grains sizes (D10, D50, D60, and D84), number of grains, and additional hydro-biogeochemical data such as water depth, flow velocity, Manning’s coefficient, friction factor, hydraulic conductivity, permeability, streambed interstitial velocity magnitude, mass transfer rate, and nitrate uptake velocity. The photos were obtained from 75 sites in the Yakima River Basin and the Columbia River shorelines, and other associated data from samples and sensors obtained when the photos were taken are publicly available (Fulton et al. 2022; Grieger et al. 2023). All files are .csv, .txt, .dat, .jpg, or .pdf. We acknowledge the Yakama Nation as owners and caretakers of the lands where we collected some of these data. We thank the Confederated Tribes and Bands of the Yakama Nation Tribal Council and Yakama Nation Fisheries for working with us to facilitate sample collection and optimization of data usage according to their values and worldview.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Guidance for Monitoring Passive Groundwater Remedies Over Extended Time Scales

Passive remediation can be appropriate where natural processes and actions such as institutional controls mitigate exposure to contaminated groundwater, achieving remedial action objectives and protectiveness of human health and the environment. Monitored natural attenuation (MNA) is a prevalent passive remediation strategy supported by a regulatory framework and monitoring design guidance. However, long-term passive remedies are usually selected in combination with at least one active remedy, such as source removal, in situ treatment, or pump-and-treat, functioning as a complementary method for achieving remediation objectives and meeting the applicable statutory and regulatory requirements. However, MNA and existing monitoring guidance primarily target situations where the remedial action objectives are met within a few decades. When time scales for passive remediation extend to many decades (50 years or more), a corresponding change in monitoring strategy is needed to adapt to the extended time scale. This document provides guidance for implementing an extended-scale monitoring (ESM) approach appropriate for long-duration passive remediation. Extended-scale is defined in this document with respect to time (i.e., a long duration of remediation) and a large enough physical scale such that downstream receptors will not be impacted within the remediation timeframe. ESM applies to slow-moving groundwater contaminant plumes and emphasizes monitoring primarily for potential exposure pathways. For this approach, the primary monitoring objective is to demonstrate that the plume diminishes before reaching the receptor zone or point of compliance and/or a receptor does not receive concentrations above the compliance limit. While the overall objectives of protecting human health and the environment are the same as for plumes where remediation can occur over a shorter time period, the time scales between decisions are longer and the dynamics of plume evolution are slower. To this end, a scenario-based strategy is described for different plume and source conditions, defining a containment and receptor zones. The containment zone is the area where the risk of exposure to groundwater contamination can be mitigated (e.g., through institutional controls) during the remediation time period. The receptor zone is defined as the area where exposure to groundwater contamination cannot be mitigated and compliance concentration standards must be met. Within the containment zone, slow plume migration may occur, leading to concentrations that exceed compliance standards. However, where distance to the receptor zone is large relative to plume migration and attenuation rate, this approach can be protective of the receptor zone. Selection of a long-duration passive remedy needs to be based on sufficient understanding of contaminant sources, hydrogeology, and contaminant plumes. A strong technical basis, supported by predictive analysis, is recommended to substantiate that contamination is expected to stay within the containment zone during the active remediation and attainment phase of the remedy, and diminish to meet compliance standards within the extended timeframe prior to reaching the receptor zone (e.g., many decades or even centuries). The ESM approach is based on verification of plume behavior and not on detailed plume dynamics. Monitoring is conducted to confirm expected behavior with an emphasis on exposure pathways to verify that plumes remain contained in areas where the protectiveness objectives can be met. ESM should not be adopted if there is significant risk of the plume extending beyond the containment zone. Given the slow movement within the containment zone, less frequent sampling is required relative to approaches used for conventional-scale remediation.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2025

Videos, photos, and AI-derived grain size data associated with “High-throughput AI Video Surveys Enable Reproducible Multiscale Sediment Size Mapping, with Implications for Hydrobiogeochemical Parameterization”

NOTE: The manuscript associated with this data package is currently in review. The data may be revised based on reviewer feedback. Upon manuscript acceptance, this data package will be updated with the final dataset and additional metadata. This data package is associated with the manuscript “High-throughput AI Video Surveys Enable Reproducible Multiscale Sediment Size Mapping, with Implications for Hydrobiogeochemical Parameterization” under review. This data package includes five data types: 1) raw photos and videos from drone survey and walking smartphone surveys; 2) images derived from raw videos; 3) manual labeling of reference scales; 4) metadata for all images and photo resolution derived from artificial intelligence (AI) models or manual labels, 5) grain size data obtained from AI models for all photos, 6) metadata and grain size data after quality control, 7) summaries of sample efficiency for all data, and 8) computational fluid dynamics (CFD) data used to support hydro-biogeochemical (HBGC) parameter estimation. Such data is used to 1) demonstrate significant improvements in accuracy, efficiency, and quality control for grain size data collection with the help of AI models, 2) study the spatial heterogeneity of grain size and observation reproducibility based on tens of thousands of data points generated by the AI models, and 3) evaluate the impacts of grain size heterogeneity on key HBGC parameters across sediment-to-reach and hourly-to-yearly scales. In particular, the data package contains 116 folders and 179696 files. The files include 41 videos in .mov format, 64047 photos in .jpg format, 13541 video-derived photos in .png format, 12747 segmentation mask data in .tif format, 12747 segmentation data in .json format, 24771 .csv files that with metadata and grain size for each individual photo as well as water depth and velocity data from CFD and observation, 51791 .txt files of raw AI predicted labels, and 11 flight record data in .srt format. The summary for all metadata and grain size statistics information is included in “Scales_V3_NG.csv” and “Statistics_V3_NG.csv”. The summary for data that pass data quality control (QC) level 0-2 is included in “QCStatistics_V3_NG.csv”. The QC level 0 represents photos whose photo resolution is positive, excluding photos that miss reference scale. The QC level 1 means reference scale circularity uncertainty is less than 5% for smartphone images while representing photo resolution is larger than 0.44 mm/pixel for drone images. The QC level 2 means excluding photos whose grain number is less than 100, a minimum number of grains recommended by classic literature. The summary for each video’s name, length, frame rates, survey area, grain number, survey efficiency, etc. can be found in “QCSummary_V3_NG.csv”. The summary for site name, GPS coordinates, and number of images at each site can be found in “SitesSummary_V3_*.csv” files. Overall computational efficiency summary is reported in Table 4 of accompanying manuscript. Additionally, the nitrate concentration data used in this work was downloaded from an existing dataset published on ESS-DIVE (Boat-Dragged Sensor Hanford Reach.csv; Conner A. et al., 2020). We thank the United States Forest Service, Washington Department of Fish and Wildlife, Washington Department of Natural Resources, Cowiche Canyon Conservatory, Port of Benton, and the Confederated Tribes and Bands of the Yakama Nation for access to field locations where the data were collected. We also thank the Yakama Nation Tribal Council and Yakama Nation Fisheries for working with us to facilitate data collection and optimization of data usage according to their values and worldview.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Energy Savings Results from Small Commercial Building Retrofits in the US

Small commercial buildings, or those comprising less than 50,000 square feet of floor area, represent 94% of U.S commercial buildings by count and consume approximately 8% of the nation’s primary energy; as such, they represent a largely unexploited opportunity for energy savings. Small commercial buildings also represent a large economic market—the National Institute of Building Sciences (NIBS) estimated the small commercial retrofit market at USD 35.6 billion. Despite the prominence of small commercial buildings and the economic opportunity for energy retrofits, many energy efficiency programs focus on large commercial buildings, and create efficiency solutions that do not meet the needs of the small commercial market. This paper presents an analysis of 34 small commercial case study projects that implemented energy efficiency retrofits. This paper contributes to the existing building retrofit body of knowledge in the following ways: (1) it identifies the decision criteria used by small commercial building stakeholders that decided to complete an energy retrofit; (2) it identifies the most commonly implemented efficiency measures in small commercial buildings, and discusses why this is the case; and (3) it provides empirical evidence about the efficacy of installing single energy efficiency measures (EEMs) compared to packages of EEMs in small commercial buildings by reporting verified energy savings. To the authors’ knowledge, this paper is the first to catalog decision criteria and energy savings for the existing small commercial buildings market, and this research illustrates that small commercial building decision-makers seem most motivated to retrofit their spaces by energy cost savings and operational concerns. Furthermore, small commercial building decision-makers opted to implement single-system retrofits in fifteen (15) of the thirty-four cases studied. Finally, this research documents the improved savings, in the small commercial buildings market, associated with a more integrated package of EEMs compared to a single-system approach, achieving approximately 10% energy savings for a single-system approach and more than 20% energy savings for integrated approaches. These savings translate to CO2 savings of 1,324,000 kgCO2/year to 2,647,000 kgCO2/year, respectively, assuming small commercial buildings are retrofit at a rate of 0.95% of the stock annually.

24 POWER TRANSMISSION AND DISTRIBUTION↗