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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 199 records · Page 11
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Modeling Assessment of Tidal Energy Extraction in the Western Passage

Numerical models have been widely used for the resource characterization and assessment of tidal instream energy. The accurate assessment of tidal stream energy resources at a feasibility or project-design scale requires detailed hydrodynamic model simulations or high-quality field measurements. This study applied a three-dimensional finite-volume community ocean model (FVCOM) to simulate the tidal hydrodynamics in the Passamaquoddy–Cobscook Bay archipelago, with a focus on the Western Passage, to assist tidal energy resource assessment. IEC Technical specifications were considered in the model configurations and simulations. The model was calibrated and validated with field measurements. Energy fluxes and power densities along selected cross sections were calculated to evaluate the feasibility of the tidal energy development at several hotspots that feature strong currents. When taking both the high current speed and water depth into account, the model results showed that the Western Passage has great potential for the deployment of tidal energy farms. The maximum extractable power in the Western Passage was estimated using the Garrett and Cummins method. Different criteria and methods recommended by the IEC for resource characterization were evaluated and discussed using a sensitivity analysis of energy extraction for a hypothetical tidal turbine farm in the Western Passage.

16 TIDAL AND WAVE POWER↗
DOE OSTI2020

A new method for operating a continuous-flow diffusion chamber to investigate immersion freezing: assessment and performance study

Abstract. Glaciation in mixed-phase clouds predominantly occurs through the immersion-freezing mode where ice-nucleating particles (INPs) immersed within supercooled droplets induce the nucleation of ice. Model representations of this process currently are a large source of uncertainty in simulating cloud radiative properties, so to constrain these estimates, continuous-flow diffusion chamber (CFDC)-style INP devices are commonly used to assess the immersion-freezing efficiencies of INPs. This study explored a new approach to operating such an ice chamber that provides maximum activation of particles without droplet breakthrough and correction factor ambiguity to obtain high-quality INP measurements in a manner that previously had not been demonstrated to be possible. The conditioning section of the chamber was maintained at −20 ∘C and water relative humidity (RHw) conditions of 113 % to maximize the droplet activation, and the droplets were supercooled with an independently temperature-controlled nucleation section at a steady cooling rate (0.5 ∘C min−1) to induce the freezing of droplets and evaporation of unfrozen droplets. The performance of the modified compact ice chamber (MCIC) was evaluated using four INP species: K-feldspar, illite-NX, Argentinian soil dust, and airborne soil dusts from an arable region that had shown ice nucleation over a wide span of supercooled temperatures. Dry-dispersed and size-selected K-feldspar particles were generated in the laboratory. Illite-NX and soil dust particles were sampled during the second phase of the Fifth International Ice Nucleation Workshop (FIN-02) campaign, and airborne soil dust particles were sampled from an ambient aerosol inlet. The measured ice nucleation efficiencies of model aerosols that had a surface active site density (ns) metric were higher but mostly agreed within 1 order of magnitude compared to results reported in the literature.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

A new method for operating a continuous flow diffusion chamber to investigate immersion freezing: assessment and performance study

Glaciation in mixed-phase clouds predominately occurs through the immersion freezing mode where ice nucleating particles (INPs) immersed within supercooled droplets induce nucleation of ice. Currently, model representations of this process are a large source of uncertainty in simulating cloud radiative properties, and to constrain these estimates, continuous flow diffusion chamber (CFDC)-style INP devices are commonly used to assess the immersion freezing efficiencies of INPs. In this study, a new approach was explored to operating such an ice chamber that provides maximum activation of particles without droplet breakthrough and correction factor ambiguity to obtain high-quality INP measurements in a manner that has not been demonstrated as possible previously. The conditioning section of the chamber was maintained at ~ –20 °C and water relative humidity (RH w ) ~ 113 % conditions to maximize the droplet activation, and the droplets were supercooled with an independently temperature-controlled nucleation section at a steady cooling rate (0.5 °C min –1 ) to induce the freezing of droplets and evaporation of unfrozen droplets. The performance of the modified ice chamber was evaluated using four INP species: K-feldspar, illite-NX, Argentinian soil dust, and airborne arable dust that had shown ice nucleation over a wide span of supercooled temperatures. Dry dispersed and size-selected K-feldspar particles were generated in the laboratory. Illite-NX and soil dust particles were sampled during the second phase of the Fifth International Ice Nucleation Workshop (FIN-02) campaign, and airborne arable dust particles were sampled from the aerosol inlet located on the rooftop of the laboratory. The measured ice nucleation efficiencies of model aerosols with a surface active site density (n s ) metric were higher, but mostly agreed within one order of magnitude compared to literature results.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Evaluation of E3SM land model snow simulations over the western United States

Abstract. Seasonal snow has crucial impacts on climate, ecosystems, and humans, but it is vulnerable to global warming. The land component (ELM) of the Energy Exascale Earth System Model (E3SM) mechanistically simulates snow processes from accumulation, canopy interception, compaction, and snow aging to melt. Although high-quality field measurements, remote sensing snow products, and data assimilation products with high spatio-temporal resolution are available, there has been no systematic evaluation of the snow properties and phenology in ELM. This study comprehensively evaluates ELM snow simulations over the western United States at 0.125∘ resolution during 2001–2019 using the Snow Telemetry (SNOTEL) in situ networks, MODIS remote sensing products (i.e., MCD43 surface albedo product), the spatially and temporally complete (STC) snow-covered area and grain size (MODSCAG) and MODIS dust and radiative forcing in snow (MODDRFS) products (STC-MODSCAG/STC-MODDRFS), and the snow property inversion from remote sensing (SPIReS) product and two data assimilation products of snow water equivalent and snow depth – i.e., University of Arizona (UA) and SNOw Data Assimilation System (SNODAS). Overall the ELM simulations are consistent with the benchmarking datasets and reproduce the spatio-temporal patterns, interannual variability, and elevation gradients for different snow properties including snow cover fraction (fsno), surface albedo (αsur) over snow cover regions, snow water equivalent (SWE), and snow depth (Dsno). However, there are large biases of fsno with dense forest cover and αsur in the Rocky Mountains and Sierra Nevada in winter, compared to the MODIS products. There are large discrepancies of snow albedo, snow grain size, and light-absorbing particle-induced snow albedo reduction between ELM and the MODIS products, attributed to uncertainties in the aerosol forcing data, snow aging processes in ELM, and remote sensing retrievals. Against UA and SNODAS, ELM has a mean bias of −20.7 mm (−35.9 %) and −20.4 mm (−35.5 %), respectively, for spring, and −13.8 mm (−27.8 %) and −10.2 mm (−22.2 %), respectively, for winter. ELM shows a relatively high correlation with SNOTEL SWE, with mean correlation coefficients of 0.69 but negative mean biases of −122.7 mm. Compared to the snow phenology of STC-MODSCAG and SPIReS, ELM shows delayed snow accumulation onset dates by 17.3 and 12.4 d, earlier snow end dates by 35.5 and 26.8 d, and shorter snow durations by 52.9 and 39.5 d, respectively. This study underscores the need for diagnosing model biases and improving ELM representations of snow properties and snow phenology in mountainous areas for more credible simulation and future projection of mountain snowpack.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Origin and characterization of single-electron events in Skipper-CCDs for light dark matter searches

This manuscript summarizes the work carried out within the SENSEI (Sub-Electron-Noise Skipper-CCD Experimental Instrument) collaboration, an effort focused on the search for light dark matter using Skipper-CCDs. Firstly, it presents the data acquisition and processing protocol developed to establish a selection criteria for events compatible with the dark matter signal. This protocol also enabled the structure and tools used for the study and characterization of phenomena that impact the quality of measurements made in the search for dark matter (measurement of the Fano factor, determination of the Compton background, and characterization of the high-energy surface background), which were carried out during this work. Secondly, it discusses the comprehensive study conducted on the origin of single-electron events in Skipper-CCDs, which allowed for the selection of detector operating parameters and improved the detection sensitivity in the search for dark matter. It is highlighted the characterization of the spatial correlation between single-electron events and high-energy events, among other developed event selection criteria, and the optimization of the output device to reduce sources of luminescence during its operation. As a result of this study, the lowest levels of dark current and spurious charge ever measured in a CCD are reported. Finally, the latest published results from SENSEI are presented. The obtained limits for the scattering of a light mediator are the best reported to date across the entire investigated mass range, while for the heavy mediator, they are the best for masses below 10 MeV. In terms of dark matter absorption, the most restringent limits below 10 eV are reported. These results, achieved with only a very small fraction of the total projected exposure for SENSEI, position Skipper-CCDs as leaders in the search for light dark matter worldwide.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2024

Advanced Manufactured Home Case Study: A Collaboration for High-Efficiency, Affordable Housing

The introduction of Zero Energy Ready Home Manufactured Homes (ZERH MH) qualification for manufactured homes has generated significant attention and interest in the industry to employ advanced manufacturing techniques. VEIC engaged with Titan Homes to create an advanced manufactured home design that employs ZERH standards, other client-driven above-code standards, and manufacturing processes improvements. This case study identifies specific energy-efficient and quality improvement measures that were implemented to achieve certification and take advantage of incentives for home manufacturers.

14 SOLAR ENERGY↗
DOE OSTI2024

National Park Air Quality Index Dataset

The National Park Air Quality Index dataset (NPS-AQI) consists of webcam images taken from the National Park Service's publicly available air quality web cameras and associated measurements for air pollutants, AQI, and meteorological data obtained via the publicly available NPS Gaseous Pollutant Monitoring Program. The full dataset is a collection of 146,822 images paired with air quality measurements. The specific measurements reported are: ozone ppm, 8-hour running average ozone ppm, so2 ppm, AQI (derived from ozone), temperature, and humidity. The images are 1500X1000 pixel PNG files arranged into folders by NPS site and named according to the time and date the image was taken. There are three CSV files (representing "training", "validation", and "testing" images splits) containing image names and associated NPS site names, air pollutant measurements, and meteorlogical data.

Svinth, Christian N↗
DOE OSTI2021

Estimating the Adequacy of a Multi-Objective Optimization

Multi-objective optimization methods can be criticized for lacking a statistically valid measure of the quality and representativeness of a solution. This stance is especially relevant to metaheuristic optimization approaches but can also apply to other methods that typically might only report a small representative subset of a Pareto frontier. Here we present a method to address this deficiency based on random sampling of a solution space to determine, with a specified level of confidence, the fraction of the solution space that is surpassed by an optimization. The Superiority of Multi-Objective Optimization to Random Sampling, or SMORS method, can evaluate quality and representativeness using dominance or other measures, e.g., a spacing measure for high-dimensional spaces. SMORS has been tested in a combinatorial optimization context using a genetic algorithm but could be useful for other optimization methods.

42 ENGINEERING↗
DOE OSTI2022

Understanding Air Quality Changes after Implementation of Mitigation Measures during a Pandemic: A Scoping Review of Literature in the United States

Traffic-related emissions continue to be a significant source of air pollution in the United States (US) and around the globe. Evidence has shown that previous policies implemented to restrict-traffic flows have affected air pollution levels. Thus, mitigation strategies associated with the COVID-19 pandemic that modified population-level mobility patterns provide a unique opportunity to study air pollution change across the US. For instance, to slow the spread of the pandemic, state and local governments started implementing various mitigation actions, including stay-at-home directives, social distancing measures, school closures, and travel restrictions. This scoping review aimed to summarize the existing evidence about how air quality changed through mitigation practices throughout the pandemic in the US. We found 66 articles that fit our inclusion criteria. Generally, the consolidated results revealed that nitrogen dioxide (NO 2 ) and carbon monoxide (CO) decreased across the country. Studies observed mixed directions and magnitudes of change for fine and coarse particulate matter (PM 2.5 , PM 10 ), ozone (O 3 ), and sulfur dioxide (SO2). Few articles tried to explain this notable heterogeneity in air quality changes by associating contextual factors, such as mobility, traffic flow, and demographic factors. However, all studies agreed that the change in air pollution was nonuniform across the US and even varied within a city.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Insight to the Duration of 120 °C Baking on the Performance of SRF Niobium Cavities

Low-temperature baking at 100 °C - 140 °C in ultra-high vacuum for several hours is the final cavity processing technique to achieve the highest accelerating gradient cavity by eliminating the high field Q-slope, typically on cavities made of high purity fine grain niobium and subjected to electropolishing. The temperature and duration of baking control the onset of the high field Q-slope and overall quality factor over the baseline measurements. The increase in quality factor is generally related to the reduction in the temperature-dependent surface resistance, which refers to BCS surface resistance due to the reduction in the electronic mean free path and elimination of high field Q-slope is still being actively investigated. Here, we present the results of a series of measurements on 1.3 GHz TESLA shape single-cell cavities with successive low-temperature baking at 120 °C up to 96 hours. The rf loss related to the trapping of residual magnetic field refer to flux trapping sensitivity was measured with respect to the duration of 120 °C bake.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2024

AmpSuite

Seismic amplitudes offer vital information about explosion source characteristics, including discrimination and yield estimation. To take advantage of this, we developed an interactive Python package to measure, control data quality, generate broad area propagation models and perform discrimination and estimate yield. Propagation models are essential in support of transportable yield and broad area discrimination. The key benefit of this package will be its ability to continuously integrate data and new techniques. The AmpSuite framework will provide standardized, repeatable, and accurate model generation and characterization routines. The capability is crucial for monitoring agencies tasked with rapid and high-quality seismic event characterization. The AmpSuite software includes a series of independent modules to perform: • Direct Phase Amplitude Measurement and Storage • Coda Envelope Measurement and Storage • Data Quality Control • New Propagation Model Developments • Seismic Discrimination and Analysis • Yield Estimation and supporting utility software. The AmpSuite software provides comprehensive solutions for monitoring agencies seeking to optimize model generation and event analysis within a contemporary Python framework. Stakeholders (AFTAC) have begun to move towards the Python language for scientific analysis as a new workforce emerges.

Alfaro, Richard↗
DOE OSTI2022

Cooperative Research and Development Agreement between National Energy Technology Laboratory and Gas Technology Institute (Abstract)

Hydrogen has the potential to play an important role in decarbonizing energy-intensive sectors, and credible and open-source protocols are needed to vet the environmental credibility of a specific production pathway, given the variability even among the same technologies. Stakeholders and markets lack consistent, transparent, technical tools and protocols to assess the carbon intensity of hydrogen production at the asset level. Gas Technology Institute (GTI) and S&P Global Platts have launched the Open Hydrogen Initiative (OHI), a new collaboration focused on brining industry within the hydrogen marketplace together to provide further transparency into the environmental greenhouse gas (GHG) impact of hydrogen production. As part of this initiative, GTI has invited NETL to participate in the effort because of NETL’s deep expertise and capabilities in Life Cycle Analysis. Therefore, NETL is joining forces with the Gas Technology Institute (GTI) to build a measurement tool, accompanying protocols, and confidence score of the quality of the measurement. This CRADA effort provides the technical research collaboration support with GTI that will be used in the broader Open Hydrogen Initiative that can provide stakeholders the technical tools and protocols to decarbonize energyintensive sectors.

08 HYDROGEN↗
DOE OSTI2022

TRACER NASA Goddard Space Flight Center TOLNet Field Campaign Report

In September 2021, the National Aeronautics and Space Administration (NASA) deployed assets to the Houston, Texas region to measure air-quality-relevant constituents at high spatial and temporal resolutions. This effort was conducted in partnership with the Texas Commission on Environmental Quality, the U.S. Department of Energy (DOE) Atmospheric Radiation Measurement (ARM) user facility-led Tracking Aerosol Convection interactions ExpeRiment (TRACER) field campaign, and several academic collaborators.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Method for automatic correction of offset drift in online sensors

Abstract Successful operation and optimization of water treatment systems hinge on the availability of high-quality online sensor measurements. Ideally, the available measurements should be simultaneously accurate (i.e., unbiased and precise), representative, voluminous, and timely. This remains a pain-point in current water infrastructures, forming a barrier to a wider adoption of advanced and autonomous control systems. While short-lived symptoms, such as outliers and spikes, can be detected or corrected with state-of-the-art tools for fault detection and identification, it is much more difficult to detect, diagnose, and correct the symptoms of slow faults, such as changes in offset or sensitivity due to drift. The time scale of drift is often longer than the time scales of the system dynamics of interest. Moreover, sensor drift has been shown to occur at the same time and with similar rates when sensors are exposed to the same conditions. This challenges data quality management strategies based on redundancy. In this contribution, we develop a new method, including both a hands-off sensor calibration mechanism and an information-seeking control architecture that can handle the unique challenge of simultaneous and similar drift in online sensors.

Chowdhury, Dhrubajit↗
DOE OSTI2024

Ventilation and Indoor Air Quality in Recently Constructed U.S. Homes: Measured Data From Select Southeastern States

Little data is available that quantifies IAQ or associates contaminant levels with air exchange in U.S. homes. To address this gap, the U.S. Department of Energy (DOE) Building America Program conducted a study to characterize IAQ in U.S. homes constructed since 2013, along with presence, functionality, and occupant use of control measures. Specific objectives of this study effort included: Measuring time-integrated concentrations and temporal profiles of established contaminants of concern; monitoring the use of ventilation equipment; and tracking activities that impact air pollutant emissions and removal processes in typical homes in various climate zones; Characterizing the prevalence, type, and installed performance of mechanical ventilation equipment in new homes; exploring regional variations in system designs and performance; Investigating associations between contaminant levels and the presence of control measures including whole-house mechanical ventilation (WHMV). The study engaged research teams to collect data at a regional level. This report introduces the study protocol and presents and discusses high-level results obtained from Florida Solar Energy Center (FSEC) data collection efforts in the southeastern U.S. states of Florida, Georgia, and South Carolina.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2019

Report on Task USA A 0931 (A.252) Implementation of Fast, Front-End Electronics for Improved Low-Dead Time Neutron Counting

The International Atomic Energy Agency's (IAEA) Department of Safeguards is working on the elaboration and implementation of advanced Non-Destructive Assay (NDA) methods, generally known as neutron noise analysis, for the verification of critical and sub-critical cores containing substantial quantities of direct use nuclear material. These verification methods rely on interpreting time properties of the neutron multiplication process, which are to be extracted from measured neutron pulse trains. The interpretations are highly dependent on the quality of the measured data, which is directly related to the capability of an employed neutron detector to resolve very close detection events originating from neutron bursts produced in a highly multiplying medium. Therefore, the application of detectors with minimum dead-time, pile-up, and other distortion effects is required. This report describes the work under Task USA A 0931 (A.252 Implementation of fast, front-end electronics for improved low-dead time neutron counting).

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2024

PeakQC: A Software Tool for Omics-Agnostic Automated Quality Control of Mass Spectrometry Data

Mass spectrometry is broadly employed to study complex molecular mechanisms in various biological and environmental fields, enabling 'omics' research such as proteomics, metabolomics, and lipidomics. As study cohorts grow larger and more complex with dozens to hundreds of samples, the need for robust quality control (QC) measures through automated software tools becomes paramount to ensure the integrity, high quality, and validity of scientific conclusions from downstream analyses and minimize the waste of resources. Since existing QC tools are mostly dedicated to proteomics, automated solutions supporting metabolomics are needed. To address this need, we developed the software PeakQC, a tool for automated QC of MS data that is independent of omics molecular types (i.e., omics-agnostic). It allows automated extraction and inspection of peak metrics of precursor ions (e.g., errors in mass, retention time, arrival time) and supports various instrumentations and acquisition types, from infusion experiments or using liquid chromatography and/or ion mobility spectrometry front-end separations and with/without fragmentation spectra from data-dependent or independent acquisition analyses. Diagnostic plots for fragmentation spectra are also generated. Here, in this paper, we describe and illustrate PeakQC’s functionalities using different representative data sets, demonstrating its utility as a valuable tool for enhancing the quality and reliability of omics mass spectrometry analyses.

47 OTHER INSTRUMENTATION↗
DOE OSTI2021

Reproducibility of protein x-ray diffuse scattering and potential utility for modeling atomic displacement parameters

Protein structure and dynamics can be probed using x-ray crystallography. Whereas the Bragg peaks are only sensitive to the average unit-cell electron density, the signal between the Bragg peaks—diffuse scattering—is sensitive to spatial correlations in electron-density variations. Although diffuse scattering contains valuable information about protein dynamics, the diffuse signal is more difficult to isolate from the background compared to the Bragg signal, and the reproducibility of diffuse signal is not yet well understood. We present a systematic study of the reproducibility of diffuse scattering from isocyanide hydratase in three different protein forms. Both replicate diffuse datasets and datasets obtained from different mutants were similar in pairwise comparisons (Pearson correlation coefficient ≥0.8). The data were processed in a manner inspired by previously published methods using custom software with modular design, enabling us to perform an analysis of various data processing choices to determine how to obtain the highest quality data as assessed using unbiased measures of symmetry and reproducibility. The diffuse data were then used to characterize atomic mobility using a liquid-like motions (LLM) model. This characterization was able to discriminate between distinct anisotropic atomic displacement parameter (ADP) models arising from different anisotropic scaling choices that agreed comparably with the Bragg data. Our results emphasize the importance of data reproducibility as a model-free measure of diffuse data quality, illustrate the ability of LLM analysis of diffuse scattering to select among alternative ADP models, and offer insights into the design of successful diffuse scattering experiments.

59 BASIC BIOLOGICAL SCIENCES↗