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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

Asthma and Particulate Matter Pollution: Insights from Health Survey and Air Quality Monitoring in the Buzzard Point, Washington, DC Neighborhood

Air pollution, climate change, and other environmental factors contribute to increasing asthma in manycities, including Washington, DC. This work provides a case study of how community input, neighborhood-level health surveys, and air quality monitoring can inform the understanding of asthma and air pollution.A partnership between residents, concerned citizens, scientists, and educators has been working for envi-ronmental health in a DC neighborhood located on a major roadway, next to concrete batch plants andclose to several construction projects. A 2016 Community Health and Safety Study by the DC Departmentof Health, Office of Health Equity, recognized this particular neighborhood as more vulnerable to healthimpacts from recent construction in the area, compared with the surrounding areas, due to lower averageincome and higher percentage of seniors and children. This work presents neighborhood health surveysand air quality monitoring data at a more granular, local level than available from DC governmentagencies. The health surveys documented residents’ experiences around air pollution, asthma,and other health concerns. A key finding was evidence that asthma might be undercounted in thisneighborhood; among residents who did not indicate a diagnosis of asthma, many discussed havingsymptoms that could reflect asthma. Air quality monitoring (particulate matter [PM]) did not indicate thatfederal air quality standards have been violated. Real-time PM data, however,illustrated how current PMstandards, such as 1- and 24-hour averages, may fail to capture shorter duration high PM events that areconsistent with resident concerns.

Shizuka Hsieh↗

Sandia National Laboratories Ecosystem for Open Science: Metadata Schema v0.2 Description.

The Ecosystem for Open Science (eOS) initiative was established in 2019. Its objective is improving openness and sharing of data and information across Defense Nuclear Nonproliferation (DNN) Research and Development (R&D) activities. To support this initiative, the eOS team at Sandia National Laboratories (SNL) developed metadata and data standards and proposed a machine-readable metadata schema. The nuclear explosion monitoring field was selected as a focus area due to its the wide range of pertinent phenomenologies.We developed the DCAT-eOS-AP metadata schema extending the Data Catalog Vocabulary version 2 (DCATv2) standard using an application profile (AP), to fit the needs of multi-disciplinary NA-22 projects. The DCAT-eOS-AP metadata schema describes data at different levels of granularity ranging from general descriptions to more domain-specific granular metadata. Its implementation and serialization is flexible with the ability to include new file or data types. Thus, it will scale with the ever-increasing data management needs of government research. Due to the multitude of phenomenologies represented in the DCAT-eOS-AP schema, we anticipate that it will be easily extensible to various projects across many DOE mission areas. This document describes data management challenges faced within the DNN R&D portfolio and provides insight on how metadata and data standards/guidelines combined with a comprehensive metadata schema can add value to programs throughout the Department of Energy (DOE). It reviews the importance of metadata standards, FAIR (Findability, Accessibility, Interoperability, and Reusability) data principles, and metadata schemas. Additionally, it summarizes input from subject matter experts (SME) at SNL and other National Laboratories that resulted in metadata and data standards/guidelines encompassing domains relevant to NA-22 projects. Finally, we discuss the DCAT-eOS-AP metadata development. Implementation recommendations and future development directions are included for those keen on adopting the DCAT-eOS-AP metadata schema.

96 KNOWLEDGE MANAGEMENT AND PRESERVATION↗

Universal L - 3 finite-size effects in the viscoelasticity of amorphous systems

We present a theory of viscoelasticity of amorphous media, which takes into account the effects of confinement along one of three spatial dimensions. The framework is based on the nonaffine extension of lattice dynamics to amorphous systems, or nonaffine response theory. The size effects due to the confinement are taken into account via the nonaffine part of the shear storage modulus G'. The nonaffine contribution is written as a sum over modes in k-space. With a rigorous argument based on the analysis of the k-space integral over modes, it is shown that the confinement size L in one spatial dimension, e.g., the z axis, leads to a infrared cutoff for the modes contributing to the nonaffine (softening) correction to the modulus that scales as L -3 . Corrections for finite sample size D in the two perpendicular dimensions scale as ~(L/D) 4 , and are negligible for L«D. For liquids it is predicted that G'~L -3 is in agreement with a previous more approximate analysis, whereas for amorphous materials G'~G' bulk +βL -3 . For the case of liquids, four different experimental systems are shown to be very well described by the L-3 law. The theory can also explain previous simulation data of confined jammed granular packings.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Pathogenesis of virulent and attenuated foot-and-mouth disease virus in cattle

Background: Understanding the mechanisms of attenuation and virulence of foot-and-mouth disease virus (FMDV) in the natural host species is critical for development of next-generation countermeasures such as live-attenuated vaccines. Functional genomics analyses of FMDV have identified few virulence factors of which the leader proteinase (Lpro) is the most thoroughly investigated. Previous work from our laboratory has characterized host factors in cattle inoculated with virulent FMDV and attenuated mutant strains with transposon insertions within Lpro. Methods: In the current study, the characteristics defining virulence of FMDV in cattle were further investigated by comparing the pathogenesis of a mutant, attenuated strain (FMDV-Mut) to the parental, virulent virus from which the mutant was derived (FMDV-WT). The only difference between the two viruses was an insertion mutation in the inter-AUG region of the leader proteinase of FMDV-Mut. All cattle were infected by simulated-natural, aerosol inoculation. Results: Both viruses were demonstrated to establish primary infection in the nasopharyngeal mucosa with subsequent dissemination to the lungs. Immunomicroscopic localization of FMDV antigens indicated that both viruses infected superficial epithelial cells of the nasopharynx and lungs. The critical differences between the two viruses were a more rapid establishment of infection by FMDV-WT and quantitatively greater virus loads in secretions and infected tissues compared to FMDV-Mut. The slower replicating FMDV-Mut established a subclinical infection that was limited to respiratory epithelial sites, whereas the faster replication of FMDV-WT facilitated establishment of viremia, systemic dissemination of infection, and clinical disease. Conclusion: The mutant FMDV was capable of achieving all the same early pathogenesis landmarks as FMDV-WT, but was unable to establish systemic infection. The precise mechanism of attenuation remains undetermined; but current data suggests that the impaired replication of the mutant is more responsible for attenuation than differences in host immunological factors. These results complement previous studies by providing data of high-granularity describing tissue-specific tropism of FMDV and by demonstrating microscopic localization of virulent and attenuated clones of the same field-strain FMDV.

59 BASIC BIOLOGICAL SCIENCES↗

NSAID use and clinical outcomes in COVID-19 patients: a 38-center retrospective cohort study

Abstract Background Non-steroidal anti-inflammatory drugs (NSAIDs) are commonly used to reduce pain, fever, and inflammation but have been associated with complications in community-acquired pneumonia. Observations shortly after the start of the COVID-19 pandemic in 2020 suggested that ibuprofen was associated with an increased risk of adverse events in COVID-19 patients, but subsequent observational studies failed to demonstrate increased risk and in one case showed reduced risk associated with NSAID use. Methods A 38-center retrospective cohort study was performed that leveraged the harmonized, high-granularity electronic health record data of the National COVID Cohort Collaborative. A propensity-matched cohort of 19,746 COVID-19 inpatients was constructed by matching cases (treated with NSAIDs at the time of admission) and 19,746 controls (not treated) from 857,061 patients with COVID-19 available for analysis. The primary outcome of interest was COVID-19 severity in hospitalized patients, which was classified as: moderate, severe, or mortality/hospice. Secondary outcomes were acute kidney injury (AKI), extracorporeal membrane oxygenation (ECMO), invasive ventilation, and all-cause mortality at any time following COVID-19 diagnosis. Results Logistic regression showed that NSAID use was not associated with increased COVID-19 severity (OR: 0.57 95% CI: 0.53–0.61). Analysis of secondary outcomes using logistic regression showed that NSAID use was not associated with increased risk of all-cause mortality (OR 0.51 95% CI: 0.47–0.56), invasive ventilation (OR: 0.59 95% CI: 0.55–0.64), AKI (OR: 0.67 95% CI: 0.63–0.72), or ECMO (OR: 0.51 95% CI: 0.36–0.7). In contrast, the odds ratios indicate reduced risk of these outcomes, but our quantitative bias analysis showed E-values of between 1.9 and 3.3 for these associations, indicating that comparatively weak or moderate confounder associations could explain away the observed associations. Conclusions Study interpretation is limited by the observational design. Recording of NSAID use may have been incomplete. Our study demonstrates that NSAID use is not associated with increased COVID-19 severity, all-cause mortality, invasive ventilation, AKI, or ECMO in COVID-19 inpatients. A conservative interpretation in light of the quantitative bias analysis is that there is no evidence that NSAID use is associated with risk of increased severity or the other measured outcomes. Our results confirm and extend analogous findings in previous observational studies using a large cohort of patients drawn from 38 centers in a nationally representative multicenter database.

60 APPLIED LIFE SCIENCES↗

ESS-DIVE Reporting Format for File-level Metadata

The ESS-DIVE reporting format for file-level metadata (FLMD) provides granular information at the data file level to describe the contents, scope, and structure of the data file to enable comparison of data files within a data package. The FLMD are fully consistent with and augment the metadata collected at the data package level. We developed the FLMD template based on a review of a small number of existing FLMD in use at other agencies and repositories with valuable input from the Environmental Systems Science (ESS) Community. Also included is a template for a CSV Data Dictionary where users can provide file-level information about the contents of a CSV data file (e.g., define column names, provide units). Files are in .csv, .xlsx, and .md. Templates are in both .csv and .xlsx (open with e.g. Microsoft Excel, LibreOffice, or Google Sheets). Open the .md files by downloading and using a text editor (e.g. Notepad or TextEdit). Though we provide Excel templates for the file-level metadata reporting format, our instructions encourage users to 'Save the FLMD template as a CSV following the CSV Reporting Format guidance'. In addition, we developed the ESS-DIVE File Level Metadata Extractor which is a lightweight python script that can extract some FLMD fields following the recommended FLMD format and structure.

54 ENVIRONMENTAL SCIENCES↗

GLUE Code: A framework handling communication and interfaces between scales

Many scientific applications are inherently multiscale in nature. Such complex physical phenomena often require simultaneous execution and coordination of simulations spanning multiple time and length scales. This is possible by combining expensive small-scale simulations (such as molecular dynamics simulations) with larger scale simulations (such continuum limit/hydro solvers) to allow for considerably larger systems using task and data parallelism. However, the granularity of the tasks can be very large and often leads to load imbalance. Traditionally, we use approximations to streamline the computation of the more costly interactions and this introduces trade-offs between simulation cost and accuracy. In recent years, the available computational power and the advances in machine learning have made computing these scale-bridging interactions and multiscale simulations more feasible. One driving application has been plasma modeling in inertial confinement fusion (ICF), which is fundamentally multiscale in nature. This requires deep understanding of how to extrapolate microscopic information into macroscopically relevant scales. For example, in ICF one needs an accurate understanding of the connection between experimental observables and the underlying microphysics. The properties of the larger scales are often affected by the microscale behavior incorporated usually into the equations of state and ionic and electronic transport coefficients (Liboff, 1959; Rinderknecht et al., 2014; Rosenberg et al., 2015; Ross et al., 2017). Instead of incorporating this information using reliable molecular dynamics (MD) simulations, one often needs to use theoretical models, due to the inability of MD to reach engineering scales (Glosli et al., 2007; Marinak et al., 1998). One approach to resolve this issue is by coupling two MD simulations of different scales via force interpolation, e.g., the AdResS method (Krekeler et al., 2018; Nagarajan et al., 2013). Another approach, which we will pursue in the scope of this work, is by enabling scale bridging between MD simulations and meso/macro-scale models through the development and support of application programming interfaces that these different applications can interact through.

54 ENVIRONMENTAL SCIENCES↗

IMoFi - Intelligent Model Fidelity: Physics-Based Data-Driven Grid Modeling to Accelerate Accurate PV Integration (Final Report)

This report summarizes the work performed under a project funded by U.S. DOE Solar Energy Technologies Office (SETO) to use grid edge measurements to calibrate distribution system models for improved planning and grid integration of solar PV. Several physics-based data-driven algorithms are developed to identify inaccuracies in models and to bring increased visibility into distribution system planning. This includes phase identification, secondary system topology and parameter estimation, meter-to-transformer pairing, medium-voltage reconfiguration detection, determination of regulator and capacitor settings, PV system detection, PV parameter and setting estimation, PV dynamic models, and improved load modeling. Each of the algorithms is tested using simulation data and demonstrated on real feeders with our utility partners. The final algorithms demonstrate the potential for future planning and operations of the electric power grid to be more automated and data-driven, with more granularity, higher accuracy, and more comprehensive visibility into the system.

14 SOLAR ENERGY↗

Electric Vehicle and Infrastructure Systems Modeling in Washington D.C. and Baltimore

This report documents the Argonne-Exelon effort to develop and utilize an agent-based model (ATEAM) of charging demand and infrastructure expansion applicable to the Washington, DC–Baltimore, MD consolidated metropolitan area. This study extends the ATEAM model time horizon to 10 years (from 2020 to 2030), expands agent behavior modeling capabilities, incorporates more granular and extensive empirical data on charging behavior, and analyzes charging needs for a much larger population of PEVs, in keeping with regional goals for significant adoption of ZEVs. With given targets for annual BEV adoption, five scenarios were developed to examine public infrastructure needs and resulting charging load, considering different home charging availabilities, as well as different PEV consumer profiles and public charging infrastructure deployment strategies. Scenario results show that if new chargers (both L2 and DCFC) are spread more widely (as with ubiquitous deployment strategies), there will be less variation in the number of chargers added to each census tract in the study area. More importantly, widespread public charging infrastructure with ubiquitous deployment strategies reduces unmet charging demand and improves charging success, even with heavy reliance on public charging. About 80 percent of BEV drivers can charge on their first attempt in scenarios with ubiquitous deployment strategies. Moreover, widespread public charging infrastructure better meets the demand for more charging, and in return, increases BEV adoption. Low home charging availability produces higher charging loads in public locations, especially during the early morning (around 8:00 a.m.) and late afternoon (around 6:00 p.m.). The evening peak load indicates that drivers are taking advantage of public charging before heading home. Study results also indicate that even with 20 percent home charging availability in 2030, just 20 percent of drivers attempt to charge on a given day. With their relatively high electric range (200+ miles), the BEVs expected to be on the road in 2030 can handle daily commutes without re-charging for a couple of days.

24 POWER TRANSMISSION AND DISTRIBUTION↗

IMoFi (Intelligent Model Fidelity): Physics-Based Data-Driven Grid Modeling to Accelerate Accurate PV Integration Updated Accomplishments

This report summarizes the work performed under a project funded by U.S. DOE Solar Energy Technologies Office (SETO), including some updates from the previous report SAND2022-0215, to use grid edge measurements to calibrate distribution system models for improved planning and grid integration of solar PV. Several physics-based data-driven algorithms are developed to identify inaccuracies in models and to bring increased visibility into distribution system planning. This includes phase identification, secondary system topology and parameter estimation, meter-to-transformer pairing, medium-voltage reconfiguration detection, determination of regulator and capacitor settings, PV system detection, PV parameter and setting estimation, PV dynamic models, and improved load modeling. Each of the algorithms is tested using simulation data and demonstrated on real feeders with our utility partners. The final algorithms demonstrate the potential for future planning and operations of the electric power grid to be more automated and data-driven, with more granularity, higher accuracy, and more comprehensive visibility into the system.

14 SOLAR ENERGY↗

Bouguer images of the North American craton and its structural evolution

Digital image processing techniques have been used to generate Bouguer images of the North American craton that diplay more of the granularity inherent in the data as compared with existing contour maps. A dominant NW-SE linear trend of highs and lows can be seen extending from South Dakota, through Nebraska, and into Missouri. The structural trend cuts across the major Precambrian boundary in Missouri, separating younger granites and rhyolites from older sheared granites and gneisses. This trend is probably related to features created during an early and perhaps initial episode of crustal assembly by collisional processes. The younger granitic materials are probably a thin cover over an older crust.

Arvidson, R. E.↗

Elastic properties of granular materials under uniaxial compaction cycles

Data on andesitic and basaltic sands are presented showing compressional sound velocity, density, and creep as functions of uniaxial loading through several compaction cycles. Maximum pressures over which acoustic measurements were made were in the range from 600 to 700 bars. The dynamic elastic modulus varies with pressure in a manner analogous to that of a static elastic modulus defined by small pressure perturbations on a typical compaction cycle. After several compaction cycles, two compressional elastic moduli apparently exist at low pressure (thus two modes of compressional wave propagation through the samples are indicated). The elastic moduli observations are briefly discussed in terms of a general expression for compressibility.

Warren, N.↗

Simulation of CMS Phase 2 Pixel Tracker for HL-LHC [Slides]

The High-Luminosity Large Hadron Collider (HL-LHC) aims to increase luminosity by a factor of 10 beyond the LHC's design value. To cope with the increased rate of particle production without compromising physics performance, the LHC detectors will undergo an extensive upgrade. CMS will replace the current inner tracker system with a new silicon tracker which will feature increased forward acceptance, improved radiation hardness, higher granularity, and compatibility with higher data rates. We present a simulation study of the CMS Phase 2 pixel tracker that investigates the expected occupancy and tracking performance for various geometric and sensor granularity options.

43 PARTICLE ACCELERATORS↗

Research challenges and directions in HVAC fault prevalence

This study provides a review of the current state of knowledge, gaps, and potential value in research on the prevalence of faults in commercial buildings. Two separate efforts were made in this study: (1) we performed a literature review to determine the extent of currently available fault prevalence data for heating, ventilation, and air-conditioning (HVAC) systems, and (2) we conducted dozens of interviews with subject matter experts and stakeholders to determine the HVAC fault data that would be of greatest value. Through the literature review and interviews, we discovered unmet needs for empirical data on the prevalence of faults at the desired level of granularity, consistency, and scale; this lack of data leads us to recommend future work studying commercial buildings’ HVAC fault prevalence, with robust fault taxonomy and a variety of meaningful fault prevalence metrics.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Isotope anomalies in the FE-group elements in meteorites and connections to nucleosynthesis in AGB stars

We study the effects of neutron captures in AGB stars on “Fe-group” elements, with an emphasis on Cr, Fe, and Ni. These elements show anomalies in {sup 54}Cr, {sup 58}Fe, and {sup 64}Ni in solar system materials, which are commonly attributed to supernovae (SNe). However, as large fractions of the interstellar medium (ISM) were reprocessed in AGB stars, these elements were reprocessed, too. We calculate the effects of such reprocessing on Cr, Fe, and Ni through 1.5 M{sub ⊙} and 3 M{sub ⊙} AGB models, adopting solar and 1/3 solar metallicities. All cases produce excesses of {sup 54}Cr, {sup 58}Fe, and {sup 64}Ni, while the other isotopes are little altered; hence, the observations may be explained by AGB processing. The results are robust and not dependent on the detailed initial isotopic composition. Consequences for other “Fe group” elements are then explored. They include {sup 50}Ti excesses and some production of {sup 46,47,49}Ti. In many circumstellar condensates, Ti quantitatively reflects these effects of AGB neutron captures. Scatter in the data results from small variations (granularity) in the isotopic composition of the local ISM. For Si, the main effects are instead due to variations in the local ISM from different SN sources. The problem of Ca is discussed, particularly with regard to {sup 48}Ca. The measured data are usually represented assuming terrestrial values for {sup 42}Ca/{sup 44}Ca. Materials processed in AGB stars or sources with variable initial {sup 42}Ca/{sup 44}Ca ratios can give apparent {sup 48}Ca excesses/deficiencies, attributed to SNe. The broader issue of galactic chemical evolution is also discussed in view of the isotopic granularity in the ISM.

79 ASTRONOMY AND ASTROPHYSICS↗

A model for live mission data systems using the OAIS reference model

Space sciences are confronted with overwhelming volume of data. The data rates are increasing, the granularity of registered observations is continuously refining, and computer technology allows producing terabytes of images and catalogs. The inexpensive emerging storage technologies, combined with the availability of high-speed communications will offer the infrastructure for extremely large data repositories to be accessible on-line. Mission data will be quickly accessible almost immediately after it has been collected from space observations. On-line science will demand for new tools and technologies for data access, data analysis, and data discovery. These trends will enhance the archival operational concepts mainly related to the long-term information preservation, placing an equally important emphasis on rapid data production, and dissemination to consumers.

mission data systems srchive system OAIS data mana↗

Analysis of laboratory data on ultrasonic monitoring of permeability reduction due to biopolymer formation in unconsolidated granular media

We show how to estimate the fluid permeability changes due to accumulated biopolymer within the pore space of a granular material using laboratory measurements of overall permeability, together with various well-known quantitative measures (e.g., porosity, specific surface area, and formation factor) of the granular medium microstructure. The main focus of the paper is on mutual validation of existing theory and a synthesis of new experimental results. Here, we find that the theory and data are in good agreement within normal experimental uncertainties. We also establish quantitative empirical relationships between seismic and/or acoustic attenuation and overall permeability for these same systems.

58 GEOSCIENCES↗

TTHRESH: Tensor Compression for Multidimensional Visual Data

Memory and network bandwidth are decisive bottlenecks when handling high-resolution multidimensional data sets in visualization applications, and they increasingly demand suitable data compression strategies. In this paper, we introduce a novel lossy compression algorithm for multidimensional data over regular grids. It leverages the higher-order singular value decomposition (HOSVD), a generalization of the SVD to three dimensions and higher, together with bit-plane, run-length and arithmetic coding to compress the HOSVD transform coefficients. Our scheme degrades the data particularly smoothly and achieves lower mean squared error than other state-of-the-art algorithms at low-to-medium bit rates, as it is required in data archiving and management for visualization purposes. Further advantages of the proposed algorithm include very fine bit rate selection granularity and the ability to manipulate data at very small cost in the compression domain, for example to reconstruct filtered and/or subsampled versions of all (or selected parts) of the data set.

97 MATHEMATICS AND COMPUTING↗