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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 127 records · Page 7
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Main belt asteroids taxonomical information from dark energy survey data

While proper orbital elements are currently available for more than 1 million asteroids, taxonomical information is still lagging behind. Surveys like SDSS-MOC4 provided preliminary information for more than 100 000 objects, but many asteroids still lack even a basic taxonomy. In this study, we use Dark Energy Survey (DES) data to provide new information on asteroid physical properties. By cross-correlating the new DES data base with other data bases, we investigate how asteroid taxonomy is reflected in DES data. While the resolution of DES data is not sufficient to distinguish between different asteroid taxonomies within the complexes, except for V-type objects, it can provide information on whether an asteroid belongs to the C- or S-complex. Here, machine learning methods optimized through the use of genetic algorithms were used to predict the labels of more than 68 000 asteroids with no prior taxonomic information. Using a high-quality, limited set of asteroids with data on gri slopes and i − z colours, we detected 409 new possible V-type asteroids. Their orbital distribution is highly consistent with that of other known V-type objects.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2021

U.S. Airport Infrastructure and Sustainable Aviation Fuel

Worldwide, aviation accounts for 2% of all manmade carbon dioxide emissions and 12% of all transportation CO 2 emissions In 2018, the U.S. accounted for 25% of the world jet fuel consumption and 21% of global enplanements. Airports and airlines are considering alternative fuel to meet environmental and sustainability goals and mandates. Sustainable aviation fuel (SAF), made from non-petroleum feedstocks, has the potential to significantly reduce emissions from air transportation. SAF must be blended with petroleum based jet fuel prior to its use in aircraft. This report explores background information on jet fuel use, quality standards and best practices, airport infrastructure, and options for delivering SAF to airports.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2021

Improving Discovery, Sharing, and Use of Water Data: Initial Findings and Suggested Future Work

Collaborative management of water resources requires a broad suite of “water data” that extends beyond basic information about water quantity and quality to other related topics such as water infrastructure, aquatic ecosystem health, socioeconomic factors, and power generation. Water data are disparate in nature because they are collected and provided by many entities, and in some cases, remain challenging to access and use. The U.S. Department of Energy’s Water Power Technologies Office initiated a project to characterize relevant categories of water data; describe the current state of accessing, using, and visualizing water data; and outline investigatory pathways for future efforts aimed at improving the discovery, sharing, and use of water data. Input on these topics was solicited from a small but diverse cross section of members of the water resources community. Fourteen broad categories of water data were identified: dams; ecology; flood control; hydroclimatology; hydrography; hydrology; hydropower; management landscape; migratory barriers; recreation and aesthetic importance; socioeconomic; water quality; water availability and use; and weather. Stakeholder perspectives on the accessibility and usability of water data indicate these aspects are affected by a complex set of technical and social factors. However, stakeholders generally agreed that better access to water data can provide a range of benefits to water management, and they stressed the need to generate broad support from water data users and producers. Two investigatory pathways were outlined that, taken together, provide a logical progression toward the goals of the project. The first pathway emphasizes further investigation to better define target audiences and data needs, identify opportunities for collaboration between related efforts, and conduct value demonstration activities to generate further support for improving discovery and access of water data. The second pathway focuses on creating a comprehensive vision for potential solutions that improve the discovery of water data. Several activities that align with the first pathway are suggested for the next phase of the project.

13 HYDRO ENERGY↗
DOE OSTI2024

Southwest Regional Partnership on Carbon Sequestration (Phase III) Underground Source of Drinking Water Monitoring at the Farnsworth Unit

The Ogallala aquifer is identified as the only underground source of drinking water (USDW) aquifer in the vicinity of the FWU. Throughout the span of the SWP project at the FWU, groundwater samples from the Ogallala Aquifer were collected and analyzed on a regular basis to obtain information that reflects the water quality baseline and any potential leakage, and to facilitate effective simulations and risk assessment. To date, hundreds of samples have been collected and tested. The water analysis results suggest that the Ogallala groundwater quality maintains stable and potable, and no leakage is indicated by these data.

42 ENGINEERING↗
DOE OSTI2025

Quantifying uncertainty in regional-scale seismic moment tensors

We examine the ability of three different inversion methods: 1) first motion (FM) inversions, 2) amplitude inversions, and 3) full waveform (FW) time variable moment tensor (TVMT) inversions, to recover an accurate source mechanism for simulated data for an earthquake as well as an explosion. The ability of inversion methods, such as the ones described above, to recover accurate models representative of the data depends on both a priori information as well as the quality of data being inverted. Therefore, we examine the effect that station geometry, geologic model, and noise level has on the inversion and estimated source mechanism. We find that FM data can provide more robust solutions than amplitude data and are not as sensitive to inaccurate earth models, especially in low-noise cases, and overall FW inversions are the most accurate out of the methods examined, but can still be biased by inaccurate earth models.

58 GEOSCIENCES↗
DOE OSTI2021

Mutual Detectability: A Targeted SETI Strategy That Avoids the SETI Paradox

As our ability to undertake searches for extraterrestrial intelligence (SETI) grows, so does interest in the controversial endeavor of messaging extraterrestrial intelligence (METI). METI proponents point to the SETI Paradox—if all civilizations refrain from METI then SETI is futile. I introduce mutual detectability as a game-theoretic strategy to increase the success potential of targeted SETI. Mutual detectability comprises four laws that establish how SETI participants can engage each other based on mutual evidence of mutual existence. I argue that the party whom both SETI participants can judge to have better quality evidence, or common denominator information (CDI), has an onus to transmit to avoid the SETI Paradox. Transiting exoplanets within the Earth Transit Zone form a target subset that satisfies mutual detectability requirements. I identify the intrinsic time-integrated transit signal strength, which for Earth is 10{sup 3} L{sub ⊙} ppm hours yr{sup −1}, as suitable CDI. Civilizations on habitable-zone planets of radius R{sub p}/R{sub ⊕}≲(L{sub ∗}/L{sub ⊙}){sup −1/7} have superior CDI on us, and so under the mutual detectability framework have game-theory incentive (onus) to transmit. While the onus to transmit falls on us for habitable planets around L{sub *} > L{sub ⊙} stars, considerations of relative stellar frequency, main-sequence lifetime and planet occurrence rates mean that such systems are likely to be in a small minority. Surveys of the Earth Transit Zone for Earth-analog transiting planets around subsolar luminosity hosts would facilitate targeted SETI programs for civilizations who have game-theory incentive to transmit signals to us. A choice to remain silent, by not engaging in METI toward such systems, does not in this case fuel concerns of a SETI Paradox.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2023

TRACER-Coastal Urban Boundary-Layer Interactions with Convection (TRACER-CUBIC) Field Campaign Report

To better understand the complicated web of processes governing convective cloud life cycle and aerosol-convection interactions, the U.S. Department of Energy (DOE)’s Atmospheric Radiation Measurement (ARM) user facility supported deployment of a variety of advanced atmospheric measurement systems to the greater Houston, Texas, area from 1 October 2021 to 30 September 2022 as part of the Tracking Aerosol Convection Interactions Experiment (TRACER). Houston was selected as a study area because isolated convection and a variety of aerosol conditions are common in this region. This one-year ARM Mobile Facility (AMF) deployment featured a four-month intensive operational period (IOP) during summer 2022 (1 June–30 September). The ARM instrumentation was deployed at three sites along an east-west transect from La Porte, Texas to an ancillary site in a less-polluted rural region southwest of downtown Houston (Figure 1). At the La Porte Site, which is located near the Houston ship channel in an area that experiences significant pollution, the first ARM Mobile Facility (AMF1) was deployed. During the IOP, the ARM tethered balloon system (TBS) operated at the ancillary site. The second-generation C-Band Scanning ARM Precipitation Radar (CSAPR) operated near Pearland, Texas, roughly halfway between the Laporte and ancillary sites. As part of the TRACER- Coastal Urban Boundary-Layer Interactions with Convection (CUBIC) project, three boundary-layer profiling systems) were deployed along a north-south transect spanning from the University of Houston Coastal Center to the Aldine site north of downtown Houston (also blue dot in Figure 1) during the TRACER IOP. These systems included the National Oceanic and Atmospheric Administration (NOAA) National Severe Storms Laboratory CLAMPS2 (C2), which was deployed at the UHCC, the University of Wisconsin SPARC, which was deployed at the ARM CSAPR site near Pearland (orange diamond in middle of map in Figure 1), and the University of Oklahoma CLAMPS1 (C1), which was deployed at Aldine. These three systems have been successfully operated in various field campaigns, providing data sets that collectively offer new insights into atmospheric-boundary-layer (ABL) processes, sea-breeze (SB) circulations, and convection initiation (CI). For the TRACER IOP window, these systems ran continuously between 1 June and 26 September, 2022. Due to commitments to NOAA projects, the Doppler lidar at the UHCC site was not available until 24 June 2022. The CLAMPS and SPARC profiling systems are self-contained platforms that have benefited from several years of development and deployment. Instruments and data processing were maintained remotely, which made the 4-month deployment for the TRACER-CUBIC IOP period possible. The same basic instrument configuration comprises each system: a scanning Doppler wind lidar for flow characterization and passive profiler(s) for characterizing planetary-boundary-layer (PBL) thermodynamic properties. Each platform includes a Halo Streamline Doppler wind lidar, an Atmospheric Emitted Radiance Interferometer (AERI), and a surface meteorology station. CLAMPS1 and CLAMPS2 each also include a microwave radiometer (MWR, Figure 1d). The TRACER-CUBIC hypotheses included (i) Interactions of SB and urban circulations and how they affect the PBL structure in the Houston environment, causing spatially (horizontally and vertically) and temporally highly variable flow patterns, (ii) heat, moisture, and aerosol transport and mixing depend on these flow dynamics, and (iii) an improved understanding of the flow patterns and PBL structure are critical for investigating the processes leading to CI. To test these hypotheses, the project aimed at (i) characterizing SB circulations and their impacts on the diurnal evolution of the structure of the ABL, (ii) studying the evolution of Houston’s complex urban boundary layer, and (iii) identifying effects of urban-induced circulations on pre-convective environments. TRACER-CUBIC observations generally provide good coverage during the summer IOP. Initial screening of the data indicates a good number of cases with bay-breeze (BB) and/or SB signatures, local CI, and interesting boundary-layer features such as strong nocturnal low-level jets (LLJs, Table 1). The numbers listed in rows 3-5 in this table will be further updated as part of ongoing in-depth analyses and systematic identification of local circulations and CI events. More detailed information about the data availability and quality for each instrument is provided in the “readme” files that were submitted to the ARM Data Center along with each archived data sets. These “readme” files also provide instrument descriptions, information about the data collection and processing procedures, data formats, and any additional information relevant for further data analysis.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Where Is the Provenance? Ethical Replicability and Reproducibility in GIScience and Its Critical Applications

As replicability and reproducibility (R&R) crises develop within emerging convergent inquiry, ethical use of provenance information is central to the establishment and preservation of trust in critical applications of GIScience and geospatial technologies. Today large volumes of geospatial data are generated at high velocity from satellite sensors and unmanned aircraft systems, citizen sensors, geolocation-based data services, global navigation satellite systems, and so on. The extensive use of these data for applications such as disaster and humanitarian response raises the issue of R&R from competing perspectives of location privacy and geospatial data quality. Although geospatial data can be integrated and linked with contextual information to identify individuals’ movements, steps taken to ensure privacy can complicate the multiuser development of high-quality geospatial workflows. Provenance information as digital records of historical (retrospective) and potential future (prospective) geospatial processes is often overlooked, misunderstood, or inadequately addressed. We explore the relationship between provenance information, location privacy, and geospatial data quality in the context of R&R with a focus on disaster analytics. Here, we argue that in the era of big data and deep learning, GIScientists and associated institutions bear greater responsibility both for geospatial workflow quality and for location privacy. Given vastly heterogenous computational landscapes, we provide practical recommendations for ethically driven provenance and R&R research and development within the GIScience community and beyond.

96 KNOWLEDGE MANAGEMENT AND PRESERVATION↗
DOE OSTI2021

Decreased land use intensity improves surface soil quality on marginal lands

The Conservation Reserve Program (CRP) has been a major factor in land transitions out of intensive row-crop management on marginally productive lands in the central United States. While CRP can protect these more environmentally sensitive lands against erosion and potential nutrient loss, information on how CRP affects soil quality over time is limited. Using a chronosequence with 0–40 yr of CRP conversion history, we evaluated soil quality under different land use intensities (CRP, pasture, row crop) using the Soil Management Assessment Framework (SMAF). Effects of slope classes (higher [14–25%] and lower [2–14%]) and soil depth (0–120 cm) were also evaluated. Our results show that the soils were functioning at 84 and 78% of their theoretical capacity under CRP and row crop, respectively. Conversion to CRP enhanced overall soil quality by increasing soil biological, physical, and chemical attributes, but soil nutrient availability decreased due to the absence of fertilizer application. Increasing soil organic C (SOC) enhanced overall soil quality because of its impact on soil biological, physical, chemical, and nutrient conditions. Conversion to CRP will likely have greater benefits for more environmentally sensitive soils (i.e., higher slope) as demonstrated by structural equation modeling. Land use effects were also depth dependent, with more prominent effects within the 0-to-5-cm than the 5-to-15-cm depth increment. Overall, our methods focused on key soil quality indicators, confirmed ecological benefits of CRP conversion, and provided guidance for improved and simplified land management recommendations.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

A Scalable & Non-Destructive Characterization Strategy to Study Semiconductor/Dielectric Interfaces and Predict Wafer-Level Device Performance

The defect density present at the dielectric-semiconductor interface in an MOS structure directly influences the channel carrier characteristics in semiconductor devices, especially in wide bandgap material systems used in power devices. While these trap defects are typically quantified through electrical characterization of MOS-capacitor test structures, this treatment offers very little insight into the physical nature of interface defects. Such shortcomings demand a physical characterization strategy to guide fabrication optimization. X-ray photoelectron spectroscopy (XPS) is suggested as a viable technique to determine chemical data for dielectric interfaces formed using atomic layer deposition (ALD) on GaN substrates. Previously, 1-D XPS characterization has confirmed the presence of a Ga x O y interlayer between ALD dielectrics and the GaN substrate. In this work, XPS data is serially collected to form 2-D images of an ALD-Al 2 O 3 /GaN interface as a proof-of-concept experiment for in-situ XPS quality monitoring during ALD processing. The information provided by this work reveals some of the challenges for incorporating XPS characterization as an in-situ strategy during fabrication of GaN-based devices. Separately, electrical mapping of a 2-D array of ALD-Al 2 O 3 /GaN MOS-capacitor devices provide a means to quantify the spatial variations in interface quality across a single wafer. Physical characterization techniques, such as time-of-flight secondary ion mass spectroscopy, provide additional chemical information about the Al 2 O 3 /Ga x O y /GaN structure that complement the electrical mapping results. This analysis shows that a higher Ga x O y content correlates with higher interface state defects for trap energies deep in the band gap.

42 ENGINEERING↗
DOE OSTI2022

FedFleet 2022: Federal Automotive Statistical Tool - FY 2021 Fleet Trends and Data Quality

This presentation presents a brief overview of the collection of information about the US government's fleet of motor vehicles using the Federal Automotive Statistical Tool (FAST), discusses the makeup and operation of the vehicle fleet during FY 2021, discusses quality of the submitted data, and touches on future aspects of fleet data collection and reporting. FAST is a web-based information system sponsored by GSA's Office of Government-wide Policy and DOE's Federal Energy Management Program to collect information about the US federal government's fleet of motor vehicles; FAST is developed, maintained, and supported by DOE's Idaho National Laboratory (INL).

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2023

Federal Automotive Statistical Tool: FY 2022 Federal Fleet Trends and Data Quality [Slides]

This presentation presents a brief overview of the collection of information about the US government's fleet of motor vehicles using the Federal Automotive Statistical Tool (FAST), discusses the makeup and operation of the vehicle fleet during FY 2022 and discusses quality of the submitted data. FAST is a web-based information system sponsored by GSA's Office of Government-wide Policy and DOE's Federal Energy Management Program to collect information about the US federal government's fleet of motor vehicles; FAST is developed, maintained, and supported by DOE's Idaho National Laboratory (INL).

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2020

Groundwater Monitoring Report, U.S. Department of Energy Y-12 National Security Complex, Oak Ridge, Tennessee

This report contains the groundwater and surface water monitoring data obtained during calendar year (CY) 2019 at the U.S. Department of Energy (DOE) Y-12 National Security Complex (Y-12) on the DOE Oak Ridge Reservation (ORR) in Oak Ridge, Tennessee. The monitoring data were obtained from wells, springs, and surface water sampling locations in three hydrogeologic regimes at Y-12. The Bear Creek Hydrogeologic Regime (Bear Creek Regime) encompasses a section of Bear Creek Valley (BCV) between the west end of Y-12 and the west end of the Bear Creek Watershed (directions are in reference to the Y-12 grid system, shown as Plant North. The Upper East Fork Poplar Creek Hydrogeologic Regime (East Fork Regime) encompasses the Y-12 industrial facilities and support structures in BCV. The Chestnut Ridge Hydrogeologic Regime (Chestnut Ridge Regime) encompasses a section of Chestnut Ridge directly south of Y-12. Background information in Section 2 of this report outlines the hydrogeologic framework for groundwater and surface water quality monitoring at Y-12 and includes an overview of the groundwater contamination in each hydrogeologic regime. Section 3 provides details regarding the groundwater and surface water sampling and analysis activities implemented under the Y-12 GWPP, including sampling locations and frequency, sample collection and handling, field measurements and laboratory analytes, quality assurance (QA)/quality control (QC) sampling, data management, and data quality assessment (DQA). However, the equivalent QA/QC or DQA information for the groundwater and surface water data associated with the monitoring programs implemented by UCOR are not included in this report and instead are deferred to referenced programmatic plans and reports issued by OREM and UCOR. Section 4 of this report presents a summary evaluation of the CY 2019 monitoring data with regard to the respective objectives of surveillance monitoring and exit pathway/perimeter monitoring. The evaluation is based primarily on the analytical results for the following principal groundwater contaminants at Y-12: nitrate, uranium, gross alpha activity, gross beta activity, and volatile organic compounds (VOCs). Section 5 summarizes the most significant findings with respect to the principal contaminants along with recommendations for any proposed changes to the ongoing groundwater and surface water quality monitoring performed under the Y-12 GWPP. Technical reports and plans cited in the narrative sections of the report are listed in Section 6. Narrative sections of this report reference several appendices. Figures (maps and diagrams) and data tables (excluding data summary tables incorporated in the narrative sections) are in Appendix A and Appendix B, respectively. Appendix C contains construction details for each well sampled during CY 2019 by either the Y-12 GWPP or UCOR, along with schematic diagrams for wells equipped with Westbay™ multiport sampling equipment or Barcad® pump systems. Appendix D supports the background summary discussion in Section 2 and provides more detailed information about the hydrogeologic framework for groundwater and surface water monitoring at Y-12, including the primary sources of groundwater contamination in each hydrogeologic regime. Results for all field measurements and laboratory analyses obtained by the Y-12 GWPP and UCOR are presented in Appendix E, which also includes the sample numbers for the QA/QC samples associated with groundwater and surface water monitoring performed by the Y-12 GWPP.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Enhancing nuclear data validation analysis by using machine learning

In this work, we demonstrate how machine learning (ML) techniques can be used as an auxiliary tool for nuclear data validation analysis. The output of the ML analysis can inform evaluators and validators on the quality, or lack thereof, of specific nuclear data and benchmark experiments with respect to simulating these experimental benchmark values. To this end, measured and simulated effective neutron multiplication factors, k eff , of 875 selected ICSBEP critical assemblies and the latter's sensitivities with respect to nuclear data as well as benchmarks' features (e.g., material nuclide, core geometry) are used as input for a random forest (RF) regression model. The RF is used to encode the complex inter-dependencies between thousands of nuclear data features (i.e., sensitivity profiles and aspects describing the measurements) and 875 simulated and experimental k eff values in order to understand what nuclear data features are most informative for predicting bias. The complexity of relationships and high-dimensional space is difficult-to-impossible to search fully using simply expert judgment. As a first proof-of-concept—step, it is demonstrated that this technique is able to correctly trace large discrepancies between simulated and experimental k eff back to fabricated shortcomings in nuclear data that were perturbed to simulated k eff values. In a second, real-case scenario, step, the RF algorithm is used to validate the ENDF/B-VIII.0 library in comparison to ENDF/B-VII.1 nuclear data. One case is showcased where the chosen ML algorithms highlighted nuclear data (the 19 F(n,inl) cross section from 0.4–0.9 MeV) that are shown to be problematic by comparing them to associated differential experimental data and nuclear data from other libraries. In addition to that, it is shown that the RF results point towards poor benchmark experiments and associated underestimated uncertainties (e.g., the PU-SOL-THERM-028 series). However, using the RF algorithm for validating nuclear data with respect to k eff is currently limited to pinpointing groups of questionable nuclear data due to the inherent correlations between features introduced by the nuclear data themselves and how k eff is simulated. Due to this, we recommend that the ML methods presented be used to augment—rather than replace—the expert knowledge of evaluators and validators.

96 KNOWLEDGE MANAGEMENT AND PRESERVATION↗
DOE OSTI2023

SAM Software Quality Assurance Plan Implementation and NQA-1 Assessment

The System Analysis Module (SAM) is an advanced and modern system analysis tool being developed at Argonne National Laboratory under the U.S. DOE Office of Nuclear Energy’s Nuclear Energy Advanced Modeling and Simulation (NEAMS) program. As a modern-day software, SAM development included efforts to follow best practices in software development. These best practices include version control using git, independent reviews of development activities, and detailed descriptions of developments and bug fixes using the GitLab issue and merge request system. In Fiscal Year 2023 (FY23), the SAM development team set out to formalize a Software Quality Assurance (SQA) program that allowed industry partners to credit the informal steps being taken by the SAM development team to ensure the quality of the software. As part of formalizing an SQA program, a SQA Plan (SQAP) was developed, implemented, and assessed. The SAM SQAP targets compliance with NQA-1-2008/2009 Addenda. The SQAP builds on the MOOSE SQAP and the Argonne SSQAPP while accounting for the needs of the multi-organization SAM development team. Modifications to the SAM repository structure, including a new testing system, updated test cases, and the development of an internal website, facilitate the implementation of the SAM SQAP. The initial assessment of the SAM SQAP indicated that the SAM SQAP was adequately and effectively implemented and additional work was required to improve the compliance of the SAM SQAP with NQA-1 2008/2009 Addenda. Several improvements to the SQAP have already been drafted to address these assessments and future work is planned to further improve the SAM SQAP in support of end-user needs.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2022

Diagnosing the DARHT Electron Beam-Target Interaction and Hydrodynamic Expansion [Dissertation]

Quantitative electron beam-target interaction studies on the Dual-Axis Radiographic Hydrodynamic Test (DARHT) electron linear induction accelerators have only been performed recently. This includes characterization of the temperature, density, pressure, extent, and expansion velocity of the plasma plume. The results presented in this dissertation present a detailed and unified overview of the accelerator systems, target heating physics, beam transport, and diagnostic tools. Additional information includes calibration sources, radiation hydrodynamics, spectroscopic-quality radiation transport modeling, experimental measurements, and analyses of electron beam driven aluminum experiments. The first set of spatially and temporally resolved spectroscopic measurements of electron beam driven aluminum are presented. Contamination quantification analyses are used to understand the origin of the strong Na-I 3p-3s lines that are observed in absorption within the aluminum plasma continuum. These results inform the creation of the first spectroscopic-quality radiation transport model that links several atomic physics codes to interpret the conditions from which the Na-I lines originate. A good agreement is found between the surface analysis results and the model which confirms the concentration of the sodium present within the aluminum alloy foil material. It also demonstrates, for the first time on electron beam-driven target experiments, the ability to interpret plasma conditions from measured absorption lines. In a second experimental campaign which focuses on pure aluminum, the Al-I 3p-4s and 3p3d doublets are both measured in emission. A detailed analysis of the Al-I 3p-4s doublet reveals that the lines undergo moderate self-absorption. A simple model of the self-absorption effect is successfully used to match measured spectra at various temperature/density/plasma scale length combinations. These measurements led to the realization of the minimum density that can be resolved by the spectrometers for the Al-I 3p-4s lines due to the large slit width required to observe a signal on aluminum. These measurements also demonstrate the sensitivity of visible and long wave UV spectroscopy to minor changes in both temperature and density. The simple self-absorption model will be useful for analysis of other beam-target interaction experiments with spectra exhibiting either self-absorption or full self-reversal. Substantial headway has been made on the modeling front by linking together several codes needed to model both the energy deposition, hydrodynamic motion, and atomic kinetics to produce synthetic spectral calculations that are compared with experimental measurements. There exists ample space for improvement, especially with benchmarking the hydrodynamics codes and equation-of-state tables with experimental measurements. The X-ray diagnostics required to make these new measurements along with the simulation capabilities required to interpret the results are under development and will be the subject of future studies.

43 PARTICLE ACCELERATORS↗
DOE OSTI2021

Feedstock Harvesting and Storage: Post-Harvest Management for Quality Preservation

Research on harvesting, collection, and storage has matured, and our understanding of feedstock supply challenges has led us to the point of our current goals. The goals of this project include using storage time to collect impactful data of critical feedstock properties in storage and to characterize the feedstock before delivery. This data will inform delivery scheduling of biomass and relevant compositional information to minimize variations in the material quality, which are critical to the preprocessing and conversion performance.

09 BIOMASS FUELS↗
DOE OSTI2022

PDFDataExtractor: A Tool for Reading Scientific Text and Interpreting Metadata from the Typeset Literature in the Portable Document Format

The layout of portable document format (PDF) files is constant to any screen, and the metadata therein are latent, compared to mark-up languages such as HTML and XML. No semantic tags are usually provided, and a PDF file is not designed to be edited or its data interpreted by software. However, data held in PDF files need to be extracted in order to comply with opensource data requirements that are now government-regulated. In the chemical domain, related chemical and property data also need to be found, and their correlations need to be exploited to enable data science in areas such as data-driven materials discovery. Such relationships may be realized using text-mining software such as the “chemistry-aware” natural-language-processing tool, ChemDataExtractor; however, this tool has limited data-extraction capabilities from PDF files. This study presents the PDFDataExtractor tool, which can act as a plug-in to ChemDataExtractor. It outperforms other PDF-extraction tools for the chemical literature by coupling its functionalities to the chemical-named entityrecognition capabilities of ChemDataExtractor. The intrinsic PDF-reading abilities of ChemDataExtractor are much improved. The system features a template-based architecture. This enables semantic information to be extracted from the PDF files of scientific articles in order to reconstruct the logical structure of articles. While other existing PDF-extracting tools focus on quantity mining, this template-based system is more focused on quality mining on different layouts. PDFDataExtractor outputs information in JSON and plain text, including the metadata of a PDF file, such as paper title, authors, affiliation, email, abstract, keywords, journal, year, document object identifier (DOI), reference, and issue number. With a self-created evaluation article set, PDFDataExtractor achieved promising precision for all key assessed metadata areas of the document text.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗