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At least 541 records · Page 30

An Integrated ML/AI Framework for Digitizing, Structuring and Searching DOE U-TRU-Fuels Data with Gap Analysis of Non-DOE Records

The U.S. Department of Energy (DOE) Advanced Fuels Campaign (AFC) is advancing transmutation fuel technologies to reduce long-lived radioactive waste by converting minor actinides into shorter-lived or stable elements through irradiation in sodium-cooled fast reactors. Key experiments such as AFC-1, AFC-2, FUels for the transmutation of Trans-URanium elements In phéniX (FUTURIX)-Fortes Teneurs en Actinides (FTA), and Experimental Breeder Reactor-II (EBR-II) X501 have provided fuel fabrication, irradiation, and performance data on various transuranic-bearing fuel forms. This report documents the creation of an artificial-intelligence assisted database, which has consolidated all DOE-owned data related to Transuranic (TRU)-bearing fuel experiments and stored across it across both the Idaho National Laboratory (INL) Nuclear Data Management and Analysis System and the INL high performance computing (HPC) infrastructure. A dedicated webpage, hosted on the INL HPC system, has been developed to support role-based access and data interaction. The database architecture allows researchers to navigate large, heterogeneous archives with far greater speed and accuracy than manual search and lays the foundation for future expansion into multimodal nuclear materials analysis environments. The database represents a major step towards a nationally integrated fuels database utilizing artificial intelligence tools.

11 - NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Indian Renewable Energy and Energy Efficiency Policy Database (Fact Sheet)

This fact sheet provides an overview of the Indian Renewable Energy and Energy Efficiency Policy Database (IREEED) developed in collaboration by the United States Department of Energy and India's Ministry of New and Renewable Energy. IREEED provides succinct summaries of India's central and state government policies and incentives related to renewable energy and energy efficiency. The online, public database was developed under the U.S.- India Energy Dialogue and the Clean Energy Solution Center.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Tundra Trait Team: A database of plant traits spanning the tundra biome

Motivation: The Tundra Trait Team (TTT) database includes field-based measurements of key traits related to plant form and function at multiple sites across the tundra biome. This dataset can be used to address theoretical questions about plant strategy and trade-offs, trait-environment relationships and environmental filtering, and trait variation across spatial scales, to validate satellite data, and to inform earth system model parameters. Main types of variable contained: The database contains 81,537 measurements of 18 plant traits. The most frequently measured traits (>1,000 observations each) include plant height, leaf area, specific leaf area, leaf fresh and dry mass, leaf dry matter content, leaf nitrogen content, leaf carbon content, leaf phosphorus content, seed mass, and stem specific density. Spatial location and grain: Measurements were collected in tundra habitats in both the northern and southern hemispheres, including Arctic sites in Alaska, Canada, Greenland, Fennoscandia, and Siberia and alpine sites in the European Alps, Colorado Rockies, Caucasus, Ural Mountains, Pyrenees, Australian Alps, and Central Otago Mountains (New Zealand). More than 99% of observations are georeferenced. Time period and grain: All data were collected between 1964 and 2016. A small number of sites have repeated trait measurements at two or more time periods. Major taxa and level of measurement: Trait measurements were made on 858 terrestrial vascular plant species growing in tundra habitats. Most observations are on individuals (87%), while a small number represent plot or site means or maximums per species. Software format: csv file and GitHub repository with data cleaning scripts in R; contribution to TRY plant trait database (www.try-db.org) to be included in the next version release.

59 BASIC BIOLOGICAL SCIENCES↗

NEWTS State-Level Database Dashboard

The National Energy Water Treatment and Speciation (NEWTS) State-Level Database Dashboard enables quick visualization and exploration of energy-related wastewater data collected from state environmental agencies and research projects across the United States. The dashboard features a subset of the NEWTS Integrated Dataset (version 1.0), which was built to provide stakeholders with a unified and standardized database to support wastewater treatment and critical minerals exploration. The full NEWTS Integrated Dataset and citations for the original data resources can be found here: https://edx.netl.doe.gov/dataset/newts-integrated-dataset-version-1-0

abandoned mine drainage↗

The PAH Emission Characteristics of the Reflection Nebula NGC 2023

We present 5–20 μ m spectral maps of the reflection nebula NGC 2023 obtained with the Infrared Spectrograph SL and SH modes on board the Spitzer Space Telescope, which reveal emission from polycyclic aromatic hydrocarbons (PAHs), C{sub 60}, and H{sub 2} superposed on a dust continuum. We show that several PAH emission bands correlate with each other and exhibit distinct spatial distributions that reveal a spatial sequence with distance from the illuminating star. We explore the distinct morphology of the 6.2, 7.7, and 8.6 μ m PAH bands and find that at least two spatially distinct components contribute to the 7–9 μ m PAH emission in NGC 2023. We report that the PAH features behave independently of the underlying plateaus. We present spectra of compact, oval PAHs ranging in size from C{sub 66} to C{sub 210}, determined computationally using density functional theory, and we investigate trends in the band positions and relative intensities as a function of PAH size, charge, and geometry. Based on the NASA Ames PAH database, we discuss the 7–9 μ m components in terms of band assignments and relative intensities. We assign the plateau emission to very small grains with possible contributions from PAH clusters and identify components in the 7–9 μ m emission that likely originate in these structures. Based on the assignments and the observed spatial sequence, we discuss the photochemical evolution of the interstellar PAH family as the PAHs are more and more exposed to the radiation field of the central star in the evaporative flows associated with the Photo-Dissociation Regions in NGC 2023.

79 ASTRONOMY AND ASTROPHYSICS↗

Quantifying Global Uncertainties in a Simple Microwave Rainfall Algorithm

While a large number of methods exist in the literature for retrieving rainfall from passive microwave brightness temperatures, little has been written about the quantitative assessment of the expected uncertainties in these rainfall products at various time and space scales. The latter is the result of two factors: sparse validation sites over most of the world's oceans, and algorithm sensitivities to rainfall regimes that cause inconsistencies against validation data collected at different locations. To make progress in this area, a simple probabilistic algorithm is developed. The algorithm uses an a priori database constructed from the Tropical Rainfall Measuring Mission (TRMM) radar data coupled with radiative transfer computations. Unlike efforts designed to improve rainfall products, this algorithm takes a step backward in order to focus on uncertainties. In addition to inversion uncertainties, the construction of the algorithm allows errors resulting from incorrect databases, incomplete databases, and time- and space-varying databases to be examined. These are quantified. Results show that the simple algorithm reduces errors introduced by imperfect knowledge of precipitation radar (PR) rain by a factor of 4 relative to an algorithm that is tuned to the PR rainfall. Database completeness does not introduce any additional uncertainty at the global scale, while climatologically distinct space/time domains add approximately 25% uncertainty that cannot be detected by a radiometer alone. Of this value, 20% is attributed to changes in cloud morphology and microphysics, while 5% is a result of changes in the rain/no-rain thresholds. All but 2%-3% of this variability can be accounted for by considering the implicit assumptions in the algorithm. Additional uncertainties introduced by the details of the algorithm formulation are not quantified in this study because of the need for independent measurements that are beyond the scope of this paper. A validation strategy for these errors is outlined.

Kummerow, Christian↗

Identification of repaglinide as a therapeutic drug for glioblastoma multiforme

Glioblastoma multiforme (GBM) is a highly aggressive brain tumor with a median survival time of only 14 months after treatment. It is urgent to find new therapeutic drugs that increase survival time of GBM patients. To achieve this goal, we screened differentially expressed genes between long-term and short-term survived GBM patients from Gene Expression Omnibus database and found gene expression signature for the long-term survived GBM patients. The signaling networks of all those differentially expressed genes converged to protein binding, extracellular matrix and tissue development as revealed in BiNGO and Cytoscape. Drug repositioning in Connectivity Map by using the gene expression signature identified repaglinide, a first-line drug for diabetes mellitus, as the most promising novel drug for GBM. In vitro experiments demonstrated that repaglinide significantly inhibited the proliferation and migration of human GBM cells. In vivo experiments demonstrated that repaglinide prominently prolonged the median survival time of mice bearing orthotopic glioma. Mechanistically, repaglinide significantly reduced Bcl-2, Beclin-1 and PD-L1 expression in glioma tissues, indicating that repaglinide may exert its anti-cancer effects via apoptotic, autophagic and immune checkpoint signaling. Taken together, repaglinide is likely to be an effective drug to prolong life span of GBM patients. - Highlights: • Gene expression signarue in long-term survived GBM patients are identified from Gene Expression Omnibus database. • Repaglinide is identified as a survival-related drug for GBM via drug repositioning in CMap. • Repaglinide effectively kills GBM cells, inhibits GBM cell migration and increases survival of mice bearing orthotopic glioma. • Repaglinide reduces Bcl-2, Beclin-1 and PD-L1 in GBM tissues.

60 APPLIED LIFE SCIENCES↗

How does uncertainty of soil organic carbon stock affect the calculation of carbon budgets and soil carbon credits for croplands in the U.S. Midwest?

Cropland carbon budget depicts the amount of carbon flowing in and out of agroecosystems and the changes in carbon stocks of soil and living biomass during the same period. Soil carbon credit is the additional change in soil carbon stock under certain farming practices compared with the business-as-usual practices. Accurately calculating cropland carbon budget and soil carbon credit is critical to assessing climate change mitigation potential in agroecosystems. The calculation of cropland carbon budget and soil carbon credit is sensitive to local soil and climatic conditions, especially initial soil organic carbon (SOC) stock, which is determined by both SOC concentration (SOC%) and bulk density (Bulk_Density). SOC stock data are either from soil sampling or gridded public survey data. In agroecosystem models, SOC stock data are a key model input for quantifying cropland carbon budget and soil carbon credit. However, various types and degrees of uncertainties exist in SOC stock datasets, which propagate to the quantification of SOC stock change. In particular, a large discrepancy is found in two widely used SOC stock datasets — Rapid Carbon Assessment dataset (RaCA) and Gridded Soil Survey Geographic Database (gSSURGO) — in the U.S. Midwest, with a relative difference (quantified using Normalized Root Mean Square Error, NRMSE) of 48.0% for 0–30 cm SOC stock between the two datasets. It remains largely unclear how uncertainty in SOC stocks affects the calculation of cropland carbon budget and soil carbon credit. To address this question, we used a well-validated process-based agroecosystem model, ecosys, to assess the impacts of SOC stock uncertainty on carbon budget and soil carbon credit calculation in the U.S. Midwestern corn-soybean rotation systems. Our results reveal the following findings: (1) A sizable discrepancy exists in simulated cropland carbon budget between using gSSURGO and using RaCA for their SOC% and Bulk_Density as model inputs, with a Pearson correlation coefficient (r) of only 0.4 for simulated change of SOC stock (ΔSOC) using these two different soil datasets. (2) Simulated cropland carbon budget components were more sensitive to initial SOC% than to Bulk_Density. For example, the upper and lower quartiles of multi-year averaged ΔSOC were –29.8 and 4.8 gC/m 2 /year for the selected counties respectively, with an uncertainty of 13.7 and 0.7 gC/m 2 /year induced by uncertainties in initial SOC% and Bulk_Density, respectively. (3) Both simulated ΔSOC and its uncertainty were negatively correlated with initial SOC%, whereas ΔSOC was negatively correlated with air temperature, and ΔSOC uncertainty was positively correlated with air temperature. (4) The uncertainty of calculated soil carbon credits was much smaller compared with the uncertainty of calculated absolute carbon budgets assuming the same SOC stock uncertainty level in the inputs. Specifically, in our assessment comparing planting cover crops vs no cover crop, the uncertainty of calculated soil carbon credits induced by initial SOC% uncertainty was less than 4% (relative to the quantified value of the soil carbon credits) for 90% of the cases. Our analysis highlights that high accuracy measurement of SOC% as inputs is needed for the calculation of cropland carbon budgets; however, soil carbon credit quantification is much less sensitive to the initial SOC% inputs, and the current publicly available soil datasets (e.g., gSSURGO) are largely suitable for the calculation of soil

54 ENVIRONMENTAL SCIENCES↗

MO-G-BRE-09: Validating FMEA Against Incident Learning Data: A Study in Stereotactic Body Radiation Therapy

Purpose: Though FMEA (Failure Mode and Effects Analysis) is becoming more widely adopted for risk assessment in radiation therapy, to our knowledge it has never been validated against actual incident learning data. The objective of this study was to perform an FMEA analysis of an SBRT (Stereotactic Body Radiation Therapy) treatment planning process and validate this against data recorded within an incident learning system. Methods: FMEA on the SBRT treatment planning process was carried out by a multidisciplinary group including radiation oncologists, medical physicists, and dosimetrists. Potential failure modes were identified through a systematic review of the workflow process. Failure modes were rated for severity, occurrence, and detectability on a scale of 1 to 10 and RPN (Risk Priority Number) was computed. Failure modes were then compared with historical reports identified as relevant to SBRT planning within a departmental incident learning system that had been active for two years. Differences were identified. Results: FMEA identified 63 failure modes. RPN values for the top 25% of failure modes ranged from 60 to 336. Analysis of the incident learning database identified 33 reported near-miss events related to SBRT planning. FMEA failed to anticipate 13 of these events, among which 3 were registered with severity ratings of severe or critical in the incident learning system. Combining both methods yielded a total of 76 failure modes, and when scored for RPN the 13 events missed by FMEA ranked within the middle half of all failure modes. Conclusion: FMEA, though valuable, is subject to certain limitations, among them the limited ability to anticipate all potential errors for a given process. This FMEA exercise failed to identify a significant number of possible errors (17%). Integration of FMEA with retrospective incident data may be able to render an improved overview of risks within a process.

60 APPLIED LIFE SCIENCES↗

Laboratory Studies of Processing of Carbonaceous Aerosols by Atmospheric Oxidants/Hygroscopicity and CCN Activity of Secondary & Processed Primary Organic Aerosols

The atmosphere is composed of a complex mixture of gases and suspended microscopic aerosol particles. The ability of these particles to take up water (hygroscopicity) and to act as nuclei for cloud droplet formation significantly impacts aerosol light scattering and absorption, and cloud formation, thereby influencing air quality, visibility, and climate in important ways. A substantial, yet poorly characterized component of the atmospheric aerosol is organic matter. Its major sources are direct emissions from combustion processes, which are referred to as primary organic aerosol (POA), or in situ processes in which volatile organic compounds (VOCs) are oxidized in the atmosphere to low volatility reaction products that subsequent condense to form particles that are referred to as secondary organic aerosol (SOA). POA and VOCs are emitted to the atmosphere from both anthropogenic and natural (biogenic) sources. The overall goal of this experimental research project was to conduct laboratory studies under simulated atmospheric conditions to investigate the effects of the chemical composition of organic aerosol particles on their hygroscopicity and cloud condensation nucleation (CCN) activity, in order to develop quantitative relationships that could be used to more accurately incorporate aerosol-cloud interactions into regional and global atmospheric models. More specifically, the project aimed to determine the products, mechanisms, and rates of chemical reactions involved in the processing of organic aerosol particles by atmospheric oxidants and to investigate the relationships between the chemical composition of organic particles (as represented by molecule sizes and the specific functional groups that are present) and the hygroscopicity and CCN activity of oxidized POA and SOA formed from the oxidation of the major classes of anthropogenic and biogenic VOCs that are emitted to the atmosphere, as well as model hydrocarbons. The general approach for this project was to carry out reactions of representative anthropogenic and biogenic VOCs and organic particles with ozone (O 3 ), and hydroxyl (OH), nitrate (NO 3 ), and chlorine (Cl) radicals, which are the major atmospheric oxidants, under simulated atmospheric conditions in large-volume environmental chambers. A combination of on-line and off-line analytical techniques were used to monitor the chemical and physical properties of the particles including their hygroscopicity and CCN activity. The results of the studies were used to (1) improve scientific understanding of the relationships between the chemical composition of organic particles and their hygroscopicity and CCN activity, (2) develop an improved molecular level theoretical framework for describing these relationships, and (3) establish a large database that is being used to develop parameterizations relating organic aerosol chemical properties and SOA sources to particle hygroscopicity and CCN activity for use in regional and global atmospheric air quality and climate models.

54 ENVIRONMENTAL SCIENCES↗

GIS-and Web-based Water Resource Geospatial Infrastructure for Oil Shale Development

The Colorado School of Mines (CSM) was awarded a grant by the National Energy Technology Laboratory (NETL), Department of Energy (DOE) to conduct a research project en- titled GIS- and Web-based Water Resource Geospatial Infrastructure for Oil Shale Development in October of 2008. The ultimate goal of this research project is to develop a water resource geo-spatial infrastructure that serves as “baseline data” for creating solutions on water resource management and for supporting decisions making on oil shale resource development. The project came to the end on September 30, 2012. This final project report will report the key findings from the project activity, major accomplishments, and expected impacts of the research. At meantime, the gamma version (also known as Version 4.0) of the geodatabase as well as other various deliverables stored on digital storage media will be send to the program manager at NETL, DOE via express mail. The key findings from the project activity include the quantitative spatial and temporal distribution of the water resource throughout the Piceance Basin, water consumption with respect to oil shale production, and data gaps identified. Major accomplishments of this project include the creation of a relational geodatabase, automated data processing scripts (Matlab) for database link with surface water and geological model, ArcGIS Model for hydrogeologic data processing for groundwater model input, a 3D geological model, surface water/groundwater models, energy resource development systems model, as well as a web-based geo-spatial infrastructure for data exploration, visualization and dissemination. This research will have broad impacts of the devel- opment of the oil shale resources in the US. The geodatabase provides a “baseline” data for fur- ther study of the oil shale development and identification of further data collection needs. The 3D geological model provides better understanding through data interpolation and visualization techniques of the Piceance Basin structure spatial distribution of the oil shale resources. The sur- face water/groundwater models quantify the water shortage and better understanding the spatial distribution of the available water resources. The energy resource development systems model reveals the phase shift of water usage and the oil shale production, which will facilitate better planning for oil shale development. Detailed descriptions about the key findings from the project activity, major accomplishments, and expected impacts of the research will be given in the sec- tion of “ACCOMPLISHMENTS, RESULTS, AND DISCUSSION” of this report.

04 OIL SHALES AND TAR SANDS↗

Energy Efficiency Finance Programs: Use Case Analysis to Define Data Needs and Guidelines

There are over 200 energy efficiency loan programs—across 49 U.S. states—administered by utilities, state/local government agencies, or private lenders.1 This distributed model has led to significant variation in program design and implementation practices including how data is collected and used. The challenge of consolidating and aggregating data across independently administered programs has been illustrated by a recent pilot of an open source database for energy efficiency financing program data. This project was led by the Environmental Defense Fund (EDF), the Investor Confidence Project, the Clean Energy Finance Center (CEFC), and the University of Chicago. This partnership discussed data collection practices with a number of existing energy efficiency loan programs and identified four programs that were suitable and willing to participate in the pilot database (Diamond 2014).2 The partnership collected information related to ~12,000 loans with an aggregate value of ~$100M across the four programs. Of the 95 data fields collected across the four programs, 30 fields were common between two or more programs and only seven data fields were common across all programs. The results of that pilot study illustrate the inconsistencies in current data definition and collection practices among energy efficiency finance programs and may contribute to certain barriers.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Developing a Power Plant Suitability Model for the Energy Zones Mapping Tool

This report provides an example of designing, developing, and running a power plant suitability model in the Energy Zones Mapping Tool (EZMT), a public, web-based mapping tool with a large spatial database focused on energy infrastructure, energy resources, and related siting factors. The example focuses on natural gas combined cycle (NGCC) power plants, which have several unique and interesting characteristics. NGCC plants typically provide peaking power to the electrical grid. Such plants can be started or stopped relatively quickly and are often used to supplement base load plants (such as nuclear or coal) during times of peak electrical consumption or to counterbalance lulls in variable power generation (such as wind or solar). Due to these and other factors, NGCC plants have been projected to increase in number under energy planning studies such as Hadley et al. The scope of the Hadley et. al. study is the Eastern Interconnection (EI), the electrical transmission grid serving much of the United States and Canada east of the Rocky Mountains. Results in the study are organized according to 22 Multi-region National—North American Electricity and Environment Model (NEEM) regions within the EI. NGCC plants usually have lower water requirements than other thermoelectric power plants they may replace; therefore, they are expected to have an interesting role in reducing the overall water requirements of energy generation.

20 FOSSIL-FUELED POWER PLANTS↗

Floating Offshore Wind US Manufacturing and Commercialization: Cooperative Research and Development (Final Report)

NREL assessed the supply chain and workforce considerations for the OCG-Wind floater technology, a floating semi-submersible offshore wind substructure, as well sharing vessel needs to inform their installation strategy. This technical assistance was in support of the FLoating Offshore Wind ReadINess (FLOWIN) Prize Phase 2 submission. NREL provided an assessment of domestic supplier capabilities for the main components of their floating offshore wind platform design and analyzed US regional and national supply chain constraints and gaps. Thirteen interviews with companies including steel distributors, forges, foundries, ports, large component fabricators, subcomponent fabricators, and secondary suppliers provided key insights such as 1) assembly ports are the key infrastructure barrier standing in the way of unlocking the domestic assembly and component fabrication for steel-based FOW platforms, 2) domestic steel producers can supply the types and quantities of steel necessary for FOW platforms, and 3) coordination between stakeholders will be a vital part of successfully developing the supply chain and infrastructure needed to domestically produce FOW platforms. In the workforce assessment, NREL documented a step-by-step approach to conduct a place-based assessment of the foundational workforce consideration for recruiting, upskilling, and retaining a workforce, such as supportive local and state policy, nearby education and training programs, and existing relevant industry. This approach was applied to Tacoma, Washington. Tacoma was indicated to have the potential be a successful location for fabrication and assembly of floating offshore wind energy in terms of workforce development. To share data on vessel requirements to install the OCG-Wind floater, NREL compiled resources that help answer the questions related to anchor handling tug vessels, shared a database of cable laying vessels, and answered questions on complying with the Jones Act.

17 WIND ENERGY↗

Solvent-Producing Clostridia Revisited

The review provides an overview of the current status of the solvent-producing clostridia. The origin and development of industrial clostridial species, as well as the history of the industrial Acetone Butanol Ethanol fermentation process, is reexamined, and the recent resurgence of interest in the production of biobutanol is reviewed. Over 300 fully sequenced genomes for solvent-producing and closely related clostridial species are currently available in public databases. These include 270 genomes sourced from the David Jones culture collection. These genomes were allocated arbitrary DJ codes, and a conversion table to identify the species and strains has now been provided. The expanded genomic database facilitated new comparative genomic and phylogenetic analysis. A synopsis of the common features, molecular taxonomy, and phylogeny of solvent-producing clostridia and the application of comparative phylogenomics are evaluated. A survey and analysis of resident prophages in solvent-producing clostridia are discussed, and the discovery, occurrence, and role of novel R-type tailocins are reported. Prophage genomes with R-type tailocin-like features were detected in all 12 species investigated. The widespread occurrence of tailocins in Gram-negative species is well documented; this survey has indicated that they may also be widespread in clostridia.

59 BASIC BIOLOGICAL SCIENCES↗

Participation in the TOMS Science Team

Because of the nominal funding provided by this grant, some of the relevant research is partially funded by other sources. Research performed for this funding period included the following items: We have investigated errors in TOMS ozone measurements caused by the uncertainty in wavelength calibration, coupled with the ozone cross sections in the Huggins bands and their temperature dependence. Preliminary results show that 0.1 nm uncertainty in TOMS wavelength calibration at the ozone active wavelengths corresponds to approx. 1% systematic error in O3, and thus potential 1% biases among ozone trends from the various TOMS instruments. This conclusion will be revised for absolute O3 Measurements as cross sections are further investigated for inclusion in the HITRAN database at the SAO, but the potential for relative errors remains. In order to aid further comparisons among TOMS and GOME ozone measurements, we have implemented our method of direct fitting of GOME radiances (BOAS) for O3, and now obtain the best fitting precision to date for GOME O3 Columns. This will aid in future comparisons of the actual quantities measured and fitted for the two instrument types. We have made comparisons between GOME ICFA cloud fraction and cloud fraction determined from GOME data using the Ring effect in the Ca II lines. There is a strong correlation, as expected, but there are substantial systematic biases between the determinations. This study will be refined in the near future using the recently-developed GOME Cloud Retrieval Algorithm (GOMECAT). We have improved the SAO Ring effect determination to include better convolution with instrument transfer functions and inclusion of interferences by atmospheric absorbers (e.g., O3). This has been made available to the general community.

Chance, Kelly↗

Livewire User Guide

The Livewire Data Platform houses a catalog of transportation- and mobility-related project data, as well as a publications database, making it easy to search and share data. It allows transportation researchers, industry, and academic partners to increase the visibility of their projects within the research community, securely share and preserve data, and leverage datasets from other projects. Public data on Livewire are open to anyone with a Livewire account. This guide will help Livewire users understand how to store project data as a data steward, as well as access data as a data consumer.

33 ADVANCED PROPULSION SYSTEMS↗

Summary Report for the SINBAD Search Tool Project

The Shielding Integral Benchmark Archive Database (SINBAD) Search Tool has been developed to serve as an interface with the SINBAD database to facilitate a simple and quick means of searching for information related to experimental benchmark problems. The Search Tool is written in Java and provides a better and efficient way to retrieve information from the SINBAD database. Searches can be performed quickly and easily. With regard to improvements, users are no longer required to know the name of the benchmarks to search the database. Instead, a search can be performed by specifying the experimental facility, constituents of the experimental benchmark, etc. In summary, a new powerful database search tool has been developed for SINBAD.

Cunha Da Silva, Alice↗