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At least 307 records · Page 17

SQL and NoSQL Databases for Cyber Physical Production Systems in Internet of Things for Manufacturing (IoTfM)

Abstract In this paper, the design and performance differences between Relational Database Management Systems (RDBMS) and NoSQL Database Systems are examined, with attention to their applicability for real-world Internet of Things for manufacturing (IoTfM) data. While previous work has extensively compared SQL and NoSQL for both generalized and IoT uses, this work specifically examines the tradeoffs and performance differences for manufacturing applications by using a high-fidelity data set collected from a large US manufacturing firm. Growing an IoT system beyond the pilot stage requires scalable data storage; this work seeks to determine the impact of selected database systems on data write performance at scale. Payload size and message frequency were used as the primary characteristics to maintain model fidelity in simulated clients. As the number of simulated asset clients grow, the data write latency was calculated to determine how both database systems’ performance were affected. To isolate the RDBMS and NoSQL differences, a cloud environment was created using Amazon Web Services (AWS) with two identical data ingestion pipelines: writing data to an RDMBS (1) using AWS Aurora MySQL, and (2) using AWS DynamoDB NoSQL. The findings may provide guidance for further experimentation in large-scale manufacturing IoT implementations.

Gamero, David↗

SU-E-J-129: A Strategy to Consolidate the Image Database of a VERO Unit Into a Radiotherapy Management System

Purpose: To present a strategy to integrate the imaging database of a VERO unit with a treatment management system (TMS) to improve clinical workflow and consolidate image data to facilitate clinical quality control and documentation. Methods: A VERO unit is equipped with both kV and MV imaging capabilities for IGRT treatments. It has its own imaging database behind a firewall. It has been a challenge to transfer images on this unit to a TMS in a radiation therapy clinic so that registered images can be reviewed remotely with an approval or rejection record. In this study, a software system, iPump-VERO, was developed to connect VERO and a TMS in our clinic. The patient database folder on the VERO unit was mapped to a read-only folder on a file server outside VERO firewall. The application runs on a regular computer with the read access to the patient database folder. It finds the latest registered images and fuses them in one of six predefined patterns before sends them via DICOM connection to the TMS. The residual image registration errors will be overlaid on the fused image to facilitate image review. Results: The fused images of either registered kV planar images or CBCT images are fully DICOM compatible. A sentinel module is built to sense new registered images with negligible computing resources from the VERO ExacTrac imaging computer. It takes a few seconds to fuse registered images and send them to the TMS. The whole process is automated without any human intervention. Conclusion: Transferring images in DICOM connection is the easiest way to consolidate images of various sources in your TMS. Technically the attending does not have to go to the VERO treatment console to review image registration prior delivery. It is a useful tool for a busy clinic with a VERO unit.

60 APPLIED LIFE SCIENCES↗

SU-D-BRB-02: Combining a Commercial Autoplanning Engine with Database Dose Predictions to Further Improve Plan Quality

Purpose: Database dose predictions and a commercial autoplanning engine both improve treatment plan quality in different but complimentary ways. The combination of these planning techniques is hypothesized to further improve plan quality. Methods: Four treatment plans were generated for each of 10 head and neck (HN) and 10 prostate cancer patients, including Plan-A: traditional IMRT optimization using clinically relevant default objectives; Plan-B: traditional IMRT optimization using database dose predictions; Plan-C: autoplanning using default objectives; and Plan-D: autoplanning using database dose predictions. One optimization was used for each planning method. Dose distributions were normalized to 95% of the planning target volume (prostate: 8000 cGy; HN: 7000 cGy). Objectives used in plan optimization and analysis were the larynx (25%, 50%, 90%), left and right parotid glands (50%, 85%), spinal cord (0%, 50%), rectum and bladder (0%, 20%, 50%, 80%), and left and right femoral heads (0%, 70%). Results: All objectives except larynx 25% and 50% resulted in statistically significant differences between plans (Friedman’s χ{sup 2} ≥ 11.2; p ≤ 0.011). Maximum dose to the rectum (Plans A-D: 8328, 8395, 8489, 8537 cGy) and bladder (Plans A-D: 8403, 8448, 8527, 8569 cGy) were significantly increased. All other significant differences reflected a decrease in dose. Plans B-D were significantly different from Plan-A for 3, 17, and 19 objectives, respectively. Plans C-D were also significantly different from Plan-B for 8 and 13 objectives, respectively. In one case (cord 50%), Plan-D provided significantly lower dose than plan C (p = 0.003). Conclusion: Combining database dose predictions with a commercial autoplanning engine resulted in significant plan quality differences for the greatest number of objectives. This translated to plan quality improvements in most cases, although special care may be needed for maximum dose constraints. Further evaluation is warranted in a larger cohort across HN, prostate, and other treatment sites. This work is supported by Philips Radiation Oncology Systems.

60 APPLIED LIFE SCIENCES↗

Databases for Microbiologists

Databases play an increasingly important role in biology. They archive, store, maintain, and share information on genes, genomes, expression data, protein sequences and structures, metabolites and reactions, interactions, and pathways. All these data are critically important to microbiologists. Furthermore, microbiology has its own databases that deal with model microorganisms, microbial diversity, physiology, and pathogenesis. Thousands of biological databases are currently available, and it becomes increasingly difficult to keep up with their development. Finally, the purpose of this minireview is to provide a brief survey of current databases that are of interest to microbiologists.

59 BASIC BIOLOGICAL SCIENCES↗

PV Shading Database [SWR-16-36]

The software is a simplified method for modeling the impact of arbitrary partial shading conditions on PV array performance. The software implements a simple method for modeling shade loss: a database of shade impact results (loss percentages), generated using a validated, detailed simulation tool and encompassing a wide variety of shading scenarios. The database is intended to predict shading losses in crystalline silicon PV arrays and is accessed using basic inputs generally available in any PV simulation tool. Performance predictions using the database are within 1-2% of measured data for several partially shaded PV systems, and within 1% of those predicted by the full, detailed simulation tool on an annual basis. The shade loss database shows potential to considerably improve performance prediction for partially shaded PV systems.

Janzou, Steven↗

The Pan-Arctic Vegetation Cover (PAVC) database v1.1

The Pan-Arctic Vegetation Cover (PAVC) database contains synthesized field-data observations of vegetation cover from 978 Arctic Alaska plots with observations from 2010 to 2021. The cover datasets contain plot data at both the plant functional type (PFT) and species-level resolution, with standardized PFT definitions and species names. We synthesized publicly available point-intercept and visual estimate plots from the Arctic Vegetation Archive of Alaska, the Alaska Vegetation Plots Database, the North Slope Science Catalog, and the National Ecological Observatory Network; as well as previously unpublished data from the Next-Generation Ecosystem Experiments: Arctic (NGEE Arctic).Users will find four synthesized datasets, 4 associated data descriptor (dd) files, and 1 metadata file in the PAVC database:synthesized_species_fcover.csv contains fractional cover (fcover) for unique accepted species names, where names include vegetation identified at the family, genus, species, subspecies, and variety levels, as well as general functional types across all 5 data sources. The synthesized_species_fcover_dd.csv accompanies this dataset with header information.synthesized_pft_fcover.csv contains fcover for the following PFTs: non-vascular plants with lichen and bryophyte subcategories, trees with deciduous and evergreen subcategories, shrubs with deciduous and evergreen subcategories, graminoids (grasses), and forbs (herbaceous flowering plants) measured as total cover. Litter and “other” cover are also included as total cover. Additional “types” include water and bare ground, which were measured as top cover. The synthesized_pft_fcover_dd.csv accompanies this dataset with header information.species_pft_checklist.csv is a lookup table containing the translation from a dataset species name to an accepted species name and to a PFT. This table can be used to clarify our species to PFT adjudications, and to aid users in assigning their own PFTs. Any issues found in this checklist should be reported in the Issues tab of our github.survey_unit_information.csv contains auxiliary information about the plots synthesized in this database. It contains useful information for filtering plots of interest based on temporal, geospatial, and contextual information about the plot surveys.flmd.csv contains metadata information about each file in the database.This research was performed as a part of the NGEE Arctic project. The NGEE Arctic project was a research effort to reduce uncertainty in Earth System Models by developing a predictive understanding of carbon-rich Arctic ecosystems and feedbacks to climate. NGEE Arctic was supported by the Department of Energy's Office of Biological and Environmental Research.The NGEE Arctic project had two field research sites: 1) located within the Arctic polygonal tundra coastal region on the Barrow Environmental Observatory (BEO) and the North Slope near Utqiagvik (Barrow), Alaska and 2) multiple areas on the discontinuous permafrost region of the Seward Peninsula north of Nome, Alaska.Through observations, experiments, and synthesis with existing datasets, NGEE Arctic provided an enhanced knowledge base for multi-scale modeling and contributed to improved process representation at global pan-Arctic scales within the Department of Energy's Earth system Model (the Energy Exascale Earth System Model, or E3SM), and specifically within the E3SM Land Model component (ELM).

54 ENVIRONMENTAL SCIENCES↗

Global Oil & Gas Infrastructure Features Database EDX Spatial Web Map

This submission offers a link to a web mapping application hosted instance of the Global Oil & Gas Features Database (GOGI), via EDX Spatial. This offers users with the ability to visualize, interact, and create maps with data of their choice, as well as download specific attributes or fields of view from the database. This data can also be downloaded as a File Geodatabse from EDX at https://edx.netl.doe.gov/dataset/global-oil-gas-features-database. Access the technical report describing how this database was produced using the following link: https://edx.netl.doe.gov/dataset/development-of-an-open-global-oil-and-gas-infrastructure-inventory-and-geodatabase” This data was developed using a combination of big data computing, custom search and data integration algorithms, and expert driven search to collect open oil and gas data resources worldwide. This approach identified over 380 data sets and integrated more than 4.8 million features into the GOGI database. Acknowledgements: This work was funded under the Climate and Clean Air Coalition (CCAC) Oil and Gas Methane Science Studies. The studies are managed by United Nations Environment in collaboration with the Office of the Chief Scientist, Steven Hamburg of the Environmental Defense Fund. Funding was provided by the Environmental Defense Fund, OGCI Companies (Shell, BP, ENI, Petrobras, Repsol, Total, Equinor, CNPC, Saudi Aramco, Exxon, Oxy, Chevron, Pemex) and CCAC.

gas↗

Energy-Community-Geo-Database

Fundamental to understanding evolving infrastructure and technology is understanding the drivers for energy communities that affect where and how infrastructure is placed and used. An Energy Community Geo Database aligned to carbon storage systems will aid stakeholders in decision making around key future infrastructure (e.g., CCS injection locations) placement while helping contextualize these analyses against past and present-day social and environmental attributes. Much of the data required to support analyses are available from authoritative, largely governmental sources, but at present are disparate and require time-consuming acquisition, integration, and upkeep for currency. The CCS-EC-GB v2.0 integrates datasets from various federal agencies and authoritative sources to aid stakeholders and decision makers of the social and environmental factors that might impact the viability of CCS and energy related project implementation. There are 5 categories in the CCS-EC-GB v2 database. Most of the layers within each category have been updated in this version. As compared to the old database, there is 1 new category in the CCS-EC-GB v2 database: infrastructure. This is an evolving project and application will be updated periodically with new datasets and information. Notes for consideration: This database/web map will be updated with additional as new data and information becomes available and has been processed, reviewed, and approved for release. Additional state and federal entity data are planned to be integrated and included in future revisions. Summary layers provided in this application are derived from proprietary layers and do not always contain key features (age, status, or TVD) and therefore might not be shown when data are queried for those features.

CCS,Carbon capture and storage,Carbon storage,U.S.↗

Prospective Seal Unit Spatial Extent Database for U.S. Sedimentary Basins

The Prospective Seal Unit Spatial Extent Database for U.S. Sedimentary Basins contains a series of spatial datasets representing spatial extents of publicly available data for caprock and seal rock units within the Appalachian Basin, Denver-Julesburg Basin, Great Valley Basin (Sacramento and San Joaquin Basins), Illinois Basin, Michigan Basin, San Juan Basin, U.S. Gulf Coast Basin, and Williston Basin. The database is designed to support carbon storage feasibility and resources assessment for carbon transport and storage (CTS) projects while displaying the spatial extent of prospective seal units and provide a guide to the original data source. This database leverages publicly available data resources from authoritative sources (e.g. U.S. Geological Survey, State Geologic Surveys, and published reports), and aims to help guide users to understand the seal unit's spatial coverage and data gaps from the regional to sub-basin/field scale. The database is organized by seal unit/formation, including the spatial extent for data found to be available for the seal unit. The various datasets represented include spatial extents of the lithologic formation, depth to top structural contour maps, and thickness/isopach maps. Included in this submission are the following resources: 1. Geodatabase/Dataset: “prospective-seal-unit-extents-2025.gdb” 2. ReadMe: “readme-prospective-seal-unit-spatial-extent-dataset-2025.pdf” 3. Data Catalog: “prospective-seal-unit-spatial-extents-data-catalog-2025.xlsx” 4. Data Sources Key: “data-source.csv” Please see NETL disclaimers here: https://netl.doe.gov/home/disclaimer

Basin↗

Development and Demonstration of Material Properties Database and Software for the Simulation of Flow Properties in Cementitious Materials

This report describes work performed by the Savannah River National Laboratory (SRNL) in fiscal year 2014 to develop a new Cementitious Barriers Project (CBP) software module designated as FLOExcel. FLOExcel incorporates a uniform database to capture material characterization data and a GoldSim model to define flow properties for both intact and fractured cementitious materials and estimate Darcy velocity based on specified hydraulic head gradient and matric tension. The software module includes hydraulic parameters for intact cementitious and granular materials in the database and a standalone GoldSim framework to manipulate the data. The database will be updated with new data as it comes available. The software module will later be integrated into the next release of the CBP Toolbox, Version 3.0. This report documents the development efforts for this software module. The FY14 activities described in this report focused on the following two items that form the FLOExcel package; 1) Development of a uniform database to capture CBP data for cementitious materials. In particular, the inclusion and use of hydraulic properties of the materials are emphasized; and 2) Development of algorithms and a GoldSim User Interface to calculate hydraulic flow properties of degraded and fractured cementitious materials. Hydraulic properties are required in a simulation of flow through cementitious materials such as Saltstone, waste tank fill grout, and concrete barriers. At SRNL these simulations have been performed using the PORFLOW code as part of Performance Assessments for salt waste disposal and waste tank closure.

97 MATHEMATICS AND COMPUTING↗

WMC Database Evaluation. Case Study Report

The WMC Database is ultimately envisioned to hold a collection of experimental data, design information, and information from computational models. This project was a first attempt at using the Database to access experimental data and extract information from it. This evaluation shows that the Database concept is sound and robust, and that the Database, once fully populated, should remain eminently usable for future researchers.

96 KNOWLEDGE MANAGEMENT AND PRESERVATION↗

Database Performance Monitoring for the Photovoltaic Systems

The Database Performance Monitoring (DPM) software (copyright in processes) is being developed at Sandia National Laboratories to perform quality control analysis on time series data. The software loads time indexed databases (currently csv format), performs a series of quality control tests defined by the user, and creates reports which include summary statistics, tables, and graphics. DPM can be setup to run on an automated schedule defined by the user. For example, the software can be run once per day to analyze data collected on the previous day. HTML formatted reports can be sent via email or hosted on a website. To compare performance of several databases, summary statistics and graphics can be gathered in a dashboard view which links to detailed reporting information for each database. The software can be customized for specific applications.

97 MATHEMATICS AND COMPUTING↗

Database on Performance of Neutron Irradiated FeCrAl Alloys

The present report summarizes and discusses the database on radiation tolerance for Generation I, Generation II, and commercial FeCrAl alloys. This database has been built upon mechanical testing and microstructural characterization on selected alloys irradiated within the High Flux Isotope Reactor (HFIR) at Oak Ridge National Laboratory (ORNL) up to doses of 13.8 dpa at temperatures ranging from 200°C to 550°C. The structure and performance of these irradiated alloys were characterized using advanced microstructural characterization techniques and mechanical testing. The primary objective of developing this database is to enhance the rapid development of a mechanistic understanding on the radiation tolerance of FeCrAl alloys, thereby enabling informed decisions on the optimization of composition and microstructure of FeCrAl alloys for application as an accident tolerant fuel (ATF) cladding. This report is structured to provide a brief summary of critical results related to the database on radiation tolerance of FeCrAl alloys.

36 MATERIALS SCIENCE↗

FIPD: EBR-II Fuels Irradiation & Physics Database

The DOE Advanced Reactor Technology program has supported efforts to recover and preserve metallic fuel data generated throughout the US sodium cooled fast reactor program (SFR). Those efforts have been focused on establishing databases of the experimental data that were mainly generated during the Integral Fast Reactor program including data generated at EBR-II, FFTF, and TREAT reactors, as well as out of pile data. The data is essential for future-licensing activities of metallic fuel based advanced fast reactors. This report describes the EBR-II Fuels Irradiation & Physics Database (FIPD). It covers the scientific knowledge available in the database, the logical storage of the data in the database, and the web interface used to access the data. The report also covers the QA plan (SQAPP) developed to cover all aspects of the FIPD system. Summaries of activities from previous years, the current fiscal year (FY17), and future plans are also provided.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

M4SF-19LL010301042: Code Development in Support of the SFWST Thermodynamic Database

This progress report (Level 4 Milestone Number M4SF-19LL010301042) summarizes research conducted at Lawrence Livermore National Laboratory (LLNL) within the Argillite Activity Number SF-19LL010301041. LLNL is leading efforts in the development of thermodynamic databases in support of the Spent Fuel and Waste and Science Technology (SFWST) program. Thermodynamic models provide the basis for understanding the stability of solid phases and speciation of aqueous species and modeling the evolution of repository conditions. The LLNL effort is being performed in coordination with other US database development efforts. The effort includes a review of available thermochemical databases and a path forward for database integration. International coordination with the NEA-TDB is supported through crystalline international work package

38 RADIATION CHEMISTRY, RADIOCHEMISTRY, AND NUCLEA↗

M4SF-20LL010301042: Updated Thermodynamic Database for Use in Generic Disposal System Assessment

This progress report (Level 4 Milestone Number M4SF-20LL010301042) summarizes research conducted at Lawrence Livermore National Laboratory (LLNL) within the Argillite Activity Number SF-20LL010301041. LLNL is leading efforts in the development of thermodynamic databases in support of the Spent Fuel and Waste Science Technology (SFWST) program. Thermodynamic models provide the basis for understanding the stability of solid phases and speciation of aqueous species and modeling the evolution of repository conditions. The LLNL effort is being performed in coordination with other US database development efforts. The effort includes a review of available thermochemical databases and a path forward for database integration. International coordination with the NEA-TDB is supported through crystalline international work package.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

Summary Report for Out-of-Pile Transient Testing Database Development

The DOE Advanced Reactor Technology program has supported knowledge preservation efforts to recover and preserve fuel data from the US sodium cooled fast reactor (SFR) program. Efforts have focused on establishing databases of experimental data generated during the Integral Fast Reactor program (at EBR-II, FFTF, and TREAT) as well as during related out-of-pile examinations of the fuel irradiated at EBR-II. The information in these databases is essential to support further development and licensing activities for advanced fast reactor designs. OPTD is a database of out-of-pile furnace transient tests on metallic fuel. It includes records of 62 tests on irradiated fuel pins conducted in furnace apparatuses constructed in the Alpha-Gamma Hot Cell Facility at ANL. This report describes efforts during FY19 to improve visibility and access, expand the content of, and improve the user experience with the FIPD and OPTD databases.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

SUPCRTNE Thermodynamic Database Engine

This progress report (Level 4 Milestone Number M4SF-21LL010301052) summarizes research conducted at Lawrence Livermore National Laboratory (LLNL) within the Argillite Activity Number SF-21LL01030105. LLNL is leading efforts in the development of thermodynamic databases in support of the Spent Fuel and Waste Science Technology (SFWST) program. Thermodynamic models provide the basis for understanding the stability of solid phases and speciation of aqueous species and modeling the evolution of repository conditions. The LLNL effort is being performed in coordination with other US database development efforts. The effort includes a review of available thermochemical databases and a path forward for database integration. International coordination with the NEA-TDB is supported through crystalline international work package.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗