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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 253 records · Page 14
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

CORAL: A framework for rigorous self-validated data modeling and integrative, reproducible data analysis

Abstract Background Many organizations face challenges in managing and analyzing data, especially when relevant datasets arise from multiple sources and methods. Analyzing heterogeneous datasets and additional derived data requires rigorous tracking of their interrelationships and provenance. This task has long been a Grand Challenge of data science and has more recently been formalized in the FAIR principles: that all data objects be Findable, Accessible, Interoperable, and Reusable, both for machines and for people. Adherence to these principles is necessary for proper stewardship of information, for testing regulatory compliance, for measuring the efficiency of processes, and for facilitating reuse of data-analytical frameworks. Findings We present the Contextual Ontology-based Repository Analysis Library (CORAL), a platform that greatly facilitates adherence to all 4 of the FAIR principles, including the especially difficult challenge of making heterogeneous datasets Interoperable and Reusable across all parts of a large, long-lasting organization. To achieve this, CORAL's data model requires that data generators extensively document the context for all data, and our tools maintain that context throughout the entire analysis pipeline. CORAL also features a web interface for data generators to upload and explore data, as well as a Jupyter notebook interface for data analysts, both backed by a common API. Conclusions CORAL enables organizations to build FAIR data types on the fly as they are needed, avoiding the expense of bespoke data modeling. CORAL provides a uniquely powerful platform to enable integrative cross-dataset analyses, generating deeper insights than are possible using traditional analysis tools.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2019

Residual Optically Stimulated Luminescent (OSL) Signals for Al 2 O 3 :C and a Readout System with Reproducible Partial Signal Clearance

Optically stimulated luminescent dosimeters (OSLDs) are devices that, when stimulated with light, emit light in proportion to the integrated ionizing radiation dose. The stimulation of OSL material results in the loss of a small fraction of signal stored within the dosimetric traps. Previous studies have investigated the signal loss due to readout stimulation, and the optical annealing of OSLDs. This study builds on former research by examining the behavior of OSL signal after annealing, exploring the functionality of a previously developed signal loss model, and comparing uncertainties for dosimeters reused with or without annealing. For a completely annealed dosimeter, the minimum signal level was 56 ± 8 counts, and readings followed a Gaussian distribution. For dosimeters above this signal level, the fractional signal loss due to the reading process has a linear relationship with the calculated signal. At low signal levels (below 20,000 counts), in this OSLD system,calculated signal percent errors increase significantly but otherwise are on average 0.72 ± 0.27%, 0.40 ± 0.19%, 0.33±0.12%, and 0.24±0.07% for 30, 75, 150, and 300 readings. Theoretical calculations of uncertainties showed that annealing before reusing dosimeters allows for dose errors below 1% with as few as 30 readings. Reusing dosimeters multiple times increases the dose errors especially with low numbers of readouts, so theoretically around 300 readings would be necessary to achieve errors around 1% or below in most scenarios. Note that these dose errors do not include the error associated with the signal-to-dose conversion factor.

61 RADIATION PROTECTION AND DOSIMETRY↗
DOE OSTI2020

Reproducing the 'Framing' by a Sequential Stress Test

The 'Framing' (local discoloration along cell edges) was induced by a simple sequential accelerated stress test (consisting of hygrothermal- and UV-stressors) applied to the PV modules with high OTR (oxygen transmission rate) backsheet, irrespective of the inclusion of UV-absorber in poly(ethylene-co-vinyl acetate) (EVA) encapsulant. UV-fluorescence imaging of the PV modules suggests that the spatially-inhomogeneous degradation of EVA material under UV-irradiating conditions is correlated to this 'Framing' indicating an underlying common mechanism. These findings would contribute to the development of test procedures to broadly mimic the actual failures observed in fielded PV.

14 SOLAR ENERGY↗
DOE OSTI2023

A Reproducible Validation of Algorithms for Estimating Array Tilt and Azimuth from Photovoltaic Power Time Series

In this research, we assess the viability of four different, publicly available algorithms for estimating the azimuth and tilt parameters of solar photovoltaic systems using only the associated AC power time series data and site latitude-longitude coordinates. In this work, we curated a benchmarking data set of 44 fixed-tilt systems, comprising 275 measured AC power inverter data streams, with known azimuth and tilt parameters. Additionally, we isolated test cases in the data set with real- world issues, including shading and clipping, to determine how algorithm performance varies based on the presence of these phenomena. Using this data set for benchmarking, we evaluated the estimated vs. actual system characteristics for each algorithm, as well as the associated algorithm execution time using a standardized benchmarking process. The two highest performing algorithms were the Solar Data Tools and the PVWatts 5- based methods, which both achieved a median absolute error of approximately 5 and 1 degrees for azimuth and tilt, respectively. During run time analysis, the SDT method was approximately 5 times faster than the PVWatts 5-based method, with the median execution time for a stream varying between 6 and 8 seconds vs. a median run time of 31 seconds for the PVWatts 5-based method.

azimuth↗
DOE OSTI2020

Role of consistent terminology in XPS reproducibility

The use of inconsistent and incorrect terminology in scientific publications contributes to misunderstanding, confusion, and erroneous results in the scientific literature. This issue is of particular importance in x-ray photoelectron spectroscopy (XPS) that is in widespread use for many different purposes by scientists with diverse backgrounds. A set of surface analysis terminology, approved through consensus by international experts, has been developed by International Organization for Standardization Technical Committee TC201 on Surface Chemical Analysis. To encourage wide use, the terminology is accessible at several web sites free of charge. This short overview provides examples to highlight the importance of agreed terminology in eliminating confusion between similar terms. Examples are provided of terms that are commonly misused or confused in the literature. Other examples highlight terminology that provides a common basis for comparing instrument parameters and performance. As science advances, it is important to clarify terminology for describing evolving concepts and developments important to XPS.

96 KNOWLEDGE MANAGEMENT AND PRESERVATION↗
DOE OSTI2019

Future-Proofing Your Microbiology Resource Announcements Genome Assembly for Reproducibility and Clarity

Descriptions of resources, like the genome assemblies reported in Microbiology Resource Announcements , are often frozen at their time of publication, yet they will need to be interpreted in the midst of continually evolving technologies. It is therefore important to ensure that researchers accessing published resources have access to all of the information required to repeat, interpret, and extend these original analyses. Here, we provide a set of suggestions to help make certain that published resources remain useful and repeatable for the foreseeable future.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

Provenance infrastructure for multimodal x-ray experiments and reproducible analysis

Exploring relationships between material structures and desired properties for material discovery and synthesis requires mining machine-readable databases and linking experimental data with sufficiently rich annotations. There are vast gaps both in these data sources and in the connections between them. We present a provenance-based data management and analysis framework that enables capturing, persisting, and reanalyzing experimental data from the BNL National Synchrotron Light Source II (NSLS-II). Our system leverages NSLS-II Bluesky for experimental data acquisition, captures analysis parameters, and enriches the search space with results from the scientific literature. We describe in detail the challenges and benefits of data-driven approaches when comparing computational and experimental data, such as the multiple possible scenarios of interest in often ill-posed inverse problems and missing data. Our infrastructure utilizes the NSLS-II event model and includes discovery mechanisms across multiple beamlines. A text and data mining module using natural language processing classification techniques extracts relevant information from the literature that is added to data sources. We describe a provenance acquisition and analysis rerun workflow based on a directed acyclic graph that keeps track of process and data provenance and allows to replay analysis.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

Performance of Convection-Permitting and Convection-Parameterized Models in Reproducing the Extreme Precipitation Intensity Relationship with Surface Conditions

Here, this study investigates the warm-season extreme precipitation–temperature scaling relationship in CONUS404, a convection-permitting (4 km) Weather Research and Forecasting (WRF) Model simulation over the conterminous United States for the past four decades, and compares it with the WRF-Thermodynamic Global Warming (WRF-TGW) historical simulation at a coarser resolution (12 km) using parameterized convection. We also analyze the NCEP stage IV and NASA Integrated Multi-satellitE Retrievals for the Global Precipitation Measurement (IMERG) datasets as observational benchmarks. We examine how extreme precipitation intensity (EPI) varies with temperature and saturation deficit over representative regions based on hourly data. The stage IV and IMERG data show a similar pattern of EPI variation with temperature and saturation deficit, except that the EPI peak is lower in IMERG than in stage IV. Under dry and hot conditions, EPI decreases too rapidly with elevated saturation deficit in both CONUS404 and WRF-TGW compared to observations, but the performance of CONUS404 is superior to WRF-TGW. When the near-surface atmosphere is saturated or close to saturated, both CONUS404 and WRF-TGW produce higher peak values of EPI relative to the observational references; IMERG exhibits scaling rates close to the Clausius–Clapeyron (C–C) relationship, while CONUS404, WRF-TGW, and stage IV all demonstrate super-C–C scaling behaviors. Despite marked warming over the past four decades, in both CONUS404 and WRF-TGW, the scaling relationship between EPI and temperature in a saturated atmosphere remains stable and robust. This indicates a strong potential for the EPI–temperature scaling rate under saturation to be used as an emergent constraint in reducing uncertainties of future extreme precipitation projection.

Atmosphere↗
DOE OSTI2018

End-to-end Provenance Traceability and Reproducibility Through "Palletized'' Simulation Data

Trusting simulation output is crucial for Sandia's mission objectives. We rely on these simulations to perform our high-consequence mission tasks given our treaty obligations. Other science and modelling needs, while they may not be high-consequence, still require the strongest levels of trust to enable using the result as the foundation for both practical applications and future research. To this end, the computing community has developed work- flow and provenance systems to aid in both automating simulation and modelling execution, but to also aid in determining exactly how was some output created so that conclusions can be drawn from the data. Current approaches for workflows and provenance systems are all at the user level and have little to no system level support making them fragile, difficult to use, and incomplete solutions. The introduction of container technology is a first step towards encapsulating and tracking artifacts used in creating data and resulting insights, but their current implementation is focused solely on making it easy to deploy an application in an isolated "sandbox" and maintaining a strictly read-only mode to avoid any potential changes to the application. All storage activities are still using the system-level shared storage. This project was an initial exploration into extending the container concept to also include storage and to use writeable containers, auto generated by the system, as a way to link the contained data back to the simulation and input deck used to create it.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2018

End-to-end Provenance Traceability and Reproducibility Through "Palletized'' Simulation Data

Trusting simulation output is crucial for Sandia's mission objectives. We rely on these simulations to perform our high-consequence mission tasks given our treaty obligations. Other science and modelling needs, while they may not be high-consequence, still require the strongest levels of trust to enable using the result as the foundation for both practical applications and future research. To this end, the computing community has developed work- flow and provenance systems to aid in both automating simulation and modelling execution, but to also aid in determining exactly how was some output created so that conclusions can be drawn from the data. Current approaches for workflows and provenance systems are all at the user level and have little to no system level support making them fragile, difficult to use, and incomplete solutions. The introduction of container technology is a first step towards encapsulating and tracking artifacts used in creating data and resulting insights, but their current implementation is focused solely on making it easy to deploy an application in an isolated "sandbox" and maintaining a strictly read-only mode to avoid any potential changes to the application. All storage activities are still using the system-level shared storage. This project was an initial exploration into extending the container concept to also include storage and to use writable containers, auto generated by the system, as a way to link the contained data back to the simulation and input deck used to create it.

97 MATHEMATICS AND COMPUTING↗