Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “Anonymization”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 109 records · Page 6
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Analysis of Dust Samples Collected from a Near-Marine East Coast ISFSI Site ("Site C")

In June of 2022, dust samples were collected from the surface of an in-service spent nuclear fuel dry storage canister during an inspection at an Independent Spent Fuel Storage Installation. The site is anonymous but is a near-marine or brackish water east coast location referred to here as "Site C". The purpose of the sampling was to assess the composition and abundance of the soluble salts present on the canister surface, information that provides a metric for potential corrosion risks. Following collection, the samples were delivered to Sandia National Laboratories for analysis. At Sandia, the soluble salts were leached from the dust and quantified by ion chromatography. In addition, subsamples of the dust were taken for scanning electron microscopy to determine the particle sizes, morphology, and mineralogy of the dust and salts. The results of those analyses are presented in this report.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2022

SARS-CoV-2 transmission control in California correctional facilities

LBNL provided technical assistance to the CalPROTECT project, which is a collaboration between the University of California, Berkeley and the University of California, San Francisco. The CalPORTECT team provided support and guidance to the California Department of Corrections and Rehabilitation (CDCR) and the California Correctional Health Care Services (CCHCS) in their response to the COVID-19 pandemic. The CalPROTECT team provided recommendations to mitigate the risk posed to the residents and staff who live and work in CDCR prisons through considering scientific knowledge of the virus, analyzing anonymized resident and staff level data from CCHCS, evaluation of statewide and institution-level policies, and data collection during site visits to CDCR prisons during the pandemic.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

Assessment of BQ-9000 Biodiesel Properties for 2022

This is the sixth in a series of reports documenting the quality of biodiesel from U.S. and Canadian-based producers that participate in the BQ-9000 program, the biodiesel industry voluntary quality assurance program. Participants agreed to provide monthly data on critical quality parameters for calendar year 2022. The quality data was provided to a team of experts, who removed any identifying company information and provided anonymized data to the National Renewable Energy Laboratory (NREL) for statistical analysis.

09 BIOMASS FUELS↗
DOE OSTI2024

Availability and Performance Loss Factors for U.S. PV Fleet Systems

In the PV Fleet Performance Data Initiative, we partner with photovoltaic (PV) fleet owners to collect time-series PV production data and publish aggregated, anonymized results. This report is an update of our previous publications, specifically a FY 2021 performance index publication and a FY 2022 fleet degradation analysis. In this analysis, we have increased our data participants and system totals by around 10% to 8.5 GW and 24,000 separate inverter data channels. Four major analysis topics are considered in this report: Performance Index (PI) trends, PV system availability, soiling losses, and PV system degradation. Performance Index and inverter availability are assessed on a larger set of data from our FY 2021 report: 1,128 systems compared with 200 systems from before. The increased number of systems is due to an improved data quality methodology, as well as introducing new systems to the analysis. Overall results are similar to previously published values - overall inverter availability is low in the first six months of system performance before reaching steady-state by the end of the first year. Excluding this six-month startup period, system-level aggregated data shows a median (P50) system availability of 0.99 and a lower 10th percentile (P90) value of 0.95 (Figure ES-1). A dependence on system size is also demonstrated, with worse inverter availability results for larger PV systems. Causes of this effect are under investigation, but may be impacted by inverter size, which also show lower availability for larger inverter sizes. This report also investigates PI, correcting for degradation, soiling, snow, and availability. Following these corrections, the median system PI over its entire lifetime is 0.95. PI values reported here are approximately 3% lower than what we presented in our previous FY 2021 report. Soiling loss is assessed in a comprehensive way for the first time in this report. Results are presented using the COmbined Degradation and Soiling (CODS) method, as implemented in RdTools (v3.0.0a4). Soiling values are presented for 255 systems, which indicated irradiance-weighted soiling loss greater than 1%. The values have been published in an updated NREL soiling map at nrel.gov/pv/soiling.html. Finally, we investigated system degradation using three different data analysis techniques: conventional RdTools (year-on-year (YOY)), CODS, and Performance Loss Rate (PLR) analysis. Overall degradation results are consistent with our previous publications. Rerunning conventional RdTools on our updated fleet shows that some data partners have systematically fallen below the median system degradation rate (change over time) of -0.75 %/year. A comparison with PLR analysis, which looks at change in annual PI over time, shows that median system degradation is consistent with -0.5% to -0.75% per year change. However, at the P90 value, system degradation is substantially faster. These two results are consistent and indicate that resulting degradation statistics depend to a great degree on the population of PV systems making up the analysis cohort and whether soiling impacts the systems. The use of CODS for degradation analysis provides a different method for degradation assessment, which explicitly excludes the impact of recoverable soiling on degradation analysis. Excluding soiling effects yields an annual system degradation around -0.5% per year on average. This indicates that a portion of system performance loss may be attributed to periodic soiling that is not fully recovered. This report provides PV system owners/operators with background and methods to analyze PV system performance, give guidance for expected cohort performance, and performance loss values for use in pro-forma financial models, which guide new-build system design and bankability reports.

14 SOLAR ENERGY↗
DOE OSTI2024

PV System Availability from Commercial and Utility-Scale Systems [Slides]

In the PV Fleet Performance Data Initiative, we partner with photovoltaic (PV) fleet owners to collect time-series PV production data, and publish aggregated, anonymized results. An assessment of system availability is conducted on 1128 systems which passed our data quality checks, and include cumulative energy meter data. Overall inverter availability is low in the first 6 months of system performance before reaching steady-state by the end of the first year. System-level aggregated data shows a median (P50) system availability of 0.99, and a lower P90 value of 0.95. A dependence on system size is also identified, with worse inverter availability results for larger PV systems. Potential causes of this effect are under investigation.

14 SOLAR ENERGY↗
DOE OSTI2024

Assessment of BQ-9000 Biodiesel Properties for 2023

This is the seventh in a series of reports documenting the quality of biodiesel from U.S.- and Canadian-based producers that participate in the BQ-9000 program, the biodiesel industry’s voluntary quality assurance program. Participants provided monthly data on critical quality parameters for calendar year 2023 with quality data provided to a team of experts, who removed any identifying company information and provided anonymized data to the National Renewable Energy Laboratory (NREL) for statistical analysis. New for 2023, data on kinematic viscosity, sulfated ash, distillation temperature, carbon residue, and cetane were collected, as well as individual levels of sodium, potassium, calcium, and magnesium. Critical quality parameters analyzed are listed in Table ES-1 with descriptive statistics.

09 BIOMASS FUELS↗
DOE OSTI2024

Evaluating a Commercial Dynamic Line Rating Software with the National PMU Dataset

To accelerate the development of data-driven applications for power systems, the Department of Energy (DOE) supported the collection and curation of a synchrophasor dataset spanning two years of observations from transmission utilities across the US. This National PMU Dataset (NPDS) was anonymized and distributed to awardees of a DOE research grant under nondisclosure agreements (NDAs) but has also been retained at PNNL to enable further research. Agreements with data contributors prevent the data from being shared outside the organization. However, establishing a blind research validation methodology is envisioned to maximize the value proposition of the NPDS. In this validation strategy, researchers may share algorithms/software (potentially as executables to protect intellectual property) with PNNL, and PNNL will share feedback about the software’s performance on subsets of the NPDS. Such a blind methodology ensures that sensitive information about critical infrastructure remains protected, but the value of the NPDS can be extended to research beyond PNNL. Through iterative feedback, the algorithms may be tweaked to address real-world artifacts. As the NPDS data is temporally and geographically diverse, it may capture features absent in smaller datasets used during the development of the algorithm under test. This report presents lessons learned from applying the blind validation methodology to LineID™, a synchrophasor-based dynamic line rating software developed by Topolonet Corporation. Improvements made to the software through iterative feedback, limitations of the validation methodology, as well as how the limitations of the NPDS affected the evaluation process are discussed. Observations indicate that the proposed validation methodology can be valuable for evaluating other tools in the future.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

Electric Vehicle Charging Analytics and Reporting Tool (EV-ChART): Data Format and Preparation Guidance (V.5.0)

The Joint Office of Energy and Transportation maintains the Electric Vehicle Charging Analytics and Reporting Tool (EV-ChART), which provides a centralized hub for submitting electric vehicle (EV) charging infrastructure data directed by the Federal Highway Administration (23 CFR 680.112(a)-(c)). EV-ChART provides a streamlined data submission process and an integrated set of analytic tools, connects to other data sources, and empowers data sharing and access across stakeholders, including the public. Any data shared publicly will be aggregated and anonymized to stay in accordance with 23 CFR 680. This EV-ChART Data Format and Preparation Guidance provides a comprehensive overview of the data reporting requirements as authorized under 23 CFR 680.112(a)-(c)). The guidance is intended to be used alongside the EV-ChART Data Input Template, which defines the tabular data structure that these data submissions must follow. Per 23 CFR 680.112(a)-(c), the annual and quarterly data submissions are required of all National Electric Vehicle Infrastructure (NEVI) Formula Program projects, as well as projects for the construction of publicly accessible EV chargers that are funded with funds made available under Title 23, United States Code, including any EV charging infrastructure project funded with federal funds that is treated as a project on a federal-aid highway. One-time data submissions are required of both the NEVI Formula Program projects and grants awarded under 23 U.S.C. 151(f) for projects that are for EV charging stations located along and designed to serve the users of designated Alternative Fuel Corridors (AFCs). Other information and data required in 23 CFR 680, such as 23 CFR 680.112(d), 23 CFR 680.116(c), and 23 CFR 680.106(a), are not discussed in this guidance.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2025

Self-Lubricating Bushing Testing for John Day Dam Ka plan Turbine Replacement

The goal of this testing program is to find suitable self-lubricated alternatives to replace the in use oil lubricated grooved-bronze bushing in Kaplan runner hubs that are currently being utilized at John Day Dam operated by the U.S. Army Corps of Engineers (USACE). Scaled bushing testing utilizing a Pacific Northwest National Laboratory designed, fabricated, and operated Bushing Test Stand under the direction and funding from USACE determined that self-lubricated bushings tested appear capable of outperforming the current oil-lubricated bronze bushings. Performance tests are focused on durability which includes cyclic load bearing properties and articulations under various loading scenarios. This testing was performed at nominally 1/5 th scale. A scaling sensitivity analysis determined that scaled testing results apply to prototypic size. This report shows the direct comparison between the current baseline bronze bushing to self-lubricated bushings from various manufacturers. Bushing data like coefficient of friction and bushing material loss (associated with bushing wear) was determined. Self-lubricated bushings tested include products manufactured specifically for hydropower applications by the following companies: Trelleborg, Kamatics, Anonymous, and Tenneco/Deva.

42 ENGINEERING↗
DOE OSTI2025

Initial Mobility Analysis for ORNL VA-EDH Synthetic Populations

Travel burdens are a major barrier to healthcare access among US Veteran patient populations, particularly those residing in rural areas. Spatial accessibility to points of care for US Veteran populations is commonly assessed in two ways. The first approach uses open data from the US Census to represent collective travel burdens, for example the distance between population-weighted census tract centroids and VHA points of care. The second approach uses restricted-access VHA patient data to measure travel costs (e.g., distance, time) for accessing points of care with respect to geolocated patient addresses and real or approximated transportation networks. While the advantage of the open data approach lies in its reproducibility, it has notable limitations in its tendency to infer individual travel behavior from aggregate population characteristics, a problem known as ecological fallacy. Conversely, while the patient data approach is able to account for individual travel behavior, its ability to account for localized access disparities (e.g., a neighborhood with exceptionally high transportation costs) and patient demographics is limited as protecting individual patient data requires their storage in closed systems with limited capacity for adequately modeling real-world travel patterns or for supplementing patient attributes. Additionally, the patient data approach cannot account for veterans who are not enrolled in the VHA system but who may be eligible for care. These challenges limit the ability to perform “what if” analyses on the effects of place-specific interventions on veteran populations with high access barriers to healthcare. To address these challenges, we explore the application of realistic synthetic populations to examine travel burdens and spatial accessibility issues among veteran patient populations. Synthetic populations provide a virtual, individually-resolved and cross-sectional representation of the veteran patient population that enables investigation of spatial access to points of care in ways in which aggregate data and patient data do not. First, synthetic populations allow one to directly assess how individuals access points of care, from synthesized residential locations to outpatient facilities on real-world transportation networks. Modeling access to points of care at the individual scale addresses the ecological fallacy problem associated with using aggregated census data to represent veteran populations and patterns of movement. Second, synthetic populations provide a means of completely representing an area’s veteran population using only publicly available, anonymized census microdata from the American Community Survey (ACS) to ensure the privacy of real-world individuals. Generating synthetic populations from the ACS also expands descriptive characteristics beyond what patient data typically offers to include socio-demographic, economic, housing, and mobility attributes. More detailed profiles of both VHA patient populations and veterans not enrolled in the VA system will provide a comprehensive picture of groups that may benefit from interventions or outreach. As an initial exercise for using synthetic populations to measure veteran travel burdens to VA care, we apply Oak Ridge National Laboratory’s (ORNL) UrbanPop capability to generate a series of synthetic VHA patient populations for 9 Veterans Integrated Services Networks (VISN) market areas in 9 Census Divisions across the continental United States, which are listed in Table 1. We use UrbanPop to produce synthetic populations for the VISN markets selected for each US Census Division, then assign VA outpatient clinic destinations to synthetic VHA patients based on travel about each VISN market’s road network. To demonstrate using the synthetic populations to evaluate healthcare travel burdens, we compare the time-based impedance between simulated home locations and VA outpatient clinics in each VISN market. We then perform validation exercises on the synthetic populations with respect to neighborhood (block group) demographic composition as well as patient mobility, comparing aggregate origin-destination statistics for the synthetic population to outpatient visits available in restricted patient data from the VA’s Corporate Data Warehouse (CDW) database.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

Assessment of BQ-9000 Biodiesel Properties for 2024

This is the eighth in a series of reports documenting the quality of biodiesel from U.S.- and Canadian-based producers that participate in the BQ-9000 program, the biodiesel industry's voluntary quality assurance program. Participants provided monthly data on critical quality parameters for calendar year 2024 with quality data provided to a team of experts, who removed any identifying company information and provided anonymized data to the National Renewable Energy Laboratory (NREL) for statistical analysis. Similar to 2023, data on kinematic viscosity, sulfated ash, distillation temperature, carbon residue, and cetane were collected, as well as individual levels of sodium, potassium, calcium, and magnesium.

09 BIOMASS FUELS↗
DOE OSTI2026

Facilitating Data Collection of Maintenance Events to Populate the Hydrogen Component Reliability Database (HyCReD)

The Hydrogen Component Reliability Database (HyCReD) is a collaborative project between the National Renewable Energy Laboratory, the University of Maryland, and hydrogen stakeholders to improve safety and reliability for hydrogen facilities by implementing component reliability data taxonomies that support hydrogen infrastructure failure rate analysis. The project aims to quantify failure rates of hydrogen components through high-quality data collection and analysis on root causes and maintenance needed. HyCReD provides a common database for cataloging hydrogen component failures which exists for reliability research in many other mature industries [2]. The database fills a gap for the hydrogen community by providing a scientifically rigorous approach to quantitative risk assessment (QRA), prognostic health management (PHM), and reliability-centered maintenance (RCM) analysis. High level results will be aggregated and anonymized to protect company sensitive information; detailed results will be used to help address issues of hydrogen components. These advanced analytics will support accelerated deployment of hydrogen infrastructure by enabling better: design and safety of projects (safety codes and standards development), infrastructure reliability and cost (component failure rates, maintenance protocols), and component R&D needs (robust supply chain). A key to a successful HyCReD implementation is facilitating the ease of reporting and data quality in the database that can be used for analysis. Maintenance data was a previously identified gap in initial efforts to populate and validate the database taxonomies [3]. Collection of maintenance data will be instrumental in identifying failure modes and rates, identifying incipient component failures or reduced performance, cataloging best practices for maintenance routines and methods for prognostic health management, and quantifying the risk and effect of different failure modes. Several key priorities are identified for streamlined data collection to achieve quality and detailed failure data: Applicability, Ease of Use, Accessibility, and Information Security. The HyCReD team has now begun deployment of the database to several companies and groups that have signed non-disclosure agreements to facilitate the data collection of failures in industry hydrogen refueling station infrastructure. This paper will provide an update into the process of HyCReD deployment including the development of a coding guide for facility personnel to reference and ensure data quality and consistency from one station to another as well as implementation of contextually dependent data fields of system taxonomy and formatted entries to provide ease of use. The goal is to communicate the lessons learned from the roll-out to technicians and engineers in the field, and the addition of need for high level of security to protect all stakeholders.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2022

Ecobee Donate Your Data 1,000 homes in 2017

This dataset is a subset of the Ecobee Donate Your Data (DYD) dataset. The Ecobee DYD data comprises user-reported metadata (of home and occupant characteristics), and data collected by Ecobee thermostats (reported in 5-minute intervals). Participant data are pulled from the Ecobee servers, and then anonymized to remove any personally identifiable information. This subset selects 1,000 single family homes in four states - California, Texas, New York, and Illinois, and span the entire year of 2017. In addition to the measurements, a metadata JSON file is included to illustrate the high-level contextual information of the dataset. The dataset can be analyzed to understand how a single-family heating, ventilation, and air-conditioning (HVAC) system operates, occupant behavior, and building thermal dynamics.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2025

Blockchain Research and Development Activities Sponsored by the U.S. Department of Energy and Utility Sector

This article provides an in-depth analysis of blockchain research in the energy sector, focusing on projects funded by the U.S. Department of Energy (DOE) and comparing them with industry-funded initiatives. A total of 110 funded activities within the U.S. power industry were successfully tracked and mapped into a newly developed categorization framework. This framework is designed to help research agencies to systematically understand their funded portfolio. Such characterization is expected to help them make effective investments, identify research gaps, measure impact, and advance technological progress to meet national goals. In line with this need, the proposed framework proposes a 2-D categorization matrix to systematically classify blockchain efforts within the energy sector.Under the proposed framework, the Energy System Domain serves as the primary classification dimension, categorizing use cases into 30 distinct applications. The second dimension, Blockchain Properties, captures the specific needs and functionalities provided by Blockchain technology. The aim was to capture blockchain’s applicability and functionality: where and why blockchain? Principles behind the selection of the viewpoint dimensions were carefully defined based on consensus obtained through the Blockchain for Optimized Security and Energy Management (BLOSEM) project. The mapped results show that activities within the Grid Automation, Coordination, and Control (31.8%), Marketplaces and Trading (25.5%), Foundational Blockchain Research (19.1%), and Supply Chain Management (17.3%) domains have been actively pursued to date. The three leading specific use case applications were identified as Transactive Energy Management for Marketplaces and Trading, Asset Management for Supply Chain Management, and Fundamental Blockchain for Foundational Blockchain Research. The Marketplaces and Trading and Retail Services Enablement domains stood out as being favored by industry by a factor greater than 2 (2.3 and 2.6, respectively), yet there seemed to be little to zero investment from DOE. Approximately 76% of the total projects prioritized Immutability, Identity Management, and Decentralization and/or Disintermediation compared to Asset Digitization and/or Tokenization, Automation, and Privacy and/or Anonymity. The greatest discrepancies between DOE and industry were in Asset Digitization and/or Tokenization and Automation. The industry efforts (36% in Asset Digitization/Tokenization and 22% in Automation) was 14 times and 2.4 times, respectively, more intensive than the DOE-sponsored efforts, indicating a significant discrepancy in industry versus government priorities. Overall, quantifying DOE-sponsored projects and industry activities through mapping provides clarity on portfolio investments and opportunities for future research.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2024

Predicting the Identities of su(met-2) and met-3 in Neurospora crassa by Genome Resequencing

A significant number of classical genetic Neurospora crassa biochemical mutants remain anonymous, unassociated with a physical genome locus. By utilizing short read next-generation sequencing methods, it is possible to sequence the genomes of mutant strains rapidly and economically for the purpose of identifying genes associated with mutant phenotypes. We have taken this approach to connect genes and mutations to “methionineless” phenotypes in N. crassa.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2026

Hourly natural gas usage surrounding NIST NEB and NWB GHG monitoring stations in 2023

This dataset includes hourly natural gas usage surrounding two National Institute of Standards and Technology (NIST) greenhouse gas (GHG) monitoring stations, Northwest Baltimore (NWB; 39.3445°N, 76.6851°W) and Northeast Baltimore (NEB; 39.3154°N, 76.5830°W), for the year 2023 in units of therms. The gas usage was provided by the local gas distribution company and includes hourly data averaged across groups of 15 or more addresses to maintain anonymity. The hourly data was averaged spatially within a radius of 1 km from each monitoring station, including all groups containing data from any address within 1km of the monitoring station. This dataset only includes gas usage from service points equipped with advanced metering infrastructure (AMI). Between the two monitoring sites, this dataset includes usage from a total of 3649 service points, which we estimate is at least 44% of the service points in the domain.

Kenion, Helen C. R. [School of Environment and Sus↗
DOE OSTI2026

Dronebase Photovoltaic (PV) Fleet Imagery Quantitative Evaluation (CRADA CRD-22-22941 Final Report)

Combine the Dronebase aerial imagery with corresponding sites in the NLR Photovoltaic (PV) Fleets database. By combining these two data sources in an aggregated, anonymized fashion, we can perform the following analyses: quantifying power loss due to outages caused by stuck trackers, string outages, and shading/snow, validate site metadata, including tilt and azimuth, and correlate.

14 SOLAR ENERGY↗
DOE OSTI2021

Distributed PV permitting survey responses

In 2019, NREL, in partnership with the Solar Energy Industries Association, developed a survey for PV installers on their experiences with delays and cancelations in the adoption process, including the impacts of permitting and interconnection. This dataset includes the anonymized responses from 147 representatives from 136 solar install companies.

14 SOLAR ENERGY↗