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At least 127 records · Page 7

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DOE OSTI2016

Data Quality Objectives Supporting the Environmental Soil Monitoring Program for the Idaho National Laboratory Site

This document describes the process used to develop data quality objectives for the Idaho National Laboratory (INL) Environmental Soil Monitoring Program in accordance with U.S. Environmental Protection Agency guidance. This document also develops and presents the logic that was used to determine the specific number of soil monitoring locations at the INL Site, at locations bordering the INL Site, and at locations in the surrounding regional area. The monitoring location logic follows the guidance from the U.S. Department of Energy for environmental surveillance of its facilities.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2023

Toward Integrating Data Quality Assessments and Radiometer Uncertainty for Determining the Expanded Uncertainty of Three-Component Solar Radiation Measurements

This presentation provides an overview on integrating data quality assessments and radiometer uncertainty for determining the expanded uncertainty of three-component solar radiation measurements.

expanded uncertainty↗

NASA NTRS1998

Data Quality of the JERS-1 SAR Global Rain Forest Mapping (GRFM) Project

The National Space Development Agency of Japan's (NASDA) JERS-1 SAR began collecting data in 1995 for the Global Rain Forest Mapping Project (GRFM). The GRFM data quality has been examined for products resulting from both the NASDA and Alaska SAR facility's (ASF) processing facilities.

JERS-1 SAR Rain Forest Mapping↗

DOE OSTI2021

Historical Data Analysis Supporting the Data Quality Objectives for the INL Site Environmental Soil Monitoring Program

This document represents the initial evaluation and soil monitoring proposed by Battelle Energy Alliance, LLC (BEA) in 2015. The evaluation included analyses of historical soil monitoring data and soil inventories, current emission estimates, and modeled potential deposition/accumulation patterns. The initially proposed monitoring included a 5-year rotation of in-situ gamma measurements augmented by soil sampling with laboratory analyses near each major active and some inactive facilities. It also proposed rotational in-situ gamma measurements and soil sampling at two centrally located onsite air monitoring locations coinciding with sampling at the traditional offsite soil monitoring locations. The chosen alternative includes only physical soil sampling with laboratory analysis and only at the Radioactive Waste Management Complex (RWMC), the two air monitors and the offsite locations as documented in Data Quality Objectives Supporting the Environmental Soil Monitoring Program for the Idaho National Laboratory (INL) Site, INL/EXT-15-34909, Revision 0, February 2016. The data and evaluations in this document are valid for comparisons with future soil data that may be collected in many INL site locations.

54 ENVIRONMENTAL SCIENCES↗

NASA NTRS2018

Sensor Data Quality and Angular Rate Down-Selection Algorithms on SLS EM-1

The NASA Space Launch System Block 1 launch vehicle is equipped with an Inertial Navigation System (INS) and multiple Rate Gyro Assemblies (RGA) that are used in the Guidance, Navigation, and Control (GN&C) algorithms. The INS provides the inertial position, velocity, and attitude of the vehicle along with both angular rate and specific force measurements. Additionally, multiple sets of co-located rate gyros supply angular rate data. The collection of angular rate data, taken along the launch vehicle, is used to separate out vehicle motion from flexible body dynamics. Since the system architecture uses redundant sensors, the capability was developed to evaluate the health (or validity) of the independent measurements. A suite of Sensor Data Quality (SDQ) algorithms is responsible for assessing the angular rate data from the redundant sensors. When failures are detected, SDQ will take the appropriate action and disqualify or remove faulted sensors from forward processing. Additionally, the SDQ algorithms contain logic for down-selecting the angular rate data used by the GNC software from the set of healthy measurements. This paper explores the trades and analyses that were performed in selecting a set of robust fault-detection algorithms included in the GN&C flight software. These trades included both an assessment of hardware-provided health and status data as well as an evaluation of different algorithms based on time-to-detection, type of failures detected, and probability of detecting false positives. We then provide an overview of the algorithms used for both fault-detection and measurement down selection. We next discuss the role of trajectory design, flexible-body models, and vehicle response to off-nominal conditions in setting the detection thresholds. Lastly, we present lessons learned from software integration and hardware-in-the-loop testing.

Park, Thomas↗

NASA NTRS2018

Sensor Data Quality and Angular Rate Down-Selection Algorithms on SLS EM-1

Park, Thomas↗

DOE OSTI2019

The Prompt Processing System and Data Quality Monitoring in the ProtoDUNE-SP Experiment

The DUNE Collaboration is conducting an experimental program (named protoDUNE) which involves a beam test of two large-scale prototypes of the DUNE Far Detector at CERN operating in 2018-2019. The volume of data to be collected by the protoDUNE-SP (the single-phase detector) will amount to a few petabytes and the sustained rate of data sent to mass storage is in the range of a few hundred MB per second. After collection the data is committed to storage at CERN and transmitted to Fermi National Accelerator Laboratory in the US for processing, analysis and long-term preservation. The protoDUNE experiment requires substantial Data Quality Monitoring capabilities in order to ascertain the condition of the detector and its various subsystems. We present the design of the protoDUNE Prompt Processing System, its deployment at CERN and its performance during the data challenges and actual data taking.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

DOE OSTI2024

Characterization of Non-Science Grade DESI CCDs and Creating Additional ICARUS Monitoring Metrics for Data Quality

DESI, otherwise known as the Dark Energy Spectroscopic Instrument, is an astronomical project measuring millions of optical spectra to characterize Dark Energy. The survey has been running for 3 years. My work delves into the data taking/analysis side of the DESI CCDs (Charge-Coupled Devices) which will help in swapping out broken CCDs on the instrument. Additionally, I worked on making new metrics for ICARUS, Imaging Cosmic and Rare Underground Signals for their monitoring of run data. This paper will talk about the types of characterizations done for DESI and additional metrics for data quality and tools used for ICARUS monitoring.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

DOE OSTI2024

PMU Data Quality and Sensor Health Monitoring

Phasor Measurement Units (PMUs) play a critical role in the evolution of the electric power industry by providing high-precision, real-time monitoring of essential power system metrics. However, effectively detecting abnormalities and critical events from PMU data is a complex task, complicated by intricate temporal patterns, a scarcity of labeled data for training algo- rithms, and constraints on online computational power. In this study, we apply TranAD, an innovative algorithm that combines transformer architectures with the refinement of adversarial learning, to both synthetic and real-world PMU datasets for developing a data quality and sensor online health monitoring platform for utilities. Our findings reveal that TranAD not only provides efficient detection and localization but also enhances the detail with which abnormalities are detected, marking a a significant step forward in the field of clean data acquisition processes for power system monitoring

deep neural network, machine learning (ML)↗

DOE OSTI2022

Waveform Data Quality Assessment

Healthy seismoacoustic sensors and accurate metadata are critical to all the science objectives of both the Source Physics Experiment (SPE) Rock Valley Direct Comparison (RV/DC) and LowYield Physics Experiment-1 (LYNM PE-1). Both projects share similar seismoacoustic stations. We provide a plan on how to move forward with waveform data quality assessments (QA) to the working groups. The identification of stations with instrument response errors will be useful to researchers using amplitudes to study source effects and Earth attenuation. The data QA can also be useful for field technicians to help identify and correct problem sites.

47 OTHER INSTRUMENTATION↗

NASA NTRSDate not supplied

Creating and Using Open Global and Local Air Quality Data at NASA GMAO

Air quality is the leading environmental health concern.

air quality↗

DOE OSTI2022

Physics-informed graph neural networks for predicting cetane number with systematic data quality analysis

Designing alternative fuels for advanced compression ignition engines necessitates a predictive model for cetane number (CN). In this study, the physics-informed graph neural networks are introduced for a reliable CN prediction by considering molecular features pertinent to the physical properties of molecules that affect CN. The reliability of measured data is another key factor to consider for improving the predictive model. Various experimental instruments for measuring CN exist, including standard and non-standard methods. In this regard, a systematic data quality analysis was carried out for the total 630 CNs collected from literature and new measurements in this study using Advanced Fuel Ignition Delay Analyzer (AFIDA). The results from this data curation process were reflected in the model by imposing lower sample weights on the data coming from less reliable measurement techniques. This approach effectively maximized the prediction accuracy while incorporating data from all available sources. Using the sample weights decreased the mean absolute error (MAE) up to 0.8 CN units. The accuracy was also improved by introducing the CN-related physical properties (the number of hydrogen bond donors and acceptors); the test set MAE is 5.74 and 7.01 for the model with and without such properties, respectively. Investigating molecular structural effects on CN was also carried out to gain chemical insights into factors used to design new fuel candidates. The dimensionality reduction analysis of feature vectors showed a clear clustering in terms of functional groups and CN and the structural effect derived from the model was consistent with the physicochemical insights. Finally, this physics-informed model and data curation would be helpful for accurate CN prediction and inform rational fuel design.

97 MATHEMATICS AND COMPUTING↗

NASA NTRS1985

LANDSAT TM image data quality analysis for energy-related applications

This project represents a no-cost agreement between National Aeronautic Space Administration Goddard Space Flight Center (NASA GSFC) and the Pacific Northwest Laboratory (PNL). PNL is a Department of Energy (DOE) national laboratory operted by Battelle Memorial Institute at its Pacific Northwest Laboratories in Richland, Washington. The objective of this investigation is to evaluate LANDSAT's thematic mapper (TM) data quality and utility characteristics from an energy research and technological perspective. Of main interest is the extent to which repetitive TM data might support DOE efforts relating to siting, developing, and monitoring energy-related facilities, and to basic geoscientific research. The investigation utilizes existing staff and facility capabilities, and ongoing programmatic activities at PNL and other DOE national laboratories to cooperatively assess the potential usefulness of the improved experimental TM data. The investigation involves: (1) both LANDSAT 4 and 5 TM data, (2) qualitative and quantitative use consideration, and 3) NASA P (corrected) and A (uncorrected) CCT analysis for a variety of sites of DOE interest. Initial results were presented at the LANDSAT Investigator's Workshops and at specialized LANDSAT TM sessions at various conferences.

Wukelic, G. E.↗

DOE OSTI2019

FAST FY 2018 Federal Fleet Data Call: Looking at Data Quality

This presentation provides an overview of fiscal year 2018 federal motor vehicle fleet data at the individual vehicle level during the fall of 2018, a preliminary summary of the data collected, how the the collecting project has reviewed that information for potential quality issues, and an overview of two key areas within the dataset that represent data quality issues. This presentation will be given at the April 2019 FedFleet training event, hosted by the US General Services Administration in Washington, DC. The information is collected through the Federal Automotive Statistical Tool (FAST) project. FAST is a Web-based information system managed by the US Department of Energy, the US General Services Administration, and the Energy Information Administration. FAST is used to collect information about the fleet of motor vehicles used and managed by the Federal government. FAST is developed and maintained by DOE's Idaho National Laboratory (INL).

99 GENERAL AND MISCELLANEOUS↗

NASA NTRS1986

Multi-station lunar laser ranging - An analysis of data quality and earth rotation results

The lunar laser ranging (LLR) results obtained from the MERIT period (Sept. 1983 through Oct. 1984) as well as from the post-MERIT period (Nov. 1, 1984 through Aug. 12, 1985) are presented. The ranging targets on the moon include the Apollo 11, 14, and 15 reflectors and a reflector on Lunokhod 2; the LLR network includes McDonald, Texas; CERGA, France; Haleakala, Hawaii; Orroral, Australia; and Crimea, USSR, stations. Data acquired with these systems are reported, and the data quality is assessed, with particular emphasis on recent ranges. During the MERIT period, sixty-five earth rotation values (UTO) were derived from LLR data, with the best accuracy being 0.25 msec; during the post-MERIT period, 115 determinations of UTO were calculated with the best inherent accuracy of about 0.1 msec. The results are compared with those from other techniques.

Dickey, J. O.↗

DOE OSTI2018

Data Quality Objective Scoping Package In Support of a Remedial Action at Exposure Unit 5 Attachment C, Rev 0 to the Upper East Fork Poplar Creek Soils Remedial Action Work Plan DOE/OR/01-2423&D1

The Department of Energy (DOE), Oak Ridge Office of Environmental Management (OREM), intends to perform characterization of Exposure Unit 5 (EU-5) slabs and soils at the Y-12 National Security Complex (Y-12). This Data Quality Objective (DQO) Scoping Package has been prepared as part of the Upper East Fork Poplar Creek (UEFPC) Soils Remedial Action Work Plan (RAWP) (DOE 2010a) as the planning document for the Dynamic Characterization Strategy (DCS) for soils in EU-5. Y-12 is located at the southeastern boundary of the Oak Ridge Reservation (ORR) and the industrialized area of Y-12 consists of approximately 600 acres located within the UEFPC watershed characterization area. The UEFPC RAWP and this DQO Scoping Package were developed in order to address the remedial action objectives of the Record of Decision for Phase II Interim Remedial Actions for Contaminated Soils and Scrapyard in UEFPC, Oak Ridge, Tennessee, DOE/OR/01-2229&D3 (Soils ROD) (DOE 2006).

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2022

Report on Data Quality Required for Modeling an MSR

Calculations were performed to assess how uncertainties in molten salt property values impact the results of behavior models of molten salt reactor systems under steady-state conditions. The thermophysical and thermochemical properties of salt mixtures being considered for use in molten salt reactors are not yet well characterized and methods used to measure property values to molten salts are not yet well established. The limited property data for salts of interest that are available in the literature are inconsistent and unreliable. Many methods used to measure property values remain developmental in the sense that not all variables affecting measured values have been identified or controlled during the measurement and not all aspects of the measurements affecting data quality are calibrated. A prior report described the repeatability of measurements made at Argonne and the reproducibility of measurements made with the same salts at several institutions is being evaluated. There is significant uncertainty in measured property values due to instrumental limitations and the effects of contaminants in the salts used to make the measurements that impacts predictions of salt behavior in a reactor. Most salts of interest are multicomponent eutectic or near-eutectic mixtures and both uncertainty in the salt composition and uncertainty in measured values. Furthermore, the salt composition evolves over time due to the uptake of impurities from the atmosphere and corrosion of containment vessels. More significantly, fission products will accumulate during operation that change the salt compositions and property values. MSR developers need to understand how this uncertainty in the basic property data of the fuel will impact modeling predictions for normal reactor operation as well was in transient scenarios that will impact the safety basis. The calculations and analyses in this report address the impact of uncertainty in measured property values under steady-state conditions through a generalized parametric study. The pooled uncertainty from contributions by a number of factors were considered and quantified, including varying composition due to impurities and fission products, imprecision in the measured values, and uncontrolled aspects of the measurement. In this way, we can begin to gain an understanding of the magnitude of the impact uncertainty will have in modeling MSR systems.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

NASA NTRS1998

Data Quality Assessment Methods for the Eastern Range 915 MHz Wind Profiler Network

The Eastern Range installed a network of five 915 MHz Doppler Radar Wind Profilers with Radio Acoustic Sounding Systems in the Cape Canaveral Air Station/Kennedy Space Center area to provide three-dimensional wind speed and direction and virtual temperature estimates in the boundary layer. The Applied Meteorology Unit, staffed by ENSCO, Inc., was tasked by the 45th Weather Squadron, the Spaceflight Meteorology Group, and the National Weather Service in Melbourne, Florida to investigate methods which will help forecasters assess profiler network data quality when developing forecasts and warnings for critical ground, launch and landing operations. Four routines were evaluated in this study: a consensus time period check a precipitation contamination check, a median filter, and the Weber-Wuertz (WW) algorithm. No routine was able to effectively flag suspect data when used by itself. Therefore, the routines were used in different combinations. An evaluation of all possible combinations revealed two that provided the best results. The precipitation contamination and consensus time routines were used in both combinations. The median filter or WW was used as the final routine in the combinations to flag all other suspect data points.

Lambert, Winifred C.↗