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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 37 records · Page 2
All sourcesNASA NTRSDOE OSTI
DOE OSTI2018

Automated data processing architecture for the Gemini Planet Imager Exoplanet Survey

The Gemini Planet Imager Exoplanet Survey (GPIES) is a multiyear direct imaging survey of 600 stars to discover and characterize young Jovian exoplanets and their environments. We have developed an automated data architecture to process and index all data related to the survey uniformly. An automated and flexible data processing framework, which we term the Data Cruncher, combines multiple data reduction pipelines (DRPs) together to process all spectroscopic, polarimetric, and calibration data taken with GPIES. With no human intervention, fully reduced and calibrated data products are available less than an hour after the data are taken to expedite follow up on potential objects of interest. The Data Cruncher can run on a supercomputer to reprocess all GPIES data in a single day as improvements are made to our DRPs. A backend MySQL database indexes all files, which are synced to the cloud, and a front-end web server allows for easy browsing of all files associated with GPIES. To help observers, quicklook displays show reduced data as they are processed in real time, and chatbots on Slack post observing information as well as reduced data products. Together, the GPIES automated data processing architecture reduces our workload, provides real-time data reduction, optimizes our observing strategy, and maintains a homogeneously reduced dataset to study planet occurrence and instrument performance.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2023

Accelerating Machine Learning Inference with GPUs in ProtoDUNE Data Processing

Abstract We study the performance of a cloud-based GPU-accelerated inference server to speed up event reconstruction in neutrino data batch jobs. Using detector data from the ProtoDUNE experiment and employing the standard DUNE grid job submission tools, we attempt to reprocess the data by running several thousand concurrent grid jobs, a rate we expect to be typical of current and future neutrino physics experiments. We process most of the dataset with the GPU version of our processing algorithm and the remainder with the CPU version for timing comparisons. We find that a 100-GPU cloud-based server is able to easily meet the processing demand, and that using the GPU version of the event processing algorithm is two times faster than processing these data with the CPU version when comparing to the newest CPUs in our sample. The amount of data transferred to the inference server during the GPU runs can overwhelm even the highest-bandwidth network switches, however, unless care is taken to observe network facility limits or otherwise distribute the jobs to multiple sites. We discuss the lessons learned from this processing campaign and several avenues for future improvements.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2018

First ARM Aerosol Chemical Speciation Monitor Users’ Meeting Report

The first U.S. Department of Energy (DOE) Atmospheric Radiation Measurement (ARM) user facility aerosol chemical speciation monitor (ACSM) users’ meeting was held on April 11-13, 2017, at Aerodyne Research, Inc. in Billerica, Massachusetts, to discuss the Southern Great Plains (SGP) atmospheric observatory ACSM data quality and establish best practices for data collection and processing. The participants examined six years of calibration and processed data. Specific issues raised by data users were addressed and case studies from two field experiments were examined. The most recent data from the ACSM installed in the newly commissioned SGP ARM Mobile Facility 7 (AMF7) were also evaluated. The participants recommended that the SGP ACSM data be reprocessed using calibration values averaged over the history of SGP ACSM calibrations. They also recommended that the data quality be evaluated by comparing (1) observed versus predicted particulate ammonium (NH4+) mass loadings, and (2) ACSM mass loadings versus mass loadings calculated from particle size and light scattering data. The contents of the datastreams from the ACSM were defined based on ARM requirements and the necessary tasks to implement these recommendations were assigned to the mentor and the instrument manufacturer. Some of the recommendations were implemented for the SGP data and are presented in this report. Data from two ARM sites located in marine environments were also analyzed. These analyses as well as instrument intercomparisons have led to further questions about data treatment. These will be addresses in the second users’ meeting scheduled for the summer of 2018.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2018

First ARM Aerosol Chemical Speciation Monitor Users’ Meeting Report

The first U.S. Department of Energy (DOE) Atmospheric Radiation Measurement (ARM) user facility aerosol chemical speciation monitor (ACSM) users’ meeting was held on April 11-13, 2017, at Aerodyne Research, Inc. in Billerica, Massachusetts, to discuss the Southern Great Plains (SGP) atmospheric observatory ACSM data quality and establish best practices for data collection and processing. The participants examined six years of calibration and processed data. Specific issues raised by data users were addressed and case studies from two field experiments were examined. The most recent data from the ACSM installed in the newly commissioned SGP ARM Mobile Facility 7 (AMF7) were also evaluated. The participants recommended that the SGP ACSM data be reprocessed using calibration values averaged over the history of SGP ACSM calibrations. They also recommended that the data quality be evaluated by comparing (1) observed versus predicted particulate ammonium (NH 4 + ) mass loadings, and (2) ACSM mass loadings versus mass loadings calculated from particle size and light scattering data. The contents of the datastreams from the ACSM were defined based on ARM requirements and the necessary tasks to implement these recommendations were assigned to the mentor and the instrument manufacturer. Some of the recommendations were implemented for the SGP data and are presented in this report. Data from two ARM sites located in marine environments were also analyzed. These analyses as well as instrument intercomparisons have led to further questions about data treatment. These will be addresses in the second users’ meeting scheduled for the summer of 2018.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2018

First ARM Aerosol Chemical Speciation Monitor Users’ Meeting Report

The first U.S. Department of Energy (DOE) Atmospheric Radiation Measurement (ARM) user facility aerosol chemical speciation monitor (ACSM) users’ meeting was held on April 11-13, 2017, at Aerodyne Research, Inc. in Billerica, Massachusetts, to discuss the Southern Great Plains (SGP) atmospheric observatory ACSM data quality and establish best practices for data collection and processing. The participants examined six years of calibration and processed data. Specific issues raised by data users were addressed and case studies from two field experiments were examined. The most recent data from the ACSM installed in the newly commissioned SGP ARM Mobile Facility 7 (AMF7) were also evaluated. The participants recommended that the SGP ACSM data be reprocessed using calibration values averaged over the history of SGP ACSM calibrations. They also recommended that the data quality be evaluated by comparing (1) observed versus predicted particulate ammonium (NH 4 + ) mass loadings, and (2) ACSM mass loadings versus mass loadings calculated from particle size and light scattering data. The contents of the datastreams from the ACSM were defined based on ARM requirements and the necessary tasks to implement these recommendations were assigned to the mentor and the instrument manufacturer. Some of the recommendations were implemented for the SGP data and are presented in this report. Data from two ARM sites located in marine environments were also analyzed. These analyses as well as instrument intercomparisons have led to further questions about data treatment. These will be addresses in the second users’ meeting scheduled for the summer of 2018.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2018

First ARM Aerosol Chemical Speciation Monitor Users’ Meeting Report

The first U.S. Department of Energy (DOE) Atmospheric Radiation Measurement (ARM) user facility aerosol chemical speciation monitor (ACSM) users’ meeting was held on April 11-13, 2017, at Aerodyne Research, Inc. in Billerica, Massachusetts, to discuss the Southern Great Plains (SGP) atmospheric observatory ACSM data quality and establish best practices for data collection and processing. The participants examined six years of calibration and processed data. Specific issues raised by data users were addressed and case studies from two field experiments were examined. The most recent data from the ACSM installed in the newly commissioned SGP ARM Mobile Facility 7 (AMF7) were also evaluated. The participants recommended that the SGP ACSM data be reprocessed using calibration values averaged over the history of SGP ACSM calibrations. They also recommended that the data quality be evaluated by comparing (1) observed versus predicted particulate ammonium (NH 4 + ) mass loadings, and (2) ACSM mass loadings versus mass loadings calculated from particle size and light scattering data. The contents of the datastreams from the ACSM were defined based on ARM requirements and the necessary tasks to implement these recommendations were assigned to the mentor and the instrument manufacturer. Some of the recommendations were implemented for the SGP data and are presented in this report. Data from two ARM sites located in marine environments were also analyzed. These analyses as well as instrument intercomparisons have led to further questions about data treatment. These will be addresses in the second users’ meeting scheduled for the summer of 2018.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2015

openPMD-viewer

Many simulation software produce data in the form of a set of field values or of a set of particle positions. (one such example is that of particle-in-cell codes, which produce data on the electromagnetic fields that they simulate.) However, each particular software uses its own particular format and layout, for the output data. This makes it difficult to compare the results of different simulation software, or to have a common visualization tool for these results. However, a standardized layout for fields and particles has recently been developed: the openPMD format ( HYPERLINK "http://www.openpmd.org/"www.openpmd.org) This format is open- source, and specifies a standard way in which field data and particle data should be written. The openPMD format is already implemented in the particle-in-cell code Warp (developed at LBL) and in PIConGPU (developed at HZDR, Germany). In this context, the proposed software (openPMD-viewer) is a Python package, which allows to access and visualize any data which has been formatted according to the openPMD standard. This package contains two main components: - a Python API, which allows to read and extract the data from a openPMD file, so as to be able to work with it within the Python environment. (e.g. plot the data and reprocess it with particular Python functions) - a graphical interface, which works with the ipython notebook, and allows to quickly visualize the data and browse through a set of openPMD files. The proposed software will be typically used when analyzing the results of numerical simulations. It will be useful to quickly extract scientific meaning from a set of numerical data.

Lehe, Remi↗
DOE OSTI2015

openPMD-viewer

Many simulation software produce data in the form of a set of field values or of a set of particle positions. (one such example is that of particle-in-cell codes, which produce data on the electromagnetic fields that they simulate.) However, each particular software uses its own particular format and layout, for the output data. This makes it difficult to compare the results of different simulation software, or to have a common visualization tool for these results. However, a standardized layout for fields and particles has recently been developed: the openPMD format ( HYPERLINK "http://www.openpmd.org/"www.openpmd.org) This format is open- source, and specifies a standard way in which field data and particle data should be written. The openPMD format is already implemented in the particle-in-cell code Warp (developed at LBL) and in PIConGPU (developed at HZDR, Germany). In this context, the proposed software (openPMD-viewer) is a Python package, which allows to access and visualize any data which has been formatted according to the openPMD standard. This package contains two main components: - a Python API, which allows to read and extract the data from a openPMD file, so as to be able to work with it within the Python environment. (e.g. plot the data and reprocess it with particular Python functions) - a graphical interface, which works with the ipython notebook, and allows to quickly visualize the data and browse through a set of openPMD files. The proposed software will be typically used when analyzing the results of numerical simulations. It will be useful to quickly extract scientific meaning from a set of numerical data.

Lehe, Remi↗
DOE OSTI2019

Effects of Improved 17 O Correction on Interlaboratory Agreement in Clumped Isotope Calibrations, Estimates of Mineral-Specific Offsets, and Temperature Dependence of Acid Digestion Fractionation

The clumped isotopic composition of carbonate-CO 2 (denoted Δ 47 ) is a function of carbonate formation temperature and in natural samples can act as a recorder of paleoclimate, burial, or diagenetic conditions. The absolute abundance of heavy isotopes in the universal standards VPDB and VSMOW (defined by four parameters: R 13 VPDB , R 17 VSMOW , R 18 VSMOW , and λ ) impact calculated Δ 47 values. In this work, we investigate whether use of updated and more accurate values for these parameters can remove observed interlaboratory differences in the measured T-Δ 47 relationship. Using the updated parameters, we reprocess 14 published calibration data sets measured in 11 different laboratories, representing many mineralogies, bulk compositions, sample types, reaction temperatures, and sample preparation and analysis methods. Exploiting this large composite data set ( n = 1,253 sample replicates), we investigate the possibility for a “universal” clumped isotope calibration. We find that applying updated parameters improves the T-Δ 47 relationship (reduces residuals) within most labs and improves overall agreement but does not eliminate all interlaboratory differences. We reaffirm earlier findings that different mineralogies do not require different calibration equations and that cleaning procedures, method of pressure baseline correction, and mass spectrometer type do not affect interlaboratory agreement. We also present new estimates of the temperature dependence of the acid digestion fractionation for Δ 47 (Δ* 25-X ), based on combining reprocessed data from four studies, and new theoretical equilibrium values to be used in calculation of the empirical transfer function. Overall, we have ruled out a number of possible causes of interlaboratory disagreement in the T-Δ 47 relationship, but many more remain to be investigated.

58 GEOSCIENCES↗
DOE OSTI2015

ERRATUM: “Automated Transient Identification in the Dark Energy Survey” (2015, AJ, 150, 82)

Here, we describe an algorithm for identifying point-source transients and moving objects on reference-subtracted optical images containing artifacts of processing and instrumentation. The algorithm makes use of the supervised machine learning technique known as Random Forest. We present results from its use in the Dark Energy Survey Supernova program (DES-SN), where it was trained using a sample of 898,963 signal and background events generated by the transient detection pipeline. After reprocessing the data collected during the first DES-SN observing season (2013 September through 2014 February) using the algorithm, the number of transient candidates eligible for human scanning decreased by a factor of 13.4, while only 1.0% of the artificial Type Ia supernovae (SNe) injected into search images to monitor survey efficiency were lost, most of which were very faint events. Here we characterize the algorithm's performance in detail, and we discuss how it can inform pipeline design decisions for future time-domain imaging surveys, such as the Large Synoptic Survey Telescope and the Zwicky Transient Facility. An implementation of the algorithm and the training data used in this paper are available at at http://portal.nersc.gov/project/dessn/autoscan.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2014

FIVE DEBRIS DISKS NEWLY REVEALED IN SCATTERED LIGHT FROM THE HUBBLE SPACE TELESCOPE NICMOS ARCHIVE

We have spatially resolved five debris disks (HD 30447, HD 35841, HD 141943, HD 191089, and HD 202917) for the first time in near-infrared scattered light by reanalyzing archival Hubble Space Telescope (HST)/NICMOS coronagraphic images obtained between 1999 and 2006. One of these disks (HD 202917) was previously resolved at visible wavelengths using the HST/Advanced Camera for Surveys. To obtain these new disk images, we performed advanced point-spread function subtraction based on the Karhunen-Loève Image Projection algorithm on recently reprocessed NICMOS data with improved detector artifact removal (Legacy Archive PSF Library And Circumstellar Environments (LAPLACE) Legacy program). Three of the disks (HD 30447, HD 35841, and HD 141943) appear edge-on, while the other two (HD 191089 and HD 202917) appear inclined. The inclined disks have been sculpted into rings; in particular, the disk around HD 202917 exhibits strong asymmetries. All five host stars are young (8-40 Myr), nearby (40-100 pc) F and G stars, and one (HD 141943) is a close analog to the young Sun during the epoch of terrestrial planet formation. Our discoveries increase the number of debris disks resolved in scattered light from 19 to 23 (a 21% increase). Given their youth, proximity, and brightness (V = 7.2-8.5), these targets are excellent candidates for follow-up investigations of planet formation at visible wavelengths using the HST/Space Telescope Imaging Spectrograph coronagraph, at near-infrared wavelengths with the Gemini Planet Imager and Very Large Telescope/SPHERE, and at thermal infrared wavelengths with the James Webb Space Telescope NIRCam and MIRI coronagraphs.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2014

Geothermal Exploration of Newberry Volcano, Oregon

Davenport Newberry (Davenport) has completed 8 years of exploration for geothermal energy on Newberry Volcano in central Oregon. Two deep exploration test wells were drilled by Davenport on the west flank of the volcano, one intersected a hydrothermal system; the other intersected isolated fractures with no hydrothermal interconnection. Both holes have bottom-hole temperatures near or above 315°C (600°F). Subsequent to deep test drilling an expanded exploration and evaluation program was initiated. These efforts have included reprocessing existing data, executing multiple geological, geophysical, geochemical programs, deep exploration test well drilling and shallow well drilling. The efforts over the last three years have been made possible through a DOE Innovative Exploration Technology (IET) Grant 109, designed to facilitate innovative geothermal exploration techniques. The combined results of the last 8 years have led to a better understanding of the history and complexity of Newberry Volcano and improved the design and interpretation of geophysical exploration techniques with regard to blind geothermal resources in volcanic terrain.

15 GEOTHERMAL ENERGY↗
DOE OSTI2019

Mid-Atlantic U.S. Offshore Carbon Storage Resource Assessment Project (Final Technical Report)

The greatest potential for carbon storage in the northeastern United States lies in the offshore geologic formations comprising the outer continental shelf (Monteverde et al., 2011). Offshore storage can be linked to large point-sources of carbon dioxide (CO 2 ) while avoiding many of the logistical difficulties and potential risks encountered when siting onshore projects, especially in densely populated areas of the East Coast. Offshore CO 2 storage assessment and research in the United States is underway to address uncertainty in potential storage resources, particularly in the mid- and north-Atlantic offshore area. Given the current knowledge base and access to publicly available data, the objectives of the Mid-Atlantic U.S. Offshore Carbon Storage Resource Assessment Project (MAOCSRAP) were fourfold: (1) complete a systematic carbon storage resource assessment of the mid-Atlantic offshore coastal region from the Georges Bank Basin (GBB) through the Long Island Platform (LIP) to the southern Baltimore Canyon Trough (BCT); (2) define key input parameters to reduce uncertainty for offshore storage resource and efficiency estimates; (3) perform a preliminary assessment of risk factors, uncertainties, and data gaps; and (4) engage industry and regulatory stakeholders through development of a Road Map to assist future project planning and implementation. The MAOCSRAP project has compiled, inventoried, and assimilated various publicly available data sets to provide a strong technical basis on which future carbon storage studies and applications can be built. The knowledge infrastructure necessary to support the development of full-scale offshore carbon storage include: Defining the geologic characteristics of candidate storage sites (Chapter 2). Using existing seismic data to better define the continuity of the storage zones and seals (Chapter 3). Cataloguing the hydrogeologic properties of mid-Atlantic offshore storage sites (Chapter 4). Calculating prospective CO 2 storage resources using net effective pore volumes and fluid displacement properties specific to offshore lithologies (Chapter 5). Examining risk factors related to offshore storage (Chapter 6). Communicating with industry and other stakeholders about the future prospects for offshore storage (Chapter 7). Ensuring technology transfer to industry and other stakeholders (Chapter 8). Led by Battelle, this project was conducted by public and private entities with expertise in offshore geology and resources for the study region, including state geological surveys of Delaware, Maryland, and Pennsylvania; United States Geological Survey-Woods Hole Coastal and Marine Science Center and Haifa University; Rutgers University; Harvard University; and Lamont-Doherty Earth Observatory (LDEO) at Columbia University. The storage resource assessment was completed for a broad region offshore of the U.S. East Coast, from Massachusetts to Virginia. The results include high-level storage resource estimates for areas not previously characterized and improved storage resource estimates for geographically expansive portions of offshore geologic units. Results of the project provide a foundation for developing CO 2 storage along offshore areas of the mid-Atlantic United States. A combination of information was used to provide confidence in project results. Key findings of the major project tasks are summarized as follows. Subsurface Data Analysis: Legacy seismic, well-log, core, and biostratigraphic data were digitized, reprocessed, and analyzed using modern techniques, augmenting previous characterization efforts. The sequence stratigraphic framework for the Cretaceous and Jurassic strata was developed by correlating well-log depositional sequences to seismic reflectors identified in the BCT, LIP, and GBB. The integration of well-log stratigraphy with seismic stratigraphy and petrophysical analysis helped to identify and map potential storage zones within sequences of the Logan Canyon (LC), Missisauga, and Mohawk formations, as well as the regionally extensive caprock comprised of the Dawson Canyon shale. Approximately 4,000 kilometers (km) of seismic data was reprocessed to create a structural framework that was used to tie together all available well data, constrain sequence stratigraphic interpretations, and make regional assessments of offshore carbon storage resources. Prospective storage resource estimates were 150 to 1136 megatons (Mt) for the combined storage zones. This suggests mid-Atlantic U.S. offshore formations can store decades of CO 2 from industrial sources in the region. Preliminary local reservoir simulations suggest that injection rates of 1 Mt CO 2 /year may be sustained for 30 years in single injection wells in the BCT. Advanced geologic modeling and new data acquisition are needed to address data gaps and advance carbon capture and storage (CCS) in key offshore areas selected for further investigation. Offshore Risk Factors: Offshore geologic risk factors include soft sediment deformation, unit continuity, sedimentological and structural features, seismicity and hydrates. CO 2 storage risks include inadequate seals, migration/leakage, and chemical interactions leading to decreased storage. Sensitive habitats, environmental impacts, disturbance to seafloor, and other risks need to be identified in advance of project activities and integrated into detailed mitigation plans for all project phases. Stakeholder Engagement: Input and participation from government, industry, and environmental groups provided input into the Road Map and address next steps needed for project deployment. Early engagement and ongoing communication, as well as policy framework development, is key to large-scale deployment of CCS. Next Steps: This project represents an important first step by completing a high-level CO 2 storage resource assessment and building the knowledge infrastructure necessary to improve quantitative storage resource estimates. The data sets that have been curated under this project provide an opportunity to conduct research and development (R&D) needed to address data gaps and reduce risk and uncertainty. Offshore characterization and validation strategies that are systematically designed to provide data and infrastructure that can be upscaled to meet commercial requirements could be developed off of this foundation.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2018

Utah FORGE: 2D and 3D Seismic Data

This set of data contains raw and Initially-processed 2D and 3D seismic data from the Utah FORGE study area near Roosevelt Hot Springs. Reprocessed versions of these data can be accessed at the linked submission in the Resources section titled "Reprocessed Seismic Reflection Data." The zipped archives numbered from 1-100 to 1001-1122 contain 3D seismic uncorrelated shot gatherers SEG-Y files. The zipped archives numbered from 1-100C to 1001-1122C contain 3D seismic correlated shot gatherers SEG-Y files. Other data have intuitive names.

15 GEOTHERMAL ENERGY↗
DOE OSTI2021

Microwave Radiometer - UND Radiometrics MWR, Rufus - Reviewed Data

Reviewed dataset that also includes post-reprocessed level1 and level2 data files from November 2015 to May 2016 (refer to "Additional Information"). Monitor real-time profiles of temperature (K), water vapor (gm-3), relative humidity (%), and liquid water (gm-3) up to 10 km.

17 WIND ENERGY↗
DOE OSTI2018

Fallon FORGE: Seismic Reflection Profiles

Newly reprocessed Naval Air Station Fallon (1994) seismic lines: pre-stack depth migrations, with interpretations to support the Fallon FORGE (Phase 2B) 3D Geologic model. Data along seven profiles (>100 km of total profile length) through and adjacent to the Fallon site were re-processed. The most up-to-date, industry-tested seismic processing techniques were utilized to improve the signal strength and coherency in the sedimentary, volcanic, and Mesozoic crystalline basement sections, in conjunction with fault diffractions in order to improve the identification and definition of faults within the study area.

15 GEOTHERMAL ENERGY↗
DOE OSTI2019

Utah FORGE: Seismic Reflection Data

This is 2D and 3D seismic reflection data from Utah FORGE reprocessed during Phase 2c. The readme file containing an explanation of the data including data formats, software that can be used, processing, and projection and datum used. The Reprocessing document gives the rationale for reprocessing and shows examples of the improvements that were obtained. For all 3D and 2D data the following datasets were created and output in SEG-Y format: - Unmigrated Time - Prestack Time Migration (PSTM), Unenhanced (UnEnh) and Enhanced (Enh) - Prestack Depth Migration (PSDM), Unenhanced (UnEnh) and Enhanced (Enh) - Velocity Model used for Migration

15 GEOTHERMAL ENERGY↗
DOE OSTI2023

Application of Principal Component Analysis to Electrochemical Reprocessing PM and NMAC

In this report, data from an electrorefiner (ER) for nuclear fuel reprocessing is evaluated for process monitoring (PM) conclusions. This data comes from tests performed at the Idaho National Laboratory in 2022. Multivariate approaches utilizing methods of Principal Component Analysis (PCA) is applied. This is based off established work in process monitoring for fault detection in industrial facilities. This report will discuss the background, methods, and results of the application and some of the conclusions and applications that can be drawn from them. PCA is applied to two different electrorefiner (ER) operations that occurred at Idaho National Laboratory between August and October 2022. The first operation occurred with little incident while the second had several noted faults in the equipment in operational logs. The data from the first run was used to train the data for “normal” operations and applied to both sets of data to determine when operations were in an “off-normal” condition and identify where the fault occurs through PCA. PCA was able to identify off-normal events and identify the cause for off-normal operations. These identified off-normal events matched with the events and their causes in the operational logs. However, small amounts of variance in the data led to false detection of “off-normal” events. Thus, careful selection of training data and a-posteriori conclusions based off operator assessments will both be required for application of PCA to PM applications. This work demonstrated that multivariate approaches and latent variables are applicable to pyroprocessing PM applications and can be further expanded in future work as quality variables such as salt concentration from sensors and sampling become available.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗