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At least 541 records · Page 30

Distributing Data to Hand-Held Devices in a Wireless Network

ADROIT is a developmental computer program for real-time distribution of complex data streams for display on Web-enabled, portable terminals held by members of an operational team of a spacecraft-command-and-control center who may be located away from the center. Examples of such terminals include personal data assistants, laptop computers, and cellular telephones. ADROIT would make it unnecessary to equip each terminal with platform- specific software for access to the data streams or with software that implements the information-sharing protocol used to deliver telemetry data to clients in the center. ADROIT is a combination of middleware plus software specific to the center. (Middleware enables one application program to communicate with another by performing such functions as conversion, translation, consolidation, and/or integration.) ADROIT translates a data stream (voice, video, or alphanumerical data) from the center into Extensible Markup Language, effectuates a subscription process to determine who gets what data when, and presents the data to each user in real time. Thus, ADROIT is expected to enable distribution of operations and to reduce the cost of operations by reducing the number of persons required to be in the center.

Hodges, Mark↗

New Total-Ionizing-Dose Resistant Data Storing Technique for NAND Flash Memory

This paper describes a new non-charge-based data storing technique in NAND flash memory called watermark that encodes read-only data in the form of physical properties of flash memory cells. Unlike traditional charge-based data storing method in flash memory, the proposed technique is resistant to total ionizing dose (TID) effects. To evaluate its resistance to irradiation effects, we analyze data stored in several commercial single-level-cell (SLC) flash memory chips from different vendors and technology nodes. These chips are irradiated using a Co-60 gamma-ray source array for up to 100 krad(Si) at Sandia National Laboratories. Experimental evaluation performed on a flash chip from Samsung shows that the intrinsic bit error rate (BER) of watermark increases from 0.8% for TID = 0 krad(Si) to 1% for TID = 100 krad(Si). Conversely, the BER of charge-based data stored on the same chip increases from 0% at TID = 0 krad(Si) to 1.5% at TID = 100 krad(Si). Overall, the results imply that the proposed technique may potentially offer significant improvements in data integrity relative to traditional charge-based data storage for very high radiation (TID > 100 krad(Si)) environments. These gains in data integrity relative to the charge-based data storage are useful in radiation-prone environments, but they come at the cost of increased write times and higher BERs before irradiation.

36 MATERIALS SCIENCE↗

The international research reactor conversion effort and its contribution to the validation of reactor physics and thermal-hydraulics codes

Full text of publication follows. With about 200 reactors in operation, civilian Research and Test Reactors (RTRs) represent approximately a third of the global nuclear fleet. RTRs make use of core designs that are drastically different from commercial power plants to perform a wide variety of non-power applications that greatly benefit society. Because they often rely on high neutron fluxes, RTRs are designed with relatively compact cores and as a result, prior to the 1980's, were often deployed using Highly Enriched Uranium fuel (HEU, {sup 235}U/U = 20 wt. %). Due to proliferation concerns, the international community aims at eliminating the use of HEU in civilian facilities and favor instead the use of Low Enriched Uranium fuel (LEU, {sup 235}U/U < 20 wt. %). A program to support conversion of the world's RTRs to LEU fuel has been initiated in 1978 by the U.S. Department of Energy (DOE). This program is still alive today and has achieved more than 103 conversion metrics. Today, the program focuses heavily on the conversion of so-called high-performance RTRs, which are far more challenging than previous conversions as they require new fuel element designs and the use of new, higher density LEU fuel forms. Development and qualification of new LEU fuel elements is ongoing and requires extensive engineering analysis and testing. Both activities require the development and validation of codes and methods for reactor physics, thermal-hydraulics, and multi-physics, which in turn rely on experiments performed in RTRs or other experimental facilities. This talk will present the collection of RTR experimental data and benchmark analyses from the international conversion program that contribute to the validation of computer codes and methods.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Precision Plant Biomass Characterization in Agriculture: Harnessing Machine Learning and Hyperspectral Imaging [Slides]

Efficient Biomass Separation Object detection of anatomical parts (Cob, Stalk, Husk) in IR images enables precise separation, improving preprocessing (e.g., drying, grinding) for biofuel production. Detailed Biomass Characterization with Hyperspectral Data Hyperspectral imaging captures spectral signatures of biomass, allowing for the identification of specific traits like moisture content, lignin levels, and nutrient composition, leading to optimized treatments for each biomass part. Enhanced Feedstock Quality By leveraging hyperspectral data, feedstock can be processed based on its chemical composition, improving conversion efficiency and biofuel yield. Automation for Large-Scale Operations Automated object detection and hyperspectral data analysis reduce manual labor, ensuring accurate sorting and faster processing, making large-scale biofuel production more efficient. Maximized Biomass Utilization Accurate identification of biomass properties minimizes waste and ensures that each part is processed according to its highest biofuel potential.

09 BIOMASS FUELS↗

Acquisition of and Access to Research Omics Data

Omics data are essential for understanding the myriad and complex effects of space environments on humans. To assure maximum benefit from these kinds of data, the NASA Human Research Program Data Management Plan stipulates that human omics data should be archived within and accessed through the NASA Life Sciences Portal (NLSP). The NLSP has the capability to acquire and provision access to omics (and other kinds of) research results for individual and ad-hoc groups of subjects at the direction of institutional review boards, or other authorizing bodies or individuals, per institutional, program and investigation-specific policies and procedures. However, because some single-subject omics data, like CT scans and other kinds of large, complex biomedical data, could be used to identify heretofore unknown risks to the subject’s health, or, in certain cases, be used to identify a subject, NASA Policy Directive 7170.1 describes various policies regarding the management of and access to “research genetic testing” data, which includes many kinds of omics data. For example, NPD 7170.1 prohibits access to human research genetic data by NASA personnel who make employment decisions for the subjects from whom the data were obtained. To meet the objective of acquiring research omics data for NLSP in compliance with the policies in NPD 7170.1 and other applicable NASA policies, we designed NOMADS (the NLSP Omics Multimodal Acquisition of Data System), a new component that supports the transfer of large research data files, including research genetic testing data, using one of several different transfer mechanisms. The choice of mechanism is made by the submitter of the data, with guiding information from the system, and is likely to often be determined in large part by the nature and source location of the data. For example, for small files where the source data files are not already stored in a cloud storage system, users are likely to prefer to transfer their data to the NLSP via a web browser. Conversely, for large sets of files already organized and stored in a cloud storage system, users may opt for NOMAD’s cloud-to-cloud transfer method. All omics datasets targeted for the NASA Life Sciences Data Archive must pass a variety of quality checks to ensure data integrity and adherence to the standards defined by the LSDA Data Submission Guidelines (DSG) (see https://nlsp.nasa.gov/explore/lsdahome/datasubmit). These include requirements that data are consistent with open standards established by the omics community. Non-compliant data will not be accepted however archivists are available to advise submitters on how to revise data submissions and re-submit until compliance is achieved. Following compliance with the LSDA DSG, omics data next undergo a variety of additional quality checks to ensure the data meet omics community standards. Domain specific Omics data quality control tools and techniques are continually evolving and linked to the advancements in omics assays utilized and thus, the tools and techniques utilized by the LSDA for data quality control and validation will need to be sustained accordingly. All human omics data will be access controlled according to the policies described above, and requiring IRB approval for any additional access grants once the data are acquired (including access for analysis using the NLSP workspace tools).

Omics↗

Acquisition of and Access to Research Omics Data

Omics data are essential for understanding the myriad and complex effects of space environments on humans. To assure maximum benefit from these kinds of data, the NASA Human Research Program Data Management Plan stipulates that human omics data should be archived within and accessed through the NASA Life Sciences Portal (NLSP). The NLSP has the capability to acquire and provision access to omics (and other kinds of) research results for individual and ad-hoc groups of subjects at the direction of institutional review boards, or other authorizing bodies or individuals, per institutional, program and investigation-specific policies and procedures. However, because some single-subject omics data, like CT scans and other kinds of large, complex biomedical data, could be used to identify heretofore unknown risks to the subject’s health, or, in certain cases, be used to identify a subject, NASA Policy Directive 7170.1 describes various policies regarding the management of and access to “research genetic testing” data, which includes many kinds of omics data. For example, NPD 7170.1 prohibits access to human research genetic data by NASA personnel who make employment decisions for the subjects from whom the data were obtained. To meet the objective of acquiring research omics data for NLSP in compliance with the policies in NPD 7170.1 and other applicable NASA policies, we designed NOMADS (the NLSP Omics Multimodal Acquisition of Data System), a new component that supports the transfer of large research data files, including research genetic testing data, using one of several different transfer mechanisms. The choice of mechanism is made by the submitter of the data, with guiding information from the system, and is likely to often be determined in large part by the nature and source location of the data. For example, for small files where the source data files are not already stored in a cloud storage system, users are likely to prefer to transfer their data to the NLSP via a web browser. Conversely, for large sets of files already organized and stored in a cloud storage system, users may opt for NOMAD’s cloud-to-cloud transfer method. All omics datasets targeted for the NASA Life Sciences Data Archive must pass a variety of quality checks to ensure data integrity and adherence to the standards defined by the LSDA Data Submission Guidelines (DSG) (see https://nlsp.nasa.gov/explore/lsdahome/datasubmit). These include requirements that data are consistent with open standards established by the omics community. Non-compliant data will not be accepted however archivists are available to advise submitters on how to revise data submissions and re-submit until compliance is achieved. Following compliance with the LSDA DSG, omics data next undergo a variety of additional quality checks to ensure the data meet omics community standards. Domain specific Omics data quality control tools and techniques are continually evolving and linked to the advancements in omics assays utilized and thus, the tools and techniques utilized by the LSDA for data quality control and validation will need to be sustained accordingly. All human omics data will be access controlled according to the policies described above, and requiring IRB approval for any additional access grants once the data are acquired (including access for analysis using the NLSP workspace tools).

Omics↗

Application of Low-Cost Fine Particulate Mass Monitors to Convert Satellite Aerosol Optical Depth Measurements to Surface Concentrations in North America and Africa

Low-cost particulate mass sensors provide opportunities to assess air quality at unprecedented spatial and temporal resolutions. Established traditional monitoring networks have limited spatial resolution and are simply absent in many major cities across sub-Saharan Africa (SSA). Satellites provide snapshots of regional air pollution but require ground-truthing. Low-cost monitors can supplement and extend data coverage from these sources worldwide, providing a better overall air quality picture. We investigate the utility of such a multi-source data integration approach using two case studies. First, in Pittsburgh, Pennsylvania, both traditional monitoring and dense low-cost sensor networks are compared with satellite aerosol optical depth (AOD) data from NASA's MODIS system, and a linear conversion factor is developed to convert AOD to surface fine particulate matter mass concentration (as PM2.5). With 10 or more ground monitors in Pittsburgh, there is a 2-fold reduction in surface PM2.5 estimation mean absolute error compared to using only a single ground monitor. Second, we assess the ability of combined regional-scale satellite retrievals and local-scale low-cost sensor measurements to improve surface PM2.5 estimation at several urban sites in SSA. In Rwanda, we find that combining local ground monitoring information with satellite data provides a 40 % improvement in surface PM2.5 estimation accuracy with respect to using low-cost ground monitoring data alone. A linear AOD-to-surface-PM2.5 conversion factor developed in Kigali, Rwanda, did not generalize well to other parts of SSA and varied seasonally for the same location, emphasizing the need for ongoing and localized ground-based monitoring, which can be facilitated by low-cost sensors. Overall, we find that combining ground-based low-cost sensor and satellite data, even without including additional meteorological or land use information, can improve and expand spatiotemporal air quality data coverage, especially in data-sparse regions.

AOD↗

An updated estimate of the Mu2e experiment sensitivity

The Mu2e experiment at Fermilab will search for the conversion of a negative muon into an electron inside the field of a nucleus. This process does not conserve charged-lepton flavour and is heavily suppressed in the Standard Model (SM), with a branching ratio < 10-50. Any evidence of it would be an undeniable evidence of new physics beyond the SM. The project sets out to achieve a single event sensitivity of $\sim 3 × 10^{-17}$ on the ratio between the probability for a conversion of a negative muon into an electron and the one for a muon capture by the nucleus. Such a sensitivity would represent a 4 orders of magnitude improvement on the previous upper limit for the process, making possible to test predictions of different extensions of the SM. Mu2e uses three superconducting solenoids to produce and measure the muon conversions. In the first solenoid, the Production Solenoid, pions and kaons are produced, together with other secondary products, by 8 GeV kinetic energy proton interactions in a tungsten target. A gradient magnetic field is specifically designed to direct low momentum particles into the Transport Solenoid, an S-shaped magnet that filters out particles with unwanted charge and momentum. Muons, produced by pion and kaon decays, finally reach the aluminum Stopping Target in the Detector Solenoid, where they eventually stop and convert. The result of the conversion process is a monochromatic electron of ~105 MeV/c momentum. The Detector Solenoid also hosts the two main detectors: a straw tube tracker and two CsI calorimeter disks, both providing measurement of event kinematics. A germanium detector and a LaBr crystal are located downstream of the Detector Solenoid to measure the X and gamma rays produced by the muon captures in the Stopping Target. A veto system of scintillators covering the Detector Solenoid and half of the Transport Solenoid is used to identify and reject cosmic rays interactions. With respect to the initial project, the Mu2e running plan has evolved to a staged configuration with 2 years at reduced intensity before the 2025 accelerator shutdown for the neutrino beam upgrade and 2 or 3 years at full intensity after that. This, together with geometry changes and a better knowledge of detector performances obtained by the first slice tests, has required a full revision of the signal over background selection that is the subject of this thesis. In order to achieve a new estimate of Mu2e sensitivity, the simulation of the data corresponding to the first 2 years of data acquisition has been performed. This includes both conversion electrons (CE) and the main sources of background: cosmics, decay-in orbits (DIO), radiative pion captures (RPC) and antiprotons. The characteristics of the signal and of the main backgrounds have been studied to define the best selection variables for CE. A special effort has been devoted to the evaluation of the antiproton background. The lack of experimental data for antiproton production cross section makes the systematic uncertainty on this background significant. A new parameterization of the cross section has been developed to fit the existing data and to provide a more reliable estimate of the systematic uncertainty by comparing the results of the old and the new model. A special effort has been devoted to the optimization of the antiprotons Monte Carlo generator. This study has also revealed that the dominant component within this background is represented by antiprotons produced in the opposite direction with respect to the Transport Solenoid entrance and then redirected to it by back-scattering processes in the Production Target. This ultimately highlights the sensitivity of the background estimate to the G4 handling of antiproton interactions in the 1 to 3 GeV/c momentum range. Finally, the final experimental sensitivity has been studied. The momentum and time selection have been optimized to obtain the 5-sigma discovery reach or, in case of no signal, the upper limit on conversion probability. The results confirm that, in the firs t two years of data taking, Mu2e will be able to improve the current experimental sensitivity for muon-to-electron conversion in an atomic field by more than 3 order of magnitudes.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Space Shuttle data acquisition and processing

The techniques of minimizing the amount of Space Shuttle data processed by using real-time ground data and on board computer to prescreen the data are presented. With the advent of long duration space flight and the large amounts of data generated, it became necessary to limit the amount of data to be processed and also to present data in a manner that highlights the most important data. The Shuttle operational data system with output of 128 kilobits/sec, the developmental flight instrumentation system, and screening of data by the analysts, flight crew, or onboard computers is described, noting that by using these monitoring methods the mission evaluation team can rapidly determine time periods for which postflight data processing is required. Postflight processing systems, batch system output products, data compression techniques, the interactive computer system, and the special telemetry conversion system are discussed, and it is concluded that the combination of Shuttle on board and ground data processing systems enhances the ability to perform a functional evaluation of the Space Shuttle vehicle.

Foster, G. B., Jr.↗

Earth-Based Ring Occultation to the PDS Rings Node

The major task of this work has been to collect, document, and translate a wide variety of occultation data sets to a common format. This work has been completed. Table I lists the 1977-1987 Uranus occultation data sets that have been retrieved and which are ready for conversion to the PDS occultation standard format, once it has been standardized. The primary documentation and original data tapes for these occultations are part of the MIT data archive, and will be submitted to the PDS from MIT. I have been in contact with Jim Elliot and Steve McDonald, who are carrying out this work, and they have informed me that some of the original data tapes have bad blocks in them. As called upon, I will continue to provide the MIT group with whatever information they require in order that the most complete versions of the data sets be provided to the PDS. 2. All data sets from MIT NOVA disk platters were transcribed to Exabyte tapes, and software was written to enable the NOVA binary data formats to be converted to IEEE standard format. The number of these files which will be contributed to the PDS will depend on the success of the MIT group in reading the original data tapes for the events recorded on these disk platters. As needed, I will supply the MIT group with translated versions of these salvaged files for submission to the PDS. 3. The imaging observations from McDonald and Lick Observatories have been calibrated in both radius and optical depth, and are available in simple binary format. 4. Final submission of the Uranus ring data sets to the PDS is awaiting final agreement by the Rings Node Advisory Council on the PDS FITS format to be adopted for occultation data set.

French, Richard G.↗

Community-Based Services that Facilitate Interoperability and Intercomparison of Precipitation Datasets from Multiple Sources

Over the past 12 years, large volumes of precipitation data have been generated from space-based observatories (e.g., TRMM), merging of data products (e.g., gridded 3B42), models (e.g., GMAO), climatologies (e.g., Chang SSM/I derived rain indices), field campaigns, and ground-based measuring stations. The science research, applications, and education communities have greatly benefited from the unrestricted availability of these data from the Goddard Earth Sciences Data and Information Services Center (GES DISC) and, in particular, the services tailored toward precipitation data access and usability. In addition, tools and services that are responsive to the expressed evolving needs of the precipitation data user communities have been developed at the Precipitation Data and Information Services Center (PDISC) (http://disc.gsfc.nasa.gov/precipitation or google NASA PDISC), located at the GES DISC, to provide users with quick data exploration and access capabilities. In recent years, data management and access services have become increasingly sophisticated, such that they now afford researchers, particularly those interested in multi-data set science analysis and/or data validation, the ability to homogenize data sets, in order to apply multi-variant, comparison, and evaluation functions. Included in these services is the ability to capture data quality and data provenance. These interoperability services can be directly applied to future data sets, such as those from the Global Precipitation Measurement (GPM) mission. This presentation describes the data sets and services at the PDISC that are currently used by precipitation science and applications researchers, and which will be enhanced in preparation for GPM and associated multi-sensor data research. Specifically, the GES-DISC Interactive Online Visualization ANd aNalysis Infrastructure (Giovanni) will be illustrated. Giovanni enables scientific exploration of Earth science data without researchers having to perform the complicated data access and match-up processes. In addition, PDISC tool and service capabilities being adapted for GPM data will be described, including the Google-like Mirador data search and access engine; semantic technology to help manage large amounts of multi-sensor data and their relationships; data access through various Web services (e.g., OPeNDAP, GDS, WMS, WCS); conversion to various formats (e.g., netCDF, HDF, KML (for Google Earth)); visualization and analysis of Level 2 data profiles and maps; parameter and spatial subsetting; time and temporal aggregation; regridding; data version control and provenance; continuous archive verification; and expertise in data-related standards and interoperability. The goal of providing these services is to further the progress towards a common framework by which data analysis/validation can be more easily accomplished.

Liu, Zhong↗

Cogeneration Technology Alternatives Study (CTAS). Volume 3: Energy conversion system characteristics

Six current and thirty-six advanced energy conversion systems were defined and combined with appropriate balance of plant equipment. Twenty-six industrial processes were selected from among the high energy consuming industries to serve as a frame work for the study. Each conversion system was analyzed as a cogenerator with each industrial plant. Fuel consumption, costs, and environmental intrusion were evaluated and compared to corresponding traditional values. The advanced energy conversion technologies indicated reduced fuel consumption, costs, and emissions. Fuel energy savings of 10 to 25 percent were predicted compared to traditional on site furnaces and utility electricity. With the variety of industrial requirements, each advanced technology had attractive applications. Fuel cells indicated the greatest fuel energy savings and emission reductions. Gas turbines and combined cycles indicated high overall annual savings. Steam turbines and gas turbines produced high estimated returns. In some applications, diesels were most efficient. The advanced technologies used coal derived fuels, or coal with advanced fluid bed combustion or on site gasifications. Data and information for both current and advanced energy conversion technology are presented. Schematic and physical descriptions, performance data, equipment cost estimates, and predicted emissions are included. Technical developments which are needed to achieve commercialization in the 1985-2000 period are identified.

Source record↗

El Chichon eruption cloud - Comparison of lidar and optical thickness measurements for October 1982

Sun photometer and lidar backscatter measurements of the El Chichon volcanic cloud were obtained during an airborne latitude survey. The observations were collected between 46 deg N and 46 deg S from Oct. 19-Nov. 7, 1982. Comparisons between these data sets have been performed. An aerosol optical model was developed for the conversion of the lidar measurements to optical thickness values using numerical aerosol size distribution data and index of refraction information collected with coordinated dustsonde balloon flights. The derived lidar optical thickness values were found to agree with the sun photometer optical thickness values within measurement uncertainties. The lidar derived values ranged from 0.16 at the equator to 0.03 at 30 deg S latitude. Peak values were concentrated between 35 deg N and 10 deg S.

Swissler, T. J.↗

Natural Resource Information System. Volume 2: System operating procedures and instructions

A total computer software system description is provided for the prototype Natural Resource Information System designed to store, process, and display data of maximum usefulness to land management decision making. Program modules are described, as are the computer file design, file updating methods, digitizing process, and paper tape conversion to magnetic tape. Operating instructions for the system, data output, printed output, and graphic output are also discussed.

Source record↗

25th Space Simulation Conference. Environmental Testing: The Earth-Space Connection

Topics covered include: Methods of Helium Injection and Removal for Heat Transfer Augmentation; The ESA Large Space Simulator Mechanical Ground Support Equipment for Spacecraft Testing; Temperature Stability and Control Requirements for Thermal Vacuum/Thermal Balance Testing of the Aquarius Radiometer; The Liquid Nitrogen System for Chamber A: A Change from Original Forced Flow Design to a Natural Flow (Thermo Siphon) System; Return to Mercury: A Comparison of Solar Simulation and Flight Data for the MESSENGER Spacecraft; Floating Pressure Conversion and Equipment Upgrades of Two 3.5kw, 20k, Helium Refrigerators; Affect of Air Leakage into a Thermal-Vacuum Chamber on Helium Refrigeration Heat Load; Special ISO Class 6 Cleanroom for the Lunar Reconnaissance Orbiter (LRO) Project; A State-of-the-Art Contamination Effects Research and Test Facility Martian Dust Simulator; Cleanroom Design Practices and Their Influence on Particle Counts; Extra Terrestrial Environmental Chamber Design; Contamination Sources Effects Analysis (CSEA) - A Tool to Balance Cost/Schedule While Managing Facility Availability; SES and Acoustics at GSFC; HST Super Lightweight Interchangeable Carrier (SLIC) Static Test; Virtual Shaker Testing: Simulation Technology Improves Vibration Test Performance; Estimating Shock Spectra: Extensions beyond GEVS; Structural Dynamic Analysis of a Spacecraft Multi-DOF Shaker Table; Direct Field Acoustic Testing; Manufacture of Cryoshroud Surfaces for Space Simulation Chambers; The New LOTIS Test Facility; Thermal Vacuum Control Systems Options for Test Facilities; Extremely High Vacuum Chamber for Low Outgassing Processing at NASA Goddard; Precision Cleaning - Path to Premier; The New Anechoic Shielded Chambers Designed for Space and Commercial Applications at LIT; Extraction of Thermal Performance Values from Samples in the Lunar Dust Adhesion Bell Jar; Thermal (Silicon Diode) Data Acquisition System; Aquarius's Instrument Science Data System (ISDS) Automated to Acquire, Process, Trend Data and Produce Radiometric System Assessment Reports; Exhaustive Thresholds and Resistance Checkpoints; Reconfigurable HIL Testing of Earth Satellites; FPGA Control System for the Automated Test of MicroShutters; Ongoing Capabilities and Developments of Re-Entry Plasma Ground Tests at EADS-ASTRIUM; Operationally Responsive Space Standard Bus Battery Thermal Balance Testing and Heat Dissipation Analysis; Galileo - The Serial-Production AIT Challenge; The Space Systems Environmental Test Facility Database (SSETFD), Website Development Status; Simulated Reentry Heating by Torching; Micro-Vibration Measurements on Thermally Loaded Multi-Layer Insulation Samples in Vacuum; High Temperature Life Testing of 80Ni-20Cr Wire in a Simulated Mars Atmosphere for the Sample Analysis at Mars (SAM) Instrument Suit Gas Processing System (GPS) Carbon Dioxide Scrubber; The Planning and Implementation of Test Facility Improvements; and Development of a Silicon Carbide Molecular Beam Nozzle for Simulation Planetary Flybys and Low-Earth Orbit.

Packard, Edward↗

Reliability of Copper Inverse Opal Surfaces for Extreme-Heat-Flux Micro-Coolers in Low-Global-Warming-Potential Refrigerant R-1233zd Pool Boiling Experiments

This presentation provides a brief snapshot of the InterPACK paper InterPACK2023-113781. The paper explores copper inverse opal (CIO) surface reliability in pool boiling experiments in water and a new, low-global-warming-potential (GWP = 1) hydrofluoroolefin (HFO) refrigerant R-1233zd. The CIO-based structure is intended to develop enhanced two-phase heat transfer surfaces for extreme-heat-flux (approximately 1 kW/cm2) micro-coolers. In this study, a limited number of pool boiling experiments were performed using water and HFO-1233zd fluid, and the reliability of the CIO-based surfaces was evaluated. Critical heat flux (CHF) values in HFO-1233zd at 40 Degrees Celsius to 45 Degrees Celsius saturation temperatures and the corresponding saturation pressures were also measured. The CHF values with the refrigerant are significantly lower compared to those with water, but the refrigerant allows for a wider usable temperature range in the end application of the micro-coolers and is not limited to data centers with controlled ambient conditions. Reliability experiments with CIO surface samples - involving pool boiling with water on the CIO surfaces for approximately 48 hours and with HFO-1233zd for 144 hours - showed no structural degradation of the enhanced surface or any significant performance drop in heat transfer coefficients. The CIO surface samples in water were oxidized, most likely due to the presence of air in water and in the experimental vessel.

critical heat flux↗

VA Determinants of Health Data Curation Documentation FY25-Q2

The U.S. Department of Veterans Affairs (VA) places the health and well-being of our nation’s veterans as its top priority. VA is dedicated to offering timely access to high-quality, evidence-based mental health care that meets the needs of veterans and supports their reintegration into society. One of our core missions is to prevent suicide among veterans through innovative approaches and resources. With funding from the VA Office of Mental Health and Suicide Prevention (OMHSP), the Determinants of Health (EDH) project has developed innovative datasets associated with specific health outcomes, a methodology for transforming spatiotemporal data from one spatial reference (e.g., a 1km grid) to another (e.g., US Census Tracts), and capabilities for modeling health outcomes. These datasets represent an enhancement of the Agency for Healthcare Research and Quality (AHRQ), addressing key gaps by introducing finer spatial resolution (Census Tract) and additional geographical covariates into existing data. The curation and standardization of these datasets is a complex task since they often originate from various sources and are measured at different spatial and temporal resolutions. For example, US Census data products typically use census blocks, block groups, or counties, while data like weather data are available on 1km grids. Some economic data may only be available at the zip code level. In this context, ‘standardized’ means that all datasets share the same spatial extent (e.g., US Census Tract and/or County), and ‘curated’ implies a repeatable process with data provenance and the use of appropriate methodologies for covariate conversion. The Determinants of Health datasets draw from multiple sources, resulting in variables with varying degrees of availability, patterns of missing data, and methodological considerations across different sources, geographies, and years.

97 MATHEMATICS AND COMPUTING↗

VA Determinants of Health Data Curation Documentation FY25-Q3

The U.S. Department of Veterans Affairs (VA) places the health and well-being of our nation’s veterans as its top priority. VA is dedicated to offering timely access to high-quality, evidence-based mental health care that meets the needs of veterans and supports their reintegration into society. One of our core missions is to prevent suicide among veterans through innovative approaches and resources. With funding from the VA Office of Mental Health and Suicide Prevention (OMHSP), the Determinants of Health (EDH) project has developed innovative datasets associated with specific health outcomes, a methodology for transforming spatiotemporal data from one spatial reference (e.g., a 1km grid) to another (e.g., US Census Tracts), and capabilities for modeling health outcomes. These datasets represent an enhancement of the Agency for Healthcare Research and Quality (AHRQ), addressing key gaps by introducing finer spatial resolution (Census Tract) and additional geographical covariates into existing data. The curation and standardization of these datasets is a complex task since they often originate from various sources and are measured at different spatial and temporal resolutions. For example, US Census data products typically use census blocks, block groups, or counties, while data like weather data are available on 1km grids. Some economic data may only be available at the zip code level. In this context, ‘standardized’ means that all datasets share the same spatial extent (e.g., US Census Tract and/or County), and ‘curated’ implies a repeatable process with data provenance and the use of appropriate methodologies for covariate conversion. The Determinants of Health datasets draw from multiple sources, resulting in variables with varying degrees of availability, patterns of missing data, and methodological considerations across different sources, geographies, and years.

97 MATHEMATICS AND COMPUTING↗