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At least 739 records · Page 41

Evaluating the Feasibility of Data Simulation for Radiation Research: Estimating RBE Values for HZE Radiation

As the drive for deep space exploration intensifies, a comprehensive understanding of the health effects of radiation exposure becomes paramount to the future of human space flight. However, epidemiological data for radiation exposure, particularly to high-energy (HZE) ions, is limited, partially due to the financial and logistical costs of radiation studies. As an alternative, this study aims to assess the viability of data simulation strategies to accurately model potential study parameters prior to utilizing laboratory conditions. This study estimates a relative biological effectiveness (RBE) factor based on the solid tumor data for outbred mice provided by Edmundson et al. 2020. Excess relative risk (ERR) models for HZE-Fe ions and gamma radiation were estimated using Poisson regression with Weibull models to represent the background solid tumor hazard without radiation. RBE values were calculated from the ratio of the heavy ion linear slope to the gamma linear slope. The parameters from these models were then applied to simulate iterations of 300 datasets across HZE-Fe doses of 0.05, 0.2, 0.4, and 0.75 Gy; gamma radiation doses of 0.75, 2, and 3 Gy, as well as an unirradiated control group. Sample size per dose varied from 100-500 mice across simulations (800-4000 mice total per dataset). 1500 datasets were generated total (300 each for sample sizes 800, 1600, 3200, and 4000). For each dataset, ERR per radiation type and RBE for HZE-Fe were calculated. The RBE from the Edmondson data was calculated to be 5.55. The RBEs from the simulated data converged around this value across the increasing sample sizes. For n = 4000, the mean RBE across the 300 datasets was 5.71 (95% CI: 5.47-5.95). These results suggest that RBEs calculated from simulated data are credible. Based on this exploration, data simulation is a viable method of testing radiation studies. It provides a method of testing study assumptions and refining research questions prior to embarking on costly laboratory experiments.

Sneha Mehta↗

Sensor-induced temporal variability of Landsat MSS data

Landsat-1 and Landsat-2 multispectral scanner (MSS) data were studied to determine the consistency of the calculated reflectance values over time. Data from six spectrally stable targets were collected over a 3-year period (1975-1977). Reflectance values calculated from the digital numbers were regressed against time to note any long term changes. Results indicate that, over a 1000-day period beginning 1 January 1975, MSS 2 reflectances were stable. MSS 1 reflectances over that same period decreased approximately 25-32 percent. The observed decreases are most likely due to a deterioration of the transmissive qualities of the Landsat-1 scanner's internal optical path. Although MSS temporal variation may be unique to MSS 1, time (days in orbit) should be considered as an independent variable when intersatellite calibration equations are computed. A case is made for a stable, monitored calibration system which would permit the calculation of true top-of-the-atmosphere reflectance measures.

Nelson, R. F.↗

UAE6 - Wind Tunnel Tests Data - UAE6 - Sequence F - Raw Data

Sequence F: Downwind High Cone (F) This test sequence used a downwind, rigid turbine with an 18° cone angle. The wind speed ranged from 10 m/s to 20 m/s. Excessive inertial loading due to the high cone angle prevented operation at lower wind speeds. Yaw angles of ±20° were achieved. The blade tip pitch was 3°. The rotor rotated at 72 RPM. Blade and probe pressure measurements were collected. The teeter dampers were replaced with rigid links, and these two channels were flagged as not applicable by setting the measured values in the data file to –99999.99 Nm. The teeter link was replaced with a shorter bar so the load cell was not installed during this test. However, the teeter link load cell channel was flagged as not applicable by setting the measured values in the data file to -99999.99 N.

17 WIND ENERGY↗

Parallel checksumming of data chunks of a shared data object using a log-structured file system

Checksum values are generated and used to verify the data integrity. A client executing in a parallel computing system stores a data chunk to a shared data object on a storage node in the parallel computing system. The client determines a checksum value for the data chunk; and provides the checksum value with the data chunk to the storage node that stores the shared object. The data chunk can be stored on the storage node with the corresponding checksum value as part of the shared object. The storage node may be part of a Parallel Log-Structured File System (PLFS), and the client may comprise, for example, a Log-Structured File System client on a compute node or burst buffer. The checksum value can be evaluated when the data chunk is read from the storage node to verify the integrity of the data that is read.

97 MATHEMATICS AND COMPUTING↗

Best Practices Guide for Energy-Efficient Data Center Design

This guide provides an overview of best practices for energy-efficient data center design which spans the categories of information technology (IT) systems and their environmental conditions, data center air management, cooling and electrical systems, and heat recovery. IT system energy efficiency and environmental conditions are presented first because measures taken in these areas have a cascading effect of secondary energy savings for the mechanical and electrical systems. This guide concludes with a section on metrics and benchmarking values by which a data center and its systems energy efficiency can be evaluated. No design guide can offer “the most energy-efficient” data center design but the guidelines that follow offer suggestions that provide efficiency benefits for a wide variety of data center scenarios.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Comparative SEM and TEM analyses of apatite phases prepared by a multi-sample loading device

Highlights: • A multi-sample loading device which ultrasonically disperses samples was developed. • Comparative EM analyses on various apatite phases were efficiently carried out. • SEM-EDS data revealed distinctive values of O/P and Ca/P intensity ratios. • TEM-SAED data presented characteristic structural features of apatite phases. • Lattice parameters of bone and fossil apatite were affected by CO{sub 3} content. - Abstract: Comparative chemical and structural characterization of various apatite phases from both synthetic and natural sources were carried out by utilizing a multi-sample loading device developed for scanning electron microscopy (SEM) and transmission electron microscopy (TEM) analyses. The device is capable of spraying nanoparticles via ultrasonication, and four separate samples were loaded on a single TEM grid by a masking tool to characterize different apatite phases in consistent instrumental and analytical conditions. SEM energy dispersive spectroscopy (EDS) analysis of the apatite samples revealed distinctive values of O/P and Ca/P intensity ratios except for the fossil apatite due to its high proportion of externally originating phases. Selected area electron diffraction (SAED) pattern analysis presented the characteristic lattice parameters of the apatite phases, especially the bone and fossil apatite which had CO{sub 3}in their chemistry. Analyzing distinctive chemical and structural features among varied apatite phases can be efficiently carried out through electron microscopy with multiple samples on a single TEM grid, and such methods can be employed for characterizing a wider range of materials.

36 MATERIALS SCIENCE↗

Real-World Driving Features for Identifying Intelligent Driver Model Parameters

Driver behavior models play a significant role in representing different driving styles and the associated relationships with traffic patterns and vehicle energy consumption in simulation studies. The models often serve as a proxy for baseline human driving when assessing energy-saving strategies that alter vehicle velocity. Such models are especially important in connectivity-enabled energy-saving strategy research because they can easily adapt to changing driving conditions like posted speed limits or change in traffic light state. While numerous driver models exist, parametric driver models provide the flexibility required to represent variability in real-world driving through different combinations of model parameters. These model parameters must be informed by a representative set of parameter values for the driver model to adequately represent a real-world driver. It stands to reason that determining the parameter values from real-world driving data would serve the purpose of representing a real-world driver. Although the published literature is replete with techniques and consequences of using real-world driving data to determine parameter values for parametric driver models, none have explored them in the context of using shorter driving features where the parameter values may change over the course of a single trip for the same driver. In this study we consider the “intelligent driver model” (IDM) as our driver behavior model and use real-world driving data from the Transportation Secure Data Center (TSDC) maintained at the National Renewable Energy Laboratory (NREL). The TSDC includes real-world travel data from across the United States, from which NREL has created a wide range of driving routes consisting of road features such as speed limits, stop locations, and turn locations. The real-world driving data are categorized into different driving regimes and extracted into driving features. The driving features are then used to calibrate the parameter values for the IDM. The distribution of the parameters and the relationships among them are reported. The insights obtained from this study enable judicious usage of IDM or similar parametric driver models to represent baseline human driver behavior in simulations.

27 ARPA - Advanced Research Projects Agency-Energy↗

Real-World Driving Features for Identifying Intelligent Driver Model Parameters: Preprint

Driver behavior models play a significant role in representing different driving styles and the associated relationships with traffic patterns and vehicle energy consumption in simulation studies. The models often serve as a proxy for baseline human driving when assessing energy-saving strategies that alter vehicle velocity. Such models are especially important in connectivity-enabled energy-saving strategy research because they can easily adapt to changing driving conditions like posted speed limits or change in traffic light state. While numerous driver models exist, parametric driver models provide the flexibility required to represent variability in real-world driving through different combinations of model parameters. These model parameters must be informed by a representative set of parameter values for the driver model to adequately represent a real-world driver. It stands to reason that determining the parameter values from real-world driving data would serve the purpose of representing a real-world driver. While the published literature is replete with techniques and consequences of using real-world driving data to determine parameter values for parametric driver models, none have explored them in the context of using shorter driving features where the parameter values may change over the course of a single trip for the same driver. In this study we consider the “Intelligent Driver Model” (IDM) as the driver behavior model to explore and real-world driving data from the Transportation Secure Data Center (TSDC) maintained at the National Renewable Energy Laboratory (NREL). The TSDC includes real-world travel data from across the United States, from which NREL has created a wide range of driving routes consisting of road features such as speed limits, stop locations and turn locations. The real-world driving data are categorized into different driving regimes and extracted into driving features. The driving features are then used to calibrate the parameter values for the IDM. The distribution of the parameters and the relationships among them are reported. The insights obtained from this study enable judicious usage of IDM or similar parametric driver models to represent baseline human driver behavior in simulations.

27 ARPA - Advanced Research Projects Agency-Energy↗

Monitoring Thermal Status of Ecosystems with MODIS Land-Surface Temperature and Vegetation Index Products

The global land-surface temperature (LST) and normalized difference vegetation index (NDVI) products retrieved from Moderate Resolution Imaging Spectroradiometer (MODIS) data in 2001 were used in this study. The yearly peak values of NDVI data at 5km grids were used to define six NDVI peak zones from -0.2 to 1 in steps of 0.2, and the monthly NDVI values at each grid were sorted in decreasing order, resulting in 12 layers of NDVI images for each of the NDVI peak zones. The mean and standard deviation of daytime LSTs and day-night LST differences at the grids corresponding to the first layer of NDVI images characterize the thermal status of terrestrial ecosystems in the NDVI peak zones. For the ecosystems in the 0.8-1 NDVI peak zone, daytime LSTs distribute from 0-35 C and day-night LST differences distribute from -2 to 22 C. The daytime LSTs and day-night LST differences corresponding to the remaining layers of NDVI images show that the growth of vegetation is limited at low and high LSTs. LSTs and NDVI may be used to monitor photosynthetic activity and drought, as shown in their applications to a flood-irrigated grassland in California and an unirrigated grassland in Nevada.

Wan, Zhengming↗

STANDARDS-BASED TECHNOLOGIES FOR EXCHANGING FATIGUE TEST DATA

Fatigue testing campaigns are a common feature in the design and operation of advanced engineering systems in the aerospace and power generation sectors. The resulting data are typically of a high inherent technical and financial value. Presently, these data are typically transferred between departments and companies by way of ad-hoc solutions reliant on obsolete or proprietary technologies, including CSV files, MS Excel® files, and PDFs. In these circumstances there is significant potential for data loss, inconsistency, and error. To address these shortcomings, there is a need for a systematic means of transferring data between different digital systems. With this in mind, a series of CEN Workshops on engineering materials data have taken place with a view to developing technologies for representing and exchanging engineering materials data. Most recently, a CEN Workshop on the topic of fatigue test data has delivered data formats derived from the ISO 12106 standard for axial strain-controlled fatigue testing. This paper describes the methodology for developing the data formats and demonstrates their use in the scope of the INCEFA PLUS project on increasing safety in nuclear power plants by covering gaps in environmental fatigue assessment.

Austin, Timothy↗

A Review of Candidates for a Validation Data Set for High-Assay Low-Enrichment Uranium Fuels

Many advanced reactor concept designs rely on high-assay low-enriched uranium (HALEU) fuel, enriched up to approximately 19.75% 235 U by weight. Efforts are underway by the US government to increase HALEU production in the United States to meet anticipated needs. However, very few data exist for validation of computational models that include HALEU, beyond a few fresh fuel benchmark specifications in the International Reactor Physics Experiment Evaluation Project. Nevertheless, there are other data with potential value available for developing into quality benchmarks for use in data- and software-validation efforts. This paper reviews the available evaluated HALEU fuel benchmarks and some of the potentially relevant benchmarks for fresh highly enriched uranium. It then introduces experimental data for HALEU fuel irradiated at Idaho National Laboratory, from relatively recent irradiation programs at the Advanced Test Reactor. Such data should be evaluated and, if valuable, collected into detailed benchmark specifications to meet the needs of HALEU-based reactor designers.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Integrating Ideas for International Data Collaborations Through The Committee on Earth Observation Satellites (CEOS) International Directory Network (IDN)

The capabilities of the International Directory Network's (IDN) version MD9.5, along with a new version of the metadata authoring tool, "docBUILDER", will be presented during the Technology and Services Subgroup session of the Working Group on Information Systems and Services (WGISS). Feedback provided through the international community has proven instrumental in positively influencing the direction of the IDN s development. The international community was instrumental in encouraging support for using the IS0 international character set that is now available through the directory. Supporting metadata descriptions in additional languages encourages extended use of the IDN. Temporal and spatial attributes often prove pivotal in the search for data. Prior to the new software release, the IDN s geospatial and temporal searches suffered from browser incompatibilities and often resulted in unreliable performance for users attempting to initiate a spatial search using a map based on aging Java applet technology. The IDN now offers an integrated Google map and date search that replaces that technology. In addition, one of the most defining characteristics in the search for data relates to the temporal and spatial resolution of the data. The ability to refine the search for data sets meeting defined resolution requirements is now possible. Data set authors are encouraged to indicate the precise resolution values for their data sets and subsequently bin these into one of the pre-selected resolution ranges. New metadata authoring tools have been well received. In response to requests for a standalone metadata authoring tool, a new shareable software package called "docBUILDER solo" will soon be released to the public. This tool permits researchers to document their data during experiments and observational periods in the field. interoperability has been enhanced through the use of the Open Archives Initiative s (OAI) Protocol for Metadata Harvesting (PMH). Harvesting of XML content through OAI-MPH has been successfully tested with several organizations. The protocol appears to be a prime candidate for sharing metadata throughout the international community. Data services for visualizing and analyzing data have become valuable assets in facilitating the use of data. Data providers are offering many of their data-related services through the directory. The IDN plans to develop a service-based architecture to further promote the use of web services. During the IDN Task Team session, ideas for further enhancements will be discussed.

Olsen, Lola M.↗

NASA R&M Efficiency through Findable, Accessible, Interoperable, and Reusable (FAIR) Digital Assets

At the intersection of mission, technology, and place is NASA’s need to modernize for a digital-forward future. Digitalization, the process of moving toward digital business, is occurring everywhere and remains an ongoing process across the federal government.”[1] Whereas, Digital Transformation is “employing digitization/digital technologies (e.g., Artificial Intelligence (AI), mobile, cloud, data) to change a process, product, or capability so dramatically (e.g., real-time, intelligent, personalized, anywhere, anytime) that it is unrecognizable compared to its traditional form.” [2] In order to facilitate a digital transformation it is essential for NASA to understand and identify where data exists today and which data are value-needed in the future, understand where there are unfulfilled data needs that limit the advancement of NASA work, and ensure NASA efficiency through Findable, Accessible, Interoperable, and Reusable (FAIR) digital assets in the future. Therefore, NASA’s Reliability & Maintainability (R&M) Enterprise Data Sharing team is working to leverage both Digitization and Digital Transformation to achieve their vision of developing an R&M data discovery framework that enables our community, our partners, and our stakeholders with the ability to efficiently, robustly, and seamlessly access information that enables real-time knowledge and model-based, analytics driven, decision-making impacting R&M. As a result the R&M Enterprise Data Sharing team has conducted a survey of its Reliability, Maintainability, and Availability (RMA) community members to identify data existence (created or used) and where there are corresponding barriers to data acquisition and/or R&M or other issues as shown within this presentation.

Digital Transformation↗

Trilateral Task Force – Reliability Analysis Supporting Mission Extension/Post Mission Disposal

At the intersection of mission, technology, and place is NASA’s need to modernize for a digital-forward future. Digitalization, the process of moving toward digital business, is occurring everywhere and remains an ongoing process across the federal government.”[1] Whereas, Digital Transformation is “employing digitization/digital technologies (e.g., Artificial Intelligence (AI), mobile, cloud, data) to change a process, product, or capability so dramatically (e.g., real-time, intelligent, personalized, anywhere, anytime) that it is unrecognizable compared to its traditional form.” [2] In order to facilitate a digital transformation it is essential for NASA to understand and identify where data exists today and which data are value-needed in the future, understand where there are unfulfilled data needs that limit the advancement of NASA work, and ensure NASA efficiency through Findable, Accessible, Interoperable, and Reusable (FAIR) digital assets in the future. Therefore, NASA’s Reliability & Maintainability (R&M) Enterprise Data Sharing team is working to leverage both Digitization and Digital Transformation to achieve their vision of developing an R&M data discovery framework that enables our community, our partners, and our stakeholders with the ability to efficiently, robustly, and seamlessly access information that enables real-time knowledge and model-based, analytics driven, decision-making impacting R&M. As a result the R&M Enterprise Data Sharing team has conducted a survey of its Reliability, Maintainability, and Availability (RMA) community members to identify data existence (created or used) and where there are corresponding barriers to data acquisition and/or R&M or other issues as shown within this presentation.

Digital Transformation, Reliability Engineering↗

Assessing the Needs of NASA's Near Real-Time Earth Observation Products

"The 2017-2027 Decadal Survey for Earth Science and Applications from Space stated that NASA's Earth Science with planned implementation of applications provides sustained earth observations for societal benefits [1]. The Decadal Survey indicated that data latency is invaluable for time-sensitive applications including disaster risk reduction, wildland fire carbon emissions quantification, real-time measurements of the state of the hydrologic systems and many more. Data latency refers to the time between earth observation and data products available to users. During the past 13 years, NASA's Land, Atmosphere Near Real-Time Capability for Earth Observing Systems (LANCE) continues to provide free access to earth observation products that are made available much quicker than routine processing allows. The latency of most LANCE data products is Near Real-time (NRT) which is defined as less than three hours from satellite observations [2]. LANCE is managed by the Earth Science Data and Information System (ESDIS) Project at NASA Goddard Space Flight Center [3], and a User Working Group (UWG) is responsible for providing guidance to LANCE. LANCE data are used by direct users and brokers who add value to the data [4]. NASA Earth Applied Sciences Program (ASP) is one of the primary users of LANCE, which collaborates with partner organizations and provides support to scientists to solve problems in applications of earth observations. ASP promotes the use of LANCE NRT data products to demonstrate applications in decision making, facilitates end-user feedback to the science team to improve data products, and provides information on future demands for research. LANCE supports applications that need a rapid response including detecting wildland fires and volcanic eruptions, tracking smoke, ash and dust plumes, monitoring air quality and tracking extreme weather events such as hurricanes, landslides, and floods. To gather feedback regarding the availability, accessibility and actionability of NASA's NRT data products for societal benefit, three surveys and a few discussions with experts involved in the topic within ASP were conducted from the perspective of users. Feedback has been collected from users who are interested in using low latency NASA data within application communities of agriculture, disasters, water resources, health and air quality, ecological conservation, wildland fires and capacity building. Analysis-ready NRT data products in a variety of formats have been mentioned many times in the collected feedback, especially for applied users with little to no experience using research-grade earth observation products. Users prefer to have products that can be easily integrated into their existing workflows and take their analysis to the data. HDF5 is a commonly used data format for research, but typically requires some conversion to a more friendly format for applications and regular use in decision-making. Users prefer the GeoTIFF data format that can be directly ingested into a GIS mapping software and platform for data analysis and visualization. For example, LANCE’s fire, flood, SO2 and Black Marble Nighttime Blue/Yellow Composite data products have been integrated into NASA Disasters Mapping Portal, which is an GIS-based open data portal, for users in the disaster management community. There are 291 LANCE NRT layers available through GIBS and Worldview, where users can download a snapshot in GeoTIFF format. Operational users expect data to be processed as close to the user as possible. The collected feedback indicates that LANCE fire products within 3 hours latency would meet the needs of the wildland fire community. The ideal latency for volcanic application is 10-15 minutes. Users in Volcanic Ash Advisory Centers (VAAC) reported that the first forecast volcanic product should be issued within 75 minutes from the volcano eruption [5]. Overall, for disaster applications, data latency within 3 hours is useful while latency greater than 12 hours is not timely enough for operational use. Capacity building and training are critical for users to be able to access, interpret and use data products and tools for their decision making, especially for applied users with limited experience using earth observation products. LANCE data products have been used in a number of capacity building projects domestically and internationally [6]. As LANCE continues to bring new products into the system, users request training to utilize LANCE new and upcoming data products and capabilities in their applications. Due to the limitation of bandwidth and downstream flow paths, users in some developing countries need tools to select and download data for a specific area of interest instead of bulk downloads. The collected feedback also shows the lack of available SAR satellite low latency data products. The advantages of SAR to monitor conditions and changes on the ground through darkness, clouds, volcanic ash, and other atmospheric conditions, are appealing to low latency users. For example, terabytes of low latency but cloudy optical images are not helpful in rapidly identifying the extent of flood or fire impacts. LANCE could be complemented with low latency measurements via the upcoming NASA-ISRO Synthetic Aperture Radar (NISAR) mission [7]. Requests for higher spatial resolution products are expressed. A user from the wildland fire management community reported that products with 30-m spatial resolution could be used to detect small fires. The 30-m Landsat OLI fire data is now part of NASA’s Fire Information for Resource Management System (FIRMS) US/Canada [8]. Within the open and free NASA resources, LANCE disseminates NRT data products in a manner that allows them to be accessible and understandable to both scientific and applied users. In many application areas, latency plays an important or even decisive role where low latency earth observations help people to observe areas of interest, detect and track changes in the environment and make timely decisions. NASA’s Earth Applied Sciences Program promotes the use of LANCE NRT products and builds a bridge between application users and research teams. The collected feedback indicates data latency within 3 hours is useful for most of the applications, and shows the needs of user-friendly, analysis-ready products, and requests training on LANCE’s new and upcoming data products. User feedback has been provided to LANCE UWG for guidance and recommendations, and for translating findings into something actionable.

Tian Yao↗

Evaluation of the 239 Pu prompt fission neutron spectrum induced by neutrons of 500 keV and associated covariances

We present evaluations of the prompt fission neutron spectrum (PFNS) of (PU)-P-239 induced by 500 keV neutrons, and associated covariances. In a previous evaluation by Talon et al. (2010), surprisingly low evaluated uncertainties were obtained, partly due to simplifying assumptions in the quantification of uncertainties from experiment and model. Therefore, special emphasis is placed here on a thorough uncertainty quantification of experimental data and of the Los Alamos model predicted values entering the evaluation. In addition, the Los Alamos model was extended and an evaluation technique was employed that takes into account the qualitative differences between normalized model predicted values and experimental shape data These improvements lead to changes in the evaluated PENS and overall larger evaluated uncertainties than in the previous work. However, these evaluated uncertainties are still smaller than those obtained in a statistical analysis using experimental information only, due to strong model correlations. Hence, suggestions to estimate model defect uncertainties are presented. which lead to more reasonable evaluated uncertainties. The calculated k(eff) of selected criticality benchmarks obtained with these new evaluations agree with each other within their uncertainties despite the different approaches to estimate model defect uncertainties. The k(eff) one standard deviations overlap with some of those obtained using ENDF/B-VILl, albeit their mean values are further away from unity. Spectral indexes for the Jezebel critical assembly calculated with the newly evaluated PFNS agree with the experimental data for selected (n,) and (n,f) reactions, and show improvements for highenergy threshold (n,2n) reactions compared to ENDF/B-VII.l. (C) 2015 Elsevier B.V. All rights reserved.

Neudecker, D.↗

Interpolating Low Time-Resolution Forecast Data

Methodology that interpolates low time-resolution data (e.g., hourly) to high time-resolution (e.g., minutely) with variability patterns extracted from historical records. Magnitude of the variability inserted into the low time resolution data can be adjusted according to the installed capacity represented by the low time-resolution data compared to that by historical records. This approach enables detailed analysis of the impacts from wind and solar on power system intra-hour operations and balancing reserve requirements even with only hourly data. It also allows convenient creation of high resolution wind or solar generation data with various degree of variability to investigate their operational impacts. The methodology comprises of the following steps: 1. Smooth the historical data (set A) with an appropriate window length l to get its trend (set B); l can be a fraction of an hour (e.g., 15 minutes) or longer than an hour, of which the length of the variability patterns will be; 2. Extract the variable component (set C) of historical data by subtracting the smooth trend from it, i.e. set C = set A - set B 3. For each window length l of the variable component data set, find the average value x (will call it base component) of the corresponding window of the historical data set; 4. Define a series of segments (set D) that the values of data will be grouped into, e.g. (0, 0.1), (0.1, 0.2), ..., (0.9, 1.0) after normalization; Link each variability pattern to a data segment based on its corresponding base component x; after this step, each data segment should be linked to multiple variability patterns after this step; 5. Use spline function to interpolate the low time-resolution forecast data (set E) to become a high time-resolution smooth curve (set F); 6. Based on the window length l , calculate the average value y in each window length of set F; find the data segment that y belongs to; then randomly select one of the variability patterns linked to this data segment; 7. Add the selected variability pattern in each window to set F to get the high time-resolution data (set G) with variability observed from historical data set A; a coefficient k can be multiplied to the selected variability pattern to reflect the potential difference in variability between forecast set E and historical data set A caused by installation capacity and other factors. 8. After set G is constructed, variability statistics can be checked for set A and set G for comparison. Adjust the coefficient k if necessary to achieve desired variability in the reconstructed data.

Lu, Shuai↗

Experimental Technetium Release from Simulated Salt-stone Cementitious Waste Form - 18419

Experiments are being conducted to evaluate the early release of technetium (Tc) from fresh salt-stone waste forms using dynamic flow-through tests. Salt-stone is a chemically reducing, grout-based waste form used by the U.S. Department of Energy (DOE) to dispose of low-activity salt solutions arising from high-level radioactive waste tank closure activities at the Savannah River Site (SRS). A key safety function of salt-stone is maintaining a low-flow, chemically reducing environment that will attenuate the release of redox-sensitive radioelements such as Tc. Salt-stone also provides a physical barrier due to its low intrinsic permeability, which limits both water and oxygen ingress. These release experiments, conducted to support the U.S. Nuclear Regulatory Commission's monitoring role during tank closure, are designed to provide independent information on how well salt-stone will perform its safety function. The dynamic leach tests were conducted in a Hassler-type core-holder permeameter system that allows an accelerated flow rate of simulated SRS groundwater through an intact cylinder of salt-stone spiked with Tc-99 at a concentration of approximately 2,100 Bq/g (3 ppm). The first salt-stone specimen to be tested (Specimen 2) was prepared with Grade 100 ground granulated blast-furnace slag and aged for 119 days in a temperature-controlled, low-oxygen, high-humidity environment. Before test completion, 9.5 pore volumes (PV) of simulated SRS groundwater were passed through the salt-stone cylinder. After a few PV, apparent saturated hydraulic conductivity (K{sub sat}) values calculated from flow data reached a steady-state value of approximately 1.0 x 10{sup -9} cm/s, which is within the range of previously reported data. Tc-99 concentrations in leachate peaked early during the leach test at 2.0 x 10{sup -7} M and then declined to approximately 4 x 10{sup -8} M after 9.5 PV. The leachate Tc-99 concentration after elution of 9.5 PV is broadly consistent with a Tc solution concentration controlled by the solubility of reduced Tc solids. The range of Tc-99 concentrations is similar to the range reported for a column test that was sponsored by DOE, but the time pattern of release differs. The second salt-stone specimen tested (Specimen 3) was aged for 372 days and it further differed from the first specimen in that its Grade 100 slag component had been finely ground using a mortar and pestle in an attempt to make it more reactive. This second test yielded Tc release behavior broadly similar to that observed during the first test, except that the early Tc peak (at 1.2 x 10{sup -6} M) was six times higher and the concentration after 6.7 PV (8.8 x 10{sup -8} M) was approximately two times higher than in the first test. In addition, the steady-state K{sub sat} was an order of magnitude lower than that of the first specimen. During the second test, the injection pump was intentionally turned off for a period of 11 days (i.e., approximate residence time for 1 PV) and a Tc spike was observed when pumping resumed, suggesting that longer residence times may promote higher Tc effluent concentrations. During a second intentional shut-down of the pump for 25 days (approximate residence time for 2 PV), another Tc spike was observed. An unplanned excursion to higher confining pressure physically affected the specimen, temporarily lowering the apparent K{sub sat} followed by a subsequent increase in both K{sub sat} and Tc effluent concentration. One hypothesis is that the transient spike in confining pressure and resulting salt-stone compression and later decompression may have induced Tc release from otherwise inactive pores. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗