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NASA NTRS2002

Novel Advancements in Internet-Based Real Time Data Technologies

AZ Technology has been working with MSFC Ground Systems Department to find ways to make it easier for remote experimenters (RPI's) to monitor their International Space Station (ISS) payloads in real-time from anywhere using standard/familiar devices. AZ Technology was awarded an SBIR Phase I grant to research the technologies behind and advancements of distributing live ISS data across the Internet. That research resulted in a product called "EZStream" which is in use on several ISS-related projects. Although the initial implementation is geared toward ISS, the architecture and lessons learned are applicable to other space-related programs. This paper presents the high-level architecture and components that make up EZStream. A combination of commercial-off-the-shelf (COTS) and custom components were used and their interaction will be discussed. The server is powered by Apache's Jakarta-Tomcat web server/servlet engine. User accounts are maintained in a My SQL database. Both Tomcat and MySQL are Open Source products. When used for ISS, EZStream pulls the live data directly from NASA's Telescience Resource Kit (TReK) API. TReK parses the ISS data stream into individual measurement parameters and performs on-the- fly engineering unit conversion and range checking before passing the data to EZStream for distribution. TReK is provided by NASA at no charge to ISS experimenters. By using a combination of well established Open Source, NASA-supplied. and AZ Technology-developed components, operations using EZStream are robust and economical. Security over the Internet is a major concern on most space programs. This paper describes how EZStream provides for secure connection to and transmission of space- related data over the public Internet. Display pages that show sensitive data can be placed under access control by EZStream. Users are required to login before being allowed to pull up those web pages. To enhance security, the EZStream client/server data transmissions can be encrypted to preclude interception. EZStream was developed to make use of a host of standard platforms and protocols. Each are discussed in detail in this paper. The I3ZStream server is written as Java Servlets. This allows different platforms (i.e. Windows, Unix, Linux . Mac) to host the server portion. The EZStream client component is written in two different flavors: JavaBean and ActiveX. The JavaBean component is used to develop Java Applet displays. The ActiveX component is used for developing ActiveX-based displays. Remote user devices will be covered including web browsers on PC#s and scaled-down displays for PDA's and smart cell phones. As mentioned. the interaction between EZStream (web/data server) and TReK (data source) will be covered as related to ISS. EZStream is being enhanced to receive and parse binary data stream directly. This makes EZStream beneficial to both the ISS International Partners and non-NASA applications (i.e. factory floor monitoring). The options for developing client-side display web pages will be addressed along with the development of tools to allow creation of display web pages by non-programmers.

Myers, Gerry↗
NASA NTRS2002

Seasonal Characteristics of Tropical Ozone Profiles using the SHADOZ Ozonesonde Data Set: Comparisons with TOMS Tropical Ozone Climatology

Advances in tropospheric ozone data products being developed for tropical and subtropical regions using TOMS (Total Ozone Mapping Spectrometer) and other satellites are motivating efforts to renew and expand the collection of balloon-borne ozonesonde observations. The SHADOZ (Southern Hemisphere ADditional OZonesondes) project is a web-based archive established since 1998. It's goals are to support validation of TOMS and SBUV (Solar Backscatter UV) satellite ozone measurements and to improve remote sensing techniques for estimating tropical and subtropical ozone. Profile data are taken from balloon-borne ozonesondes, currently at 11 stations coordinating weekly to bi-weekly launches. Station data are publically available at a central location via the internet: . Since the start of the project, the SHADOZ archive has accumulated over 1500 ozonesonde profiles. Data also includes measurements from various SHADOZ supported field campaigns, such as, the Indian Ocean Experiment (INDOEX), Sounding of Ozone and Water in the Equatorial Region (SOWER) and Aerosols99 Atlantic Cruise. Using data from the archive, profile climatologies from selected stations will be shown to 1/characterize the variability of tropospheric tropical ozone among stations, 2/illustrate the seasonal offsets with respect to the tropical profile used in the TOMS v7 algorithm, and 3/estimate the potential error in TOMS retrieval estimates of the tropospheric portion of the atmosphere.

Witte, J. C.↗
NASA NTRSDate not supplied

Global 3D Data Visualization and Analysis Platform with Advanced Machine Learning Capabilities in Support of Lunar Exploration

Introduction: The science goals for NASA’s Artemis program include: a) Understanding the character and origin of lunar polar volatiles, b) Conducting experimental science in the lunar environment and c) Investigating and mitigating exploration risks. The permanently shadowed regions (PSRs) on the Lunar south pole are expected to host large quantities of water-ice and volatiles that are important for sustainable Lunar exploration. There are several missions such as onboard Korea Pathfinder Lunar Orbiter (KPLO: Korean name Danuri) with onboard ShadowCam camera, Astrobotic Peregrine Mission One [4], and other efforts underway to obtain high resolution topographic, minerals, volatiles and other information on the moon. We envision a need in immediate future for platforms to integrate these data sets, provide rendering and visualization capabilities in the context of a 3D Lunar globe for easier information access and analysis. NASA's Celestial Mapping System (CMS) is developed to address the need for 3D tools for planetary science investigations, mission planning, in-situ operations, in a 3D-first design constructed around a unified view of a planetary globe. At present CMS provides many critical functionalities that include: 1) equipment planning and optimized placement on Lunar surface 2) line-of-sight (LOS) analysis 3) powerful measurement tools based on 3D terrain with realistic 3D models to represent rovers, astronauts and equipment 4) visualization of derived mapping products (e.g. resource maps), and 5) a data engine for hosting new observations that are not available in other contemporary lunar data tools. Planetary Data Ingestion: CMS can consume and analyze data from locally hosted and external third party sources. It is compatible with Open Geospatial Consortium (OGC) data and file standards and currently integrates datasets from the Astrogeology Science Center of USGS. This includes global and local data acquired from NASA (LRO, Clementine, Lunar Orbiter) and JAXA (SELENE/Kaguya), with capability of integrating more datasets. In addition, users can specify other WMS-hosted data endpoints, which CMS can then query and stream data from automatically. To set-up an automated process for ingestion and accurate rendering, visualization and analysis of external 3rd party planetary datasets within CMS, we initiated the process of ingesting unique dataset of super-enhanced images of the permanently shadowed regions (PSRs) at the lunar poles which were produced by the Hyper-effective nOise Removal U-net Software (HORUS) tool. This tool was developed to enhance the extremely low-light images of the interior of PSRs and provide the ability to see within these regions at and discern surface features (i.e. boulders and craters) down to 3 meters in size. We focused on the Nobile region on the Lunar south pole, selected site for VIPER mission and stitched several images to create a high-resolution map within one of the PSR of Nobile crater. Figure 1 shows the dark PSR zone form the original NAC layer of LRO as the base layer (left image) and the illuminated areas within that crater (center) which was created by ingesting and merging several of HORUS generated images. At present we employ a semi-automated process to ensure spatial accuracy and merger of several overlapping zones. However, we are in the process of completely automating this process by employing AI based techniques that would rank, sort, and stack the images based on their information density. The georectification of the images would employ selected features. Analysis on Ingested Planetary Datasets: Once an external planetary data-set is successfully ingested, georectified and merged seamlessly as a data-layer; CMS’ numerous analysis tools can be used on this data. A Line of Sight (LOS) tool has been developed for CMS which analyzes terrain profiles and obstructions to determine visibility for remote observers. Figure 1 (right image) shows the viewshed analysis on the same PSR in the Nobile region. The yellow pin shows the observer location outside the PSR. The yellow area shows the visible part of PSR. The obstructed area with no visibility for the observer is shown in red. The Measurements tool allows the user to take area and distance measurements of features on the terrain using various shapes. Measurement type can be specified in a number of ways: Line, Path, Polygon, Circle, Ellipse, Square, Rectangle or Freehand. Once the shape is specified, elevation information can then be extracted along each of these shapes. Figure 2 (left) shows the measurements performed on a crater n illuminated PSR in Nobile region. The equipment placement tool allows the user to place a 3D equipment model at a desired location and analyze its coverage area. The equipment placement tool is coupled with LOS to determine the coverage. Figure 2 (right) shows an equipment placed on the Lunar terrain and it’s coverage area. The red rays are blocked sight lines and the green rays are non-obstructed sight lines with the cyan lines showing the point of intersection with the terrain. More details are provided in the video demonstrations in Reference 5. Overcoming Polar Distortions: 3D geospatial applications exhibit significant distortions in polar imagery due to several reasons: 1) distortions in the source imagery, 2) incompatible tessellation algorithms at the poles, and 3) map projections. We are leveraging new tessellation algorithms and reprojecting data using projections that are better suited for Lunar poles. The goal is to seamlessly switch to polar projections while maintaining 3D view and navigation.

Maps↗
NASA NTRSDate not supplied

Global 3D Data Visualization and Analysis Platform With Advanced Machine Learning Capabilities in Support of Lunar Exploration

Introduction: The science goals for NASA’s Artemis program include: a) Understanding the character and origin of lunar polar volatiles, b) Conducting experimental science in the lunar environment and c) Investigating and mitigating exploration risks [1]. The permanently shadowed regions (PSRs) on the Lunar south pole are expected to host large quantities of water-ice and volatiles that are important for sustainable Lunar exploration [2]. There are several missions such as onboard Korea Pathfinder Lunar Orbiter (KPLO: Korean name Danuri) with onboard ShadowCam camera [3], Astrobotic Peregrine Mission One [4], and other efforts underway to obtain high resolution topographic, minerals, volatiles and other information on the moon. We envision a need in immediate future for platforms to integrate these data sets, provide rendering and visualization capabilities in the context of a 3D Lunar globe for easier information access and analysis. NASA's Celestial Mapping System (CMS) [5] is developed to address the need for 3D tools for planetary science investigations, mission planning, in-situ operations, in a 3D-first design constructed around a unified view of a planetary globe. At present CMS provides many critical functionalities that include: 1) equipment planning and optimized placement on Lunar surface 2) line-of-sight (LOS) analysis 3) powerful measurement tools based on 3D terrain with realistic 3D models to represent rovers, astronauts and equipment 4) visualization of derived mapping products (e.g. resource maps), and 5) a data engine for hosting new observations that are not available in other contemporary lunar data tools [5, 7]. Planetary Data Ingestion: CMS can consume and analyze data from locally hosted and external third party sources. It is compatible with Open Geospatial Consortium (OGC) data and file standards and currently integrates datasets from the Astrogeology Science Center of USGS. This includes global and local data acquired from NASA (LRO, Clementine, Lunar Orbiter) and JAXA (SELENE/Kaguya), with capability of integrating more datasets. In addition, users can specify other WMS-hosted data endpoints, which CMS can then query and stream data from automatically. To set-up an automated process for ingestion and accurate rendering, visualization and analysis of external 3rd party planetary datasets within CMS, we initiated the process of ingesting unique dataset of super-enhanced images of the permanently shadowed regions (PSRs) at the lunar poles which were produced by the Hyper-effective nOise Removal U-net Software (HORUS) tool [8]. This tool was developed to enhance the extremely low-light images of the interior of PSRs and provide the ability to see within these regions at and discern surface features (i.e. boulders and craters) down to 3 meters in size. We focused on the Nobile region on the Lunar south pole, selected site for VIPER mission and stitched several images to create a high-resolution map within one of the PSR of Nobile crater. Figure 1 shows the dark PSR zone form the original NAC layer of LRO as the base layer (left image) and the illuminated areas within that crater (center) which was created by ingesting and merging several of HORUS generated images. At present we employ a semi-automated process to ensure spatial accuracy and merger of several overlapping zones. However, we are in the process of completely automating this process by employing AI based techniques that would rank, sort, and stack the images based on their information density. The georectification of the images would employ selected features. Analysis on Ingested Planetary Datasets: Once an external planetary data-set is successfully ingested, georectified and merged seamlessly as a data-layer; CMS’ numerous analysis tools can be used on this data. A Line of Sight (LOS) tool has been developed for CMS which analyzes terrain profiles and obstructions to determine visibility for remote observers [5,6]. Figure 1 (right image) shows the viewshed analysis on the same PSR in the Nobile region. The yellow pin shows the observer location outside the PSR. The yellow area shows the visible part of PSR. The obstructed area with no visibility for the observer is shown in red. The Measurements tool allows the user to take area and distance measurements of features on the terrain using various shapes. Measurement type can be specified in a number of ways: Line, Path, Polygon, Circle, Ellipse, Square, Rectangle or Freehand. Once the shape is specified, elevation information can then be extracted along each of these shapes. Figure 2 (left) shows the measurements performed on a crater n illuminated PSR in Nobile region. The equipment placement tool allows the user to place a 3D equipment model at a desired location and analyze its coverage area. The equipment placement tool is coupled with LOS to determine the coverage. Figure 2 (right) shows an equipment placed on the Lunar terrain and it’s coverage area. The red rays are blocked sight lines and the green rays are non-obstructed sight lines with the cyan lines showing the point of intersection with the terrain. More details are provided in the video demonstrations in Reference 5. Overcoming Polar Distortions: 3D geospatial applications exhibit significant distortions in polar imagery due to several reasons: 1) distortions in the source imagery, 2) incompatible tessellation algorithms at the poles, and 3) map projections. We are leveraging new tessellation algorithms and reprojecting data using projections that are better suited for Lunar poles. The goal is to seamlessly switch to polar projections while maintaining 3D view and navigation.

Maps↗
DOE OSTI2022

Machine Learning Based Network Parameter Estimation Using AMI Data

The expansion of distribution power system and the growing penetration of distributed energy resources present new challenges for situational awareness. Calibrating the extended system model with sensor measurements and maintaining the usability is critical for utilities. This paper presents a distribution network parameter estimation (DNPE) approach using machine learning (ML) and metering data that improve the quality of extended distribution power system modeling. The reliability model can improve the ability of endpoint data to be translated into network-level situational awareness in real time and help distribution system operators (DSOs) solve branch flow and voltage problems. In addition, a data analytic and automate processing scheme is proposed to improve the sensor data quality and prevent misleading information. The effectiveness of the proposed method is verified with actual advanced metering infrastructure (AMI) data on a real utility feeder model, while considering the higher penetration of photovoltaic power generation. The test of DNPE and study results are demonstrated in this paper.

Parameter estimation, machine learning, power dist↗
DOE OSTI2025

Proceedings for the Workshop on Applied Nuclear Data Activities 2025

The 2025 Workshop for Applied Nuclear Data Activities (WANDA) covered four topic areas in nuclear data: Nuclear Data and Deterrence, Nuclear Data Prioritization for Fusion, High-Assay Low-Enriched Uranium and Novel Moderators for Advanced Reactors, and Data Preservation and Data Workflows. The intention of this workshop is to connect different communities that are invested in nuclear data and have their own unique sets of needs for the purposes of sharing information, fostering collaboration in areas of shared interest, and leveraging synergistic capabilities. The attendance of federal program managers at these workshops is essential in creating awareness of the needs of their respective communities and in providing information to better guide funding investments. In each of these topical sessions, a general description of the nuclear data needs and/or capabilities was presented, along with discussions of existing capabilities that could be leveraged, potential synergistic needs or resources, and challenges that must be overcome for the application space to progress. There are many synergistic nuclear data needs among these application spaces. The discussion largely focused on increasing the accuracy of the nuclear data and better quantifying the data uncertainties that have the greatest impact on applications. The full-day session on data processing and data workflows was by nature intended to be synergistic and applicable to all technical sessions at WANDA. A notable common theme that was highlighted across all sessions was the need for accelerated delivery of nuclear data products across complex and time-consuming workflows.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2024

BEAST DB: Grand-Canonical Database of Electrocatalyst Properties

We present BEAST DB, an open-source database comprised of ab initio electrochemical data computed using grand-canonical density functional theory in implicit solvent at consistent calculation parameters. The database contains over 20,000 surface calculations and covers a broad set of heterogeneous catalyst materials and electrochemical reactions. Calculations were performed at self-consistent fixed potential as well as constant charge to facilitate comparisons to the computational hydrogen electrode. This article presents common use cases of the database to rationalize trends in catalyst activity, screen catalyst material spaces, understand elementary mechanistic steps, analyze the electronic structure, and train machine learning models to predict higher fidelity properties. Users can interact graphically with the database by querying for individual calculations to gain a granular understanding of reaction steps or by querying for an entire reaction pathway on a given material using an interactive reaction pathway tool. BEAST DB will be periodically updated, with planned future updates to include advanced electronic structure data, surface speciation studies, and greater reaction coverage.

database↗
NASA NTRS1995

Calibration of the advanced microwave sounding unit-A for NOAA-K

The thermal-vacuum chamber calibration data from the Advanced Microwave Sounding Unit-A (AMSU-A) for NOAA-K, which will be launched in 1996, were analyzed to evaluate the instrument performance, including calibration accuracy, nonlinearity, and temperature sensitivity. The AMSU-A on NOAA-K consists of AMSU-A2 Protoflight Model and AMSU-A1 Flight Model 1. The results show that both models meet the instrument specifications, except the AMSU-A1 antenna beamwidths, which exceed the requirement of 3.3 +/- 10%. We also studied the instrument's radiometric characterizations which will be incorporated into the operational calibration algorithm for processing the in-orbit AMSU-A data from space. Particularly, the nonlinearity parameters which will be used for correcting the nonlinear contributions from an imperfect square-law detector were determined from this data analysis. It was found that the calibration accuracies (differences between the measured scene radiances and those calculated from a linear two-point calibration formula) are polarization-dependent. Channels with vertical polarizations show little cold biases at the lowest scene target temperature 84K, while those with horizontal polarizations all have appreciable cold biases, which can be up to 0.6K. It is unknown where these polarization-dependent cold biases originate, but it is suspected that some chamber contamination of hot radiances leaked into the cold scene target area. Further investigation in this matter is required. The existence and magnitude of nonlinearity in each channel were established and a quadratic formula for modeling these nonlinear contributions was developed. The model was characterized by a single parameter u, values of which were obtained for each channel via least-squares fit to the data. Using the best-fit u values, we performed a series of simulations of the quadratic corrections which would be expected from the space data after the launch of AMSU-A on NOAA-K. In these simulations, the cosmic background radiance corresponding to a cold space temperature 2.73K was adopted as one of the two reference points of calibration. The largest simulated nonlinear correction is about 0.3K, which occurs at channel 15 when the instrument temperature is at 38.09 deg C. Others are less than 0.2K in the remaining channels. Possible improvement for future instrument calibration is also discussed.

Mo, Tsan↗
DOE OSTI2024

Enhancing Discoverability and Management of Atmospheric Data at Scale: Solutions from the ARM Data Center

The Atmospheric Radiation Measurement (ARM) is a multi-laboratory and multi-institutional U.S. Department of Energy (DOE) Office of Science National User Facility. The ARM Data Center (ADC), located at Oak Ridge National Laboratory, collects, archives, and shares vast atmospheric data crucial for climate research. The ADC manages over 7 PB of data from 460 instruments worldwide, processing it into more than 11,000 diverse data products using the Network Common Data Form (NetCDF) for machine-independent accessibility. The primary challenge addressed in this paper is the efficient management and distribution of vast and diverse datasets essential for the climate research community, enhancing accessibility through advanced tools like Data Discovery. The ADC has developed advanced infrastructure and software architecture to handle the continuous influx of heterogeneous data to enhance data discoverability, resulting in increased scientific collaboration. In 2023, users from over 34 countries downloaded and utilized ARM data, resulting in 1,455 publications. The ADC’s efforts have significantly improved the discoverability and usability of atmospheric data, fostering extensive scientific research and collaboration. This paper details the solutions implemented by the ADC team for efficient data discovery and distribution, and it demonstrates ARM’s capability of staging processed data for scientific analysis.

Shah, Chirag [ORNL] (ORCID:0000000203145737)↗
NASA NTRS1981

Analysis of Meteorological Satellite location and data collection system concepts

A satellite system that employs a spaceborne RF interferometer to determine the location and velocity of data collection platforms attached to meteorological balloons is proposed. This meteorological advanced location and data collection system (MALDCS) is intended to fly aboard a low polar orbiting satellite. The flight instrument configuration includes antennas supported on long deployable booms. The platform location and velocity estimation errors introduced by the dynamic and thermal behavior of the antenna booms and the effects of the presence of the booms on the performance of the spacecraft's attitude control system, and the control system design considerations critical to stable operations are examined. The physical parameters of the Astromast type of deployable boom were used in the dynamic and thermal boom analysis, and the TIROS N system was assumed for the attitude control analysis. Velocity estimation error versus boom length was determined. There was an optimum, minimum error, antenna separation distance. A description of the proposed MALDCS system and a discussion of ambiguity resolution are included.

Wallace, R. G.↗
NASA NTRS1983

The Telecommunications and Data Aquisition Report

Tracking and ground-based navigation techniques are discussed in relation to DSN advanced systems. Network data processing and productivity are studied to improve management planning methods. Project activities for upgrading DSN facilities are presented.

Posner, E. C.↗
DOE OSTI2025

Community Requirements Meta-Analysis: Characterizing Needs and Opportunities for HPDF

This High Performance Data Facility (HPDF) Project is creating a new scientific user facility to provide advanced infrastructure for data-intensive science, supporting the DOE’s Office of Science (SC) community. HPDF’s mission is to enable and accelerate scientific discovery by delivering state-of-the-art data management infrastructure, capabilities, and tools. This meta-analysis examines the needs of the breadth of the SC community, captured in publicly available community reports or mission documents. The meta-analysis identifies and provides initial characterization of fifteen core requirements for the HPDF Project team to consider during the conceptual design phase. The fifteen requirements illustrate how scientific work among SC communities requires modern, seamless user experiences across the ASCR Ecosystem to advance the use of large volumes of heterogeneous data. The scientific community requires support for the missing middle of compute between local and HPC to interactively and collaboratively use growing datasets. Data producers and end users will benefit from enhanced data catalogs and portals that improve data access through advanced search of well curated data. The fifteen requirements are examined here organized across five themes for discussion. Examples in each theme illustrate the array of scientific needs that convey the important role that the fully realized and operational High Performance Data Facility will be able to play as an integral part of the evolving ASCR Ecosystem. Our amalgamated data tables from ESnet reports demonstrate ranges to the volumes of data HPDF must be concerned with, but limitations are inherent to this meta-analysis (see Key Challenges & Limitations). Feedback and validation of these requirements along with additional details and emergent community requirements will be gathered through user research and design activities.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS2024

Temporal Activation of Extravehicular Activity Science and Operations Data: How Rise2's Enablement of a Novel Data Management Prototype Influenced ISS and Artemis Advancements

SSERVI's RIS4E and Rise2 nodes provided early and repeated opportunities to prototype the organization and visualization of science and field operations data together via temporal vs. type-indexing. This data management approach was first explored in our Apollo in Real Time initiative through its meticulous reconciliation and integration of Apollo 11, 13, and 17 mission data, providing an unparalleled temporal and contextual understanding of these historic missions. The positive results from these prototypes served as pre-cursor examples of what eventually became the Collaborative Operations Data Activation (CODA) application at NASA Johnson Space Center (JSC).

B Feist↗
NASA NTRS1997

Geospace Multiprobes

The foregoing science discussions, the required measurements and the detailed implementation plans should provide ample evidence in support of the contention that geospace multiprobes are the next logical step forward in exploration of our environment. The advancement of technology in areas such as mechanical engineering, power systems, circuit miniaturization, high-capacity data storage, and innovative propulsion systems all allow the implementation of multiple satellite configurations within a constrained budget. The problems that have plagued our interpretation of previous data and the advancements that could not be made without the availability of multiple platforms can now be overcome. New multiprobe missions promise to produce a real leap forward in our understanding of the geospace environment for they will allow all the required measurements to be made in all the right places. The most efficient use of resources, and application of experience and knowledge, will be achieved from a series of missions such as envisioned by Solar Terrestrial Probes. The return for our investment in a multiprobe mission sequence is the organized advancement of our understanding in two key areas. First, we will understand the geospace environment to a level that will allow real quantitative assessment of the impacts of humans and the vulnerability of human space systems. Second, this advancement will allow us to more fully evaluate present and future data from other planetary environments to assess differences important to habitability.

Source record↗
NASA NTRS2005

An Advanced Orbiting Systems Approach to Quality of Service in Space-Based Intelligent Communication Networks

As humans and robotic technologies are deployed in future constellation systems, differing traffic services will arise, e.g., realtime and non-realtime. In order to provide a quality of service framework that would allow humans and robotic technologies to interoperate over a wide and dynamic range of interactions, a method of classifying data as realtime or non-realtime is needed. In our paper, we present an approach that leverages the Consultative Committee for Space Data Systems (CCSDS) Advanced Orbiting Systems (AOS) data link protocol. Specifically, we redefine the AOS Transfer Frame Replay Flag in order to provide an automated store-and-forward approach on a per-service basis for use in the next-generation Interplanetary Network. In addition to addressing the problem of intermittent connectivity and associated services, we propose a follow-on methodology for prioritizing data through further modification of the AOS Transfer Frame.

Riha, Andrew P.↗
NASA NTRS1988

Space communication link propagation data for selected cities within the multiple beam and steerable antenna coverage areas of the advanced communications technology satellite

Rain attenuation propagation data for 68 cities within the coverage area of the multiple beam and steerable antennas of the Advanced Communications Technology Satellite (ACTS) are presented. These data provide the necessary data base for purposes of communication link power budgeting and rain attenuation mitigation controller design. These propagation parameters are derived by applying the ACTS Rain Attenuation Prediction Model to these 68 locations. The propagation parameters enumerated in tabular form for each location are as follows: (1) physical description of the link and location (e.g., latitude, longitude, antenna elevation angle, etc.), link availability versus attenuation margin (also in graphical form), fading time across fade depths of 3, 5, 8, and 15 dB versus fade duration, and required fade control response time for controller availabilities of 99.999, 99.99, 99.9, and 99 percent versus sub-threshold attenuation levels. The data for these specific locations can be taken to be representative of regions near these locations.

Manning, Robert M.↗
DOE OSTI2020

BISON TRISO Modeling Advancements and Validation to AGR-1 Data

BISON is a finite element-based nuclear fuel performance code. Among its unique characteristics are its ability to model 1D, 2D, and 3D geometries and its applicability to a wide variety of nuclear fuels. For the last eight years, BISON has included a beginning capability to model tri-structural isotropic (TRISO) fuel. Recently, interest in TRISO fuel has grown, and a significant effort has been made to improve BISON’s capabilities in this area. Capability development has occurred for each material present in TRISO fuel particles: the buffer, inner pyrolytic carbon, silicon carbide, and outer pyrolytic carbon layers, as well as the fuel kernel. New elastic, creep, swelling, thermal expansion, thermal conductivity, and fission gas release (FGR) models are available. New models for the graphite matrix are also now available. Another important addition is the ability to perform statistical failure analysis of large samples of fuel particles. This new capability, which continues to grow, enables evaluation of failure due to pressure or crack formation by analyzing many thousands of particles. This enables realistic calculations of fission product release from the many particles in a TRISO-fueled reactor. These capabilities were checked via regression and verification tests. A large number of code benchmarking problems were also run, showing that BISON’s results closely match those of other software tools. Finally, a significant validation effort was completed in which fission product release, measured as part of the AGR-1 capsule experiments, was compared to BISON outputs. BISON outputs compared very well to the experimental data and to PARFUME results. Interest in BISON’s TRISO capabilities is growing, with the U.S. Nuclear Regulatory Commission (NRC) and Westinghouse Electric Company receiving training during the past year. Multiple other entities have expressed interest in or are actively using BISON. Kairos Power, LLC, has a strong partnership with Idaho National Laboratory (INL) regarding the use of BISON for TRISO analysis. While its capabilities still continue to grow, BISON has already become a powerful tool for TRISO analysis.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗