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NASA NTRS2017

Autonomous, Context-Sensitive, Task Management Systems and Decision Support Tools II: Contextual Constraints and Information Sources

Recent advances in artificial intelligence, machine learning, data mining and sensor technology have resulted in the availability of a vast amount of digital data and information and the development of advanced automated reasoners. This creates the opportunity for the development of a robust dynamic task manager and decision support tool that is context sensitive and integrates information from a wide array of on-board and off aircraft sourcesa tool that monitors systems and the overall flight situation, anticipates information needs, prioritizes tasks appropriately, keeps pilots well informed, and is nimble and able to adapt to changing circumstances. This is the second of two companion reports exploring issues associated with autonomous, context-sensitive, task management and decision support tools. In the first report, we explored fundamental issues associated with the development of such a system. In this report, we extend this work to focus on two critical aspects of these systems: 1) the constraints and conditions that drive the dynamic prioritization and presentation of data and information to the pilots, and 2) specific data and information to be accessed, monitored, integrated, and displayed in such a system.

context-sensitive↗

NASA NTRS2012

Restoration of APOLLO Data by the NSSDC and PDS Lunar Data Node

The Apollo Lunar Surface Experiment Packages (ALSEPs), suites of instruments deployed by the Apollo 12. 14, 15, 16 and 17 astronauts on the lunar surface, still represent the only in-situ measurements of the Moon's environment taken over long time periods, Much of these data are housed at the National Space Science Data Center (NSSDC) at Goddard Space Flight Center but are in forms that are not readily usable, such as microfilm, hardcopy, and magnetic tapes with older, obsolete formats. The Lunar Data Node (LDN) has been formed under the auspices of the Planetary Data System (PDS) Geosciences Node to put relevant, scientifically important Apollo data into accessible digital form for use by researchers and mission planners. The LDN has prioritized the restoration of these data based on their scientific and engineering value and the level of effort required. We will report on progress made and plans for future data restorations.

Williams, David R.↗

DOE OSTI2023

Community Resilience Indicator Analysis: Commonly Used Indicators from Peer-Reviewed Research (Updated for Research Published 2003-2021)

In 2017, FEMA’s National Integration Center (NIC) Technical Assistance (TA) Branch identified a need to establish a data-driven basis for prioritizing locations for TA investment and guiding local emergency management planning. To achieve this goal, FEMA tasked Argonne National Laboratory (Argonne) with identifying commonly used indicators of community resilience across the landscape of published peer-reviewed research. FEMA and Argonne completed the first Community Resilience Indicator Analysis (CRIA) in 2018 and repeated the process in 2022. The CRIA process begins with a literature review and cataloguing of published peer-reviewed assessment methodologies on social vulnerability and community resilience. The literature review findings are then filtered by inclusion criteria established by the CRIA research team to ensure the methodologies are: (1) Quantitative, (2) Data and methodology are publicly available, (3) Calculated at the county level or lower, (4) Examine generalized hazard risk (rather than a singular hazard), and (5) Focused on pre-disaster community conditions. After this, the research team identifies the commonly used indicators across these methodologies and selects the best data source for each indicator. Finally, the research team bins the data for visual display, conducts a correlation analysis and creates a composite index, the FEMA Community Resilience Index (FEMA CRI). In 2018, the CRIA identified eight resilience and vulnerability assessment methodologies and 20 commonly used indicators (indicators used in three or more of the eight methodologies). The FEMA CRI in 2018 was created from these 20 indicators and was produced for at the county level. The 2022 CRIA updated the literature review to expand the list of methodologies examined and followed the same process, resulting in an analysis of 14 methodologies published between 2003 and 2021 and 22 indicators identified as commonly used (indicators used in five or more of the 14 methodologies). In 2022, the research team produced the FEMA CRI at the county and the census tract levels. To make the CRIA data more accessible and more actionable, each individual indicator and the FEMA CRI is binned and included in FEMA’s Resilience Analysis and Planning Tool (RAPT). RAPT enables emergency managers and community partners to quickly visualize relative differences in potential resilience by county, tribe and census tract. By reviewing the data for each of these 22 indicators individually, emergency managers can gain insights for targeted outreach strategies, planning, mitigation investments and response and recovery operations. Communities, regional governments and others can use this data to better understand potential challenges to resilience. As the social science field of examining and validating indicators of resilience evolves, FEMA will update RAPT to provide emergency managers and community partners with additional data and tools to inform planning, mitigation, response and recovery. It is important to understand that the role of the emergency manager is not to change or to “improve” the data, but to plan appropriately for the community characteristics reflected in the data. These datasets are community characteristics that researchers have identified as important considerations for resilience. For example, people with disabilities may have greater challenges to be resilient to disasters. If a community has a high population of people with disabilities, the emergency manager(s) may need to create tailored preparedness outreach programs and strategies to ensure those residents have support if evacuation is necessary. Rather than label these indicators as an absolute measure of resilience, FEMA considers “potential challenges to resilience” a better frame to understand these indicators. Everyone is vulnerable to disasters. While scholars theorize that certain characteristics may make an individual or a household more socially vulnerable, the data does not reflect measures that individuals and/or communities have taken to address potential challenges, such as emergency management planning and outreach or household preparedness measures. To aid emergency managers in understanding how to use these indicators, calling them potential challenges to resilience supports a more positive and strategic application of the data in all phases of emergency management.

99 GENERAL AND MISCELLANEOUS↗

NASA NTRS2019

LEAVES: Lofted Environmental and Atmospheric Venus Sensors

LEAVES (Lofted Environmental Atmospheric Venus Sensors) is a design exercise with the goal of dramatically decreasing the cost of obtaining prioritized chemical and physical data in planetary atmospheres. Through the application of a swarm approach this concept parallelizes atmospheric exploration, with geographic coverage far exceeding what is possible with conventional monolithic platforms or sondes. Each unit in the swarm is exceptionally compact, with a powered payload mass of only a few tens of grams and a high-drag, semi-rigid structure that acts to slow each probe as it descends through the atmosphere. This structural design can collapse into a planar form to allow for efficient stowage prior to arrival at the target body. With a total per-unit mass of only 120 g, a fleet of 100 (or more) units can be very reasonably accommodated on a carrier spacecraft.Science operations, which begin when the LEAVES probes reach an altitude of 100 km, are targeted for the cloud-bearing region of Venus' atmosphere. During the roughly 9 hour, terminal velocity descent through the atmosphere, LEAVES collects data of the state and composition of the atmosphere in parallel across multiple units. These data would represent an unprecedented constraint on the distribution and concentration of targeted chemical species, and the detection of local and regional variations in both chemistry and physical properties.A novel and compelling result of this exercise was that the same optimization that produced a structure with an exceptionally low areal mass density (0.126 kg/m2) also resulted in a probe that can be deployed directly from an aerobraking orbit (~140 km at 5 km/s) without the need for aeroshell protection. This translates to a tremendous mass savings and gives LEAVES the flexibility to be carried as a secondary payload aboard either a descending surface probe or an orbital radar mapper. Because such missions are under active development or have already been proposed (but not flown), we infer that LEAVES is well positioned as a technology

Swarm↗

DOE OSTI2021

Data Driven Analysis for Modernization Program Management

NNSA is responsible for managing national nuclear security missions: ensuring a safe, secure, and reliable nuclear deterrent; supplying nuclear fuel to the Navy; and supporting the nation’s nuclear nonproliferation efforts. However, over half of NNSA’s facilities are more than 40 years old, and roughly one-third date back to the Manhattan Project. To execute its critical nuclear security missions, NNSA is making large investments to modernize its nuclear production capabilities. This ramp up represents NNSA’s largest modernization effort since the Cold War. Given the scale of these efforts, NNSA’s Office of Secondary Stage Production Modernization has implemented data driven techniques to prioritize investments and inform strategic decision making. NNSA, with support from its site managing contractors, has developed and implemented an integrated schedule and risk management system to address the issues and limitations with the traditional approach. The multi-year integrated schedules are key to identifying program linkages and managing large portfolios comprised of many different projects and efforts. In conjunction with the integrated schedule, a new program risk management system has also been developed and implemented, which manages program risks and opportunities, along with specific mitigation strategies to reduce or eliminate the risks per timelines that are tracked in the integrated schedule. This paper is supplemented with a follow-on presentation on effective management of program material and throughput modeling.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

DOE OSTI2026

Exploring the keV-scale physics potential of CUORE

We present the analysis techniques developed to explore the keV-scale energy region of the Cryogenic Underground Observatory for Rare Events (CUORE) experiment, based on more than 2 metric ton yr of data collected over five years. By prioritizing a stricter selection over a larger exposure, we are able to optimize data selection for thresholds at 10 keV and 3 keV with 691 kg yr and 11 kg yr of data, respectively. We study how the performance varies among the 988-detector array with different detector characteristics and data-taking conditions. We achieve an average baseline resolution of 2.54 ±0.14 keV FWHM and 1.18 ±0.02 keV FWHM for the data selection at 10 keV and 3 keV, respectively. The analysis methods employed reduce the overall background by about an order of magnitude, reaching 2.06±0.05 counts/(keV kg days) and 16±2 counts/(keV kg days) at the thresholds of 10 keV and 3 keV. We evaluate for the first time the near-threshold reconstruction efficiencies of the CUORE experiment, and find these to be 50 ±2% and 26 ±4% at 10 keV and 3 keV, respectively. This analysis provides crucial insights into rare decay studies, new physics searches, and keV-scale background modeling with CUORE. We demonstrate that ton-scale cryogenic calorimeters can operate across a wide energy range, from keV to MeV, establishing their scalability as versatile detectors for rare event and dark matter physics. These findings also inform the optimization of future large mass cryogenic calorimeters to enhance the sensitivity to low-energy phenomena.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

NASA NTRS2022

Data Needs to be…

Findable, Accessible, Interoperable, and Reusable (FAIR) data are essential to heliophysics, indeed all scientific research. We make recommendations intended to prioritize resources needed to satisfy FAIR data principles, treating them as a fundamental research infrastructure, rather than a simple research product.

A Halford↗

NASA NTRS1983

Description of data base management activities

ARC's current and future data processing needs have been identified and defined. Requirements for improved data processing capabilities are listed: (1) Centralized control of system data files. Establish a DBA/data base administrator position with responsibility for management of the Centers numerous data bases; (2) Programmer tools to improve efficiency of performance; (3) Direct and timely access to information. Presently, the user submits query requests to the data processing department where they are prioritized with other queries and then batch processed using a report generator; (4) On line data entry. With the merger of the Dryden facility with ARC on line data entry, edit and updates have become mandatory for timely operation and reporting. A DBMS software package was purchased to meet the above requirements.

Source record↗

DOE OSTI2024

Chlorine Validation through Critical Integral Experiments

An increased interest in the validation of chlorine nuclear data, specifically 35Cl, in recent years has led to the prioritization of conducting chlorine critical experiments for nuclear data validation and criticality safety evaluations. A previous experiment was conducted with PVC and CPVC (chlorinated polyvinyl chloride) to reduce the margin of subcriticality for PF-4 operations with aqueous plutonium chloride solutions. Challenges in determining the composition of specific polymers, namely the CPVC, made it difficult to characterize, and therefore benchmark. Additional materials that were utilizable for chlorine validation were not immediately clear, as form, strength, purity, and composition are all important. A series of possible absorber materials were identified and studied, but ultimately granular sodium chloride was chosen. In addition to the needs of LANL’s PF-4 other industry collaborators have brought attention to the need for chlorine validation. Specifically, the need for HEU electrorefining with LiCl salts at Y-12 was taken into consideration for this experiment, with the experimental configurations being finely tuned to best meet their needs. Needs for validation were also presented by Idaho National Lab (INL) and TerraPower for validation of their Molten Chloride Reactor Experiment (MCRE) and Molten Chloride Fast Reactor (MCFR) and have also been considered.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

DOE OSTI2024

Mid-Range Science Objectives for the Event Horizon Telescope

The first images of the black holes in Sagittarius A* and M87* have created a wide range of new scientific opportunities in gravitational physics, compact objects, and relativistic astrophysics. We discuss here the scientific opportunities that arise from the rich data sets that have already been obtained and the new data sets that will be obtained, exploiting a wide range of technical advances, including observational agility, receiver upgrades, and the addition of new stations. This document provides a 5-year framework for Event Horizon Telescope (EHT) science structured around four fundamental questions that are used to prioritize the analysis of existing data, guide technical upgrades, and determine the optimal use of future observational opportunities with EHT, ALMA, and multi-wavelength facilities. Through enhancements over this period, the EHT will create the first movie of M87* connecting black hole and jet physics, provide detailed studies of the structure and dynamics of Sgr A*, characterize the magnetospheres of both systems through polarimetric imaging, and explore the spacetime properties of black holes with greater precision and range.

79 ASTRONOMY AND ASTROPHYSICS↗

NASA NTRS1983

On the design of prioritized multiplexing systems

Systems in which many data sources are multiplexed over a single communication channel are considered. Data from all the sources are generated in fixed-length packets, and are stored in a common buffer with finite capacity. Packets overflowed or removed from the buffer prior to transmission are lost. The system performance measure is the set of packet loss probabilities associated with the sources. Queueing disciplines vary depending on the stringency of prioritization and the utilization of system resources. The set of all possible performances is characterized as the set of all queueing disciplines is spanned. Whether a given performance is possible can be deduced. Strategies that achieve the minimum overall loss probability are identified. The extreme disciplines are specified, and their performances are calculable by means of a given algorithm.

Clare, L. P.↗

NASA NTRS1987

Performance boundaries for prioritized multiplexing systems

Systems in which many data sources are multiplexed over a single communication channel are considered. Data from all the sources are generated in fixed-length packets and are stored in a common buffer with finite capacity. Packets that overflowed or were removed from the buffer prior to transmission are lost. The system performance measure is the set of packet loss probabilities associated with the sources. Queueing disciplines vary depending on the stringency of prioritization and the utilization of the system resources. The set of all possible performances is characterized as the set of all queueing disciplines is spanned. Whether a given performance is possible can be deduced. Strategies that achieve the minimum overall loss probability are identified. The extreme disciplines are specified, and their performances are calculable by means of a given algorithm.

Clare, Loren P.↗

NASA NTRS2009

Robotic Recon for Human Exploration

Robotic reconnaissance has the potential to significantly improve scientific and technical return from lunar surface exploration. In particular, robotic recon may increase crew productivity and reduce operational risk for exploration. However, additional research, development and field-testing is needed to mature robot and ground control systems, refine operational protocols, and specify detailed requirements. When the new lunar surface campaign begins around 2020, and before permanent outposts are established, humans will initially be on the Moon less than 10% of the time. During the 90% of time between crew visits, robots will be available to perform surface operations under ground control. Understanding how robotic systems can best address surface science needs, therefore, becomes a central issue Prior to surface missions, lunar orbiters (LRO, Kaguya, Chandrayyan-1, etc.) will map the Moon. These orbital missions will provide numerous types of maps: visible photography, topographic, mineralogical and geochemical distributions, etc. However, remote sensing data will not be of sufficient resolution, lighting, nor view angle, to fully optimize pre-human exploration planning, e.g., crew traverses for field geology and geophysics. Thus, it is important to acquire supplemental and complementary surface data. Robotic recon can obtain such data, using robot-mounted instruments to scout the surface and subsurface at resolutions and at viewpoints not achievable from orbit. This data can then be used to select locations for detailed field activity and prioritize targets to improve crew productivity. Surface data can also help identify and assess terrain hazards, and evaluate alternate routes to reduce operational risk. Robotic recon could be done months in advance, or be part of a continuing planning process during human missions.

Deans, Matthew↗

NASA NTRS2016

Heuristics for Relevancy Ranking of Earth Dataset Search Results

As the Variety of Earth science datasets increases, science researchers find it more challenging to discover and select the datasets that best fit their needs. The most common way of search providers to address this problem is to rank the datasets returned for a query by their likely relevance to the user. Large web page search engines typically use text matching supplemented with reverse link counts, semantic annotations and user intent modeling. However, this produces uneven results when applied to dataset metadata records simply externalized as a web page. Fortunately, data and search provides have decades of experience in serving data user communities, allowing them to form heuristics that leverage the structure in the metadata together with knowledge about the user community. Some of these heuristics include specific ways of matching the user input to the essential measurements in the dataset and determining overlaps of time range and spatial areas. Heuristics based on the novelty of the datasets can prioritize later, better versions of data over similar predecessors. And knowledge of how different user types and communities use data can be brought to bear in cases where characteristics of the user (discipline, expertise) or their intent (applications, research) can be divined. The Earth Observing System Data and Information System has begun implementing some of these heuristics in the relevancy algorithm of its Common Metadata Repository search engine.

science data management↗

NASA NTRS2017

Relevancy Ranking of Satellite Dataset Search Results

science data management↗

NASA NTRS2012

GeoLab 2011: New Instruments and Operations Tested at Desert RATS

GeoLab is a geological laboratory and testbed designed for supporting geoscience activities during NASA's analog demonstrations. Scientists at NASA's Johnson Space Center built GeoLab as part of a technology project to aid the development of science operational concepts for future planetary surface missions [1, 2, 3]. It is integrated into NASA's Habitat Demonstration Unit, a first generation exploration habitat test article. As a prototype workstation, GeoLab provides a high fidelity working space for analog mission crewmembers to perform in-situ characterization of geologic samples and communicate their findings with supporting scientists. GeoLab analog operations can provide valuable data for assessing the operational and scientific considerations of surface-based geologic analyses such as preliminary examination of samples collected by astronaut crews [4, 5]. Our analog tests also feed into sample handling and advanced curation operational concepts and procedures that will, ultimately, help ensure that the most critical samples are collected during future exploration on a planetary surface, and aid decisions about sample prioritization, sample handling and return. Data from GeoLab operations also supports science planning during a mission by providing additional detailed geologic information to supporting scientists, helping them make informed decisions about strategies for subsequent sample collection opportunities.

Evans, Cindy A.↗

DOE OSTI2025

A Performant, Scalable Processing Pipeline for High‐Quality and FAIR Environmental Sensor Data

High-resolution environmental monitoring is necessary to record, understand, and predict biogeochemical and ecological changes particularly in coastal systems but brings significant challenges in processing and making rapidly available the resulting data. The COMPASS-FME project established a network of coastal observational sites across the Chesapeake Bay and western Lake Erie regions extensively instrumented with soil, vegetation, and weather sensors logging data every 15 min. Our data processing framework, written in R and completely open source, prioritizes rapid model-experiment iteration and makes biogeochemical data rapidly available for quality assurance/quality control, analysis, and model ingestion. This pipeline is distinguished by a standardized and modular approach to data curation, extensive metadata and documentation, and its high performance. These attributes combine to make biogeochemical data rapidly accessible across COMPASS-FME and the broader community. Flexible, powerful, and reproducible approaches to handling high-volume environmental data are crucial for accelerating biogeosciences research.

Pennington, Stephanie C. [Pacific Northwest Nation↗

DOE OSTI2026

Integrating Resilience Planning in Distribution System Planning

Electric utilities, regulators, and stakeholders face increasing risks of severe storms, freezes, floods, and heat waves damaging grid infrastructure and causing power outages—and increasing risks of utility equipment igniting wildfires. At the same time, customer electricity rates have risen substantially in recent years, due in part to replacing aging infrastructure and improving resilience to natural hazards and physical threats. To address these challenges, utilities are beginning to move beyond traditional, siloed planning processes to balance resilience with other fundamental grid objectives such as affordability, reliability, safety, and serving new loads. This study presents a framework for states and utilities that want to advance integration of resilience and distribution planning processes to improve planning efficiency, better prioritize cost-effective grid expenditures, and balance planning objectives. The framework includes 7 key integration points between these planning processes: -Strategy process -Data -Threat assessments -Solution identification and prioritization -Optimization opportunities -Consideration of other grid needs -Metrics Lawrence Berkeley National Laboratory reviewed utility distribution system plans and interviewed subject matter experts to identify emerging practices for each of the 7 integration points. This report presents these practices, which can be used as a guide toward more holistic planning and cohesive investment strategies. It also includes 3 case studies to provide practical examples of how utilities apply such integrated planning processes: two pole hardening programs and one microgrid planning effort. The report concludes by identifying opportunities for future research.

24 POWER TRANSMISSION AND DISTRIBUTION↗