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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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All sourcesNASA NTRSDOE OSTI
NASA NTRS2005

Knowledge Representation Standards and Interchange Formats for Causal Graphs

In many domains, automated reasoning tools must represent graphs of causally linked events. These include fault-tree analysis, probabilistic risk assessment (PRA), planning, procedures, medical reasoning about disease progression, and functional architectures. Each of these fields has its own requirements for the representation of causation, events, actors and conditions. The representations include ontologies of function and cause, data dictionaries for causal dependency, failure and hazard, and interchange formats between some existing tools. In none of the domains has a generally accepted interchange format emerged. The paper makes progress towards interoperability across the wide range of causal analysis methodologies. We survey existing practice and emerging interchange formats in each of these fields. Setting forth a set of terms and concepts that are broadly shared across the domains, we examine the several ways in which current practice represents them. Some phenomena are difficult to represent or to analyze in several domains. These include mode transitions, reachability analysis, positive and negative feedback loops, conditions correlated but not causally linked and bimodal probability distributions. We work through examples and contrast the differing methods for addressing them. We detail recent work in knowledge interchange formats for causal trees in aerospace analysis applications in early design, safety and reliability. Several examples are discussed, with a particular focus on reachability analysis and mode transitions. We generalize the aerospace analysis work across the several other domains. We also recommend features and capabilities for the next generation of causal knowledge representation standards.

Throop, David R.↗
DOE OSTI2024

High Energy Arcing Fault (HEAF): Sandia National Laboratories 2023 Report

High Energy Arcing Faults (HEAFs) are hazardous events in which an electrical arc leads to the rapid release of energy in the form of heat, vaporized metal, and mechanical force. In Nuclear Power Plants (NPPs), these events are often accompanied by loss of essential power and complicated shutdowns. To confirm the probabilistic risk analysis (PRA) methodology in NUREG/CR-6850, which was formulated based on limited observational data, the NRC led an international experimental campaign from 2014 to 2016. The results of these experiments uncovered an unexpected hazard posed by aluminum components in or near electrical equipment and the potential for unanalyzed equipment failures. Sandia National Laboratories (SNL), in support of the NRC work, collaborated with NIST, BSI, KEMA, and NRC to support the full-scale HEAF test campaign in 2023. SNL provided high speed and real time from visible and infrared video/data of tests that collected data from copper and aluminum busses from switchgears and bus-ducts. Part of SNL work was to place cameras with high-speed data collection capability at different vantage points that provide the NRC a more complete and granular view of the test events.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2023

High Energy Arcing Fault (HEAF) Photometrics 2022 Test Report

High Energy Arcing Faults (HEAFs) are hazardous events in which an electrical arc leads to the rapid release of energy in the form of heat, vaporized metal, and mechanical force. In Nuclear Power Plants, these events are often accompanied by loss of essential power and complicated shutdowns. To confirm the probabilistic risk analysis (PRA) methodology in NUREG/CR-6850, which was formulated based on limited observational data, the NRC led an international experimental campaign from 2014 to 2016. The results of these experiments uncovered an unexpected hazard posed by aluminum components in or near electrical equipment and the potential for unanalyzed equipment failures. Sandia National Laboratories (SNL), in support of the NRC work, collaborated with NIST, BSI, KEMA, and NRC to support the full-scale HEAF test campaign in 2022. SNL provided high speed visible and infrared video/data of ten tests that collected data from HEAFs originated on copper and aluminum buses inside switchgears and bus ducts. Part of the SNL scope was to place cameras with high-speed data collection at different vantage points within the test facility to provide NRC a more complete and granular view of the test events.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
NASA NTRS2010

Constellation Probabilistic Risk Assessment (PRA): Design Consideration for the Crew Exploration Vehicle

Managed by NASA's Office of Safety and Mission Assurance, a pilot probabilistic risk analysis (PRA) of the NASA Crew Exploration Vehicle (CEV) was performed in early 2006. The PRA methods used follow the general guidance provided in the NASA PRA Procedures Guide for NASA Managers and Practitioners'. Phased-mission based event trees and fault trees are used to model a lunar sortie mission of the CEV - involving the following phases: launch of a cargo vessel and a crew vessel; rendezvous of these two vessels in low Earth orbit; transit to th$: moon; lunar surface activities; ascension &om the lunar surface; and return to Earth. The analysis is based upon assumptions, preliminary system diagrams, and failure data that may involve large uncertainties or may lack formal validation. Furthermore, some of the data used were based upon expert judgment or extrapolated from similar components~systemsT. his paper includes a discussion of the system-level models and provides an overview of the analysis results used to identify insights into CEV risk drivers, and trade and sensitivity studies. Lastly, the PRA model was used to determine changes in risk as the system configurations or key parameters are modified.

Prassinos, Peter G.↗
NASA NTRSDate not supplied

Developing A New Medical Condition List for Exploration Spaceflight

For the last decade, the National Aeronautics and Space Administration (NASA) has utilized a probabilistic risk analysis tool called the Integrated Medical Model (IMM), which contains 100 medical conditions, to conduct medical trade-space analyses and risk assessments for International Space Station (ISS) operations. Planning for future missions to the Moon and Mars will require updated tools and evidence that consider the unique features of exploration missions. To address this need, the Exploration Medical Capability (ExMC) Element of the NASA Human Research Program is developing an advanced trade-space analysis tool suite, IMPACT. As a part of this effort, ExMC has produced the IMPACT version 1 Condition List (ICL 1.0) which expands the scope and definition of medical conditions.

Amy Jean Kreykes↗
NASA NTRSDate not supplied

Exploration Medical Capability Science and Research Overview and Update

The mission of the Exploration Medical Capability (ExMC) Element is to advance medical system design and risk-informed decision making for exploration beyond Low Earth Orbit to promote human health and performance in space. To accomplish this mission, ExMC focuses on several key areas: • Investigating specific risks that are relevant for human exploration spaceflight, including in-flight medical conditions, degraded or toxic medications, and renal stones • Developing medical probabilistic risk analysis tools that are integrated with systems engineering processes to inform the medical system trade space and support the development of robust requirements • Demonstrating and defining requirements for a prototype clinical decision support system • Developing and demonstrating novel medical technologies that will improve future medical capabilities in space This presentation will focus on selected scientific and technical conceptual drivers for the Element and its current and future research risks and gaps while providing an overview of the Element’s progress in 2021 and areas of focus for 2022.

Benjamin Easter↗
NASA NTRSDate not supplied

IMPACT-ing Exploration Spaceflight Risk Prediction and Medical System Design

Human exploration spaceflight missions to the Moon and Mars present unprecedented challenges for in-mission medical care. Compared with the ISS, the greater distance from Earth will mean increased mission durations, communication delays, limited to no resupply opportunities, and significant limitations on the evacuation of ill or injured crew. Spacecraft mass, volume, and power will be curtailed while higher demands will be placed on the crew’s knowledge, skills, and abilities. In this higher risk environment, it is important to: a) quantitatively estimate human system risk attributable to medical conditions, a process known as Probabilistic Risk Analysis, and b) use these estimates to inform medical system design. IMPACT (Informing Mission Planning via Analysis of Complex Tradespaces) is a PRA and medical trade space analysis tool developed by NASA to advance exploration mission medical system design. IMPACT improves upon and will soon replace NASA’s existing tool, the Integrated Medical Model, with: a novel evidence base baselined to exploration environments; an expanded list of 120 medical conditions; a significant increase in the number of medical resources that can be utilized and in the flexibility of their use; and the modelling of time lost performing mission-specific tasks due to medical conditions. IMPACT provides evidence-based, mission-specific PRA estimates of in-flight medical risk and an initial list of clinical capabilities and medical resources/hardware to be considered. In addition, sophisticated trade space capabilities estimate how human system risk varies with changes to the mission architecture or medical capability set (e.g., if the system mass constraint decreases by 10% or ultrasound is removed). This panel will provide an overview of IMPACT, its intended use cases, and future development plans. The panel will be the first public presentation of IMPACT results, including medical risk estimates for extended duration Artemis missions, the medical conditions most influencing medical risk metrics, and the clinical capabilities that have the largest effect on medical risk.

Ben Easter↗
NASA NTRSDate not supplied

Preliminary Medical Risk Estimates and Clinical Capability Needs for Artemis IV

BACKGROUND Human exploration spaceflight missions to the Moon and Mars present unprecedented challenges for in- mission medical care. Compared with the ISS, the greater distance from Earth will mean increased mission durations, communication delays, limited to no resupply opportunities, and significant limitations on the evacuation of ill or injured crew. Spacecraft mass, volume, and power will be curtailed while higher demands will be placed on the crew’s knowledge, skills, and abilities. In this higher risk environment, it is important to: a) quantitatively estimate human system risk attributable to medical conditions, a process known as Probabilistic Risk Analysis, and b) use these estimates to inform medical system design. IMPACT (Informing Mission Planning via Analysis of Complex Tradespaces) is a PRA and medical trade space analysis tool developed by NASA to advance exploration mission medical system design. IMPACT v1.0 improves upon and will soon replace NASA’s existing tool, the Integrated Medical Model, with: a novel evidence base baselined to exploration environments; an expanded list of 119 medical conditions; a significant increase in the number of medical resources that can be utilized and in the flexibility of their use; and the modelling of time lost performing mission-specific tasks due to medical conditions. METHODOLOGY: This abstract will present IMPACT estimates of medical system risk and clinical capability needs for the Artemis IV mission. Artemis IV is currently scheduled for 2026 and will visit the Gateway space station in lunar orbit prior to the second lunar landing of the Artemis program. The baseline Artemis IV mission that was modeled was 28 days in duration with phases including Orion outbound, 4 days on the Gateway space station in lunar orbit, 2 crew on the surface of the Moon for approximately one week, an additional 5 days on Gateway, and then return to Earth. This baseline was compared to two alternative 34-day design reference missions (DRMs) that shifted the lunar sortie earlier or later in the mission profile. Assumptions included 2 female and 2 male crew and a notional medical system mass of 25 kg. Medical system risk estimates include loss of crew life (LOCL), consideration of medical evacuation (known as return to definitive care – RTDC), and an estimate of crew time lost due to medical conditions (Task Time Lost – TTL). The presentation will also describe the medical conditions that are the greatest drivers of risk as well as the clinical capabilities and resources that have the largest effect on risk. RESULTS: All three DRMs had very low probability of LOCL from medical conditions, primarily due to short duration. RTDC was also similar across the DRMs. In contrast, TTL was higher in the early lunar sortie DRM due to earlier occurrence of EVA-related medical conditions. Taken as a whole, there was no clinically significant difference in medical risk across the three missions. Results for clinical capabilities and an example medical equipment list will be discussed but were similar across DRMs.

D Hilmers↗
NASA NTRSDate not supplied

Medical Risk Estimates and Clinical Capability Needs for A Long Duration Artemis Mission

BACKGROUND Human exploration spaceflight missions to the Moon and Mars present unprecedented challenges for in-mission medical care. Compared with the ISS, the greater distance from Earth will mean increased mission durations, communication delays, limited to no resupply opportunities, and significant limitations on the evacuation of ill or injured crew. Spacecraft mass, volume, and power will be curtailed while higher demands will be placed on the crew’s knowledge, skills, and abilities. In this higher risk environment, it is important to: a) quantitatively estimate human system risk attributable to medical conditions, a process known as Probabilistic Risk Analysis, and b) use these estimates to inform medical system design. IMPACT (Informing Mission Planning via Analysis of Complex Tradespaces) is a PRA and medical trade space analysis tool developed by NASA to advance exploration mission medical system design. IMPACT v1.0 improves upon and will soon replace NASA’s existing tool, the Integrated Medical Model, with: a novel evidence base baselined to exploration environments; an expanded list of 119 medical conditions; a significant increase in the number of medical resources that can be utilized and in the flexibility of their use; and the modelling of time lost performing mission-specific tasks due to medical conditions. DISCUSSION: This abstract will present IMPACT estimates of medical system risk and clinical capability needs for an extended duration Artemis mission of approximately 9 months, with phases including outbound transit, 3 months on the Lunar Gateway space station, 3 months on the Lunar surface with EVAs, 3 months on Gateway (simulating the return phase of a Mars mission), and transit back to Earth. Medical system risk estimates include loss of crew life (LOCL), consideration of medical evacuation (known as return to definitive care – RTDC), and an estimate of crew time lost due to medical conditions (Task Time Lost – TTL). The presentation will also describe the medical conditions that are the greatest drivers of risk as well as the clinical capabilities and resources that have the largest effect on risk.

W Thompson↗
NASA NTRS2022

Medical Risk Estimates and Clinical Capability Needs for a Late Artemis Mission

BACKGROUND Human exploration spaceflight missions to the Moon and Mars present unprecedented challenges for in-mission medical care. Compared with the ISS, the greater distance from Earth will mean increased mission durations, communication delays, limited to no resupply opportunities, and significant limitations on the evacuation of ill or injured crew. Spacecraft mass, volume, and power will be curtailed while higher demands will be placed on the crew’s knowledge, skills, and abilities. In this higher risk environment, it is important to: a) quantitatively estimate human system risk attributable to medical conditions, a process known as Probabilistic Risk Analysis, and b) use these estimates to inform medical system design. IMPACT (Informing Mission Planning via Analysis of Complex Tradespaces) is a PRA and medical trade space analysis tool developed by NASA to advance exploration mission medical system design. IMPACT v1.0 improves upon and will soon replace NASA’s existing tool, the Integrated Medical Model, with: a novel evidence base baselined to exploration environments; an expanded list of 119 medical conditions; a significant increase in the number of medical resources that can be utilized and in the flexibility of their use; and the modelling of time lost performing mission-specific tasks due to medical conditions. DISCUSSION: This abstract will present IMPACT estimates of medical system risk and clinical capability needs for an extended duration Artemis mission of approximately 9 months, with phases including outbound transit, 3 months on the Lunar Gateway space station, 3 months on the Lunar surface with EVAs, 3 months on Gateway (simulating the return phase of a Mars mission), and transit back to Earth. Medical system risk estimates include loss of crew life (LOCL), consideration of medical evacuation (known as return to definitive care –RTDC), and an estimate of crew time list due to medical conditions (Task Time Lost –TTL). The presentation will also describe the medical conditions that are the greatest drivers of risk as well as the clinical capabilities and resources that have the largest effect on risk.

A Anderson↗
NASA NTRS2024

Preliminary Medical Risk Estimates and Clinical Capability Needs for Late Artemis Missions

BACKGROUND Human exploration spaceflight missions to the Moon and Mars present unprecedented challenges for in- mission medical care. Compared with the ISS, the greater distance from Earth will mean increased mission durations, communication delays, limited to no resupply opportunities, and significant limitations on the evacuation of ill or injured crew. Spacecraft mass, volume, and power will be curtailed while higher demands will be placed on the crew’s knowledge, skills, and abilities. In this higher risk environment, it is important to: a) quantitatively estimate human system risk attributable to medical conditions, a process known as Probabilistic Risk Analysis, and b) use these estimates to inform medical system design. IMPACT (Informing Mission Planning via Analysis of Complex Tradespaces) is a PRA and medical trade space analysis tool developed by NASA to advance exploration mission medical system design. IMPACT v1.0 improves upon and will soon replace NASA’s existing tool, the Integrated Medical Model, with: a novel evidence base baselined to exploration environments; an expanded list of 119 medical conditions; a significant increase in the number of medical resources that can be utilized and in the flexibility of their use; and the modelling of time lost performing mission-specific tasks due to medical conditions. METHODOLOGY: This abstract will present IMPACT estimates of medical system risk and clinical capability needs for the Artemis IV mission. Artemis IV is currently scheduled for 2026 and will visit the Gateway space station in lunar orbit prior to the second lunar landing of the Artemis program. The baseline Artemis IV mission that was modeled was 28 days in duration with phases including Orion outbound, 4 days on the Gateway space station in lunar orbit, 2 crew on the surface of the Moon for approximately one week, an additional 5 days on Gateway, and then return to Earth. This baseline was compared to two alternative 34-day design reference missions (DRMs) that shifted the lunar sortie earlier or later in the mission profile. Assumptions included 2 female and 2 male crew and a notional medical system mass of 25 kg. Medical system risk estimates include loss of crew life (LOCL), consideration of medical evacuation (known as return to definitive care – RTDC), and an estimate of crew time lost due to medical conditions (Task Time Lost – TTL). The presentation will also describe the medical conditions that are the greatest drivers of risk as well as the clinical capabilities and resources that have the largest effect on risk. RESULTS: All three DRMs had very low probability of LOCL from medical conditions, primarily due to short duration. RTDC was also similar across the DRMs. In contrast, TTL was higher in the early lunar sortie DRM due to earlier occurrence of EVA-related medical conditions. Taken as a whole, there was no clinically significant difference in medical risk across the three missions. Results for clinical capabilities and an example medical equipment list will be discussed but were similar across DRMs.

D. Hilmers↗
NASA NTRSDate not supplied

Evaluating Faulty State Occurrence in Wildfire UAS Missions Using Markov Chains

As autonomous technology advances, unmanned aircraft systems are increasingly integrated into emergency response missions, such as wildfire response. These systems must be be safe with less risk than non-autonomous counter parts, yet quantifying the risk associated with present-day and future systems conventionally relies solely on expert opinion and little data. Instead, combining narrative mishap reports with probabilistic analysis can provide a method for evolutionary and timely risk analysis. In this paper, we present a framework for a data-driven probabilistic risk assessment style analysis, where hazard events and rates originate from documented UAS mishaps. The framework is applied to a UAS mapping mission in wildfire response, including a fault tree analysis, event tree analysis, and probabilistic analysis using Markov Chains. The analysis provides an enumeration of hazards in the system, hazard events that can lead to faults, the probability of a mission experiencing any fault, the probability of experiencing a specific fault, and the expected time spent until faulty states occur in present-day operations.

risk analysis↗
NASA NTRSDate not supplied

Evaluating Faulty State Occurrence in Wildfire UAS Missions Using Markov Chains

As autonomous technology advances, unmanned aircraft systems are increasingly integrated into emergency response missions, such as wildfire response. These systems must be be safe with less risk than non-autonomous counter parts, yet quantifying the risk associated with present-day and future systems conventionally relies solely on expert opinion and little data. Instead, combining narrative mishap reports with probabilistic analysis can provide a method for evolutionary and timely risk analysis. In this paper, we present a framework for a data-driven probabilistic risk assessment style analysis, where hazard events and rates originate from documented UAS mishaps. The framework is applied to a UAS mapping mission in wildfire response, including a fault tree analysis, event tree analysis, and probabilistic analysis using Markov Chains. The analysis provides an enumeration of hazards in the system, hazard events that can lead to faults, the probability of a mission experiencing any fault, the probability of experiencing a specific fault, and the expected time spent until faulty states occur in present-day operations.

risk analysis↗
NASA NTRS2011

Command Process Modeling & Risk Analysis

Commanding Errors may be caused by a variety of root causes. It's important to understand the relative significance of each of these causes for making institutional investment decisions. One of these causes is the lack of standardized processes and procedures for command and control. We mitigate this problem by building periodic tables and models corresponding to key functions within it. These models include simulation analysis and probabilistic risk assessment models.

functional analysis↗
NASA NTRS2021

Risk Assessment Metrics for NASA Fission Reactor Applications

Risk assessment is an important part of many NASA activities. In August 2019, the White House issued NSPM-20, which defines acceptable levels of risk for nuclear launches, but does not prescribe the particular methodologies or metrics that are to be used for comparison to the defined acceptance criteria. There are a variety of metrics that are possible and can be readily generated by a probabilistic risk assessment (PRA). This paper will explore alternative metrics that can be provided, along with some discussion of their characteristics and important factors to consider during a space fission reactor risk analysis.

Probabilistic Risk Assessment↗