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NASA NTRS2017

Human Reliability Assessments: Using the Past (Shuttle) to Predict the Future (Orion)

NASA (National Aeronautics and Space Administration) Johnson Space Center (JSC) Safety and Mission Assurance (S&MA) uses two human reliability analysis (HRA) methodologies. The first is a simplified method which is based on how much time is available to complete the action, with consideration included for environmental and personal factors that could influence the human's reliability. This method is expected to provide a conservative value or placeholder as a preliminary estimate. This preliminary estimate or screening value is used to determine which placeholder needs a more detailed assessment. The second methodology is used to develop a more detailed human reliability assessment on the performance of critical human actions. This assessment needs to consider more than the time available, this would include factors such as: the importance of the action, the context, environmental factors, potential human stresses, previous experience, training, physical design interfaces, available procedures/checklists and internal human stresses. The more detailed assessment is expected to be more realistic than that based primarily on time available. When performing an HRA on a system or process that has an operational history, we have information specific to the task based on this history and experience. In the case of a Probabilistic Risk Assessment (PRA) that is based on a new design and has no operational history, providing a "reasonable" assessment of potential crew actions becomes more challenging. To determine what is expected of future operational parameters, the experience from individuals who had relevant experience and were familiar with the system and process previously implemented by NASA was used to provide the "best" available data. Personnel from Flight Operations, Flight Directors, Launch Test Directors, Control Room Console Operators, and Astronauts were all interviewed to provide a comprehensive picture of previous NASA operations. Verification of the assumptions and expectations expressed in the assessments will be needed when the procedures, flight rules, and operational requirements are developed and then finalized.

DeMott, Diana L.↗
NASA NTRS2017

And the Human Saves the Day or Maybe They Ruin It, The Importance of Humans in the Loop

Flying a mission in space requires a massive commitment of resources, and without the talent and commitment of the people involved in this effort we would never leave the atmosphere of Earth as safely as we have. When we use the phrase "humans in the loop", it could apply to almost any endeavor since everything starts with humans developing a concept, completing the design process, building or implementing a product and using the product to achieve a goal or purpose. Narrowing the focus to spaceflight, there are a variety of individuals involved throughout the preparations for flight and the flight itself. All of the humans involved add value and support for program success. The paper discusses the concepts of human involvement in technological programs, how a Probabilistic Risk Assessment (PRA) accounts for the human in the loop for potential missions using a technique called Human Reliability Analysis (HRA) and the tradeoffs between having a human in the loop or not. Human actions can increase or decrease the overall risk via initiating events or mitigating them, thus removing the human from the loop doesn't always lowers the risk.

DeMott, Diana L.↗
NASA NTRS2018

Modeling In-Space Aborts for NASA Human Exploration Missions

NASA is developing capabilities for crewed missions beyond Low Earth Orbit (LEO) for the first time in nearly 50 years. Given the greater distances from Earth that these missions will entail, it is prudent to develop in-space abort capabilities in order to save the crew in the event of critical life-threatening failures that may occur. NASA has developed a Cross Program PRA (XPRA) of the integrated vehicle, from pre-launch through landing and rescue of the crew. An ascent abort model has already been developed as part of this XPRA model to assess the risk associated with failures during prelaunch and ascent. The scope of the analysis discussed here is focused on aborts associated with the in-space portion of the mission up to and including the Trans-Lunar Injection (TLI) burn, which places the Orion spacecraft on a trajectory to the Moon.

Bigler, Mark A.↗
NASA NTRS2018

Modeling In-Space Aborts for NASA Human Exploration Missions

NASA is developing new capabilities to send humans beyond low Earth orbit (LEO) for the first time in several decades with the new Multi-purpose Crew Vehicle (MPCV) Orion spacecraft and Space Launch System (SLS) launch vehicle. As part of these capabilities, NASA is developing means to terminate missions prior to reaching mission destinations in order to save the crew in the event of critical life-threatening failures. This abort capability exists for both ascent and in-space operations. While the risk associated with ascent aborts has been modeled in detail, less has been done in the area of in-space aborts (e.g. Apollo 13). Recent efforts have started to better assess the risk associated with in-space aborts. This paper will describe these efforts. The in-space abort model described in this paper is part of a larger Cross-Program PRA (XPRA) model of exploration missions planned in the next few years to the vicinity of the Moon. The model consists of linked event trees and fault trees and associated rules built using the Systems Analysis Program for Hands-On Integrated Reliability Evaluations (SAPHIRE) tool. This model structure is being built with flexibility in mind in order to perform risk trades and further expansion of the model.

Bigler, Mark A.↗
NASA NTRS2018

Modeling the Risk of U.S. Offshore Oil & Gas Exploration-Well Drilling, Commercial Nuclear Plants, and Human Spaceflight

Probabilistic Risk Assessment (PRA) has been applied in different industries for many years. Each industry and technology area presents varying challenges and priorities, and the risk models therefore need to be somewhat different. This paper compares aspects of risk modeling of offshore drilling, nuclear plant operation, and human spaceflight. Risk models in all three technology areas have certain high-level similarities: (1) they employ redundancy and diversity in their means to prevent or mitigate risk, including a mix of active and passive systems designed to respond to off-normal evolutions; (2) they are affected by human reliability; (3) their models require consideration of coupling between scenario structure and scenario phenomenology. But in examining the models in more detail, one sees important differences in methodology and emphasis. For purposes of comparison, this paper discusses aspects of a risk model of an offshore drilling operation in the U.S. Gulf of Mexico, focusing on where such a development differs in important ways from models of commercial U.S. nuclear plants and models developed for human spaceflight.

Boyer, Roger L.↗
NASA NTRS2018

A Prognostic Launch Vehicle Probability of Failure Assessment Methodology for Conceptual Systems Predicated on Human Causal Factors

Create an improved method to calculate reliability of a conceptual launch vehicle system prior to fabrication by using historic data of actual root causes of failures. While failures have unique "proximate causes", there are typically a finite amount of common "root causes". Heretofore launch vehicle reliability evaluation typically hardware-centric statistical analyses, while most root causes of failures are been shown to be human-centric. A method based on human-centric root causes can be used to quantify reliability assessments and focus proposed actions to mitigate problems. Existing methods have been optimistic in their projections of launch vehicle reliability compared to actuals. Hypothesis: reliability of a conceptual launch vehicle can be more accurately evaluated based on a rational, probabilistic approach using past failure assessment teams' findings predicated on human-centric causes."Human Reliability Analysis Methods Selection Guidance for NASA"Chandler F.T., et al., NASA HQ/OSMA study group, July 2006. Outside HRA experts from academia, other federal labs, and the private sector. 50 system reliability methods considered, fourteen selected for further study, four finally selected as best suited for human spaceflight. Probabilistic Risk Analysis (PRA) + Human Reliability Analysis (HRA) enabled incorporating effects and probabilities of human errors. While four down-selected methods deemed appropriate for failure assessment, it did not appear that these methods could be concisely applied to perform major system-wide assessment of probability of failure of a conceptual design without becoming unwieldy."Engineering a Safer World", Detailed, comprehensive study external to NASA Leveson N. G., MIT, 2011.Systems-Theoretic Accident Model and Processes (STAMP). All-encompassing accident model based on systems theory analyzed accidents after they occurred and created approaches to prevent occurrence in developing systems not focused on failure prevention per se, but rather reducing hazards by influencing human behavior through use of constraints, hierarchical control structures, and process models to improve system safetySystem Theoretic Process Analysis (STPA) addresses predictive part of problem (a "hazard analysis"). Includes all causal factors identified in STAMP: "...design errors, software flaws, component interaction accidents, cognitively complex human decision-making errors, and social organizational and management factors contributing to accidents" can guide design process rather than require it to exist before-hand did not appear capable of concise application for system-wide assessment of probability of failure of a conceptual design without becoming unwieldy.

Williams, Craig H.↗
NASA NTRS2018

The Growth of Mass and Reliability Source Database and Me

Mass and Reliability Source (MaRS) is a database which draws together information from multiple other sources and databases (MADS, VMDB, ISS PART, Bayesian PowerPoint, etc.). Information such as mass, operating hours, and failure data are compiled to create a tool for the building of probabilistic Risk Assessment (PRA) models. MaRS also has great potential for deep space mission planning. Understanding the lowest point of failure within an ORU helps to inform the efficient selection of spare parts necessary for a journey where mass and volume are at a premium and resupply is not possible.

George, Cory A.↗
NASA NTRS2020

MEDPRAT-SEL: Medical Resource Set Selector Searching High-Dimensionality Space

NASA Human Research Program's (HRP) next generation risk model closes the loop on medical risk and resource evaluation, providing researchers with a tool to assess and choose capabilities scientifically. The Medical Extensible Dynamic Probabilistic Risk Assessment Tool (MEDPRAT) simulator (SIM) evaluates resources in terms of medical benefit, such as reduced crew quality time lost (QTL), vs. cost, in mass or volume. The MEDPRAT resource set selector (SEL) searches the space of resource benefits v. cost, closing a feedback loop around the simulator, thus selecting resource sets with best benefit for cost. We discuss the design and results of the resource set selector. NASA HRP's emphasis on scientific assessment of risk, PRA, has led to the Cross-cutting Computational Modeling Project (CCMP).

Leinweber, Lawrence↗
NASA NTRS2020

Enabling Space Exploration Medical System Development Using a Tool Ecosystem

The NASA Human Research Program’s (HRP) Exploration Medical Capability (ExMC) Element is utilizing a Model Based Systems Engineering (MBSE) approach to enhance the development of systems engineering products that will be used to advance medical system designs for exploration missions beyond Low Earth Orbit. In support of future missions, the team is capturing content such as system behaviors, functional decompositions, architecture, system requirements and interfaces, and recommendations for clinical capabilities and resources in Systems Modeling Language (SysML) models. As these products mature, SysML models provide a way for ExMC to capture relationships among the various products, which includes supporting more integrated and multi-faceted views of future medical systems. In addition to using SysML models, HRP and ExMC are developing supplementary tools to support two key functions: 1) prioritizing current and future research activities for exploration missions in an objective manner; and 2) enabling risk-informed and evidence-based trade space analysis for future space vehicles, missions, and systems. This paper will discuss the long-term HRP and ExMC vision for the larger ecosystem of tools, which include dynamic Probabilistic Risk Assessment (PRA) capabilities, additional SysML models, a database of system component options, and data visualizations. It also includes a review of an initial Pilot Project focused on enabling medical system trade studies utilizing data that is coordinated across tools for consistent outputs (e.g., mission risk metrics that are associated with medical system mass values and medical conditions addressed). This first Pilot Project demonstrated successful operating procedures and integration across tools. Finally, the paper will also cover a second Pilot Project that utilizes tool enhancements such as medical system optimization capabilities, post-processing, and visualization of generated data for subject matter expert review, and increased integration amongst the tools themselves.

Amador, Jennifer R.↗
NASA NTRS2020

Enabling Space Exploration Medical System Development Using a Tool Ecosystem

The NASA Human Research Program's (HRP) Exploration Medical Capability (ExMC) Element is utilizing a Model Based Systems Engineering (MBSE) approach to enhance the development of systems engineering products that will be used to advance medical system designs for exploration missions beyond Low Earth Orbit. In support of future missions, the team is capturing content such as system behaviors, functional decompositions, architecture, system requirements and interfaces, and recommendations for clinical capabilities and resources in Systems Modeling Language (SysML) models. As these products mature, SysML models provide a way for ExMC to capture relationships among the various products, which includes supporting more integrated and multi-faceted views of future medical systems. In addition to using SysML models, HRP and ExMC are developing supplementary tools to support two key functions: 1) prioritizing current and future research activities for exploration missions in an objective manner; and 2) enabling risk-informed and evidence-based trade space analysis for future space vehicles, missions, and systems. This paper will discuss the long-term HRP and ExMC vision for the larger ecosystem of tools, which include dynamic Probabilistic Risk Assessment (PRA) capabilities, additional SysML models, a database of system component options, and data visualizations. It also includes a review of an initial Pilot Project focused on enabling medical system trade studies utilizing data that is coordinated across tools for consistent outputs (e.g., mission risk metrics that are associated with medical system mass values and medical conditions addressed). This first Pilot Project demonstrated successful operating procedures and integration across tools. Finally, the paper will also cover a second Pilot Project that utilizes tool enhancements such as medical system optimization capabilities, post-processing, and visualization of generated data for subject matter expert review, and increased integration amongst the tools themselves.

Amador, Jennifer R.↗
NASA NTRS2016

Model Based Mission Assurance: NASA's Assurance Future

Model Based Systems Engineering (MBSE) is seeing increased application in planning and design of NASA’s missions. This suggests the question: what will be the corresponding practice of Model Based Mission Assurance (MBMA)? Contemporaneously, NASA’s Office of Safety and Mission Assurance (OSMA) is evaluating a new objectives based approach to standards to ensure that the Safety and Mission Assurance disciplines and programs are addressing the challenges of NASA’s changing missions, acquisition and engineering practices, and technology. MBSE is a prominent example of a changing engineering practice. We use NASA’s objectives-based strategy for Reliability and Maintainability as a means to examine how MBSE will affect assurance. We surveyed MBSE literature to look specifically for these affects, and find a variety of them discussed (some are anticipated, some are reported from applications to date). Predominantly these apply to the early stages of design, although there are also extrapolations of how MBSE practices will have benefits for testing phases. As the effort to develop MBMA continues, it will need to clearly and unambiguously establish the roles of uncertainty and risk in the system model. This will enable a variety of uncertainty-based analyses to be performed much more rapidly than ever before and has the promise to increase the integration of CRM (Continuous Risk Management) and PRA (Probabilistic Risk Analyses) even more fully into the project development life cycle. Various views and viewpoints will be required for assurance disciplines, and an over-arching viewpoint will then be able to more completely characterize the state of the project/program as well as (possibly) enabling the safety case approach for overall risk awareness and communication.

Evans, John↗
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↗
NASA NTRSDate not supplied

The Challenger Tradgedy was Caused by an Apollo Mistake, Terminating Risk Analysis

NASA’s attitude toward risk changed drastically between the Apollo and Space Shuttle design. [1]Apollo engineers were seriously alarmed about riskbecause of the fatal Apollo 1 fire and the fact that the estimated probability of another fatal accident was extremely high. The predictions were so appalling thatmanagement terminated risk analysis to avoid public apprehension. Because risk analysis was not done, the Space Shuttle design accepted excessively high andunknown risk. The immediate cause of the Challengertragedy was the mistaken decision to launch in coldweather that impaired the O-ring seals, but the fundamental cause was the high risk of the shuttle design. Before Challenger, management asserted that the probability of a fatal accident was 1 in 100,000.Probabilistic Risk Analysis (PRA) found a roughly 1 in 100 chance of a shuttle failure.

Harry W Jones↗
NASA NTRSDate not supplied

Probabilistic Risk Assessment of a Sustained Lunar Presence

The Artemis Base Camp will be our first sustainable foothold on the lunar frontier. The base camp includes a lunar surface habitat, power systems, and infrastructure needed to develop capabilities on future missions to Mars. NASA Probabilistic Risk Assessment (PRA) methodologies tend to focus on in-flight Loss of Crew (LOC) or Loss of Vehicle (LOV) risk estimates for short mission durations. However, lunar habit support systems and power generation systems will need to continuously operate. Existing risk methodologies will need to adapt to understand risk drivers in new environments under different operating conditions, such as lunar dust and increased micro-meteoroid exposure. Insights from the nuclear and oil industries can provide guidance to NASA risk practitioners to tackle this new challenge.

risk assessment↗
NASA NTRS2020

Bayesian Framework For Bioburden Density Calculations To Perform Planetary Protection Probabilistic Risk Assessment

The planetary protection discipline aims to minimize the microbial contamination on spacecraft to prevent the inadvertent contamination of other planetary bodies, known as forward planetary protection (PP). Planetary protection probabilistic risk assessment (PRA) relies on two core methodologies-the contamination probability event tree analysis and statistical parameter estimation. Planetary protection engineers combine several techniques to estimate the bioburden present on spacecraft components. A direct assay to enumerate CFU (colony forming units) is the preferred methodology, but given a similar processing environment the bioburden present on certain components is inferred using: (1) a NASA defined bioburden estimate based upon the biological cleanliness of the manufacturing/assembly environment or (2) sampled data from a similar spacecraft component. The paper presents an empirical Bayesian framework to systematically treat bioburden estimation and its uncertainties on different levels starting with measurement procedures to combining different components to subsystems and whole spacecraft. It is shown that the Bayesian approach can effectively handle estimations and their uncertainties at different levels and produce a reliable estimate for bioburden to be used to evaluate the probability of contamination.

Seuylemezian, Arman↗
NASA NTRSDate not supplied

Impact Outputs for A Representative Extended Duration Artemis Mission

BACKGROUND: As NASA and private industry begin preparation for long-duration spaceflight, quantifying the impact that potential human health and performance capabilities have on crew health outcomes is imperative for medical risk mitigation. NASA’s Informing Mission Planning via Analysis of Complex Tradespaces tool (IMPACT) applies Probabilistic Risk Assessment (PRA) methodology to estimate these outcomes. OVERVIEW: As NASA prepares to return to the Moon, medical system planning has already begun for extended Artemis missions, which will see humans spending months at a time in cis-lunar space and on the surface of the Moon. The Long Duration Lunar Orbital and Lunar Surface (LDLOLS) design reference mission (DRM) lasts 9 months, including 3 months on the lunar surface, and involves 2 male and 2 female crewmembers. LDLOLS assumes no extravehicular activities (EVAs) in orbit, but, while on the lunar surface, involves 2-4 EVAs/month in a pressurized rover and 2-4 EVAs/month in an unpressurized rover or on foot. This DRM assumes a physician level Crew Medical Officer with commensurate knowledge, skills, and abilities. The IMPACT tool was utilized to estimate in-flight medical risk for this mission. More specifically, 100,000 simulations of this DRM were modeled, and overall estimates for loss of crew life (LOCL), need for evacuation (RTDC; return to definitive care), and crew task time lost (TTL; a measure of disability) were calculated. A recommended medical capability set, with appropriate mass and volume constraints, was also generated. DISCUSSION: This abstract reviews the IMPACT-derived risk for these mission outcomes with and without treatment, a macroscopic look at the total mass and volume necessary for full diagnostic and treatment capability, and how these change with input mission parameters.

J G Steller↗
NASA NTRSDate not supplied

Derivation of the Most Influential Medical Conditions for An Extended Duration Artemis Mission

BACKGROUND: The risk of loss of mission due to medical conditions may be influenced by loss of crew life (LOCL), need for evacuation (RTDC; return to definitive care), and crew task time lost. Predicting what medical conditions are most likely to lead to crew morbidity and mortality may influence medical system design, clinical capability prioritization, and research strategies. NASA’s Informing Mission Planning via Analysis of Complex Tradespaces tool (IMPACT) applies Probabilistic Risk Assessment (PRA) methodology to assess these risks. OVERVIEW: A team of subject matter experts (SME) from a variety of medical disciplines developed a consensus-based process to determine 120 of the most clinically relevant medical conditions for long-duration exploration missions (LDEMs) . This IMPACT Condition List (ICL) expanded upon previous work done for Integrated Medical Model (IMM). For each condition a best-case and worst-case definition were derived. These definitions were used to identify probability of occurrence, proportion of cases that are best case vs. worst case, clinical phase duration, and risk of outcomes (task time loss [TTL], RTDC, and LOCL) for both treated and untreated states. These data were sources from existing spaceflight databases (e.g. Longitudinal Survey of Astronaut Health), relevant models (e.g. the ISS fire model), and/or terrestrial literature. Each condition was then tied to diagnostic and therapeutic resources and capabilities. IMPACT was then run for the LDLOLS DRM (see Abstract #2 for this panel). DISCUSSION: This abstract will present the process for generating the IMPACT condition list, the relevant data for each clinical condition, and present results for the ten most influential conditions impacting LOCL, RTDC, and TTL for a representative extended duration Artemis mission.

A Nelson↗
NASA NTRSDate not supplied

Aggregate Risk Tool for Human Space Flight

This project utilized Data fusion capabilities developed from the 2020-2022 Information Fusion (IFDA) IRAD to enhance functionality of a Human Spaceflight (HSF) Aggregate Risk Product developed by the JSC Flight Safety Office. The tool compiles and presents risk data from multiple Program and Commercial Provider vehicles to provide a holistic assessment of residual risk to Program Managers and Technical Authorities prior to HSF Launches. The aggregation or coupling of risks from multiple sources (Examples: PRA, variances, anomaly data bases, Program Risk Management data bases, technical review board minutes, Hazard Analysis, etc.) when analyzed, identify potential areas of elevated risk in components, systems or mission phases that would otherwise be undetected by nonintegrated program risk management tools and possesses.

Patrick Huckaby↗