Results for “Risk Analyses” — Page 8

NASA NTRS2012

Bayesian Analysis for Risk Assessment of Selected Medical Events in Support of the Integrated Medical Model Effort

The Exploration Medical Capability project is creating a catalog of risk assessments using the Integrated Medical Model (IMM). The IMM is a software-based system intended to assist mission planners in preparing for spaceflight missions by helping them to make informed decisions about medical preparations and supplies needed for combating and treating various medical events using Probabilistic Risk Assessment. The objective is to use statistical analyses to inform the IMM decision tool with estimated probabilities of medical events occurring during an exploration mission. Because data regarding astronaut health are limited, Bayesian statistical analysis is used. Bayesian inference combines prior knowledge, such as data from the general U.S. population, the U.S. Submarine Force, or the analog astronaut population located at the NASA Johnson Space Center, with observed data for the medical condition of interest. The posterior results reflect the best evidence for specific medical events occurring in flight. Bayes theorem provides a formal mechanism for combining available observed data with data from similar studies to support the quantification process. The IMM team performed Bayesian updates on the following medical events: angina, appendicitis, atrial fibrillation, atrial flutter, dental abscess, dental caries, dental periodontal disease, gallstone disease, herpes zoster, renal stones, seizure, and stroke.

Gilkey, Kelly M.↗

NASA NTRSDate not supplied

Statistical Approach on Utilizing Ground-based Experiments to Model Break-up Events

Two laboratory-based impact tests have been conducted to develop and extend the capability of NASA satellite breakup models. The first experiment, the Satellite Orbital Debris Characterization Impact Test (SOCIT), was conducted by the U.S. Department of Defense and NASA in 1992. It employed a fully functional U.S. Navy Transit spacecraft, fabricated from materials commonly used in the 1960s. SOCIT fragmentation data formed the basis of the current NASA Standard Satellite Breakup Model (SSBM). A second experiment, DebriSat, was conducted in 2014 by the DebriSat consortium: the NASA Orbital Debris Program Office; the United States Space Force Space Systems Command, formerly the Air Force Space and Missile Systems Center, the Air Force Arnold Engineering Development Complex, and the University of Florida. This impact test was performed on a high-fidelity mock-up satellite assembled from modern components. Data from both experiments are expected to contribute to the next-generation models for on-orbit breakup analyses, long-term environment predictions, and debris risk assessment. This paper uses the direct statistical sampling of the SOCIT and DebriSat data ensembles to model an on-orbit breakup event, rather than the analytic expressions estimated from the samples as with as with the NASA SSBM and its predecessor. This direct method involves drawing fragments (i.e., sampling with replacement) from each fragmentation data-subset containing mass, shape category, material density, characteristic length, mass, and cross-sectional area. As part of the sampling process, the properties of sampled fragment data (e.g., area-to-mass ratios) are numerically checked to ensure they do not contain unrealistic quantities. The process to simulate a breakup cloud composed of fragments from SOCIT and DebriSat datasets is discussed. The methodology for ensuring that conservation of overall mass of the sampled fragment cloud under this sampling approach is highlighted. Finally, the results are compared with simulated clouds generated from SSBM for specific historical breakup events.

Andrew Vavrin↗

NASA NTRS2023

Statistical Approach on Utilizing Ground-Based Experiments to Model Break-Up Events

Two laboratory-based impact tests have been conducted to develop and extend the capability of NASA satellite breakup models. The first experiment, the Satellite Orbital Debris Characterization Impact Test (SOCIT), was conducted by the U.S. Department of Defense and NASA in 1992. It employed a fully functional U.S. Navy Transit spacecraft, fabricated from materials commonly used in the 1960s. SOCIT fragmentation data formed the basis of the current NASA Standard Satellite Breakup Model (SSBM). A second experiment, DebriSat, was conducted in 2014 by the DebriSat consortium: the NASA Orbital Debris Program Office, the United States Space Force Space Systems Command, formerly the Air Force Space and Missile Systems Center, the Air Force Arnold Engineering Development Complex, and the University of Florida. This impact test was performed on a high-fidelity mock-up satellite assembled from modern components. Data from both experiments are expected to contribute to the next-generation models for on-orbit breakup analyses, long-term environment predictions, and debris risk assessment. This paper uses the direct statistical sampling of the SOCIT and DebriSat data ensembles to model an on-orbit breakup event, rather than the analytic expressions estimated from the samples in the SSBM and its predecessor. This direct method involves drawing fragments (i.e., sampling with replacement) from each fragmentation data-subset containing mass, shape category, material density, characteristic length, mass, and cross-sectional area. As part of the sampling process, the properties of sampled fragment data (e.g., area-to-mass ratios) are numerically checked to ensure they do not contain unrealistic quantities. The process to simulate a breakup cloud composed of fragments from SOCIT and DebriSat datasets is discussed. The methodology for ensuring that conservation of overall mass of the sampled fragment cloud under this sampling approach is highlighted. Finally, the results are compared with simulated clouds generated from SSBM for specific historical breakup events.

Andrew Vavrin↗

NASA NTRSDate not supplied

Quantifying the Sensitivity of Condition Incidence Parameters in the Evidence Library

One approach to quantifying spaceflight risk at NASA makes use event driven probabilistic techniques. The Medical Extensible Dynamic Probabilistic Risk Assessment Tool (MEDPRAT) is such a tool that estimates medical risk metrics via simulation and enables optimization of medical resources subject to mission constraints [1]. Previous analyses have informed medical set composition, exercise countermeasures, and water intake, where each analysis quantifies the risk associated with proposed variations in system design. As future mission profiles extend beyond Low-Earth Orbit (LEO) and lengthen in duration, understanding these risks and contributing factors is critical. MEDPRAT employs Monte Carlo sampling techniques to simulate missions and track the occurrence of medical events. These events follow fault-tree-like progressions through levels of severity and mitigation via medical treatment to many possible outcomes and these are reported throughout the mission. Making this possible, are the medical databases that contain evidence gathered by the Human Research Program (HRP). Quantifying the impact of uncertainty or variability in the input data is an important step in evaluating the credibility of modeling and simulation results. In this work, we investigate the sensitivity of medical risk metrics with respect to the condition incidence parameters within the Evidence Library (EL) [2] as the medical database input for MEDPRAT. The medical conditions, contained in the EL, are equipped with incidence rates that describe the likelihood that the condition will occur. These incidence rates reflect historical spaceflight data or when appropriate, terrestrial data. In this presentation, we will explore how uncertainty in these rates propagate to the medical risk described by MEDPRAT. These results identify the conditions and parameters with the largest contribution to medical risks.

Ian Lim↗

NASA NTRS1991

The Marshall Engineering Thermosphere model atmosphere Statistical Analysis Mode (MET-SAM)

The minimum, mean, and maximum exospheric temperature on the globe were calculated for every three hour period from 1947 through 1989 using the algorithms in the Marshall Engineering Thermosphere (MET) model and the appropriate solar activity input parameters. Cumulative percent frequency (CPF) distributions were then calculated for each of these temperatures at five levels of solar activity as defined by the 13-month smoothed values of the 10.7-cm solar radio noise flux. Next, the 50, 95, 97.7, and 100 percentile temperature values in each of these five levels of solar activity were curve fit as a function of the 13-month smoothed 10.7-cm flux. The resulting algorithms are used to compute the exospheric temperature in the MET model instead of the technique developed by Jacchia in his 1970 model. These temperatures are then used to enter tables to determine the total mass density and/or the atomic oxygen number density for application to engineering problems. Users can specify the risk level they are willing to accept in the results of analyses that require neutral atmosphere parameters inputs. The model eliminates the guess work in how to combine the solar activity input parameters to insure that the results provide answers at the proper risk levels.

Smith, Robert E.↗

NASA NTRS2001

Risk estimation based on chromosomal aberrations induced by radiation

The presence of a causal association between the frequency of chromosomal aberrations in peripheral blood lymphocytes and the risk of cancer has been substantiated recently by epidemiological studies. Cytogenetic analyses of crew members of the Mir Space Station have shown that a significant increase in the frequency of chromosomal aberrations can be detected after flight, and that such an increase is likely to be attributed to the radiation exposure. The risk of cancer can be estimated directly from the yields of chromosomal aberrations, taking into account some aspects of individual susceptibility and other factors unrelated to radiation. However, the use of an appropriate technique for the collection and analysis of chromosomes and the choice of the structural aberrations to be measured are crucial in providing sound results. Based on the fraction of aberrant lymphocytes detected before and after flight, the relative risk after a long-term Mir mission is estimated to be about 1.2-1.3. The new technique of mFISH can provide useful insights into the quantification of risk on an individual basis.

STS Shuttle Project↗

NASA NTRS2020

IV&V Assurance Case Design for Artemis II

As human-rated missions like those in NASA’s Artemis program continue to grow in both size and complexity, and the role of software in achieving mission objectives expands dramatically, NASA’s Independent Verification and Validation (IV&V) Teams face evolving challenges in assuring the safety and performance of the safety- and mission-critical embedded software that is essential to landing astronauts on the surface of the Moon by 2024. Key among these challenges is IV&V’s desire to present a cohesive, integrated assurance statement to its stakeholders that encapsulates and summarizes our assurance positions across the integrated Artemis systems and their combined role in support of a safe and successful flight. In order to meet this challenge, the IV&V Teams have begun a transition to using formal assurance case concepts and documentation in the Goal Structuring Notation (GSN) to build an argument in support of software assurance. IV&V recognizes significant benefits to the logical argumentation structure provided by assurance cases and GSN over our current practices for documenting and managing assurance claims. In order to reap these benefits, IV&V is integrating the use of assurance case concepts with our paradigm of follow-the-risk capability based assurance. Because of this, assurance cases created and used by IV&V are distinct from the sort of assurance case created by a development project or embedded software assurance organization. IV&V’s assurance cases depend much less upon standards and regulations, and more on evidence captured by IV&V regarding the environment, requirements, design, and implementation. IV&V constructs an independent network of claims based on an independent decomposition of arguments. Based upon the risk posture of these claims and their associated software and software artifacts, IV&V then develops and executes engineering analyses and testing, which provide evidence to either support or refute the claim. This emerging risk-informed assurance case methodology is being put into practice as IV&V plans for support of the Artemis II mission, the first flight of the Orion capsule and Space Launch System with astronauts on board.

Gerek Whitman↗

NASA NTRS2020

IV&V Assurance Case Design for Artemis II

As human-rated missions like those in NASA's Artemis program continue to grow in both size and complexity, and the role of software in achieving mission objectives expands dramatically, NASA's Independent Verification and Validation (IV&V) Teams face evolving challenges in assuring the safety and performance of the safety- and mission-critical embedded software that is essential to landing astronauts on the surface of the Moon by 2024. Key among these challenges is IV&V's desire to present a cohesive, integrated assurance statement to its stakeholders that encapsulates and summarizes our assurance positions across the integrated Artemis systems and their combined role in support of a safe and successful flight. In order to meet this challenge, the IV&V Teams have begun a transition to using formal assurance case concepts and documentation in the Goal Structuring Notation (GSN) to build an argument in support of software assurance. IV&V recognizes significant benefits to the logical argumentation structure provided by assurance cases and GSN over our current practices for documenting and managing assurance claims. In order to reap these benefits, IV&V is integrating the use of assurance case concepts with our paradigm of follow-the-risk capability based assurance. Because of this, assurance cases created and used by IV&V are distinct from the sort of assurance case created by a development project or embedded software assurance organization. IV&V's assurance cases depend much less upon standards and regulations, and more on evidence captured by IV&V regarding the environment, requirements, design, and implementation. IV&V constructs an independent network of claims based on an independent decomposition of arguments. Based upon the risk posture of these claims and their associated software and software artifacts, IV&V then develops and executes engineering analyses and testing, which provide evidence to either support or refute the claim. This emerging risk-informed assurance case methodology is being put into practice as IV&V plans for support of the Artemis II mission, the first flight of the Orion capsule and Space Launch System with astronauts on board.

Whitman, Gerek↗

NASA NTRS2019

An Astronaut's Risk of Experiencing a Critical Impact from Lunar Ejecta During Lunar EVA

The Moon is under constant bombardment by meteoroids. When the meteoroid is large, the impact craters the surface, launching crater ejecta far from the impact potentially threatening astronauts on the lunar surface. In the early 1960’s, the ejecta impact flux was thought no more than the sporadic meteoroid flux but with speeds one to two orders of magnitude smaller. However, the Lunar Module designers realized by 1965 that meteoroid bumpers do not perform well at the smaller ejecta impact speeds. Their estimates of the Lunar Module risk of penetration by ejecta were 25 to 50% of the total risk. This was in spite of the exposure time to ejecta being only a third of that to sporadic meteoroids. The standard committee based the 1969 NASA SP-8013 lunar ejecta environment on Zook’s 1967 flux analysis and Gault, Shoemaker and Moore’s 1963 test data for impacts into solid basalt targets. However, Zook noted in his 1967 analysis, that if the lunar surface was composed of soil, that the ejected soil particles would be smaller than ejected basalt fragments and that the ejection speeds would be smaller. Both effects contribute to reducing the risk of a critical failure due to lunar ejecta. The authors revised Zook’s analysis to incorporate soil particle size distributions developed from analysis of Apollo lunar soil samples and ejected mass as a function of ejecta speed developed from coupling parameter analyses of soil impact-test data. The authors estimated EVA risk by assuming failure occurs at a critical impact energy. At these impact speeds, this might be true for suit hard and soft goods. However, these speeds are small enough that there may be significant strength effects that require new test data to modify the hypervelocity critical energy failure criterion. With these caveats, Christiansen, Cour-Palais and Freisen list the critical energy of the ISS EMU hard upper torso as 44 J and the helmet and visor as 71 J at hypervelocity. The authors then assumed that the lunar EVA suit fails at 50 J critical energy. This results in a 1,700,000 years mean time to failure using the results of this analysis and a 3,800 years mean time to failure using NASA SP-8013.

Bjorkman, Michael D.↗

NASA NTRSDate not supplied

Pre-Flight Hazardous Gas Assessment Methodology for the Space Launch System

The complexity of the Artemis I liquid rocket propulsion systems produces many sources of hazards during the operation of the vehicle. Pre-flight hazardous gas leakages pose fire and explosion risks to rocket that could potentially lead to loss of the vehicle, mission, and crew. The National Aeronautics and Space Administration (NASA) uses a probability risk assessment strategy to assess the likelihood of the hazard and the consequence should the hazardous situation occur. For high probability hazards that pose a potentially catastrophic consequence to the vehicle, the most effective strategy for reducing the risk is accomplished by engineering and implementing systems that actively mitigate the hazard. A hazards analysis is completed to determine the likelihood and severity of each hazard. These hazard analyses are informed using relevant empirical data and physics-based analytical models. Time-accurate Computational Fluid Dynamics models used to quantify and understand the risks posed to Artemis I due to expulsions of hazardous gas near the vehicle. Several sources of hazardous gas that posed a risk to Artemis I during nominal pre-flight operations are analyzed in this work. The results of the analyses were used to develop flight rationale and make risk acceptance decisions for the Artemis I launch.

Brian R. Richardson↗

NASA NTRSDate not supplied

Pre-Flight Hazardous Gas Assessment Methodology for the Space Launch System

The complexity of the Artemis I liquid rocket propulsion systems produces many sources of hazards during the operation of the vehicle. Pre-flight hazardous gas leakages pose fire and explosion risks to rocket that could potentially lead to loss of the vehicle, mission, and crew. The National Aeronautics and Space Administration (NASA) uses a probability risk assessment strategy to assess the likelihood of the hazard and the consequence should the hazardous situation occur. For high probability hazards that pose a potentially catastrophic consequence to the vehicle, the most effective strategy for reducing the risk is accomplished by engineering and implementing systems that actively mitigate the hazard. A hazards analysis is completed to determine the likelihood and severity of each hazard. These hazard analyses are informed using relevant empirical data and physics-based analytical models. Time-accurate Computational Fluid Dynamics models used to quantify and understand the risks posed to Artemis I due to expulsions of hazardous gas near the vehicle. Several sources of hazardous gas that posed a risk to Artemis I during nominal pre-flight operations are analyzed in this work. The results of the analyses were used to develop flight rationale and make risk acceptance decisions for the Artemis I launch.

Brian R. Richardson↗

NASA NTRS1990

A methodology for evaluating the reliability and risk of structures under complex service environments

The theoretical basis and numerical implementation of NESSUS (Numerical Evaluation of Stochastic Structures Under Stress; Cruse et al., 1988), a computer code for probabilistic structural analyses of aerospace components, are described, with an emphasis on the use of NESSUS for reliability and risk assessment. Topics addressed include the structure of NESSUS, the material-properties model, computational procedures, probabilistic models of fatigue-crack initiation, risk/cost evaluation, fatigue-fracture analyses, and fatigue-crack propagation. Numerical results from typical applications are presented in extensive graphs and briefly characterized; the usefulness of NESSUS predictions for establishing inspection and retirement schedules and for component certification is indicated.

Shiao, Michael C.↗

NASA NTRS1976

Space-based solar power conversion and delivery systems study. Volume 1: Executive summary

The technical and economic aspects of satellite solar power systems are presented with a focus on the current configuration 5000 MW system. The technical studies include analyses of the orbital system structures, control and stationkeeping, and the formulation of program plans and costs for input to the economic analyses. The economic analyses centered about the development and use of a risk analysis model for a system cost assessment, identification of critical issues and technologies, and to provide information for programmatic decision making. A preliminary economic examination of some utility interface issues is included. Under the present state-of-knowledge, it is possible to formulate a program plan for the development of a satellite solar power system that can be economically justified. The key area of technological uncertainty is man's ability to fabricate and assemble large structures in space.

Hazelrigg, G. A., Jr.↗

NASA NTRS2011

NASA Accident Precursor Analysis Handbook, Version 1.0

Catastrophic accidents are usually preceded by precursory events that, although observable, are not recognized as harbingers of a tragedy until after the fact. In the nuclear industry, the Three Mile Island accident was preceded by at least two events portending the potential for severe consequences from an underappreciated causal mechanism. Anomalies whose failure mechanisms were integral to the losses of Space Transportation Systems (STS) Challenger and Columbia had been occurring within the STS fleet prior to those accidents. Both the Rogers Commission Report and the Columbia Accident Investigation Board report found that processes in place at the time did not respond to the prior anomalies in a way that shed light on their true risk implications. This includes the concern that, in the words of the NASA Aerospace Safety Advisory Panel (ASAP), "no process addresses the need to update a hazard analysis when anomalies occur" At a broader level, the ASAP noted in 2007 that NASA "could better gauge the likelihood of losses by developing leading indicators, rather than continue to depend on lagging indicators". These observations suggest a need to revalidate prior assumptions and conclusions of existing safety (and reliability) analyses, as well as to consider the potential for previously unrecognized accident scenarios, when unexpected or otherwise undesired behaviors of the system are observed. This need is also discussed in NASA's system safety handbook, which advocates a view of safety assurance as driving a program to take steps that are necessary to establish and maintain a valid and credible argument for the safety of its missions. It is the premise of this handbook that making cases for safety more experience-based allows NASA to be better informed about the safety performance of its systems, and will ultimately help it to manage safety in a more effective manner. The APA process described in this handbook provides a systematic means of analyzing candidate accident precursors by evaluating anomaly occurrences for their system safety implications and, through both analytical and deliberative methods used to project to other circumstances, identifying those that portend more serious consequences to come if effective corrective action is not taken. APA builds upon existing safety analysis processes currently in practice within NASA, leveraging their results to provide an improved understanding of overall system risk. As such, APA represents an important dimension of safety evaluation; as operational experience is acquired, precursor information is generated such that it can be fed back into system safety analyses to risk-inform safety improvements. Importantly, APA utilizes anomaly data to predict risk whereas standard reliability and PRA approaches utilize failure data which often is limited and rare.

Groen, Frank↗

NASA NTRS2020

Ensemble Methodologies for Astronaut Cancer Risk Assessment in the face of Large Uncertainties

A new approach to NASA space radiation risk modeling has successfully extended the current NASA probabilistic cancer risk model to an ensemble framework able to consider sub-model parameter uncertainty (e.g. uncertainty in a radiation quality parameter) as well as model-form uncertainty associated with differing theoretical or empirical formalisms (e.g. combined dose-rate and radiation quality effects). Ensemble methodologies are already widely used in weather prediction, modeling of infectious disease outbreaks, and certain terrestrial radiation protection applications to better understand how uncertainty may influence risk decision-making. Applying ensemble methodologies to space radiation risk projections offers the potential to efficiently incorporate emerging research results, allow for the incorporation of future (including international) models, improve uncertainty quantification for underlying sub-models developed against sparse experimental data, and reduce the impact of subjective bias on risk projections. Moreover, risk forecasting across an ensemble of multiple predictive models can provide stakeholders additional information on risk acceptance if current health/medical standards cannot be met or the level of knowledge doesn’t permit a specific risk or exposure limit to be developed for future space exploration missions. In this work, ensemble risk projections implementing multiple sub-models of radiation quality, dose and dose-rate effectiveness factors, excess risk, and latency as ensemble members are presented. Initial consensus methods for ensemble model weights and correlations to account for individual model bias are discussed. In these analyses, the ensemble forecast compares well to results from NASA's current operational cancer risk projection model used to assess permissible exposure limits and permissible mission durations for astronauts. However, a large range of projected risk values are obtained at the upper 95th confidence level where models must extrapolate beyond available biological data sets; closer agreement is seen at the median + one sigma due to the inherent similarities in available models. Future work, including the addition of new models and methods for statistical correlation between predictive members are discussed to define alternate ways of thinking about risk and ‘acceptable’ uncertainty with respect to NASA’s current permissible exposure limits.

space radiation↗

NASA NTRSDate not supplied

Ensemble Cancer Risk Model for Astronaut Risk Assessment

A new approach to NASA space radiation risk modeling has successfully extended the current NASA probabilistic cancer risk model to an ensemble framework able to consider sub-model parameter uncertainty (e.g. uncertainty in a radiation quality parameter) as well as model-form uncertainty associated with differing theoretical or empirical formalisms (e.g. combined dose-rate and radiation quality effects). Ensemble methodologies are already widely used in weather prediction, modeling of infectious disease outbreaks, and certain terrestrial radiation protection applications to better understand how uncertainty may influence risk decision-making. Applying ensemble methodologies to space radiation risk projections offers the potential to efficiently incorporate emerging research results, allow for the incorporation of future (including international) models, improve uncertainty quantification for underlying sub-models developed against sparse experimental data, and reduce the impact of subjective bias on risk projections. Moreover, risk forecasting across an ensemble of multiple predictive models can provide stakeholders additional information on risk acceptance if current health/medical standards cannot be met or the level of knowledge doesn’t permit a specific risk or exposure limit to be developed for future space exploration missions. In this work, ensemble risk projections implementing multiple sub-models of radiation quality, dose and dose-rate effectiveness factors, excess risk, and latency as ensemble members are presented. Initial consensus methods for ensemble model weights and correlations to account for individual model bias are discussed. In these analyses, the ensemble forecast compares well to results from NASA's current operational cancer risk projection model used to assess permissible exposure limits and permissible mission durations for astronauts. However, a large range of projected risk values are obtained at the upper 95th confidence level where models must extrapolate beyond available biological data sets; closer agreement is seen at the median + one sigma due to the inherent similarities in available models. Future work, including the addition of new models and methods for statistical correlation between predictive members are discussed to define alternate ways of thinking about risk and ‘acceptable’ uncertainty with respect to NASA’s current permissible exposure limits.

Lisa C Simonsen↗

NASA NTRS1996

Risk as a Resource - A New Paradigm

NASA must change dramatically because of the current United States federal budget climate. The American people and their elected officials have mandated a smaller, more efficient and effective government. For the past decade, NASA's budget had grown at or slightly above the rate of inflation. In that era, taking all steps to avoid the risk of failure was the rule. Spacecraft development was characterized by extensive analyses, numerous reviews, and multiple conservative tests. This methodology was consistent with the long available schedules for developing hardware and software for very large, billion dollar spacecraft. Those days are over. The time when every identifiable step was taken to avoid risk is being replaced by a new paradigm which manages risk in much the same way as other resources (schedule, performance, or dollars) are managed. While success is paramount to survival, it can no longer be bought with a large growing NASA budget.

Risk Resource↗

NASA NTRSDate not supplied

IMPACT 1.0—Task Impairment: A Novel Approach for Assessing Impairment during Exploration-Class Missions

Exploration-class and International Space Station (ISS) missions have significantly different levels of associated medical risk for crewmembers. The Integrated Medical Model (IMM), the probabilistic risk assessment tool used for ISS medical trade-space analyses, uses a Functional Impairment (FI) metric to determine quality time lost should a crewmember be afflicted with a medical condition. While IMM-based FI has been successful for ISS operations, it has limitations when applied to exploration-class missions. As the National Aeronautics and Space Administration (NASA) looks ahead to Gateway, Artemis, and Martian missions, a novel, dynamic, and mission-appropriate impairment paradigm is necessary for accurate contingency planning. This paradigm, Task Impairment (TI), fulfills that need by utilizing mission-specific tasks. TI will allow future capability for a loss of mission metric, previously not available with IMM. TI serves as a replacement metric for FI within IMPACT, the next-generation trade-space analysis tool suite created to replace the IMM. IMPACT significantly increases the fidelity of probabilistic risk assessment for exploration-class missions. The Human Exploration of Mars Preliminary List of Crew Tasks (MTL, a source of 1100+ exploration-class mission-specific tasks for crewmembers) was used to calculate TI. Using the Task List, 18 individual Human System Categories were identified as being required to perform each task (e.g., Cardiopulmonary, Cognitive, etc.). Each of the 1200+ tasks were mapped to the Human System categories listed in the Task List. The total number of tasks in each category were tallied to determine how many tasks required each Human System. Lastly, each of the 120 medical conditions from the IMPACT condition list were mapped to the Human System categories to complete the TI calculation. NASA subject matter experts across five medical specialties established consensus for the mapping of each condition. The resulting total tasks impaired by each condition were used to calculate discrete TI values. This process was repeated for each of the four severity/resource utilization variants of each condition, and for each of the three phases of clinical care. Through this process, discrete TI values were calculated for each of the 120 IMPACT medical conditions and their variants. The Task Impairment metric provides higher fidelity, dynamic utility, and quicker analysis of medical impairment compared to the previous Functional Impairment metric used for the Integrated Medical Model. TI will be used for higher fidelity medical impairment analysis and contingency planning during Lunar, Martian, and other long-term exploration-class missions.

William L Fernandez↗