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At least 19 records

Long-Term Health Risk Quantification

Astronauts face hazards during spaceflight, including space radiation exposure, isolation and confinement, traveling far distances from Earth, reduced gravity levels, and closed and hostile environments. These hazards drive the definition of human health and performance risks associated with spaceflight. NASA’s Human System Risk Board maintains the human spaceflight risk posture for in-mission risks, as well as post-flight, Long-Term Health (LTH)risks potentially occurring later in the astronaut’s life. LTH risk encompasses the timeframe from immediately post-flight, through the rest of an astronaut’s career, through retirement, and until death. Possible LTH risk outcomes include the time and interventions needed for the astronaut to return to preflight physiological states after experiencing spaceflight hazards and recovery from any in-mission medical events that persist into the post-flight timeframe. It includes chronic complications that may arise due to experiencing in-flight medical conditions or injuries and medical conditions that occur later in life with a higher probability of occurrence or with more severity because of their spaceflight exposure. Finally, LTH risk outcomes can also include a reduction in life expectancy due to spaceflight exposures. There have been 144 medical conditions identified by NASA’s Lifetime Surveillance of Astronaut Health team to be associated with LTH risk. Epidemiological studies have been performed for some of these conditions to determine if astronauts suffer from an increased prevalence or severity of the condition due to their spaceflight experience compared to a comparable cohort .Differences in astronaut mortality or morbidity due to spaceflight experience were not detected in several of these studies. There were two cases where a modest increase in the incidence rate of astronaut LTH outcomes was detected. The first suggested an increase in the incidence of melanoma cases in astronauts, where the number of cases in astronauts were similar to the elevated number of cases observed in airplane pilots. The second provided some evidence of elevated numbers of cardiovascular disease events in astronauts compared to an appropriate healthy comparator cohort, which may warrant additional investigation. The lack of detection of LTH risk outcomes should not ease concerns about astronaut LTH. The studies highlighted here constitute only a small portion of the potential LTH conditions that could occur. Once epidemiological studies are performed on all conditions, significant findings may be detected. The analysis of astronaut LTH also suffers from limited numbers of data points because of the limited numbers of astronauts overall and the even fewer who have reached an age where LTH outcomes may begin to manifest. As shuttle and ISS astronauts begin to age and increase the feasibility of analysis, LTH outcomes may be detected. An application of risk quantification is the use of risk metrics within trade studies for resource prioritization and decision making. Trade studies regarding countermeasures to LTH risk outcomes would benefit from a quantification of LTH risk. NASA has ground-based processes in place such as astronaut screening and access to continuous medical monitoring and care during and after their astronaut career which are the main methods for mitigating LTH risk. In-mission countermeasures, such as acceptable levels of medical care and available countermeasures to counter spaceflight related physiological decrements, can mitigate a poor health and performance status immediately post-flight. Identifying appropriate risk metrics, obtaining valid quantities for them, and tying them to LTH countermeasures are necessary steps for realizing their use in trade studies. This presentation will highlight the challenges associated with the identification, quantification, and utilization of LTH risk metrics

Beth Lewandowski

Strategy for Risk Quantification of Spaceflight Crew Health and Performance Using Dynamic Probabilistic Risk Assessment

At NASA, the Crew Health and Performance (CHP) system represents the span of countermeasures, capabilities, interventions, and tested processes and procedures that in combination work to mitigate the human component of spaceflight mission risk. Across the varying NASA mental models of the CHP system, the different functionalities needed to meet human flight systems standards can be broken down into specific categories (i.e. medical capability, environmental health, behavioral health). These categories can be further broken down into specific subgroups generally associated with the CHP functionalities meant to mitigate or buy down individual human system risks. Taking a similar development approach we seek to leverage dynamic probabilistic risk assessment as a means to quantify and relatively assess the human risk state within the crew health and performance domain. By utilizing existing tools as integrators, we propose a rapid development strategy for incorporating research and operational data that represent the influence of the CHP system functionalities, in order to provide order of magnitudes estimates of the influence on most human system risks outcomes. The model system utilizes a modest cumulative risk approach and that limits the scope to primary paths of influence between the CHP functionalities and human system risks, thus enabling quick prototypes of the integrative effects of CHP functional combinations to solicit valuable feedback from stakeholders and customers on the data, relationship, and structure of the integration.

Drayton Munster

Ground Risk Informed Operational Planning for Small Unmanned Aerial Systems

Increasing quantities of small Unmanned Aerial Systems (sUAS) operations present many challenges in terms of safe adoption and integration into existing airspace. The ability to study and quantify the risk to third parties on the ground prior to flight is an important step toward enabling Beyond Visual Line of Sight (BVLOS) operations. The Ground Risk Assessment Service Provider (GRASP) software is a capability developed by NASA to assist with third-party risk quantification and risk-informed flight planning. In this paper, two nominal flight paths intended to represent an infrastructure inspection mission are evaluated using the software to demonstrate its utility. A method is also introduced for adding other NASA-developed capabilities into a single architecture to assess a broader set of operational risks associated with BVLOS operations. These capabilities include a navigation system performance prediction tool, a high fidelity vehicle dynamics model, high resolution wind field data, and other information pertinent to operators. Data produced by these capabilities are combined to enable use of the Performance Based Navigation (PBN) concept borrowed from conventional aviation, providing quantified flight path uncertainty for where the sUAS is likely to be relative to its nominal flight plan. Ground risk is assessed within this region of uncertainty, giving a higher level of confidence in the solution compared to an analysis of only the nominal flight path.

Ground Risk

Data Driven UAM Flight Energy Consumption Prediction and Risk Assessment

With the current technological advancements revolutionizing the concept of Urban Air Mobility (UAM) and package delivery, there is also, a concurrent need to quantify the operational safety of these vehicles in terms of their associated risk. Conducting safe flight operations is critical for UAM vehicles which are electrically Vertical Takeoff and Landing (eVTOL) vehicles, to operate in current Air traffic control. In this paper, a data-driven method for UAM vehicle energy consumption prediction and risk quantification with conditional value-at-risk based on energy consumption distribution is presented. Significant factors affecting energy consumption, such as density altitude, aircraft design, airspeed, and collision avoidance algorithms, are considered in the data-driven based energy consumption prediction of different eVTOL

Data-driven

Evidence Report: Risk of Cardiovascular Disease and Other Degenerative Tissue Effects from Radiation Exposure

Occupational radiation exposure from the space environment may result in non-cancer or non-CNS degenerative tissue diseases, such as cardiovascular disease, cataracts, and respiratory or digestive diseases. However, the magnitude of influence and mechanisms of action of radiation leading to these diseases are not well characterized. Radiation and synergistic effects of radiation cause DNA damage, persistent oxidative stress, chronic inflammation, and accelerated tissue aging and degeneration, which may lead to acute or chronic disease of susceptible organ tissues. In particular, cardiovascular pathologies such as atherosclerosis are of major concern following gamma-ray exposure. This provides evidence for possible degenerative tissue effects following exposures to ionizing radiation in the form of the GCR or SPEs expected during long-duration spaceflight. However, the existence of low dose thresholds and dose-rate and radiation quality effects, as well as mechanisms and major risk pathways, are not well-characterized. Degenerative disease risks are difficult to assess because multiple factors, including radiation, are believed to play a role in the etiology of the diseases. As additional evidence is pointing to lower, space-relevant thresholds for these degenerative effects, particularly for cardiovascular disease, additional research with cell and animal studies is required to quantify the magnitude of this risk, understand mechanisms, and determine if additional protection strategies are required.The NASA PEL (Permissive Exposure Limit)s for cataract and cardiovascular risks are based on existing human epidemiology data. Although animal and clinical astronaut data show a significant increase in cataracts following exposure and a reassessment of atomic bomb (A-bomb) data suggests an increase in cardiovascular disease from radiation exposure, additional research is required to fully understand and quantify these adverse outcomes at lower doses (less than 0.5 gray (SI unit for ionizing radiation dosage, i.e. one joule of radiation energy per one kilogram of matter)) to facilitate risk prediction. This risk has considerable uncertainty associated with it, and no acceptable model for projecting degenerative tissue risk is currently available. In particular, risk factors such as obesity, alcohol, and tobacco use can act as confounding factors that contribute to the large uncertainties. The PELs could be violated under certain scenarios, including following a large SPE (solar proton event) or long-term GCR (galactic cosmic ray) exposure. Specifically, for a Mars mission, the accumulated dose is sufficiently high that epidemiology data and preliminary risk estimates suggest a significant risk for cardiovascular disease. Ongoing research in this area is intended to provide the evidence base for accurate risk quantification to determine criticality for extended duration missions. Data specific to the space radiation environment must be compiled to quantify the magnitude of this risk to decrease the uncertainty in current PELs and to determine if additional protection strategies are required. New research results could lead to estimates of cumulative radiation risk from CNS and degenerative tissue diseases that, when combined with the cancer risk, may have major negative impacts on mission design, costs, schedule, and crew selection. The current report amends an earlier report (Human Research Program Requirements Document, HRP-47052, Rev. C, dated Jan 2009) in order to provide an update of evidence since 2009.

Patel, Zarana

A Reliable Earth Return System for Safe Recovery of Mars Samples

The objective of a Mars sample return mission is to bring selected Mars surface materials to Earth. Numerous approaches for the Earth-return segment have been analyzed including propulsive or aerocapture return to low-Earth orbit followed by Space Shuttle rendezvous and direct entry. Of these approaches, ballistic entry of a small capsule terminating in a ground landing has been shown to be the lowest risk strategy. Over the past two years, significant work has been performed towards development of a robust direct entry vehicle for Mars sample return. In June 1999, the NASA Planetary Protection Officer provided initial guidance to the former Mars Sample Return Project. The sample return phase of the mission was assigned a restricted Earth return planetary protection classification. The draft mission requirement states that the total mean probability of release of unsterilized Mars material into the Earth;s biosphere must be less than 1.0E-06 (1 in a million). This strict requirement drives the approach and design of the Earth return system. To meet this requirement, selection of the Earth return strategy and development of the Earth return system must be guided by risk, not performance, based decisions. An initial Probabilistic Risk Assessment (PRA) was performed to address the direct entry Earth return system containment assurance reliability and to identify high-risk elements of this system. The results of this PRA identified risk elements that include thermal protection system performance during entry, spin-eject orientation and aerodynamic stability during entry, structural integrity under atmospheric deceleration and impact loads, and tracking/recovery of this system. This initial probabilistic risk quantification demonstrates that, with the proper development program, a prototypical direct entry design can satisfy the containment assurance reliability requirement. Through the current Mars Sample Return Advanced Technology Development effort, an extensive design, analysis, and test program is presently proceeding with the aim of reducing the containment assurance risk of this system. This technology development effort, guided by a continuing PRA, focuses on key risk areas of a direct entry Earth return system including: the thermal protection system, impact dynamics, structural performance, aerodynamic stability, and ground recovery. This development program will culminate in a system validation flight test, 1-2 years prior to launch of the flight system. This flight test would include the launch, entry, and recovery of a full-scale Earth return system, as a scientific validation of the key risk elements to verify nominal design performance. The results of the initial PRA suggested several dominant failure sequences that can be validated in a flight test. These include: demonstrating the thermal protection system reliability and performance during entry, demonstrating the spin-eject orientation and aero-dynamic stability during entry, demonstrating the structural integrity under atmospheric deceleration and impact loads, and demonstrating tracking and recovery of the Earth return system. This single test will directly address over 50% of the total containment assurance risk elements. This presentation will begin by presenting the relative risk of various Earth return strategies. The results of the initial probabilistic risk assessment will be presented followed by a discussion of the development accomplishments and plans for demonstration of a highly reliable direct entry Earth return system.

Braun, R.

Exploration Health Risks: Probabilistic Risk Assessment

Maintenance of human health on long-duration exploration missions is a primary challenge to mission designers. Indeed, human health risks are currently the largest risk contributors to the risks of evacuation or loss of the crew on long-duration International Space Station missions. We describe a quantitative assessment of the relative probabilities of occurrence of the individual risks to human safety and efficiency during space flight to augment qualitative assessments used in this field to date. Quantitative probabilistic risk assessments will allow program managers to focus resources on those human health risks most likely to occur with undesirable consequences. Truly quantitative assessments are common, even expected, in the engineering and actuarial spheres, but that capability is just emerging in some arenas of life sciences research, such as identifying and minimize the hazards to astronauts during future space exploration missions. Our expectation is that these results can be used to inform NASA mission design trade studies in the near future with the objective of preventing the higher among the human health risks. We identify and discuss statistical techniques to provide this risk quantification based on relevant sets of astronaut biomedical data from short and long duration space flights as well as relevant analog populations. We outline critical assumptions made in the calculations and discuss the rationale for these. Our efforts to date have focussed on quantifying the probabilities of medical risks that are qualitatively perceived as relatively high risks of radiation sickness, cardiac dysrhythmias, medically significant renal stone formation due to increased calcium mobilization, decompression sickness as a result of EVA (extravehicular activity), and bone fracture due to loss of bone mineral density. We present these quantitative probabilities in order-of-magnitude comparison format so that relative risk can be gauged. We address the effects of conservative and nonconservative assumptions on the probability results. We discuss the methods necessary to assess mission risks once exploration mission scenarios are characterized. Preliminary efforts have produced results that are commensurate with earlier qualitative estimates of risk probabilities in this and other operational contexts, indicating that our approach may be usefully applied in support of the development of human health and performance standards for long-duration space exploration missions. This approach will also enable mission-specific probabilistic risk assessments for space exploration missions.

Rhatigan, Jennifer

Space Shuttle critical function audit

A large fault-tolerance model of the main propulsion system of the US space shuttle has been developed. This model is being used to identify single components and pairs of components that will cause loss of shuttle critical functions. In addition, this model is the basis for risk quantification of the shuttle. The process used to develop and analyze the model is digraph matrix analysis (DMA). The DMA modeling and analysis process is accessed via a graphics-based computer user interface. This interface provides coupled display of the integrated system schematics, the digraph models, the component database, and the results of the fault tolerance and risk analyses.

Sacks, Ivan J.

Computational Modeling of Space Physiology

The Digital Astronaut Project (DAP), within NASAs Human Research Program, develops and implements computational modeling for use in the mitigation of human health and performance risks associated with long duration spaceflight. Over the past decade, DAP developed models to provide insights into space flight related changes to the central nervous system, cardiovascular system and the musculoskeletal system. Examples of the models and their applications include biomechanical models applied to advanced exercise device development, bone fracture risk quantification for mission planning, accident investigation, bone health standards development, and occupant protection. The International Space Station (ISS), in its role as a testing ground for long duration spaceflight, has been an important platform for obtaining human spaceflight data. DAP has used preflight, in-flight and post-flight data from short and long duration astronauts for computational model development and validation. Examples include preflight and post-flight bone mineral density data, muscle cross-sectional area, and muscle strength measurements. Results from computational modeling supplement space physiology research by informing experimental design. Using these computational models, DAP personnel can easily identify both important factors associated with a phenomenon and areas where data are lacking. This presentation will provide examples of DAP computational models, the data used in model development and validation, and applications of the model.

simulation

Quantification of Operational Risk Using A Data Mining

What is Data Mining? - Data Mining is the process of finding actionable information hidden in raw data. - Data Mining helps find hidden patterns, trends, and important relationships often buried in a sea of data - Typically, automated software tools based on advanced statistical analysis and data modeling technology can be utilized to automate the data mining process

Perera, J. Sebastian

Quantification of Uncertainty and Risk Sensitivity for Safety of Emerging Operations

The growing need to develop and deploy small unmanned aerial vehicles (sUAVs) for various applications in the airspace necessitates reliable tools to accurately predict the flight trajectories of the sUAVs. The knowledge of the predicted trajectories help decision makers anticipate potential conflict, assess the risk, and take appropriate risk mitigation actions. In addition, uncertainties in vehicle models, weather, and controller action further highlights the need for reliable prediction tools. In this project, the application of mixed sparse grid-based quadrature and generalized polynomial chaos(gPC) expansion method for uncertainty quantification and collision assessment in air traffic consisting of fixed-wing small unmanned aerial vehicles (sUAV) was studied. From the results obtained, it can be concluded that this provides a reliable framework to carry out quantitative conflict assessment in an unmanned air traffic, which when employed, can improve the functionalities of the unmanned traffic management system. It was observed that the results from the gPC expansion framework developed in the project can be utilized to conduct rapid probabilistic collision assessment for near real-time unmanned traffic management in the airspace. From the vehicle models, position updates, and wind-field data, a priori gPC based 3-σcon-fidence ellipses can provide estimates of potential conflict at some future instants. The computational costs scaled linearly when the uncertain inputs were fewer. Further, the largest allowable distribution of para-metric uncertainties that leads to the smallest risk of collision in traffic of small unmanned aerial vehicles could be calculated. The time of closest approach between two sUAVs can be established paving way for development of proactive mitigation strategies. The separation between the sUAVs was found to be most significantly affected by uncertainties in the maximum available thrusts, zero-lift drag coefficients, and wing planform areas of the sUAVs. The study of uncertain wind-fields indicated that a heterogeneous traffic mix resulted in an increased probability of conflict. Increased measurement update rate reduced the uncertain-ties in the trajectories of the vehicles, further reducing the probability of conflict but rapid updates of all vehicles in the airspace poses a stringent communication limitation. The gPC framework also provided the means to analyze vehicle impact (crash region) due to loss of control resulting from actuator failure in sUAS traffic, essentially to predict impact and crash zones for representative vehicles. The predicted regions when compared with non-participant density, provides a means to develop an early mitigation strategy, should the sUAV detect an imminent actuator failure.

Rajnish Bhusal

Improving Quantification of Medical Evacuation Risk for Human Spaceflight in the IMPACT Model

Traditionally, mission planners have used a heuristic and qualitative approach to design medical systems based on prior experience however this approach may result in high variability and implicit bias to design and could put missions and crewmembers at risk. The Informing Mission Planning through Analysis of Complex Tradespaces (IMPACT) tool is a probabilistic risk assessment tool designed by NASA to model medical risk in long duration missions outside of low earth orbit (LEO). This tool can quantify risk metrics such as risk of crewmember death, loss of crew task time, and the need for medical evacuation to better inform and augment the more traditional approach to medical system design. The risk metric of Return to Definitive Care (RTDC) represents the likelihood of requiring medical evacuation and has been difficult to quantify in a reliable and standardized manner. Initial development of the RTDC metric was constrained due to the complexity of a medical evacuation decision and the lack of prior spaceflight data and this presentation will discuss the review and improvement process used to increase model accuracy and fidelity.

Prashant Parmar

Pitfalls and Precautions When Using Predicted Failure Data for Quantitative Analysis of Safety Risk for Human Rated Launch Vehicles

Launch vehicle reliability analysis is largely dependent upon using predicted failure rates from data sources such as MIL-HDBK-217F. Reliability prediction methodologies based on component data do not take into account risks attributable to manufacturing, assembly, and process controls. These sources often dominate component level reliability or risk of failure probability. While consequences of failure is often understood in assessing risk, using predicted values in a risk model to estimate the probability of occurrence will likely underestimate the risk. Managers and decision makers often use the probability of occurrence in determining whether to accept the risk or require a design modification. Due to the absence of system level test and operational data inherent in aerospace applications, the actual risk threshold for acceptance may not be appropriately characterized for decision making purposes. This paper will establish a method and approach to identify the pitfalls and precautions of accepting risk based solely upon predicted failure data. This approach will provide a set of guidelines that may be useful to arrive at a more realistic quantification of risk prior to acceptance by a program.

Hatfield, Glen S.

Pitfalls and Precautions When Using Predicted Failure Data for Quantitative Analysis of Safety Risk for Human Rated Launch Vehicles

Launch vehicle reliability analysis is largely dependent upon using predicted failure rates from data sources such as MIL-HDBK-217F. Reliability prediction methodologies based on component data do not take into account system integration risks such as those attributable to manufacturing and assembly. These sources often dominate component level risk. While consequence of failure is often understood, using predicted values in a risk model to estimate the probability of occurrence may underestimate the actual risk. Managers and decision makers use the probability of occurrence to influence the determination whether to accept the risk or require a design modification. The actual risk threshold for acceptance may not be fully understood due to the absence of system level test data or operational data. This paper will establish a method and approach to identify the pitfalls and precautions of accepting risk based solely upon predicted failure data. This approach will provide a set of guidelines that may be useful to arrive at a more realistic quantification of risk prior to acceptance by a program.

Hatfield, Glen S.

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

Mission risk appraisal.

Mission risk appraisal technique for identification and quantification of high risk areas for unmanned interplanetary missions

MISSION PLANNING

The interaction of high voltage systems with the environments of the moon and Mars

An evaluation is made of the consequences of the interaction of high-voltage spacecraft systems designed for use in orbit or on the lunar and Martian surfaces with such environmental components as electrically charged dust, low pressure atmospheres, ionospheric plasmas and neutral gas species, and chemically reactive species. An account is given of plausible means for obtaining the requisite data and developing priorities for the study of each of the identified interactions. Attention is given to the computational tools whose development is required for the simulation and quantification of risk factors for the various likely interactions.

Hillard, G. B.