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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↗

Managing Space Radiation Risks on Lunar and Mars Missions: Risk Assessment and Mitigation

Radiation-induced health risks are a primary concern for human exploration outside the Earth's magnetosphere, and require improved approaches to risk estimation and tools for mitigation including shielding and biological countermeasures. Solar proton events are the major concern for short-term lunar missions (<60 d), and for long-term missions (>60 d) such as Mars exploration, the exposures to the high energy and charge (HZE) ions that make-up the galactic cosmic rays are the major concern. Health risks from radiation exposure are chronic risks including carcinogenesis and degenerative tissue risks, central nervous system effects, and acute risk such as radiation sickness or early lethality. The current estimate is that a more than four-fold uncertainty exists in the projection of lifetime mortality risk from cosmic rays, which severely limits analysis of possible benefits of shielding or biological countermeasure designs. Uncertainties in risk projections are largely due to insufficient knowledge of HZE ion radiobiology, which has led NASA to develop a unique probabilistic approach to radiation protection. We review NASA's approach to radiation risk assessment including its impact on astronaut dose limits and application of the ALARA (As Low as Reasonably Achievable) principle. The recently opened NASA Space Radiation Laboratory (NSRL) provides the capability to simulate the cosmic rays in controlled ground-based experiments with biological and shielding models. We discuss how research at NSRL will lead to reductions in the uncertainties in risk projection models. In developing mission designs, the reduction of health risks and mission constraints including costs are competing concerns that need to be addressed through optimization procedures. Mitigating the risks from space radiation is a multi-factorial problem involving individual factors (age, gender, genetic makeup, and exposure history), operational factors (planetary destination, mission length, and period in the solar cycle), and shielding characteristics (materials, mass, and topology). We review optimization metrics for radiation protection including scenarios that integrate biophysics models of radiation risks, operational variables, and shielding design tools needed to assess exploration mission designs. We discuss the application of a crosscutting metric, based on probabilistic risk assessment, to lunar and Mars mission trade studies including the assessment of multi-factorial problems and the potential benefits of new radiation health research strategies or mitigation technologies.

Cucinotta, F. A.↗

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↗

Risk cross sections and their application to risk estimation in the galactic cosmic-ray environment

Radiation risk cross sections (i.e. risks per particle fluence) are discussed in the context of estimating the risk of radiation-induced cancer on long-term space flights from the galactic cosmic radiation outside the confines of the earth's magnetic field. Such quantities are useful for handling effects not seen after low-LET radiation. Since appropriate cross-section functions for cancer induction for each particle species are not yet available, the conventional quality factor is used as an approximation to obtain numerical results for risks of excess cancer mortality. Risks are obtained for seven of the most radiosensitive organs as determined by the ICRP [stomach, colon, lung, bone marrow (BFO), bladder, esophagus and breast], beneath 10 g/cm2 aluminum shielding at solar minimum. Spectra are obtained for excess relative risk for each cancer per LET interval by calculating the average fluence-LET spectrum for the organ and converting to risk by multiplying by a factor proportional to R gamma L Q(L) before integrating over L, the unrestricted LET. Here R gamma is the risk coefficient for low-LET radiation (excess relative mortality per Sv) for the particular organ in question. The total risks of excess cancer mortality obtained are 1.3 and 1.1% to female and male crew, respectively, for a 1-year exposure at solar minimum. Uncertainties in these values are estimated to range between factors of 4 and 15 and are dominated by the biological uncertainties in the risk coefficients for low-LET radiation and in the LET (or energy) dependence of the risk cross sections (as approximated by the quality factor). The direct substitution of appropriate risk cross sections will eventually circumvent entirely the need to calculate, measure or use absorbed dose, equivalent dose and quality factor for such a high-energy charged-particle environment.

NASA Discipline Radiation Health↗

An Improved Risk Priority Measure for the Management of Project Risk

Monte Carlo-based project risk models are essential tools in project risk management, particularly for large, complex projects in which it is difficult to glean intuitively the importance of individual risks to the overall project. Conventional correlation-based methods for measuring the importance of contributing risks in such models are argued here to be both statistically flawed and unintuitive in the importance metrics they produce. Drawing on and adapting methods more traditionally associated with engineering risk models, Risk Reduction Worth (RRW) is introduced as an importance measure. RRW is shown to be statistically robust and provide an easily interpretable, quantitative measure of the importance of a risk to the overall performance of a project; specifically, measuring the extent to which removal of a risk would improve confidence in project outcomes. To ensure practicality of the method, an approach is described in which RRWs can be produced for all contributing risks based on a single Monte Carlo sample. This is demonstrated through application to a large, complex project risk model from which intuitive risk importance insights provide a robust, transparent basis for the allocation of risk management resources.

Risk↗

Perceptions of Climate Risk and Use of Climate Risk Information by Natural Resource Conservation Stakeholders Participating in ADVANCE Projects in Asia and Latin America

Integrating climate risk information into resilience-building activities in the field is important to ensure that adaptation is based on the best available science. Despite this, many challenges exist when developing, communicating, and incorporating climate risk information. There are limited resources on how stakeholders perceive risks, use risk information, and what barriers exist to limit knowledge integration. This paper seeks to define the following: 1) What do conservation stakeholders consider to be the most significant climate risks they face now and possibly in the future? 2) What have been the most significant barriers to their using climate risk information? 3) What sources and types of knowledge would be most useful for these managers to overcome these barriers? A survey was conducted among stakeholders (n = 224) associated with World Wildlife Fund projects in tropical and subtropical countries. A very high proportion of stakeholders used climate risk information and yet faced integration-related challenges, which included too much uncertainty and the lack of a relevant scale for planning. The main factors preventing the use of climate risk information in decision-making were unavailability of climate risk information, no or limited financial or human resources available to respond, lack of organizational mandate or support, and no or limited institutional incentives. Comparing perceived current and future risks revealed a decline in concern for some future climate hazards. Survey respondents identified scientific reports, climate scientists, and online sources as the most useful information sources of climate risk information, while (i) maps and illustrations; (ii) scenarios format; and (iii) data tables, graphs, and charts were identified as user-friendly formats.

Climate risk↗

Influence of Comorbidity on the Risk of Mortality in Men With Unfavorable-Risk Prostate Cancer Undergoing High-Dose Radiation Therapy Alone

Purpose: To explore whether a subgroup of men with unfavorable-risk prostate cancer (PC) exists in whom high-dose radiation therapy (RT) alone is sufficient to avoid excess PC death due to competing risk from cardiometabolic comorbidity. Methods and Materials: This was a cohort study of 7399 men in whom comorbidity (including congestive heart failure, diabetes mellitus, or myocardial infarction) was assessed and recorded with T1-3NxM0 PC treated with brachytherapy with or without neoadjuvant RT, October 1997 to May 2013 at a single providing institution. Cox and competing risks regression analyses were used to assess whether men with unfavorable–intermediate/high-risk versus favorable–intermediate/low-risk PC were at increased risk of PC-specific, all-cause, or other-cause mortality (PCSM, ACM, OCM), adjusting for number of comorbidities, age at and year of brachytherapy, RT use, and an RT treatment propensity score. Results: After a median follow-up of 7.7 years, 935 men died: 80 of PC and 855 of other causes. Among men with no comorbidity, PCSM risk (adjusted hazard ratio [AHR] 2.74 [95% confidence interval (CI) 1.49-5.06], P=.001) and ACM risk (AHR 1.30 [95% CI 1.07-1.58], P=.007) were significantly increased in men with unfavorable–intermediate/high-risk PC versus favorable–intermediate/low-risk PC, with no difference in OCM (P=.07). Although PCSM risk was increased in men with 1 comorbidity (AHR 2.87 [95% CI 1.11-7.40], P=.029), ACM risk was not (AHR 1.03 [95% CI 0.78-1.36], P=.84). Neither PCSM risk (AHR 4.39 [95% CI 0.37-51.98], P=.24) or ACM risk (AHR 1.43 [95% CI 0.83-2.45], P=.20) was increased in men with 2 comorbidities. Conclusions: To minimize death from PC, high-dose RT alone may be sufficient treatment in men with 2 or more cardiometabolic comorbidities and unfavorable–intermediate- and high-risk PC.

62 RADIOLOGY AND NUCLEAR MEDICINE↗

Risk Ratio and Risk Difference Estimation in Case-cohort Studies

Background: In case-cohort studies with binary outcomes, ordinary logistic regression analyses have been widely used because of their computational simplicity. However, the resultant odds ratio estimates cannot be interpreted as relative risk measures unless the event rate is low. The risk ratio and risk difference are more favorable outcome measures that are directly interpreted as effect measures without the rare disease assumption. Methods: We provide pseudo-Poisson and pseudo-normal linear regression methods for estimating risk ratios and risk differences in analyses of case-cohort studies. These multivariate regression models are fitted by weighting the inverses of sampling probabilities. Also, the precisions of the risk ratio and risk difference estimators can be improved using auxiliary variable information, specifically by adapting the calibrated or estimated weights, which are readily measured on all samples from the whole cohort. Finally, we provide computational code in R (R Foundation for Statistical Computing, Vienna, Austria) that can easily perform these methods. Results: Through numerical analyses of artificially simulated data and the National Wilms Tumor Study data, accurate risk ratio and risk difference estimates were obtained using the pseudo-Poisson and pseudo-normal linear regression methods. Also, using the auxiliary variable information from the whole cohort, precisions of these estimators were markedly improved. Conclusion: The ordinary logistic regression analyses may provide uninterpretable effect measure estimates, and the risk ratio and risk difference estimation methods are effective alternative approaches for case-cohort studies. These methods are especially recommended under situations in which the event rate is not low.

60 APPLIED LIFE SCIENCES↗

High Value Risk Targets in Human System Risk

The Human System Risk Board (HSRB) has the overall responsibility for tracking the evolution of the top ~30 human system risks that it has identified to be associated with human spaceflight. The Board is also charged with maintaining a consistent, integrated process to mitigate those risks, and developing evidence-based risk posture recommendations. Each Risk Custodian Team (RCT) identifies High Value Risk Mitigation Targets (HVRMT) that have the highest likelihood or greatest impact in reducing their risk. These typically include areas where there are major gaps in knowledge or capability; or other targets that promise to yield returns worthy of investments in time, money and other resources by stakeholders interested in reducing Human System Risk. As part of the review of each risk the Board members consider and discuss the HVRMT statements, which are then approved by the Board Chair. High Value Risk Mitigation Targets can include research activities funded by the Human Research Program, but often involve recommending standards, monitoring, or other operational goals to reduce risk. This presentation will discuss common themes and highlights of the approved HVRTs to inform IWS attendees and the wider research community.

D M Buckland↗

Application of Risk Assessment Tools in the Continuous Risk Management (CRM) Process

Marshall Space Flight Center (MSFC) of the National Aeronautics and Space Administration (NASA) is currently implementing the Continuous Risk Management (CRM) Program developed by the Carnegie Mellon University and recommended by NASA as the Risk Management (RM) implementation approach. The four most frequently used risk assessment tools in the center are: (a) Failure Modes and Effects Analysis (FMEA), Hazard Analysis (HA), Fault Tree Analysis (FTA), and Probabilistic Risk Analysis (PRA). There are some guidelines for selecting the type of risk assessment tools during the project formulation phase of a project, but there is not enough guidance as to how to apply these tools in the Continuous Risk Management process (CRM). But the ways the safety and risk assessment tools are used make a significant difference in the effectiveness in the risk management function. Decisions regarding, what events are to be included in the analysis, to what level of details should the analysis be continued, make significant difference in the effectiveness of risk management program. Tools of risk analysis also depends on the phase of a project e.g. at the initial phase of a project, when not much data are available on hardware, standard FMEA cannot be applied; instead a functional FMEA may be appropriate. This study attempted to provide some directives to alleviate the difficulty in applying FTA, PRA, and FMEA in the CRM process. Hazard Analysis was not included in the scope of the study due to the short duration of the summer research project.

Paul S. Ray↗

Managing Lunar and Mars Mission Radiation Risks: Cancer Risks, Uncertainties, and Shielding Effectiveness - Part 1

This document addresses calculations of probability distribution functions (PDFs) representing uncertainties in projecting fatal cancer risk from galactic cosmic rays (GCR) and solar particle events (SPEs). PDFs are used to test the effectiveness of potential radiation shielding approaches. Monte-Carlo techniques are used to propagate uncertainties in risk coefficients determined from epidemiology data, dose and dose-rate reduction factors, quality factors, and physics models of radiation environments. Competing mortality risks and functional correlations in radiation quality factor uncertainties are treated in the calculations. The cancer risk uncertainty is about four-fold for lunar and Mars mission risk projections. For short-stay lunar missins (<180 d), SPEs present the most significant risk, but one effectively mitigated by shielding. For long-duration (>180 d) lunar or Mars missions, GCR risks may exceed radiation risk limits. While shielding materials are marginally effective in reducing GCR cancer risks because of the penetrating nature of GCR and secondary radiation produced in tissue by relativisitc particles, polyethylene or carbon composite shielding cannot be shown to significantly reduce risk compared to aluminum shielding. Therefore, improving our knowledge of space radiobiology to narrow uncertainties that lead to wide PDFs is the best approach to ensure radiation protection goals are met for space exploration.

Cucinotta, Francis A.↗

Risky Business: The Science and Art of Radiation Risk Communication in the High Risk Context of Space Travel

Successfully communicating the complex risks associated with radiation exposure is a difficult undertaking; communicating those risks within the high-risk context of space travel is uniquely challenging. Since the potential risks of space radiation exposure are not expected to be realized until much later in life, it is hard to draw comparisons between other spaceflight risks such as hypoxia and microgravity-induced bone loss. Additionally, unlike other spaceflight risks, there is currently no established mechanism to mitigate the risks of incurred radiation exposure such as carcinogenesis. Despite these challenges, it is the duty of the Space Radiation Analysis Group (SRAG) at NASA's Johnson Space Center to provide astronauts with the appropriate information to effectively convey the risks associated with exposure to the space radiation environment. To this end, astronauts and their flight surgeons are provided with an annual radiation risk report documenting the astronaut's individual radiation exposures from space travel, medical, and internal radiological procedures throughout the astronaut's career. In an effort to improve this communication and education tool, this paper critically reviews the current report style and explores alternative report styles to define best methods to appropriately communicate risk to astronauts, flight surgeons, and management.

Elgart, Shona Robin↗

New risk metrics and mathematical tools for risk analysis: Current and future challenges

The current status of the food safety supply world wide, has led Food and Agriculture Organization (FAO) and World Health Organization (WHO) to establishing Risk Analysis as the single framework for building food safety control programs. A series of guidelines and reports that detail out the various steps in Risk Analysis, namely Risk Management, Risk Assessment and Risk Communication is available. The Risk Analysis approach enables integration between operational food management systems, such as Hazard Analysis Critical Control Points, public health and governmental decisions. To do that, a series of new Risk Metrics has been established as follows: i) the Appropriate Level of Protection (ALOP), which indicates the maximum numbers of illnesses in a population per annum, defined by quantitative risk assessments, and used to establish; ii) Food Safety Objective (FSO), which sets the maximum frequency and/or concentration of a hazard in a food at the time of consumption that provides or contributes to the ALOP. Given that ALOP is rather a metric of the public health tolerable burden (it addresses the total ‘failure’ that may be handled at a national level), it is difficult to be interpreted into control measures applied at the manufacturing level. Thus, a series of specific objectives and criteria for performance of individual processes and products have been established, all of them assisting in the achievement of FSO and hence, ALOP. In order to achieve FSO, tools quantifying the effect of processes and intrinsic properties of foods on survival and growth of pathogens are essential. In this context, predictive microbiology and risk assessment have offered an important assistance to Food Safety Management. Predictive modelling is the basis of exposure assessment and the development of stochastic and kinetic models, which are also available in the form of Web-based applications, e.g., COMBASE and Microbial Responses Viewer), or introduced into user-friendly softwares, (e.g., Seafood Spoilage Predictor) have evolved the use of information systems in the food safety management. Such tools are updateable with new food-pathogen specific models containing cardinal parameters and multiple dependent variables, including plate counts, concentration of metabolic products, or even expression levels of certain genes. Then, these tools may further serve as decision-support tools which may assist in product logistics, based on their scientifically-based and “momentary” expressed spoilage and safety level.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Chemoprevention Uptake for Breast Cancer Risk Reduction Varies by Risk Factor

Background/Objective: The efficacy of chemoprevention for breast cancer risk reduction has been demonstrated in randomized controlled trials; however, use remains low. We sought to determine whether uptake differed by risk factors, and to identify reasons for refusal and termination. Methods: Women seen in a high-risk clinic from October 2014 to June 2017 considered eligible for chemoprevention (history of lobular carcinoma in situ, atypia, family history of breast/ovarian cancer, genetic mutation, or history of chest wall radiation) were retrospectively identified. Breast cancer risk factors were compared among those with and without chemoprevention use, and compliance was noted. Results: Overall, 1506 women were identified, 24% with prior/current chemoprevention use. Women ≥ 50 years of age were more likely to use chemoprevention than women < 50 years of age (28% vs. 11%, p < 0.001). Chemoprevention use by risk factor ranged from 7 to 40%. Having multiple risk factors did not increase use. Significant variation by risk factor was present among women ≥ 50 years of age (p < 0.001), but not among women < 50 years of age (p = 0.1). Among women with a documented discussion regarding chemoprevention (575/1141), fear of adverse effects was the most common refusal reason (57/156; 36%). The majority of women (61%) who initiated chemoprevention completed 5 years. Conclusion: Chemoprevention use among women at increased risk for breast cancer remains low, with more frequent use among women ≥ 50 years of age. These data highlight the need for ongoing educational efforts and counseling, as the majority who begin therapy complete 5 years of use. Given the fear of adverse effects as well as low uptake, particularly among women < 50 years of age, alternative risk-reducing strategies are needed.

62 RADIOLOGY AND NUCLEAR MEDICINE↗

Task 12 PV Sustainability - Human Health Risk Assessment Methods for PV, Part 3: Module Disposal Risks

End-of-life management is important for addressing large future photovoltaic (PV) waste volumes and conserving raw materials for use in new PV modules. In regions without regulatory mandates for PV recycling, end-of-life PV modules can be disposed in accordance with general waste laws. Given the use of various metals as raw materials in semiconductor compounds and electrical contacts in commercial PV modules, some stakeholders have raised concerns regarding potential environmental impacts if PV modules are subject to improper disposal instead of being recycled or disposed in sanitary landfills, as is required in most world regions. To evaluate these concerns, screening-level risk assessment methods are developed herein that evaluate potential human health risks from groundwater and surface (air, soil, surface water) exposure pathways. The methods estimate potential impacts from disposal of end-of-life (EOL) PV modules in non-sanitary landfills under the following worst-case conditions: no leachate collection or groundwater monitoring, no liner for preventing leachate migration, uncovered waste, and lack of stormwater management. Examining worst-case conditions allows the exploration of maximum potential risk to attempt to ensure disposal does not increase health risk above regulatory thresholds. Specifically, this report presents an analysis of potential human health risks associated with non-sanitary landfill disposal for three PV technologies, focusing on release of the highest-prioritized chemical element for each: lead (Pb) in crystalline-silicon (c-Si) PV modules, cadmium (Cd) in thin film cadmium telluride (CdTe) PV modules, and selenium (Se) in thin film copper indium selenide (CIS) PV modules. The prioritization of these chemical elements for analysis is based on stakeholder interest. Because the methodology is chemical-specific, the risk assessment results for these chemicals cannot be directly generalized to other chemicals, although the risk assessment methodology can be applied to other chemicals. If the chemicals chosen are indeed the ones presenting greatest risk, then the results herein should represent the upper bound of health risk from exposure to a single constituent.

14 SOLAR ENERGY↗

Program Risk Planning with Risk as a Resource

The current focus of NASA on cost effective ways of achieving mission objectives has created a demand for a change in the risk management process of a program. At present, there is no guidelines as to when risk taking is justified due to high cost for a marginal improvement in risk. As a remedial step, Dr. Greenfield of NASA, developed a concept of risk management with risk as a resource. In the report, the following topics are addressed: (1) the risk management approach; (2) planning risk and program life cycle; (3) key components of a typical program; (4) the risk trading methodology; (5) review and decision process; (6) merits of the proposed risk planning approach; and (7) recommendations.

Ray, Paul S.↗

Assessing the Relative Risk of Aerocapture Using Probabalistic Risk Assessment

A recent study performed for the Aerocapture Technology Area in the In-Space Propulsion Technology Projects Office at the Marshall Space Flight Center investigated the relative risk of various capture techniques for Mars missions. Aerocapture has been proposed as a possible capture technique for future Mars missions but has been perceived by many in the community as a higher risk option as compared to aerobraking and propulsive capture. By performing a probabilistic risk assessment on aerocapture, aerobraking and propulsive capture, a comparison was made to uncover the projected relative risks of these three maneuvers. For mission planners, this knowledge will allow them to decide if the mass savings provided by aerocapture warrant any incremental risk exposure. The study focuses on a Mars Sample Return mission currently under investigation at the Jet Propulsion Laboratory (JPL). In each case (propulsive, aerobraking and aerocapture), the Earth return vehicle is inserted into Martian orbit by one of the three techniques being investigated. A baseline spacecraft was established through initial sizing exercises performed by JPL's Team X. While Team X design results provided the baseline and common thread between the spacecraft, in each case the Team X results were supplemented by historical data as needed. Propulsion, thermal protection, guidance, navigation and control, software, solar arrays, navigation and targeting and atmospheric prediction were investigated. A qualitative assessment of human reliability was also included. Results show that different risk drivers contribute significantly to each capture technique. For aerocapture, the significant drivers include propulsion system failures and atmospheric prediction errors. Software and guidance hardware contribute the most to aerobraking risk. Propulsive capture risk is mainly driven by anomalous solar array degradation and propulsion system failures. While each subsystem contributes differently to the risk of each technique, results show that there exists little relative difference in the reliability of these capture techniques although uncertainty for the aerocapture estimates remains high given the lack of in-space demonstration.

Percy, Thomas K.↗