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NASA NTRS2002

How do we get from cell and animal data to risks for humans from space radiations?

After four decades of human exploration in space, many scientists consider the medical consequences from radiation exposures to be the major biological risk associated with long-term missions. This conclusion is based upon results from a research program that has evolved over the past thirty years. Despite the diversity in both opinions and approaches that necessarily arise in research endeavors such as this, a commonality has emerged from our community. We need epidemiological data for humans, animal data in areas where no human data exist, and data on mechanisms to get from animal to humans. We need a programmatic infrastructure that addresses specific goals as well as basic research. These concepts might be deemed overly simplistic and even tautologous were it not for the fact that they are frequently underutilized and even ignored. This article examines the goals, premises, and infrastructures proposed by expert panels and agencies to address radiation risks in space. It is proposed that the required level of effort and the resources available demand a unified, focused international effort that is, at the same time, subjected to rigorous peer review if it is to be successful. There is a plan; let us implement it.

Non-NASA Center↗

NASA NTRS2001

Genomic instability, bystander effect, cytoplasmic irradiation and other phenomena that may achieve fame without fortune

The possible risk of induced malignancies in astronauts, as a consequence of the radiation environment in space, is a factor of concern for long term missions. Cancer risk estimates for high doses of low LET radiation are available from the epidemiological studies of the A-bomb survivors. Cancer risks at lower doses cannot be detected in epidemiological studies and must be inferred by extrapolation from the high dose risks. The standard setting bodies, such as the ICRP recommend a linear, no-threshold extrapolation of risks from high to low doses, but this is controversial. A study of mechanisms of carcinogenesis may shed some light on the validity of a linear extrapolation. The multi-step nature of carcinogenesis suggests that the role of radiation may be to induce a mutation leading to a mutator phenotype. High energy Fe ions, such as those encountered in space are highly effective in inducing genomic instability. Experiments involving the single particle microbeam have demonstrated a "bystander effect", ie a biological effect in cells not themselves hit, but in close proximity to those that are, as well as the induction of mutations in cells where only the cytoplasm, and not the nucleus, have been traversed by a charged particle. These recent experiments cast doubt on the validity of a simple linear extrapolation, but the data are so far fragmentary and conflicting. More studies are necessary. While mechanistic studies cannot replace epidemiology as a source of quantitative risk estimates, they may shed some light on the shape of the dose response relationship and therefore on the limitations of a linear extrapolation to low doses.

NASA Discipline Radiation Health↗

NASA NTRS2004

The NASA Continuous Risk Management Process

As an intern this summer in the GRC Risk Management Office, I have become familiar with the NASA Continuous Risk Management Process. In this process, risk is considered in terms of the probability that an undesired event will occur and the impact of the event, should it occur (ref., NASA-NPG: 7120.5). Risk management belongs in every part of every project and should be ongoing from start to finish. Another key point is that a risk is not a problem until it has happened. With that in mind, there is a six step cycle for continuous risk management that prevents risks from becoming problems. The steps are: identify, analyze, plan, track, control, and communicate & document. Incorporated in the first step are several methods to identify risks such as brainstorming and using lessons learned. Once a risk is identified, a risk statement is made on a risk information sheet consisting of a single condition and one or more consequences. There can also be a context section where the risk is explained in more detail. Additionally there are three main goals of analyzing a risk, which are evaluate, classify, and prioritize. Here is where a value is given to the attributes of a risk &e., probability, impact, and timeframe) based on a multi-level classification system (e.g., low, medium, high). It is important to keep in mind that the definitions of these levels are probably different for each project. Furthermore the risks can be combined into groups. Then, the risks are prioritized to see what risk is necessary to mitigate first. After the risks are analyzed, a plan is made to mitigate as many risks as feasible. Each risk should be assigned to someone in the project with knowledge in the area of the risk. Then the possible approaches to choose from are: research, accept, watch, or mitigate. Next, all risks, mitigated or not, are tracked either individually or in groups. As the plan is executed, risks are re-evaluated, and the attribute values are adjusted as necessary. Metrics are established and monitored as tools for risk tracking. Also a trigger or threshold should be set on the metric data that indicates when an action is needed. Results of this tracking are usually evaluated and reported in a relevant format at weekly or monthly meetings. Choosing controls is the subsequent step, which involves the effects of the tracking. The three basic controls are: close, continue tracking, and re- plan. Finally communicate & document is the last step, but occurs throughout the process. It is vital that main risks, plans, changes, and progress are known by everyone in the project. A good way to keep everyone updated and inform other projects of common issues is by thoroughly documenting project risks. NASA sees value in risk management and believes that projects have greater probability or success by using the NASA Continuous Risk Management Process.

Pokorny, Frank M.↗

NASA NTRS2017

A Probabilistic Asteroid Impact Risk Model

Asteroid threat assessment requires the quantification of both the impact likelihood and resulting consequence across the range of possible events. This paper presents a probabilistic asteroid impact risk (PAIR) assessment model developed for this purpose. The model incorporates published impact frequency rates with state-of-the-art consequence assessment tools, applied within a Monte Carlo framework that generates sets of impact scenarios from uncertain parameter distributions. Explicit treatment of atmospheric entry is included to produce energy deposition rates that account for the effects of thermal ablation and object fragmentation. These energy deposition rates are used to model the resulting ground damage, and affected populations are computed for the sampled impact locations. The results for each scenario are aggregated into a distribution of potential outcomes that reflect the range of uncertain impact parameters, population densities, and strike probabilities. As an illustration of the utility of the PAIR model, the results are used to address the question of what minimum size asteroid constitutes a threat to the population. To answer this question, complete distributions of results are combined with a hypothetical risk tolerance posture to provide the minimum size, given sets of initial assumptions. Model outputs demonstrate how such questions can be answered and provide a means for interpreting the effect that input assumptions and uncertainty can have on final risk-based decisions. Model results can be used to prioritize investments to gain knowledge in critical areas or, conversely, to identify areas where additional data has little effect on the metrics of interest.

Asteroid↗

NASA NTRSDate not supplied

Risk Characterization Research for Artemis II: Human Factors and Behavioral Performance

BACKGROUND Artemis II will be the first time NASA astronauts go beyond low-Earth orbit (LEO) since the Apollo era, and the first astronauts heading into space in the Orion vehicle. As such, it provides a critical opportunity to refine our understanding of the likelihood and consequences associated with the Behavioral Medicine (BMed), Team, Human System Integration Architecture (HSIA), and Sleep Risks, and prepare for future Moon and Mars missions. However, Artemis II research efforts are uniquely shaped by in-mission data collection constraints. There is currently no in-mission crew time available to complete measures. In-mission data will need to be collected unobtrusively from available data streams (e.g., audiovisual, existing records such as schedules, and actigraphy). Accordingly, the overarching goal of our research is to utilize Artemis II data to further define the likelihood and consequences of these risks, and to create an unobtrusive research infrastructure that can be expanded to include future Artemis missions. This goal spans four aims across three research phases: (1) identify and operationally define key performances metrics and constructs across the four aforementioned risks, (2) develop an unobtrusive methodology and coding scheme for in-mission data collection, (3) characterize performance decrements due to Bmed, Team, HSIA, and Sleep Risks, and (4) develop a data infrastructure for future Artemis missions. The following details results of Phase I efforts in which we address Aims 1 and 2 to develop an unobtrusive measurement plan and coding scheme to capture key constructs, contributing factors, and performance decrements across each risk area. METHOD As part of Phase I, we conducted an interdisciplinary literature review and consulted with SMEs to identify unobtrusive methodologies that leverage text, audio, and/or video data as well as conceptualize key performance metrics, contributing factors, and BMed, Team, HSIA, and Sleep risk constructs related to performance decrements. The Phase I effort resulted in a finalized pre- and post-mission protocol for Artemis II, along with a measurement and coding scheme for in-mission Artemis II data. Phase II will involve data collection from the upcoming Artemis II mission. Phase III will include data processing, coding, depiction, analysis, and report writing of the Artemis II data. RESULTS & DISCUSSION To date, we have completed Phase I efforts. Specifically, we identified BMed, Team, HSIA, and Sleep risk constructs related to performance metrics, summarized how these constructs can be measured using audiovisual data collected during the mission, and worked with NASA’s HFBP Element to finalize a data collection protocol that leverages audiovisual input from the Orion spacecraft system. Our protocol includes novel unobtrusive methodologies that adhere to in-mission data streams and subsequent constraints (e.g., limited storage space on GoPro cameras, ambient noise impeding audio files) to best capture in-mission phenomena across each risk area. We will present our results from Phase I efforts, namely best practices for unobtrusive measurement as identified through literature reviews and SME consultation as well as codebook excerpts for use in Artemis II. We will include a description of planned work as we prepare for Phase II and Phase III of this research plan and the Artemis II mission itself. SUMMARY We describe progress on our Human Factors and Behavioral Performance Research for Artemis II study.

behavioral health↗

NASA NTRS2006

A Holistic Approach for Risk Management During Design

In this paper, an approach for the identification, assessment, mitigation and continuous management of risks during the process of designing a space mission is presented. This approach has been developed by observing the risk patterns that occur at the Project Design Center of the Jet Propulsion Laboratory (TeamX) which develops conceptual, concurrent design of Space Missions. TeamX develops an end-to-end conceptual design of a Space Mission in a matter of one or two weeks. As the risk chair in TeamX, the author has had the opportunity to observe the risk patterns that occur during design over the course of many design sessions. This paper introduces an abstraction and generalization of those patterns. Risk is defined as anything that can go wrong, along with its approximate likelihood and consequence. The indicators, and causes, and effects of these risks are cross cutting across the multiple levels of people and processes involved in the design, and the actual design product itself.

reliability analysis↗

NASA NTRS2008

Assessment of Medical Risks and Optimization of their Management using Integrated Medical Model

The Integrated Medical Model (IMM) Project is a software-based technique that will identify and quantify the medical needs and health risks of exploration crew members during space flight and evaluate the effectiveness of potential mitigation strategies. The IMM Project employs an evidence-based approach that will quantify probability and consequences of defined in-flight medical risks, mitigation strategies, and tactics to optimize crew member health. Using stochastic techniques, the IMM will ultimately inform decision makers at both programmatic and institutional levels and will enable objective assessment of crew health and optimization of mission success using data from relevant cohort populations and from the astronaut population. The objectives of the project include: 1) identification and documentation of conditions that may occur during exploration missions (Baseline Medical Conditions List [BMCL), 2) assessment of the likelihood of conditions in the BMCL occurring during exploration missions (incidence rate), 3) determination of the risk associated with these conditions and quantify in terms of end states (Loss of Crew, Loss of Mission, Evacuation), 4) optimization of in-flight hardware mass, volume, power, bandwidth and cost for a given level of risk or uncertainty, and .. validation of the methodologies used.

Fitts, Mary A.↗

NASA NTRS2013

PRA (Probabilistic Risk Assessments) Participation versus Validation

Probabilistic Risk Assessments (PRAs) are performed for projects or programs where the consequences of failure are highly undesirable. PRAs primarily address the level of risk those projects or programs posed during operations. PRAs are often developed after the design has been completed. Design and operational details used to develop models include approved and accepted design information regarding equipment, components, systems and failure data. This methodology basically validates the risk parameters of the project or system design. For high risk or high dollar projects, using PRA methodologies during the design process provides new opportunities to influence the design early in the project life cycle to identify, eliminate or mitigate potential risks. Identifying risk drivers before the design has been set allows the design engineers to understand the inherent risk of their current design and consider potential risk mitigation changes. This can become an iterative process where the PRA model can be used to determine if the mitigation technique is effective in reducing risk. This can result in more efficient and cost effective design changes. PRA methodology can be used to assess the risk of design alternatives and can demonstrate how major design changes or program modifications impact the overall program or project risk. PRA has been used for the last two decades to validate risk predictions and acceptability. Providing risk information which can positively influence final system and equipment design the PRA tool can also participate in design development, providing a safe and cost effective product.

DeMott, Diana↗

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

Brian R. Richardson↗

NASA NTRS2011

A Team Mental Model Perspective of Pre-Quantitative Risk

This study was conducted to better understand how teams conceptualize risk before it can be quantified, and the processes by which a team forms a shared mental model of this pre-quantitative risk. Using an extreme case, this study analyzes seven months of team meeting transcripts, covering the entire lifetime of the team. Through an analysis of team discussions, a rich and varied structural model of risk emerges that goes significantly beyond classical representations of risk as the product of a negative consequence and a probability. In addition to those two fundamental components, the team conceptualization includes the ability to influence outcomes and probabilities, networks of goals, interaction effects, and qualitative judgments about the acceptability of risk, all affected by associated uncertainties. In moving from individual to team mental models, team members employ a number of strategies to gain group recognition of risks and to resolve or accept differences.

Cooper, Lynne P.↗

NASA NTRS2024

Risk of Bone Fracture due to Spaceflight-induced Changes to Bone

The Human Research Program (HRP) is taking a biomechanical approach to assessing subsequent fracture risk in active astronauts as a consequence of spaceflight exposure. Triennial testing of active and retired astronauts continues as Space Medicine monitors for a premature diagnosis of primary osteoporosis, which is associated with age-related bone loss and skeletal fragility. This updated 2023 Fracture Evidence Report has expanded the description of skeletal changes to capture the full effects of spaceflight on bone: • Recent analysis of fractures from health records of the full astronaut cohort, suggests an increased incidence rate of hip and spine fractures in astronauts following longer spaceflight duration flights compared to incident rates found in shorter duration flights. • Routine preflight-to-postflight surveillance by DXA (dual-energy x-ray absorptiometry) does not provide the full detection of loss and recovery in the long-duration (LD) astronaut nor the full recovery of hip trabecular bone. • The inclusion of hip quantitative computed tomography (QCT) in flight studies delineates effects of spaceflight, of countermeasures, and of post-flight recovery on cortical and trabecular bone parameters—some of which are verified predictors of hip fracture in the aged. • QCT detects and compares the distinct countermeasure effects of the pharmaceutical alendronate and of resistive exercise (on the Advanced Resistive Exercise Device, ARED) in specific cortical and trabecular bone sub-regions during spaceflight. • A published comparison of QCT-determined loss rates of hip trabecular bone in LD astronauts compared to terrestrial cohorts suggest that accelerated loss rates in trabecular volumetric BMD (vBMD) during spaceflight might be analogous to skeletal effects of accelerated loss rates in females due to menopause, potentially leading to disruptions in trabecular microarchitecture. • A dataset of finite element (FE) estimates of hip bone strength in aging terrestrial cohorts (spanning astronaut age-range) provides comparative context for changes in the FE of hip bone strength in LD astronauts, including comparison (force unit of newton) to percentiles (50th, 75th, and 100th) of sex-matched aged humans with hip fractures. • Risk of fracture, due to the mechanical overloading of bones, is being updated with IMPACT, the next-generation tool suite for probabilistic risk assessment (PRA) for exploration missions being created by the Exploration and Medical Capability Element (ExMC) at NASA. IMPACT is currently in development and will not be included in this 2024 update. The risk for fracture necessitates understanding the relationship between applied loads to bone and the biomechanical competence of bone. The Risk for Early Onset Osteoporosis focuses on the weakened condition of bone (including development of new technologies, measurements of novel skeletal attributes, translation of multiple measures to an index of bone fragility, and interpretations of data used to reflect a weakened bone), while the Risk for Fracture assesses factors that influence the probability an astronaut would encounter applied loads exceeding the biomechanical competence of bones, resulting in fracture. This Evidence Report combines the research gaps and tasks associated with both risks.

Fracture↗

NASA NTRS1996

Differences in Femoral Geometry and Structure Due to Immobilization

Reduction in bone mass of the lower extremity is well documented in individuals with paralysis resulting from spinal cord injury (SCI). The consequent osteopenia leads to elevated fracture risk with fractures occurring more commonly in the femoral shaft and supracondylar regions than the hip. A model has recently been described to estimate geometry and structure of the femoral midshaft from whole body scans by dual X-ray absorptiometry (DXA). Increases in femoral geometric and structural properties during growth were primarily related to mechanical loading as reflected by body mass. In this study, we investigate the relationship between body mass and femoral geometry and structure in adults with normal habitual mechanical loading patterns and those with severely reduced loading. The subjects were 78 ambulatory men (aged 20-72 yrs) and 113 men with complete paralysis from SCI of more than 4 years duration (aged 21 73 yrs). Subregional analysis was performed on DXA whole body scans to obtain bone mineral content (BMC, g), cortical thickness (cm), crosssectional moment of inertia (CSMI, cm4), and section modulus (cm3) of the femoral midshaft. All measured bone variables were significantly lower in SCI compared with ambulatory subjects: -29% (BMC), -33% (cortical thickness), -23% (CSMI), and -22% (section modulus) while body mass was not significantly different. However, the associations between body mass and bone properties were notably different; r2 values were higher for ambulatory than SCI subjects in regressions of body mass on BMC (0.48 vs 0.20), CSMI (0.59 vs 0.32), and section modulus (0.59 vs 0.31). No association was seen between body mass and cortical thickness for either group. The greatest difference between groups is in the femoral cortex, consistent with reduced bone mass via endosteal expansion. The relatively lesser difference in geometric and structural properties implies that there is less effect on mechanical integrity than would be expected from bone mass results alone. The reduced association in SCI subjects between body mass and bone properties is not unexpected. Although mean body mass differs little between ambulatory and SCI individuals, the association between body mass and in vivo skeletal loading is no longer present, as mechanical influences are removed except for transfer activities. The residual association is probably attributable to the strength of this influence during growth. These results highlight the importance of examining geometry and structure in conjunction with bone mass.

Kiratli, Beatrice Jenny↗

NASA NTRS2011

Altered Innate and Lymphocytic Immune Responses in Mouse Splenocytes Post-Flight

Space flight is known to affect immune responses of astronauts and animals, decreasing lymphocytic responses to mitogenic stimuli, delayed typed hypersensitivity reactions, and T-cell activation. Despite changes in immune suppression, there are no reports of consistent adverse clinical events post flight. To further investigate the spectrum of affected immune responses, murine splenocytes were stimulated immediately post-shuttle flight (14 days on STS-135) with T-cell stimulators or toll-like receptor agonists. Comparisons were made to ground control splenocytes from age-matched mice. Cell phenotypes were assessed, as well as activation markers and associated cytokine production. The CD4+ population decreased with no concurrent decrease in CD8+ cells from shuttle mice post flight compared to ground controls. Regarding antigen presenting cell populations, the number of CD11c+ cells were slightly elevated post flight, compared to ground controls, with increased MHC Class I expression (I-A(sup b)) and no change in Class II expression (H-2K(sup b)). CD86+ populations were also significantly diminished. However, the decreased markers did not correlate with activity. Stimulation of splenocytes post flight showed significant increase in bead uptake, increased Class I expression, increased TNF-alpha and IL-6 production in response to TLR-2 (zymosan) and TLR-4 (LPS) agonists. While most activated (ConA or anti-CD3/anti-CD28) CD4+ cells showed markedly diminished responses (reduced IL-2 production), non-specific T cell responses to superantigen (SEA/SEB) increased post flight as determined by expression of early activation markers. Production of additional cytokines was also dysregulated postflight. Overall, persistent immune changes during space flight could represent unique clinical risks for exploration class missions. The consequences of pathogenic encounter remain an important concern that should be addressed.

Hwang, ShenAn↗

NASA NTRS2014

The New NASA Orbital Debris Engineering Model ORDEM 3.0

The NASA Orbital Debris Program Office (ODPO) has released its latest Orbital Debris Engineering Model, ORDEM 3.0. It supersedes ORDEM 2.0. This newer model encompasses the Earth satellite and debris flux environment from altitudes of low Earth orbit (LEO) through geosynchronous orbit (GEO). Debris sizes of 10 microns through 1 m in non-GEO and 10 cm through 1 m in GEO are modeled. The inclusive years are 2010 through 2035. The ORDEM model series has always been data driven. ORDEM 3.0 has the benefit of many more hours from existing data sources and from new sources that weren't available to past versions. Returned surfaces, ground tests, and remote sensors all contribute data. The returned surface and ground test data reveal material characteristics of small particles. Densities of fragmentation debris particles smaller than 10 cm are grouped in ORDEM 3.0 in terms of high-, medium-, and lowdensities, along with RORSAT sodium-potassium droplets. Supporting models have advanced significantly. The LEO-to-GEO ENvironment Debris model (LEGEND) includes an historical and a future projection component with yearly populations that include launched and maneuvered intacts, mission related debris (MRD), and explosion and collision fragments. LEGEND propagates objects with ephemerides and physical characteristics down to 1 mm in size. The full LEGEND yearly population acts as an a priori condition for a Bayesian statistical model. Specific, well defined populations are added like the Radar Ocean Reconnaissance Satellite (RORSAT) sodium-potassium (NaK) droplets, recent major accidental and deliberate collision fragments, and known anomalous debris event fragments. For microdebris of sizes 10 microns to 1 mm the ODPO uses an in-house Degradation/Ejecta model in which a MLE technique is used with returned surface data to estimate populations. This paper elaborates on the upgrades of this model over previous versions highlighting the material density splits and consequences of that to the penetration risk to spacecraft.

Krisko, P. H.↗

NASA NTRS2017

NASA Space Radiation Protection Strategies: Risk Assessment and Permissible Exposure Limits

Permissible exposure limits (PELs) for short-term and career astronaut exposures to space radiation have been set and approved by NASA with the goal of protecting astronauts against health risks associated with ionizing radiation exposure. Short term PELs are intended to prevent clinically significant deterministic health effects, including performance decrements, which could threaten astronaut health and jeopardize mission success. Career PELs are implemented to control late occurring health effects, including a 3% risk of exposure induced death (REID) from cancer, and dose limits are used to prevent cardiovascular and central nervous system diseases. For radiation protection, meeting the cancer PEL is currently the design driver for galactic cosmic ray and solar particle event shielding, mission duration, and crew certification (e.g., 1-year ISS missions). The risk of cancer development is the largest known long-term health consequence following radiation exposure, and current estimates for long-term health risks due to cardiovascular diseases are approximately 30% to 40% of the cancer risk for exposures above an estimated threshold (Deep Space one-year and Mars missions). Large uncertainties currently exist in estimating the health risks of space radiation exposure. Improved understanding through radiobiology and physics research allows increased accuracy in risk estimation and is essential for ensuring astronaut health as well as for controlling mission costs, optimization of mission operations, vehicle design, and countermeasure assessment. We will review the Space Radiation Program Element's research strategies to increase accuracy in risk models and to inform development and validation of the permissible exposure limits.

Huff, J. L.↗

NASA NTRSDate not supplied

Consequences of Asteroid Characterization on the State of Knowledge about Inferred Physical Properties and Impact Risk

Physical characteristics of Near-Earth Objects (NEOs) are essential inputs to planetary defense assessments. The size, density, and strength of an NEO are critical inputs to modeling behavior during atmospheric entry as well as assessing the risk of impact. Similarly, knowledge of the physical characteristics of an object are necessary to evaluate the probable result of a mitigation mission. Usually, these attributes cannot be directly measured, but increasingly sophisticated methods have been developed to infer physical properties from related measurements of asteroids, meteors, and/or meteorites. Fortuitously, some of these measurements have been obtained for enough NEOs to elucidate the distribution of values across the sampled population. However, the situation becomes more challenging when considering a specific asteroid, since it is unlikely that all the relevant measurements have been made for any given object. We have developed a Bayesian network that can combine available information about a particular NEO with knowledge of the larger population to infer probabilistic values and uncertainties for physical characteristics of interest. Distributions of asteroid population albedos, taxonomic classes, and macroporosities, along with meteorite density distributions and associations between taxonomic classes and meteorite classes, provide the default distributions for the network’s parameter nodes. The inference network links parameters for each virtual asteroid either deterministically or probabilistically as appropriate, and eliminates any unphysical combinations of parameters. Within the context of planetary defense, our Bayesian network can be used to constrain the ranges of likely impactor properties, which can subsequently reduce the uncertainty in modelling of atmospheric entry, mitigation efficacy, and impact risk assessment. When additional measurements become available for a specific object, the network incorporates those measurements to generate virtual asteroids with property distributions that are consistent with the measurements. We will use the 2023 PDC scenario to demonstrate how the inference network can be combined with plausible characterization measurements to refine the state of knowledge about likely combinations of physical parameters and the resulting impact risk.

risk assessment↗

NASA NTRSDate not supplied

Analytical Framework for Rodent/NHP Data Set Utilization to Inform Human CNS Risk Estimation

Objectives Review and inform on tactics to analyze & communicate data from animal research (e.g., rodents, mini-pigs, NHPs, et al) exposed to single and combinations of spaceflight hazards, using NASA’s Human System Risk Board (HSRB) process for the Behavioral Medicine Risk - To quantitatively inform Behavioral Medicine Risk posture - i.e., likelihood (L) and consequence (C) - To help inform estimation of crew health standards for operational task performance (i.e., Fitness For Duty, Space Permissible Exposure Levels, Permissible Operational Limits).

Brain↗