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At least 397 records · Page 22

Target Diagnostic Menu Lawrence Livermore National Laboratory SYSM-5620: Design Thinking and Systems Engineering

Target Diagnostic’s Engineering Science (TDES) currently supports over 80 diagnostic systems, all of which draw from a fixed budget that covers staff time and procurement. As the division continues to add new diagnostics, demand on these limited resources increases, yet the budget remains unchanged. Shot Responsible Individuals (RIs) have unrestricted freedom to select any number or type of diagnostics for each experiment, often by copying previous shot configurations with only minor modifications. This practice makes it easy to generate new shots but does not encourage critical evaluation of diagnostic necessity. As a result, many diagnostics are routinely included in a shot without a clear justification, and in practice, much of the data collected is not analyzed. The ever-growing arsenal of diagnostics also increases the burden on TDES personnel, requiring more staff for support, maintenance, and service. This environment creates challenges in focusing resources on diagnostics that provide the greatest value to the NIF mission and raises concerns about the continued justification for maintaining all existing systems. The static TDES budget cannot sustain the ongoing growth in demand for new diagnostic systems. Shot RIs currently face no constraints on the number or type of diagnostics they assign to each experiment, often defaulting to previous configurations without critically assessing the necessity of each diagnostic. This results in the routine inclusion of diagnostics whose data may not be analyzed or may no longer directly support the NIF mission. Consequently, TDES is required to maintain and support an expanding set of diagnostics, straining limited resources and risking inefficient use of staff and funding. There is a need for TDES to efficiently allocate limited resources by establishing a process that requires shot RIs to critically evaluate and justify the inclusion of each diagnostic in their experiments. This process should discourage the routine, unexamined inclusion of diagnostics, support the identification of underutilized or obsolete systems, and ensure that only those diagnostics providing the greatest value to the NIF mission are maintained and supported. Ultimately, this approach must enable TDES to operate within budget constraints while maximizing scientific impact and operational efficiency.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Budget Constrained Machine Learning for Early Prediction of Adverse Outcomes for COVID-19 Patients

Background: Machine learning (ML) based risk stratification models of Electronic Health records (EHR) data may help to optimize treatment of COVID-19 patients, but are often limited by their lack of clinical interpretability and cost of laboratory tests. We develop a ML based tool for predicting adverse outcomes based on EHR data to optimize clinical utility under a given cost structure. This cohort study was performed using deidentified EHR data from COVID-19 patients from ProMedica Healthcare in northwest Ohio and southeastern Michigan. Methods: We tested performance of various ML approaches for predicting either increasing ventilatory support or mortality and the set of model features under a budget constraint was optimized via exhaustive search across all combinations of features. Results: The optimal sets of features for predicting ventilation under any budget constraint included demographics and comorbidities (DCM), basic metabolic panel (BMP), D-dimer, lactate dehydrogenase (LDH), erythrocyte sedimentation rate (ESR), CRP, brain natriuretic peptide (BNP), and procalcitonin and for mortality included DCM, BMP, complete blood count, D-dimer, LDH, CRP, BNP, procalcitonin and ferritin. Conclusions: This study presents a quick, accurate and cost-effective method to evaluate risk of deterioration for patients with SARS-CoV-2 infection at the time of clinical evaluation.

Cadena Pico, JoseE.↗

ReVise: A Human-AI Interface for Incremental Algorithmic Recourse

The recent adoption of artificial intelligence in socio-technical systems raises concerns about the black-box nature of the resulting decisions in fields such as hiring, finance, admissions, etc. If data subjects—such as job applicants, loan applicants, and students—receive an unfavorable outcome, they may be interested in algorithmic recourse, which involves updating certain features to yield a more favorable result when re-evaluated by algorithmic decision-making. Unfortunately, when individuals do not fully understand the incremental steps needed to change their circumstances, they risk following misguided paths that can lead to significant, long-term adverse consequences. Existing recourse approaches focus exclusively on the final recourse goal but neglect the possible incremental steps to reach the goal with real-life constraints, user preferences, and model artifacts. To address this gap, we formulate a visual analytic workflow for incremental recourse planning in collaboration with AI/ML experts and contribute an interactive visualization interface that helps data subjects efficiently navigate the recourse alternatives and make an informed decision. We also present one of the many usage scenarios, developed during exploratory feedback sessions with twelve graduate students using a real-world dataset, which demonstrates that our approach can be instrumental for data subjects in choosing a suitable recourse path.

algorithmic recourse↗

Micro-Power Sources Enabling Robotic Outpost Based Deep Space Exploration

Robotic outpost based exploration represents a fundamental shift in mission design from conventional, single spacecraft missions towards a distributed risk approach with many miniaturized semi-autonomous robots and sensors. This approach can facilitate wide-area sampling and exploration, and may consist of a web of orbiters, landers, or penetrators. To meet the mass and volume constraints of deep space missions such as the Europa Ocean Science Station, the distributed units must be fully miniaturized to fully leverage the wide-area exploration approach. However, presently there is a dearth of available options for powering these miniaturized sensors and robots. This group is currently examining miniaturized, solid state batteries as candidates to meet the demand of applications requiring low power, mass, and volume micro-power sources. These applications may include powering microsensors, battery-backing rad-hard CMOS memory and providing momentary chip back-up power. Additional information is contained in the original extended abstract.

West, W. C.↗

Orion Crew Member Injury Predictions during Land and Water Landings

A review of astronaut whole body impact tolerance is discussed for land or water landings of the next generation manned space capsule named Orion. LS-DYNA simulations of Orion capsule landings are performed to produce a low, moderate, and high probability of injury. The paper evaluates finite element (FE) seat and occupant simulations for assessing injury risk for the Orion crew and compares these simulations to whole body injury models commonly referred to as the Brinkley criteria. The FE seat and crash dummy models allow for varying the occupant restraint systems, cushion materials, side constraints, flailing of limbs, and detailed seat/occupant interactions to minimize landing injuries to the crew. The FE crash test dummies used in conjunction with the Brinkley criteria provides a useful set of tools for predicting potential crew injuries during vehicle landings.

Lawrence, Charles↗

The Use of a Vehicle Acceleration Exposure Limit Model and a Finite Element Crash Test Dummy Model to Evaluate the Risk of Injuries During Orion Crew Module Landings

A review of astronaut whole body impact tolerance is discussed for land or water landings of the next generation manned space capsule named Orion. LS-DYNA simulations of Orion capsule landings are performed to produce a low, moderate, and high probability of injury. The paper evaluates finite element (FE) seat and occupant simulations for assessing injury risk for the Orion crew and compares these simulations to whole body injury models commonly referred to as the Brinkley criteria. The FE seat and crash dummy models allow for varying the occupant restraint systems, cushion materials, side constraints, flailing of limbs, and detailed seat/occupant interactions to minimize landing injuries to the crew. The FE crash test dummies used in conjunction with the Brinkley criteria provides a useful set of tools for predicting potential crew injuries during vehicle landings.

Lawrence, Charles↗

Orion Crew Member Injury Predictions during Land and Water Landings

A review of astronaut whole body impact tolerance is discussed for land or water landings of the next generation manned space capsule named Orion. LS-DYNA simulations of Orion capsule landings are performed to produce a low, moderate, and high probability of injury. The paper evaluates finite element (FE) seat and occupant simulations for assessing injury risk for the Orion crew and compares these simulations to whole body injury models commonly referred to as the Brinkley criteria. The FE seat and crash dummy models allow for varying the occupant restraint systems, cushion materials, side constraints, flailing of limbs, and detailed seat/occupant interactions to minimize landing injuries to the crew. The FE crash test dummies used in conjunction with the Brinkley criteria provides a useful set of tools for predicting potential crew injuries during vehicle landings.

Lawrence, Charles↗

Geophysical Constraints on Decarbonized Systems—Building Spatio-Temporal Uncertainties into Future Electricity Grid Planning

Future electricity grids will be characterized by the high penetration of renewables to support the decarbonization process. Yet, this transition will further expose grids to a broad spectrum of geophysical forces, such as weather and climate, land and space, minerals and materials. Understanding their role is thus important to support the grid decarbonization process. Here, we synthesize the current body of knowledge on the relationship between geophysical constraints and electricity grid planning. Additionally, we show that there have been promising advances in the data, methods, and modelling tools needed to incorporate the effect of geophysical constraints on demand, resource availability, and grid operations. There are, however, multiple research avenues that deserve further attention. More system-specific and finer-scale analyses are necessary to better understand how spatio-temporal variability---and associated uncertainty---in geophysical forces affect grid planning. Moreover, we need a broader focus on the multi-sectoral implications of grid decarbonization efforts, so as to limit the risk of unintended consequences. Importantly, all these efforts are challenged by the computational requirements of existing power system models, which often limit our ability to characterize uncertainty, scale analyses across larger domains, or study the multi-sector implications of grid expansion decisions.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Sampling Size Optimization for Bioburden Density Estimation in Planetary Protection

Planetary protection (PP) is a discipline that focuses on minimizing the biological contamination of spacecraft to ensure compliance with international policy. Precise estimation of bioburden - the total number of microbes in or on spacecraft hardware – and the bioburden density are of utmost importance for PP. Such estimation is the way concordance with requirements is demonstrated, and it is critical for quantifying the potential risk of inadvertently contaminating other planetary bodies. Although a suite of molecular techniques have been used to thoroughly characterize and profile the microbiome of various cleanroom environments and spacecraft, the gold standard remains the physical enumeration of microbes via culturing of samples directly taken from spacecraft and associated surfaces. However, due to technical, budgetary, and programmatic constraints, only a manageable portion (around 10%) of the entire spacecraft surface is directly sampled with cotton swabs or wipes. To generate the bioburden current best estimate (CBE) for components not directly verifiable, the accepted approach is to apply a NASA-defined bioburden estimate based on the components’ manufacturing or assembly environment. This approach utilizes a prespecified bioburden density estimation that applies a maximum value across the total surface area of the specified component. For hardware components that underwent similar assembly processes, an implied bioburden is adopted for all components, based on a direct verification of a representative component within the same lot. Once all components have a CBE, the bioburden estimates are generated. In previous publication [ 1], we have shown that statistical risks quantifying the accuracy of the estimates for sampled, prespecified, and implied components can be derived and ranked. For mean squared error (MSE) function, the risks are available analytically and hence a cost function can be obtained to optimize the risks with respect to the sampling area and sampling cost. Since the sampling area and sampling cost are two complimentary variables, their sum will have a well-defined minimum. This paper presents the multivariate optimization of the integrated risk of an empirical Bayes estimator to determine the optimal sampling schedule for a given number of components. It is assumed that given a number of components, N, the bioburden density for each component can either be sampled, implied, or prespecified. The multivariate optimization searches through different options to sample, imply or prespecify the bioburden density for a component, and account for the component’s surface area and cost of sampling. The idea of the optimization is based on the observation that the statistical risk of using an estimator is a monotonically decreasing function of the sampled area. The larger the sampled area, the lower the risk of using the estimator as the estimator becomes more and more accurate as the sampling area increases. On the other hand, the cost of sampling is monotonically increasing as the sampled surface grows. This makes the risk and total cost of sampling complimentary variables which can be counterbalanced to achieve an optimal overall value with respect to the sampled surface. In this paper, the integrated risk has been used to quantify the accuracy of the estimator. This risk has been selected because it depends on neither the true value of the parameter nor on the collected data. The cost of each sample was also available to obtain the total cost of sampling of N components. The paper will present the results based on computer-simulated data as well as the data collected during the InSight mission. The computer-simulated data have N components with randomly generated total areas and each component assigned to one of the three categories according to the method of estimating of bioburden density: sampled, implied, or prespecified. The cost of sampling is also available. The cost of sampling is estimated based on a cost model provided by the planetary protection group at JPL. For this paper, the overall cost was assumed to be a linear function of exposure. The optimization process finds the allocation of the components to the three categories that minimizes the tradeoff between integrated risk and total cost. For the InSight data, a set of components is selected representing all three categories, and optimization is performed to determine if the performed allocation was optimal or if a better allocation could have been obtained. To the best of our knowledge, this work is the first attempt not only perform an accurate estimation of bioburden density but also do it in an optimal way.

97 - MATHEMATICS AND COMPUTING↗

Recommendations from NASA's Operational and Research Musculoskeletal Summit

Introduction: Continuously evolving medical standards of care, limited crew training time, and the inherent constraints of space flight necessitate regular revisions of the mission medical support infrastructure and methodology. A three-day Operational and Research Musculoskeletal Summit was held to review NASA s current strategy for preflight health maintenance and injury screening, risk mitigation for musculoskeletal injuries or syndromes, treatment methods during flight, and research topics to mitigate risks to astronaut health. The Summit also undertook consideration of the best evidence-based terrestrial musculoskeletal practices to recommend their adaptation for use in space. Methods: The types and frequencies of musculoskeletal injuries sustained by short- and long-duration astronauts were obtained from the Longitudinal Study of Astronaut Health. The Summit panel was comprised of experts from the clinical and research communities, as well as representatives from NASA Headquarters, the Astronaut corps, and the offices of JSC Medical Operations, JSC Human Adaptation and Countermeasures, Glenn Research Center Human Research, and Astronaut Strength Conditioning and Rehabilitation. Before the summit, panelists participated in a Web-based review of NASA s Space Medical Conditions List (SMCL). Results: The Summit generated seventy-five operational and research recommendations to the NASA Office of Space Medicine, including changes to the SMCL and to the musculoskeletal section of the ISS debrief questionnaire. From these recommendations, seven were assigned highest value and priority, and could be immediately adopted for the exploration architecture. Discussion: Optimized exercise and conditioning to improve performance and forestall musculoskeletal damage on orbit were the primary area of focus. Special attention was paid to exercise timing and muscle group specificity. The panel s recommendations are currently in various stages of consideration or integration into the ISS and Exploration programs. This effort serves to enhance the on-orbit system so comprehensive treatment can be delivered in a more effective and standardized manner.

Jones, J. A.↗

Concept, Design, and Prototyping of XSAS: A High Power Extendable Solar Array for CubeSat Applications

CubeSats have proven themselves as a reliable and cost-effective method to perform experiments in space, but they are highly constrained by their specifications and size. One such constraint is the average continuous power, about 5 W, which is available to the typical CubeSat. To improve this constraint, we have developed the eXtendable Solar Array System (XSAS), a deployable solar array prototype in a CubeSat package, which can provide an average 23 W of continuous power. The prototype served as a technology demonstrator for the high risk mechanisms needed to release, deploy, and control the solar array. Aside from this drastic power increase, it is in the integration of each mechanism, their application within the small CubeSat form-factor, and the inherent passive control benefit of the deployed geometry that make XSAS a novel design. In this paper, we discuss the requirements and design process for the XSAS system and mechanical prototype, and provide qualitative and quantitative results from numerical simulations and prototype tests. We also discuss future work, including an upcoming NASA zero-gravity flight campaign, to further improve on XSAS and prepare it for future launch opportunities.

Senatore, Patrick↗

Mars Ascent Vehicle-Propellant Aging

This project is to develop and test a new propellant formulation specifically for the Mars Ascent Vehicle (MAV) for the robotic Mars Sample Return mission. The project was initiated under the Planetary Sciences Division In-Space Propulsion Technology (ISPT) program and is continuing under the Mars Exploration Program. The two-stage, solid motor-based MAV has been the leading MAV solution for more than a decade. Additional studies show promise for alternative technologies including hybrid and bipropellant options, but the solid motor design has significant propellant density advantages well suited for physical constraints imposed while using the SkyCrane descent stage. The solid motor concept has lower specific impulse (Isp) than alternatives, but if the first stage and payload remain sufficiently small, the two-stage solid MAV represents a potential low risk approach to meet the mission needs. As the need date for the MAV slips, opportunities exist to advance technology with high on-ramp potential. The baseline propellant for the MAV is currently the carboxyl terminated polybutadiene (CTPB) based formulation TP-H-3062 due to its advantageous low temperature mechanical properties and flight heritage. However, the flight heritage is limited and outside the environments, the MAV must endure. The ISPT program competed a propellant formulation project with industry and selected ATK to develop a new propellant formulation specifically for the MAV application. Working with ATK, a large number of propellant formulations were assessed to either increase performance of a CTPB propellant or improve the low temperature mechanical properties of a hydroxyl terminated polybutadiene (HTPB) propellant. Both propellants demonstrated potential to increase performance over heritage options, but an HTPB propellant formulation, TP-H-3544, was selected for production and testing. The test plan includes propellant aging first at high vacuum conditions, representative of the Mars transit, followed by an additional year at simulated Mars surface conditions. The actual Mars surface environment is based on the igloo design, actively maintains the propellant at or above -40 degC, 95% carbon dioxide at Mars surface pressure. The NASA Marshall Space Flight Center (MSFC) Mars environment test facility is shown in figure 1 and located in the East Test area of Redstone Arsenal due to storage of live propellants. The facility consists of a vacuum chamber placed inside a large freezer unit. The facility includes pressure and temperature monitoring equipment in addition to a vacuum quality monitoring system spectrometer to record any outgassing products.

Dankanich, John↗

Taking Climate Model Evaluation to the Next Level

Earth system models are complex and represent a large number of processes, resulting in a persistent spread across climate projections for a given future scenario. Owing to different model performances against observations and the lack of independence among models, there is now evidence that giving equal weight to each available model projection is suboptimal. This Perspective discusses newly developed tools that facilitate a more rapid and comprehensive evaluation of model simulations with observations, process-based emergent constraints that are a promising way to focus evaluation on the observations most relevant to climate projections, and advanced methods for model weighting. These approaches are needed to distil the most credible information on regional climate changes, impacts, and risks for stakeholders and policy-makers.

Eyring, Veronika↗

Enabling Renewable Energy While Protecting Wildlife: An Ecological Risk-Based Approach to Wind Energy Development Using Ecosystem-Based Management Values

Acceptance of wind energy development is challenged by stakeholders’ concerns about potential effects on the environment, specifically on wildlife, such as birds, bats, and (for offshore wind) marine animals, and the habitats that support them. Communities near wind energy developments are also concerned with social and economic impacts, as well as impacts on aesthetics, historical sites, and recreation and tourism. Lack of a systematic, widely accepted, and balanced approach for measuring the potential damage to wildlife, habitats, and communities continues to leave wind developers, regulators, and other stakeholders in an uncertain position. This paper explores ecological risk-based management (RBM) in wind energy development for land-based and offshore wind installations. This paper provides a framework for the adaptation of ecosystem-based management to wind energy development and examines that framework through a series of case studies and best management practices for applying risk-based principles to wind energy. Ten case studies indicate that wind farm monitoring is often driven by regulatory requirements that may not be underpinned by scientific questions. While each case applies principles of adaptive management, there is room for improvement in applying scientific principles to the data collection and analysis. Challenges and constraints for wind farm development to meet RBM framework criteria include collecting sufficient baseline and monitoring data year-round, engaging stakeholder facilitators, and bringing together large and diverse scientific teams. The RBM framework approach may provide insights for improved siting and consenting/permitting processes for regulators and their advisors, particularly in those nations where wind energy is still in the early development stages on land or at sea.

17 WIND ENERGY↗

Sustaining Thermal Protection Systems Needed for Uranus Probes

Summary: Achieving Uranus in-situ science objectives through deploying probes in the atmosphere requires thermal protection systems capable of withstanding extreme entry environments. NASA’s 3-D Woven based thermal protection systems (TPS), developed specifically to meet this challenge, are mature, efficient, and capable of withstanding such entry. These science-enabling capabilities need to be sustained, otherwise mission implementation risk may increase to the point that the mission is untenable. The heatshield technology has been developed in concert with industry, and manufacturing processes have been technology transferred. Current technology readiness does not guarantee future availability. Sustainment requires maintaining expertise within NASA as well as ensuring that proven industrial expertise and capabilities will be readily available in the future. A constant awareness and risk assessment followed by risk mitigation are required. The scientific community needs to be aware of these challenges. It needs to engage NASA to ensure these capabilities will be available when needed. As was the case with the atrophy of heritage carbon phenolic that led to developing the 3-D Woven capabilities, our vigilance is again needed to sustain these enabling TPS capabilities for Uranus and for other missions. Background: NASA invested in and developed Heatshield for Extreme Entry Environment Technology (HEEET) TPS that was matured to TRL 6 in 2019 as a tiled system with seams and gap-fillers. Manufacturing readiness included development of specialized looms, molding, and infusion processes using commercial partners. In support of the Mars Sample Return mission, a single-layer, seamless, single-piece variant referred to as 3MDCP (3-D woven Mid-Density Carbon-Phenolic) was developed and is limited to a 1.3m maximum diameter scale due to weaving width limitations of 80”. Molding techniques developed to transform a flat, 2”-thick 3-D woven preform into a sphere-cone shape prior to phenolic resin infusion has been demonstrated. A team at NASA Ames is currently working with industry to demonstrate infusion at full-scale. By 2026, 3MDCP will be at a high level of maturity in technical, manufacturing, and integration readiness as well as material characterization. HEEET and 3MDCP for Uranus Entry: Several system studies have evaluated and baselined 3-D Woven TPS for Uranus entry, both HEEET as well as 3MDCP. If the aeroshell carrying the descent probe is 1.3m or less, then 3MDCP is a very capable and the most mass-efficient choice. If the aeroshell is bigger than 1.3m diameter, then HEEET can meet the mission need as it allows for an aeroshell of any diameter. HEEET and 3MDCP are capable of Saturn in-situ science missions prioritized in the New Frontiers-5 draft Announcement of Opportunity (AO) and if Saturn is the mission of choice, there is a pathway for sustaining the capability. Capability Sustainment: Given NASA’s current budgetary constraints, the postponement of the next New Frontiers AO to no earlier than 2026 and the unknown delay in starting the UOP flagship effort point to potential gap years for the HEEET and 3MDCP capabilities. The first step in capability sustainment is to understand the risks as they emerge, assess those risks, and develop plans to mitigate them. Keeping the science community, who are interested in UOP as well as the larger Giant Planet missions, informed of the emerging challenges requires continuous risk assessment/mitigation. Without these steps, atrophy is more likely within the industrial partners with which NASA has partnered. This presentation will provide more details as well as steps NASA can take to minimize the impact to the UOP mission.

Ethiraj Venkatapathy↗

Optimization Framework to Assess the Demand Response Capacity of a Water Distribution System

As large electricity consumers, water distribution system (WDS) pumping stations have the potential to become meaningful participants in demand response (DR) programs. The authors propose an optimization framework for assessing the DR capacity of a WDS and identifying the optimal bidding strategy for maximizing WDS revenue in the DR spot market. The proposed mixed integer linear programming (MILP) model overcomes computational constraints of previous DR optimization models by adopting a preprocessing procedure to minimize the number of binary variables and implementing a convex relaxation technique to linearize the hydraulic equations. The proposed MILP model also explicitly accounts for varying levels of risk tolerance of WDS operators by varying the recovery period over which pumping returns to business-as-usual operation. The optimization framework is implemented on a skeletonized 48-node WDS model that includes 7 pumps, 6 tanks, and 39 pipes. Using a simulated DR event and water consumption profile, the authors derive the optimal DR supply curves (i.e., compensation price versus load curtailment quantity) and revenue potential of the WDS under six scenarios for DR participation.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Methodology to Calibrate Fragility Curves Using Limited Real-World Data

With increasing human dependence on electricity and increasing energy demand, electrical infrastructure has emerged to be one of the most critical services. This is one of the main reasons for making the power grid more resilient to extreme events during which uninterrupted power supply is crucial in keeping the consequences of the extreme event limited. The first step towards making the overall power grid more resilient is to evaluate the probabilities of failure for all assets at risk from the excitation caused by extreme events. Thus, this paper presents the methodology to calibrate fragility curves. The strength of the proposed approach is its ability to calibrate the fragility curves utilizing limited data, which is the most common constraint in carrying out such analyses. This paper describes the calibration of transmission tower fragility curves for Puerto Rico utilizing only damage reports for hurricane Maria. That, combined with Puerto Rico's wind modeling & geographic information system, this study also calibrates fragility curves for transmission towers made with four different construction materials.

Bereta dos Reis, Fernando↗

Duration Limits for Orbital Flight: Current Considerations for the International Space Station

According to ISS documentation, long-duration missions are defined as missions exceeding 30 days. The ISS medical organization has set a 180-day limit for ISS missions from a medical perspective, with a possibility of planning missions of up to 220days with additional consideration. The ISS medical community does not currently consider changes to the existing duration constraints for ISS mission planning. However, longer stays on orbit may be highly desirable or even necessary in certain foreseeable operational circumstances. To develop a methodology for contingency planning, the ISS medical community, led by NASA, has identified medically relevant risks associated with extended stays of crewmembers aboard the ISS.

Smith, Gwen↗