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NASA NTRS2024

Loads and Structural Dynamics Requirements for Spaceflight Hardware

The NASA Exploration Systems Development Mission Directorate requires Crewed Space Systems (CSS) to meet the intent of a set of Engineering Technical Authority (TA) documents called out in HEOMD-003, Crewed Deep Space Systems Human Rating Certification Requirements and Standards for NASA Missions. For the Loads and Dynamics technical discipline, the document invoked by the HEOMD-003 is JSC 65829, Loads and Structural Dynamics Requirements for Spaceflight Hardware. JSC 65829 was originally developed for the NASA Commercial Crew Program as an implementation of NASA STD-5002, Load Analyses of Spacecraft and Payloads, for that Program. Since that time, tailored alternatives to JSC 65829 have been produced for the Gateway, Human Landing System, and Extravehicular Activity and Human Surface Mobility Programs. Experience with those Programs has shown that the reduced set of less-prescriptive requirements in those tailored documents offers an advantage over the set of requirements in JSC 65829 Rev A and is a better fit for the paradigm of NASA procurement of commercially developed systems for crewed spaceflight. Revision B of JSC 65829 has been constructed to align with those tailored documents. The reduction in the number and specificity of requirements is balanced by a new requirement for hardware developers to create and provide a Loads Control Plan which describes how the approaches used to generate design-to loads and dynamic environments and substantiate dynamic model validity satisfy the requirements herein. The Plan will establish an agreement between the hardware developer and the TA for the loads and dynamics discipline and offer an opportunity for reengagement if the Plan changes during development.

Kenneth Schultz↗
NASA NTRSDate not supplied

Alternate Methods of Model Reduction to Avoid Dynamic Modal Truncation Error

Loads analysis is traditionally performed using dynamically reduced models, which provides the benefit to reduce run time. If the reduced model frequency cutoff is not chosen appropriately, the model will lack the dynamic content required to fully represent the response of the non-reduced model. Standard guidance for reduced model frequency content, provided in NASA-STD-5002, is to solve fixed base modes up to a minimum of 1.5x the model frequency content of interest and to employ static modal truncation methods such as residual vectors, the mode acceleration method, and the residual flexibility method to account for the truncated flexibility of the missing modes. Fixed base modes require the selection of a set of degrees of freedom to be constrained which, if not properly selected, may affect the accuracy of the reduced model by excluding some of the dynamic characteristic of the full model. In this case, the standard NASA guidance would be insufficient, but it may not be readily apparent that a portion of the reduced model response is missing. This error was encountered during an independent verification and validation (IV&V) effort, where it was observed that the resulting dynamic response was lower than the inline analysis. In this specific case, despite following the standard NASA model reduction guidelines in the selection of the frequency cutoff, the inline model still did not fully capture the necessary dynamic content. As part of the IV&V, an alternate reduction methodology was employed using an unconstrained mode acceleration method. The original model initially performed a constrained reduction to twice the frequency content of interest before doing a free-free run, employing the mode acceleration method to account for the truncated modes. In contrast in the IV&V, the unconstrained model reduced directly to the needed frequency content of the free-free run, avoiding any interactions between constraints and dynamic content. To verify the model, the original reduction methodology was used to generate a series of Hurty-Craig-Bampton reductions, each with a higher frequency cutoff than the previous. The results were shown to converge once the frequency cutoff increased past eight times the frequency content of interest. At the same frequency cutoff, the results of the Hurty-Craig-Bampton model converged with the results of the unconstrained mode acceleration model. This comparative study provided confidence that the results of the unconstrained modal acceleration reduced model were correct and that the Hurty-Craig-Bampton needed to increase its frequency cutoff to fully capture the dynamic response.

Erin Simmons↗
NASA NTRSDate not supplied

Alternate Methods of Model Reduction to Avoid Dynamic Modal Truncation Error

Loads analysis is traditionally performed using dynamically reduced models, which provides the benefit to reduce run time. If the reduced model frequency cutoff is not chosen appropriately, the model will lack the dynamic content required to fully represent the response of the non-reduced model. Standard guidance for reduced model frequency content, provided in NASA-STD-5002, is to solve fixed base modes up to a minimum of 1.5x the model frequency content of interest and to employ static modal truncation methods such as residual vectors, the mode acceleration method, and the residual flexibility method to account for the truncated flexibility of the missing modes. Fixed base modes require the selection of a set of degrees of freedom to be constrained which, if not properly selected, may affect the accuracy of the reduced model by excluding some of the dynamic characteristic of the full model. In this case, the standard NASA guidance would be insufficient, but it may not be readily apparent that a portion of the reduced model response is missing. This error was encountered during an independent verification and validation (IV&V) effort, where it was observed that the resulting dynamic response was lower than the inline analysis. In this specific case, despite following the standard NASA model reduction guidelines in the selection of the frequency cutoff, the inline model still did not fully capture the necessary dynamic content. As part of the IV&V, an alternate reduction methodology was employed using an unconstrained mode acceleration method. The original model initially performed a constrained reduction to twice the frequency content of interest before doing a free-free run, employing the mode acceleration method to account for the truncated modes. In contrast in the IV&V, the unconstrained model reduced directly to the needed frequency content of the free-free run, avoiding any interactions between constraints and dynamic content. To verify the model, the original reduction methodology was used to generate a series of Hurty-Craig-Bampton reductions, each with a higher frequency cutoff than the previous. The results were shown to converge once the frequency cutoff increased past eight times the frequency content of interest. At the same frequency cutoff, the results of the Hurty-Craig-Bampton model converged with the results of the unconstrained mode acceleration model. This comparative study provided confidence that the results of the unconstrained modal acceleration reduced model were correct and that the Hurty-Craig-Bampton needed to increase its frequency cutoff to fully capture the dynamic response.

Erin Simmons↗
NASA NTRSDate not supplied

Rolling Horizon with K-Position Search Method for Strategic Deconfliction of Package Delivery UAS

This research focuses on the strategic deconfliction of unmanned aircraft systems (UAS) in an urban package delivery environment with two depots and multiple drop-off locations. Since the formulated mixed-integer nonlinear programming (MINLP) problem is non-deterministic polynomial-time (NP) hard, a heuristic algorithm called "rolling horizon with k-position search (KPS)" is used to compute the departure sequence and scheduled time of departure (STD) of each UAS at a depot, considering temporal constraints at en-route crossing waypoints and depots for strategic deconfliction. The simulation studies show that an increase in the value of k (local neighborhood search) in the KPS reduces the average ground delay at the cost of an increase in the computation time for a given number of UAS, size of the rolling horizon window, and number of depots involved in the local neighborhood search. The studies also show that for a given rolling horizon window, the computation time increases exponentially with an increase in the total number of UAS flights when serial processing the local neighborhood search of KPS (with k > 1) and drops by an order of magnitude upon performing the local neighborhood search of KPS using parallel processing instead of serial processing. The computation time drops with the reduction in air traffic complexity of a scenario for a given number of flights, k (local neighborhood search), and rolling horizon window.

UTM↗
NASA NTRS2025

Modeling and Simulation Credibility Assessments of Musculoskeletal Computational Models for Simulating Astronaut Injuries Due to a Poor Spacesuit Fit

The musculoskeletal (MS) system of astronauts is subject to physiological changes, potentially leading to injuries due to the exposure to different gravitational environments experienced during spaceflight. These injuries can occur while an astronaut is performing an Extravehicular Activity (EVA) in space, on lunar or planetary surfaces or while wearing a spacesuit during terrestrial training for an EVA. The OpenSim MS modeling software can assess EVA induced MS injury mechanisms such as muscle strains, ligament injuries and joint injuries. One area of concern, since there are only a few different spacesuit sizes with limited adjustability, is the possibility of a poorly fitting spacesuit. This can cause unnatural joint motions and torques resulting in various MS injuries. A credibility assessment of the OpenSim modeling and simulation procedures is performed per NASA-STD-7009A to provide information on the credibility of the model’s use in simulating EVA related injury mechanisms. The credibility assessment evaluated various OpenSim models against the following eight credibility factors: data pedigree, input pedigree, code verification, solution verification, conceptual validation, referent validation, results uncertainty and results robustness (sensitivity). The models evaluated for EVA injuries will require additional credibility factor analysis and upgrades to the model features, such as adding ligaments to a whole-body model, to reliably predict and analyze the EVA injuries expected to occur due to a poor spacesuit fit. The degree of elevation strategy required to increase the credibility assessment scores will depend on the model complexity and the injury mechanism.

Christopher A. Gallo↗
NASA NTRS2024

Lessons Learned from Particulate Characterization Laboratory Anomalies

The White Sands Test Facility chemistry laboratory provides quality control for cleanroom operations including cleanliness verification of aerospace hardware by particulate counts and non-volatile residue determinations, particulate counts for liquid hypergolic propellants, gaseous helium and nitrogen propellant pressurizing agents used for ground support equipment and flight test article valve actuation, gaseous oxygen primarily used for component testing, and deionized water for refurbished propellant hardware flushing. Cleanliness verification includes particulate counts and non-volatile residue determinations to industry standard, NASA, and program specifications and levels. Particulate counts are typically to customer-specified specifications and levels including JPR 5322.1H (2016) Levels 50 and 100, Orion (MPCV 70156. Revision H (2018)) Level 100, RPTSTD-8070-0001 Revision 3 (2022), and IEST-STD-CC1246E (2013) Levels 50 and 100. The laboratory issues high pressure filter holders containing membrane filters to test operations personnel, who collect samples by flowing the required volumes of fluid through the filter holder, and the filter holder is returned to the lab for counting. A passing particulate count is required before testing may proceed. Rapid data reduction and issuing of reports indicating a pass or fail of the particulate specification are required. Corrective action and resampling invariably occurs if a sample fails. Consequently, the laboratory must maintain the highest degree of reliability to facilitate quality data used to decide if testing may proceed. Experience and continual improvements have enabled reliability. However, anomalies attributed to lab processes and hardware including filter holders, membranes, and Petri dishes have been encountered. This paper presents a summary of problems, solutions, successes, and lessons learned from particle counting experience for over 35 years.

Lessons Learned↗
NASA NTRSDate not supplied

Next Generation Exercise Device (NGED): Advancing Exercise Capabilities for Future Space Missions Through Biomechanical Modeling

BACKGROUND As space exploration extends to long-duration missions on the Moon and Mars, maintaining astronaut health and fitness becomes increasingly critical. The Next Generation Exercise Device (NGED), developed and tested by the HumanWorks Lab in NASA Johnson Space Center's (JSC) Software, Robotics, and Simulation Division, aims to address this challenge through innovative approaches. This study presents the development and evaluation of an NGED system, focusing on its adaptability to various mission scenarios, including prospective use in a Lunar Pressurized Rover (LPR). Central to this project is the application of biomechanical modeling to optimize exercise efficacy and safety in microgravity and partial gravity environments. The project is a collaborative effort with the Human Health and Performance group at Johnson Space Center, ensuring a comprehensive approach to astronaut well-being that integrates biomechanical principles with practical exercise solutions. The NGED represents the next generation of exercise capabilities for missions in space, on the Moon and Mars, with a specific focus on applications such as the LPR. METHODS AND RESULTS Data collection for NGED development was conducted with two motor-driven Beyond Power Voltra I [1] systems and a custom test structure to allow placement of the cable-based devices on the ground, at shoulder height, and overhead. The collection was performed in JSC’s Prototype Immersive Technology (PIT) Lab, utilizing an OptiTrack motion capture system and AMTI force platform, to enable detailed biomechanical analysis via OpenSim [2,3]. Motion capture data were collected for three subjects representing different body types and statures. The marker set used was an enhanced version of the full-body Plug-in Gait marker set [4], with additional markers strategically placed for the primary objective of informing exercise volume requirements. Subjects performed a series of 17 exercises, carefully selected to engage various muscle groups, including novel spaceflight exercises such as skiing (ergometer style), lateral pulldowns, wood chops, triceps extensions, and flies, with load variations ranging from 10 to 90 pounds to maintain kinematic form. This comprehensive approach allowed for a thorough evaluation of the NGED's performance across a wide range of motions and loads. The biomechanical modeling and analysis were conducted using a modified OpenSim Full Body Rajagopal Model [4,5] and also scaled to the maximum and minimum anthropometry provided in NASA-STD-3001 [6]. Volumetric convex hulls were generated based on model marker trajectories and aggregated into geometric assemblies. These can be placed in models of vehicle designs to assess fit to protect for exercise as well as to adapt NGED exercise to fit available space. Preliminary findings from the collection indicate that the NGED prototype demonstrates significant adaptability across varying user anthropometrics and exercise types. The device showed consistent performance in load-bearing exercises, with subjects able to perform exercises effectively while maintaining proper biomechanical form. CONCLUSION NGED represents a forward-looking advancement in exercise capabilities for future space missions. In the future, this system can be used to capture valuable metrics (e.g., isometric mid-thigh pull for force output measurements, assessments of postural muscle strength, overall isometric strength). Its versatility in accommodating various exercises and user physiques, coupled with the ability to provide targeted biomechanical loading, makes it a promising approach for maintaining astronaut health during long-duration missions to the Moon and Mars. Future work will focus on refining the NGED based on initial biomechanical findings, leveraging the detailed insights provided by motion capture and analysis techniques. Particular emphasis will be placed on optimizing its use within the confined spaces of a LPR and other space habitats. This work contributes significantly to NASA's goals of supporting human health and performance in deep space exploration, paving the way for sustainable long-term presence beyond Low Earth Orbit through advanced, biomechanically-informed exercise solutions.

C Wang↗
NASA NTRSDate not supplied

Nasa Exploration Atmosphere Tests 3 & 4: Development and Validation of Planetary Extravehicular Activity Prebreathe Protocols for Alternate Atmospheres and Suit Pressures

INTRODUCTION: Space suits operate at low pressures to optimize astronauts’ performance. The drop in pressure from the habitat environment to the suit carries a risk of decompression sickness (DCS), which is mitigated by a 95% O2 prebreathe protocol. Prebreathe protocols for the lunar surface have a significantly higher risk compared to International Space Station microgravity Extravehicular Activities (EVA). In previous studies, we validated a prebreathe protocol from a 56.5 kPa 34% O2 cabin to a 29.6 kPa EVA pressure; however, the enriched oxygen cabin environment poses a flammability risk that requires significant changes to material design and selections. Here, we report outcomes for prebreathe protocols from a sub-30% O2 cabin and associated changes necessary to control DCS risk critical to upcoming lunar missions. METHODS: Fourteen volunteers completed 11-day hypobaric chamber studies with an “alternate exploration atmosphere” of 66.2kPa, 28.5% O2. Subjects acclimated for 48 hrs and then participated in five 6-hour simulated EVAs at 29.6 or 35.6kPa, 95% O2. Prior to EVA, subjects underwent a 20, 90, or 150-minute prebreathe. The EVA simulation was designed to be representative of future planetary EVAs, proportionate to the subject’s VO2max. Decompression stress was monitored by real-time doppler and echocardiograph alternating every 15 min, as well as clinical monitoring for DCS signs/symptoms. Venous gas emboli (VGE) and DCS outcomes were verified against NASA-STD-3001 acceptance criteria. RESULTS AND DISCUSSION: Venous gas emboli (VGE) were identified during all EVAs. A neurological DCS case was identified in the 90-min/29.6kPa prebreathe, terminating further testing of this protocol. No DCS cases were identified in the 150 min/29.6kPa protocol. The 20 min/36.5kPa protocol was rejected due to a Type II DCS case. All DCS symptoms resolved with treatment, with no sequelae post initial treatment of DCS. These various test points highlighted to the significant benefit of elevated suit pressure to shorten prebreathe protocols, but also the difficulty in assessing and managing DCS during sustained EVA operations in remote planetary surfaces.

decompression sickness↗
NASA NTRSDate not supplied

Parameter, Post-Processing Sensitivities, and Qualification Approach of Laser Powder Bed Fusion Hydrogen Resistant Alloy NASA HR-1

Metal additive manufacturing (AM) processes are being used to enable economical manufacturing of legacy alloys as well as advancing new alloys. Laser powder bed fusion (L-PBF) is a metal AM process that has high maturity and being used to produce a variety of parts for space applications including complex propulsion components. The National Aeronautics and Space Administration (NASA) has identified the need to develop and advance new materials in unique space applications such as high-pressure hydrogen environments. NASA HR-1 is a high strength Fe-Ni based superalloy designed to resist high pressure hydrogen environment embrittlement (HEE), oxidation, and corrosion that has been successfully adapted to laser powder directed energy deposition (LP-DED). Insights gained from the NASA HR-1 development for LP-DED have guided the development process for L-PBF. However, adapting NASA HR-1 to L-PBF posed new challenges due to the distinct differences between the additive manufacturing processes. During parameter development, sensitivities were observed in post-processing that necessitated additional optimization of heat treatments. Additionally, the variations in thickness and how it influenced the microstructural response during heat treatment was characterized. Understanding these sensitivities is important to qualification of the material in a L-PBF machine. This ensures that the microstructures and properties of the material maintain consistency in production. This presentation will cover parameter development along with post-processing challenges and solutions will be discussed in addition to key material properties as it pertains to application performance and qualification per NASA-STD-6030. Improvements made by developing a derivative alloy, NASA HR-2, will be highlighted through preliminary small scale parameter development, material characterization, and initial property testing.

NASA HR-1↗
NASA NTRSDate not supplied

Transformation of the NASA Life Sciences Portal to a FAIR Data Point

The FAIR principles emphasize optimizing metadata, the vast majority of which are textual in nature, and often organized into attribute name-value pairs. This uniformity has led to the development of guidelines and best practices for providing programmatic access to scientific data through their metadata, yielding the first iteration of the FAIR Data Point Specifications (FDPS). A key feature of the FDPS is its support for automated agents seeking and fetching data without first needing to learn a plethora of different application programming interfaces. These software agents can interrogate metadata catalogs that adhere to FDPS in a uniform manner because each catalog describes itself and its metadata schema consistently. This approach enhances the sustainability of data retrieval support, allowing systems to refine and update their metadata schemas as needed and without requiring data-seeking software agents to change how they interrogate FDPS catalogs. An essential aspect of the FDPS is the standardization of data catalog semantics, which formalizes concepts such as “metadata” and “metadata service” and links them to other concepts specifications including the Data Catalog Vocabulary (DCAT), a W3C standard that is also the basis of NASA-STD-2831 “Metadata Standard for Data Discoverability,” authored by NASA’s Office of the Chief Information Officer. The FDPS references DCAT (version 2) elements which focus on the distribution of datasets and support the goal of stream-lined catalog integration across repositories for improved data discovery. Additionally, the FDPS also prescribe the use of Linked Data Platform elements for data catalog-metadata record containment descriptions, allowing users to ascertain which data and metadata belong to which catalogs. NASA’s Life Sciences Portal is implementing the FDPS while formalizing its metadata schema to support the accelerated synthesis of knowledge from space life sciences investigations.

platform↗
NASA NTRS2025

NASA Planetary Protection Handbook

This handbook provides guidance to mission providers and Planetary Protection (PP) practitioners on implementing PP measures for both robotic and crewed space missions. This handbook represents major updates to PP practices since a previously drafted handbook from 2010. In 2017, NASA reorganized the Office of Planetary Protection (OPP) from the Science Mission Directorate (SMD) to a Technical Authority (TA) within the Office of Safety and Mission Assurance (OSMA). With this organizational change came a complete overhaul of NASA’s PP policy and technical standards. This handbook reflects the latest NASA PP policy updates in NPR 8715.24, Planetary Protection Provisions for Robotic Extraterrestrial Missions and technical requirements of NASA-STD-8719.27, Implementing Planetary Protection Requirements for Space Flight. This handbook is a companion document to the NPR and technical standard and provides guidance, best practices, background information, and advice for practitioners to consider when implementing PP on NASA missions and NASA-partnered missions.

Nick Benardini↗
NASA NTRS2024

Modeling and Simulation Credibility Assessments of Musculoskeletal Computational Models for Simulating Astronaut Injuries Due to a Poor Spacesuit Fit

The musculoskeletal (MS) system of astronauts is subject to physiological changes, potentially leading to injuries due to the exposure to different gravitational environments experienced during spaceflight. These injuries can occur while an astronaut is performing an Extravehicular Activity (EVA) in space, on lunar or planetary surfaces or while wearing a spacesuit during terrestrial training for an EVA. The OpenSim MS modeling software can assess EVA induced MS injury mechanisms such as muscle strains, ligament injuries and joint injuries. One area of concern, since there are only a few different spacesuit sizes with limited adjustability, is the possibility of a poorly fitting spacesuit. This can cause unnatural joint motions and torques resulting in various MS injuries. A credibility assessment of the OpenSim modeling and simulation procedures is performed per NASA-STD-7009A to provide information on the credibility of the model’s use in simulating EVA related injury mechanisms. The credibility assessment evaluated various OpenSim models against the following eight credibility factors: data pedigree, input pedigree, code verification, solution verification, conceptual validation, referent validation, results uncertainty and results robustness (sensitivity). The models evaluated for EVA injuries will require additional credibility factor analysis and upgrades to the model features, such as adding ligaments to a whole-body model, to reliably predict and analyze the EVA injuries expected to occur due to a poor spacesuit fit. The degree of elevation strategy required to increase the credibility assessment scores will depend on the model complexity and the injury mechanism.

Christopher A Gallo↗
NASA NTRSDate not supplied

Earth-Independent Medical Operations (EIMO) Concept of Operations

In contrast to the current crew health paradigm for low-Earth orbit and Lunar missions, which depends on real-time communication with Mission Control, deep-space exploration missions will require a significant shift in medical operations. This shift is driven by the constraints of operating at a considerable distance from Earth, such as resource limitations—lack of resupply, restricted mass, power, volume, and data—as well as communication delays and the inability to evacuate back to Earth during emergencies. To move toward a more self-reliant medical model, a strategy is needed to gradually increase space-based crew autonomy and reduce risks to mission success in the challenging environment of deep space. This transformative change, known as "Earth-Independent Medical Operations" (EIMO), explores the gradual transfer of medical care and decision-making from Earth-based support to space-based systems. The goal of this transition is to enhance astronaut health and performance while minimizing mission risks. EIMO requires the development of a medical system that integrates seamlessly with mission planning, vehicle and spacesuit design, and data architecture. This integration is crucial for building a robust medical infrastructure that not only safeguards astronaut well-being but also ensures overall mission success. The Human Research Program (HRP) Exploration Medical Capability (ExMC) Element has revised the EIMO model-based Concept of Operations (ConOps) which outlines an initial vision for EIMO. The ConOps, which is built on the stakeholders’ need, system goals, and objectives (NGOs), presents an array of in-mission scenarios that span a wide range of medical conditions demonstrating the system’s capabilities from basic to complex events. Developed by a multidisciplinary team of systems engineers, scientists, and clinicians within ExMC, the ConOps revision includes two new scenarios(Barotrauma and Self-Medical Management and Behavioral Health and Chronic Medical Care), and implementation of findings from EIMO technical interchange meetings that focused on data and training. The envisioned EIMO Medical System (MS) operates as a system of systems, gathering data from various sources such as reference databases, real-time wearable sensors, point-of-care diagnostics, and environmental controls. The MS also incorporates advanced training tools to support autonomous medical care, assisting the Crew Medical Officer (CMO) during medical events where Ground Support is either unavailable or communication-delayed beyond practicality. Furthermore, MS functions and capabilities were decomposed from the scenarios to establish foundational requirements for EIMO and traced to the NASA Spaceflight Human-System Standard(NASA-STD-3001, Volumes 1 and 2). These traces were performed to gain insights on the alignment of EIMO requirements with the NASA standard. This work serves as an initial recommendation to increase crew autonomy gradually and safely for Mars missions and future deep-space exploration.

medical system↗
NASA NTRSDate not supplied

Endogenous Microbial Survival in Brewed Tea

Loose-leaf bagged tea is a commonly requested beverage item that comprises up to 7% of the microbiological samples from the space food systems. As loose-leaf tea blends often contain herbs and spices that frequently have high microbial loads, they have a high failure rate as defined by the microbiological standards outlined in NASA-STD-3001, which are more stringent than the limits set for industry. Between April 2019 and September 2022, 54.8% of loose-leaf teas submitted for microbiological testing have failed, necessitating the evaluation of a variety of brands and lot numbers of each requested tea type to meet crew preference requests, which are typically specific, resulting in excess labor and material costs to provide a single product for spaceflight consumption. Attempts to identify specific brands or ingredients that are less likely to produce a failure have been unsuccessful, as to date, no trends in those measures have been identified. We have, however, noticed a trend in types of teas (spiced and herbal) which are more likely to fail. Of additional concern, hot water available for brewing tea on ISS is dispensed at a lower temperature than the CDC recommended brewing temperature. In a study we previously reported, we found that that brewing water temperature may not have a significant impact on the number of aerobic bacteria in chamomile tea, as there were no significant differences in the total microbial load between tea brewed with boiling, ISS-like, or room temperature waters. It did appear that ISS temperature water was similarly effective to boiling water against a pathogenic bacterial species. In this study, we aim to assess whether the total number of aerobic bacteria of other high-fail-rate tea types is similarly unaffected when brewing tea in room temperature or boiling water. Data from this study and the previous study, as well as additional analysis of every tea product that has been tested as part of the normal food system since April 2019, will be used to determine the expected typical microbial load for loose-leaf teas, which we will compare to existing industry limits so that we can recommend a new microbiological limit for loose-leaf teas that accurately reflects the true risk of consuming brewed teas in spaceflight.

space flight food↗
NASA NTRSDate not supplied

Performance Risk Model (PRisM) Proof-of-Concept: An Operational Decision Support Tool to Predict Crew Performance in Space from Available Performance Tests

The Crew Health and Performance-Probabilistic Risk Assessment (CHP-PRA) team at NASA Glenn Research Center has developed a range of tools to evaluate astronaut health during spaceflight and to optimize the medical set required for missions. Among these, the Performance Risk Model (PRisM) represents a novel advancement, extending CHP-PRA’s focus beyond medical systems into the domain of human performance. Such tool could be pivotal in optimizing astronaut capabilities during space travel, thereby enhancing overall mission success. PRisM leverages data from well-established performance assessments conducted during previous crewed space missions and Earth analogs to strategically predict outcomes for planned tasks, even when direct performance testing has not been conducted for those specific tasks. To evaluate performance, PRisM references the various metrics outlined in NASA-STD-3001 and employs a methodology to integrate different performance scales. This framework analyzes the contribution of various human system task categories (HSTCs) to task execution and compares these contributions to the HSTCs’ involvement in other known tests. The model further employs a Monte Carlo simulation to sample performance scores from their distribution in operationally relevant tests such as those in Mulavara et al. (2018) and, by leveraging similarities in HSTC involvement, transfers this knowledge to actual mission tasks, such as those outlined in the "Human Exploration of Mars: Preliminary List of Crew Tasks”. The current PRisM proof-of-concept includes analyses of the impact of exercise and specific medications on astronauts’ performance, with provisions to incorporate additional countermeasures as data becomes available. Furthermore, the tool is customizable to include any system necessary to fully encompass the domain of human systems and can be adapted to evaluate performance for any spaceflight activities as requested by operational stakeholders. PRisM has the potential to assist the Human Research Program in exploring the capabilities trade space for optimized crew performance.

performance modeling↗
NASA NTRSDate not supplied

The Future of Integrated Performance Modeling in the Crew Health and Performance – Probabilistic Risk Assessment Project

The NASA engineering community utilizes event-driven and fault-tree probabilistic techniques to classify risks in the space environment by taking advantage of the inherent knowledge of complex spaceflight system design and testing to quantify failure risk. In harmonizing the risk of human space flight, answering the question of ‘How do we balance health, performance and resource risks with other engineering risks on long duration space missions?’ remains a deeply challenging and largely qualitative practice. The Human Research Program’s Medical Extensible Dynamic Probabilistic Risk Assessment Tool (MEDPRAT) was a significant step forward in efforts to robustly quantify the risk to crew health for exploration missions. However, there remains a significant gap in the ability to comprehensively assess and characterize risk across the disparate functionalities and capabilities which comprise the Crew Health and Performance (CHP) system. The Crew Health and Performance – Probabilistic Risk Assessment (CHP-PRA) project seeks to characterize CHP risks by expanding beyond the foundation established by its PRA predecessors like IMM and MEDPRAT, that simulate medical risk metrics like loss of crew life and evacuations. One of the new risk measures in the CHP-PRA system is embodied in our Performance Risk Model (PRisM). PRisM provides a novel way of assessing crew performance on mission tasks, using a generalized framework which relates back to NASA-STD-3001. This approach allows PRisM to capture and integrate data from a variety of different domains into a single, unified, reproducible representation of astronaut performance. In this presentation, we discuss the motivation for the CHP-PRA work and give a high level overview of the goals of the project, outline the forward work for PRisM, and discuss collaboration opportunities for the community who might explore if their domain knowledge and data could be represented, integrated, and quantified with these tools, whose outcomes are metrics useful for supporting operational mission planning and decision making.

Lauren McIntyre↗
NASA NTRSDate not supplied

Assessing the Relationships Between Sensorimotor Biomarkers and Post-Landing Functional Task Performance

Spaceflight drives adaptive changes in healthy individuals appropriate for sensorimotor function in a microgravity environment. These changes are maladaptive for return to earth's gravity. The inter-individual variability of sensorimotor decrements is striking, although poorly understood. The goal of this study was to identify a set of behavioral, neuroimaging and genetic measures that can be used to predict early post-flight performance on a set of sensorimotor tasks. Astronauts were recruited who previously participated in sensorimotor field tests and/or posturography soon after long-duration spaceflight. Behavioral tests included assessments of sensory dependency and adaptability. Visual dependency involved treadmill walking while viewing a moving virtual visual scene. Vestibular perceptual thresholds were measured while seated during lateral translations. Proprioception dependency was measured during one-legged stance on a horizontal air-bearing surface. Ground assessment of adaptability was performed (1) during treadmill walking with a virtual linear hallway and a moving walking surface, and (2) during multiple trials of navigating an obstacle course while wearing reversing prisms (adaptive Functional Mobility Test, aFMT). The neuroimaging tests characterized individual differences in regional brain volumes (using Structural MRI) and white matter microstructure (using Diffusion Tensor Imaging) to serve as potential predictors of adaptive capacity. The genetic tests utilized saliva samples to examine variations in four genes chosen because of their ability to differentiate sensorimotor adaptation ability in a normative population, including Catechol-O-methyltransferase (COMT), Dopamine Receptor D2 (DRD2), Brain-derived neurotrophic factor (BDNF) and the α2-adrenergic receptor. Thirty ISS crewmembers were recruited, including 12 first-time fliers, 6F, and mission durations lasting 185.5 ± 45.5 days, mean ± std. We utilized a combination of three post-flight functional task outcomes: tandem walk, recovery from fall and dynamic posturography. There was considerable variability among all post-flight performance outcomes. Based on an ordinal scale survey, 72% indicated their ability to perform functional tasks were more impacted postflight relative to inflight with 50% indicating they needed to restrict movements for a longer period postflight relative to inflight. While there is a strong association within tests obtained at different R+0 timepoints, by R+24 hr performance on one post-flight test does not necessarily correlate with performance on other post-flight tests. Preliminary statistical analysis indicates combining biomarkers will increase predictive power and this will be explored with future analyses. Our preliminary findings underscore the importance of a comprehensive post-flight test battery including different types of tasks with varying sensory feedback. Understanding the relationships between these sensorimotor biomarkers and post-flight functional task performance improve both our understanding of the individual variability and our strategy to optimize sensorimotor countermeasures.

biomarkers↗
DOE OSTI2024

Blind QC trend presentation

Blind testing is used to evaluate performance of the radiobioassay laboratory. DOE-STD-1112-2019 requires a radiobioassay program to perform blind testing at a documented frequency including accuracy, false positive, false negative, and sensitivity evaluations. INL trends accuracy determinations over time for bias, agreement, and precision. Trends have been identified for certain isotopes in urine and feces that have not been fully explained. This presentation will review those identified trends and discuss possible causes and solutions.

38 RADIATION CHEMISTRY, RADIOCHEMISTRY, AND NUCLEA↗