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NASA NTRSDate not supplied

Improving Efficacy and Safety of Pharmacological Treatment Through Precision Health and Pharmacogenomics

INTRODUCTION: Future spaceflight will require increased crew medical autonomy as exploration class missions expand in duration and distance from Earth, especially for Mars missions. As mission duration increases, it will be essential to have appropriate amounts of effective medication to ensure the maintenance of crew health and performance. Conversely, mass and volume constraints will become more severe as future spaceflight expands beyond low Earth orbit, where resupply is difficult or becomes impossible. These constraints thus convey an urgency to tailor medications for individual crewmembers and further examine appropriate dosing regimens. BACKGROUND: Precision Health is an exciting area of medicine focused on maintaining an individual’s health and performance through in-depth understanding of an individual’s unique clinical and environmental history, genetic makeup, and molecular profiles. This approach can be adapted to better predict, monitor, and address physiological responses to the spaceflight environment. A subset of this field is pharmacogenomics (PGX), the study of how the expressed genome impacts drug responses with the goal of prescribing the right dose of the right drug at the right time. Specifically, PGX testing provides valuable information on an individual’s precise allelic variations to guide physicians in making informed decisions on drug choice and dosing to avoid adverse events and maximize efficacy. The study goal was to identify which current space pharmacy drugs could be evaluated using PGX testing and to understand the potential impact on the health and wellness of the astronaut population. Additionally, we sought to evaluate clinically available FDA-approved PGX testing solutions to better understand its applicability. METHODS: A complete list of drugs on the ISS was analyzed for risk and likelihood of drug failure and PGX actionability. This analysis encompassed both astronauts’ personal medications, including supplements and over the counter drugs (n=151) contained in the ISS medical accessory kit (IMAK), and ISS MedKit formulary medications (n=95). Duplicate medications and different formulations were removed, which resulted in a total of 157 drugs used in the subsequent analysis. A 5x5 risk assessment table was produced by examining the likelihood of drug failure compared to the consequence of drug failure (LxC). Likelihood of individual drug failure was defined by whether existing processes are sufficient to prevent ineffective treatment or impactful side effect events, as ranked from 1 (very low, can easily be prevented) to 5 (very high, cannot be prevented) during a Mars mission. In contrast, the consequence of drug failure was defined by impact to safety, schedule, cost, or technical criteria and ranked from 1 (very low) to 5 (very high). An assessment of PGX reference laboratories is currently underway to evaluate sample requirements, benefit analysis (cost vs. utility of allele variant analysis), relevance to inflight medication usage, quality of reporting in enabling clinical application, and ease of integration into electronic medical records. RESULTS: Risk assessments (LxC 5x5 table) indicated 128 medications were in the green zone where risk is acceptable, with the remaining 29 of the medications in the yellow or red zone driven predominantly due to drug failure or safety concerns. We found that current PGX testing results could impact 21% of the total medications in the ISS MedKit and IMAK; of these, 9 medications currently have direct clinically actionable guidance available. Results of the clinical PGX solution evaluations as related to these medications will be presented. CONCLUSION: PGX testing has demonstrated clear benefits in terrestrial medicine and clinical environments for the selection of proper medications, avoiding adverse drug reactions, and maximizing drug efficacy. We propose that similar benefits would be bestowed on the astronaut and commercial spaceflight passenger population by performing preemptive preflight PGX testing to reduce risk of mission failure due to ineffective or toxic medications, improve drug efficacy, and further open the door to countermeasure research. For example, PGX results could allow tailoring of specific medications at optimal doses more precisely to each individual astronaut, particularly in areas of space motion sickness, sleep aids, and analgesics. An additional benefit is that PGX results could provide information for better planning of the components of a space pharmacy for deep space missions to be more effective and efficient in the utilization of limited pharmaceutical resources. Finally, while PGX testing of the astronaut corps is not currently conducted, this approach could provide immediate impact in support of mission success by reducing risks, optimizing astronaut performance, and providing valuable insights into long-term astronaut health. Such advancements in clinical decision making are important next steps in building dynamic individual risk profiles for astronauts, increasing selection of the best treatment choice, and providing tailored countermeasures for individual crewmembers.

Pharmacogenomics↗

NASA NTRS2020

Fault Propagation, EMI Propagation, and Fault Containment in Aerospace Systems

The occurrence of faults in aerospace system hardware and software have consequences ranging from minor effects to catastrophic effects, and such faults can directly affect the safety of hardware and personnel. There are many origins to fault conditions, and the hardware that is capable of still meeting its performance requirements after experiencing itself a fault is said to be fault tolerant. A fault tolerant hardware is capable of detecting, isolating, and recovering from a fault condition; and this is a subfield of control engineering. An aerospace system that has been shown to have electromagnetic compatibility (EMC) in all its subsystems and systems cannot induced faults caused by electromagnetic interference (EMI). It can be proposed that the presence of EMI (or lack of EMC) is analogous to a potential fault initiator and the effects can likewise range from minor to severe. This paper starts by addressing the consequences of hardware failure in aerospace systems from a fault perspective, because the design of fault tolerant system is a major endeavor in aerospace. To arrive to this goal the paper starts with the concepts of fault, fault propagation, and a new concept called fault containment region. The paper then proceeds to provide two very recent examples in the aircraft industry of fault propagation with catastrophic effects. The paper proceeds to introduce the concept of EMI fault containment and a brief introduction to another new concept called the EMI containment region. The paper proceeds with an example of EMI fault containment region. The paper ends with a lesson learned conclusions.

Perez, Reinaldo↗

NASA NTRSDate not supplied

NASA's Identified Risk of Adverse Outcomes due to Inadequate Human Systems Integration Architecture

The NASA Human System Risk Board (HSRB) is responsible for tracking the evolution of the top ~30 human system risks identified to be associated with human spaceflight. As part of this process, the Board is charged with maintaining a consistent, integrated process to evaluate those risks and developing evidence-based risk posture recommendations. Risks are ranked by likelihood and consequence. Intermediate causal relationships between risk contributing factors and countermeasures that link hazards to outcomes are described using Directed Acyclic Graphs (DAGs). The DAGs are also useful for identifying common factors and countermeasures across the top 30 risks as well as communicating how astronaut exposure to spaceflight hazards leads to meaningful mission-level health and performance outcomes. One of the top risks tracked by the HSRB is The Risk of Adverse Outcomes Due to Inadequate Human-Systems Integration Architecture (HSIA). This risk captures the possibility that due to decreasing real-time ground support during missions beyond LEO, crew will be unable to adequately respond to unanticipated critical malfunctions or detect safety-critical procedural errors. The HSIA risk is ranked red (high) for Lunar surface and Mars missions due to the probability of Loss of Crew and Loss of Mission consequences. This paper describes the evidence that supports the HSIA risk ranking and presents the central narrative of the HSIA risk DAG-- i.e., anomaly detection, diagnosis, intervention, and task performance. Characterizations of the current state of practice for each of the DAG’s central nodes and the future tools needed for successful anomaly response are provided.

human-systems integration architecture↗

NASA NTRS2022

An Adaptation of ISO 11204 using Customized Correction Grades to Mitigate Ambient Noise Effects when Computing Sonic Boom Loudness Levels

A spectral-based correction adapted from ISO 11204 [1] is investigated here to mitigate the effects of ambient noise contamination of sonic booms recorded by noise monitors during field tests. The algorithm from sections 5.4.2 and 7 of ISO 11204 is customized using six nonstandard correction grades in addition to implementing the two standardized grades described in ISO 11204. The six nonstandard grades allow for more aggressive correction of the levels of the sonic boom spectrum when they are proximate to the ambient spectrum. Of the eight correction grades, the most aggressive custom correction grade, termed “Custom F” here, performed best under the conditions that were studied. Consequently, “Custom F” is recommended for use when processing in-field recordings of X-59 sonic booms. To evaluate the eight correction grades, mock X-59 acoustic recordings were generated using predicted ground-level X-59 sonic booms. These ground-level waveforms were created by Doebler [2] by propagating nearfield CFD solutions of the X-59 C612A configuration to the ground using PCBoom [3] (please see Acknowledgements and Refs. [4, 5, 2, 6]). To generate the mock acoustic recordings from those ground-level waveforms, they were further modified using turbulence filters developed during the NASA SonicBAT effort [7], post boom noise audio clips from the NASA SonicBAT tests [7], and ambient noise from the NASA QSF18 test [8, 9]. These mock acoustic recordings enabled evaluation of the ambient noise mitigation methods since the proper loudness levels of the X-59 waveforms in absence of ambient noise are known. Specifically, these known levels provide a benchmark against which the corrected loudness levels are compared, where the corrected loudness levels are computed when ambient noise is present within the waveforms. Importantly, similar analyses using in-field recordings are not possible since the proper loudness levels of the sonic boom waveforms in absence of ambient noise are unknowable when analyzing in-field recordings. Consequently, if additional analyses of ambient noise mitigation methods are needed, then use of mock recordings like those used here is recommended.

Sonic boom↗

NASA NTRSDate not supplied

Introduction to the IMPACT Probabilistic Risk and Tradespace Analysis Tool for Medical System Design

Background: Probabilistic risk analysis (PRA) is a method for estimating risk in complex engineered systems that, at a basic level, focuses on what can go wrong and the likelihood and consequences of those occurrences. NASA has used PRA as an integral component of medical system risk estimation and design for spaceflight. IMPACT (Informing Mission Planning via Analysis of Complex Tradespaces) is a novel tool to meet these goals for exploration missions. Overview: IMPACT performs hundreds of thousands of Monte Carlo simulations of missions to build aggregate pictures of medical risk. These simulations are based on 120 possible medical conditions (the IMPACT Condition List) selected in a consensus-based process because they are of highest likelihood and/or consequence for exploration spaceflight. The conditions are then tied to clinical capabilities which can be used for management (e.g., inserting an IV) and then to over 600 specific resources needed to deliver a capability (e.g., an angiocath or an ultrasound). Different mission profiles can be simulated with user-specified inputs such as mission duration, destination, number of crew and pre-existing medical conditions, and EVA frequency. While the IMPACT evidence base is designed for exploration environments, these user inputs allow the tool to be used across a broad range of missions. IMPACT’s primary outcome metrics include loss of crew life (LOCL, a measure of in-flight mortality due to medical conditions), need for evacuation (RTDC, return to definitive care), and crew disability (TTL, task time lost based on how medical conditions impact the ability to perform over 1000 specific exploration mission crew tasks). In addition to modeling medical risk, IMPACT also accepts user-specified constraints, such as limitations of mass or volume, and will output a recommended clinical capability set and specific medical resources that meet the mission constraints. Discussion: This abstract will provide an introduction to IMPACT and describe the nature of the underlying medical evidence. It will also detail potential use cases for how this tool can be utilized by NASA or commercial spaceflight providers.

Ben Easter↗

NASA NTRS2023

What’s That Supposed to Mean? Capturing Micro-Behaviors in Teams

Future long-duration space exploration (LDSE) crews will require extensive coordination, cooperation, and team functioning as they face a myriad of challenges rooted in both taskwork and teamwork (Bell et al., 2015; Landon et al., 2018). While exposed to extreme conditions, crew members must navigate living and working together in prolonged confinement. Moreover, astronaut teams are becoming increasingly diverse, introducing significant variability in team composition. This increasing diversity, alongside traditional constraints of LDSE, introduces additional challenges into effective team functioning. To date, most methods for capturing team functioning rely on self-report measures. Such measures are prone to several limitations, including but not limited to social desirability bias, halo effect, and leniency effects (Trull & Ebner-Priemer, 2013), which skew data and limit nuanced understandings of phenomena at play. Self-report measures broadly capture team functioning, lending the nature of such methods to identifying underlying “macro”-behaviors (i.e., behaviors that are long-standing and last over time). However, team functioning is far more complex than a series of macro-behaviors, rendering reliance on self-report data deficient for accurate measurement. Recent research demonstrates the potential of alternative methods for capturing team functioning, such as speech and physiological data (Chaffin et al., 2017; Murray & Oertel, 2018). Consequently, these methods are more suitable for capturing micro-behaviors: brief, often unconscious expressions that affect the extent to which an individual feels included by others around them (Paletz et al., 2013). Micro-behaviors can be further classified into microaggressions (i.e., subtle, negative exchanges; Keller & Galgay, 2010) or micro-affirmations (i.e., subtle, positive exchanges; Kyte et al. 2020), both of which influence team functioning. Due to the subtle nature of micro-behaviors, contextual factors have a significant impact when determining if it is aggressive or affirmative. Additionally, several iterations of microbehaviors can have lingering effects on team interactions. For example, the use of “mm-hmm” by a crew member can function as both a micro-affirmation and micro-aggression. Specifically, it can be indication of active listening (i.e., micro-affirmation) or as an expression of annoyance (i.e., aggression) depending on the context in which it occurs. Auditory features (e.g., tone, frequency) can help delineate between the two forms; however, the contextual factors (e.g., previous interactions between team members, crew demographics) add a layer of complexity that render auditory features alone as insufficient to capture micro-behaviors. Consequently, this paper seeks to provide a novel approach in which multi-modal data (i.e., auditory features and contextual features) are used in a random-forest model to better identify distinguishing characteristics between micro-affirmations and micro-aggressions. In turn, detected micro-behaviors are used to predict team performance, thereby demonstrating the value of capturing micro-behaviors as supplemental data to macro-behaviors.

Sydney R. Begerowski↗

NASA NTRS2022

On the paragenetic modes of minerals: A mineral evolution perspective

A systematic survey of 57 different paragenetic modes distributed among 5659 mineral species reveals patterns in the diversity and distribution of minerals related to their evolving formational environments. The earliest minerals in stellar, nebular, asteroid, and primitive Earth contexts were dominated by relatively abundant chemical elements, notably H, C, O, Mg, Al, Si, S, Ca, Ti, Cr, and Fe. Significant mineral diversification subsequently occurred via two main processes, first through gradual selection and concentration of rarer elements by fluid-rock interactions (for example, in hydrothermal metal deposits, complex granite pegmatites, and agpaitic rocks), and then through near-surface biologically mediated oxidation and weathering. We find that 3349 mineral species (59.2%) are known from only one paragenetic context, whereas another 1372 species (24.2%) are associated with two paragenetic modes. Among the most genetically varied minerals are pyrite, albite, hornblende, corundum, magnetite, calcite, hematite, rutile, and baryte, each with 15 or more known modes of formation. Among the most common paragenetic modes of minerals are near-surface weathering/oxidation (1998 species), subsurface hydrothermal deposition (859 species), and condensation at volcanic fumaroles (459 species). In addition, many species are associated with compositionally extreme environments of highly differentiated igneous lithologies, including agpaitic rocks (726 species), complex granite pegmatites (564 species), and carbonatites and related carbonate-bearing magmas (291 species). Biological processes lead to at least 2707 mineral species, primarily as a consequence of oxidative weathering but also through coal-related and other taphonomic minerals (597 species), as well as anthropogenic minerals, for example as byproducts of mining (603 minerals). However, contrary to previous estimates, we find that only ~34% of mineral species form exclusively as a consequence of biological processes. By far the most significant factor in enhancing Earth’s mineral diversity has been its dynamic hydrological cycle. At least 4583 minerals—81% of all species—arise through water-rock interactions. A timeline for mineral-forming events suggests that much of Earth’s mineral diversity was established within the first 250 million years. If life is rare in the universe, then this view of a mineralogically diverse early Earth provides many more plausible reactive pathways over a longer timespan than previous models. If, however, life is a cosmic imperative that emerges on any mineral- and water-rich world, then these findings support the hypothesis that life on Earth developed rapidly in the early stages of planetary evolution

Robert M. Hazen↗

NASA NTRS2023

Intensified Warming and Aridity Accelerate Terminal Lake Desiccation in the Great Basin of the Western United States

Terminal lakes in the Great Basin (GB) of the western US host critical wildlife habitat and food for migrating birds and can be associated with serious human health and economic consequences when they desiccate. Water levels have declined dramatically in the last 100+ years due to diversion of inflows, drought and climate change. Satellite-derived environmental science data records (ESDRs) from the MODerate-resolution Imaging Spectroradiometer (MODIS) (snow cover, evapotranspiration (ET) and land surface temperature (LST)), enable a unique approach to evaluate the effects of aridification on terminal lakes and to study their individual vulnerabilities. Surface and air temperatures in the GB are rising dramatically, with a sharp rise in the rate of increase observed beginning around 2011, while the number of days of snow cover is declining especially in the western mountainous part of the GB as exemplified in Mono Basin, California. Rising temperatures coincide with fewer days of snow cover, a decrease of inflow to the lakes and greater evaporation of water from the lakes. MODIS ESDRs show strong and statistically significant increasing surface temperature (LST) in the GB, a reduction in the number of days of snow cover, and mixed results in ET. ET declined slightly in the more arid parts of the GB due to greater moisture restrictions to evaporation from extended drought, while ET increased in the more-vegetated, wetter, mountainous northeastern parts as temperatures have risen. Severe and costly ecological, human health and economic consequences are expected if the lakes continue to decline as predicted.

land surface temperature↗

NASA NTRS2022

Chandra Observations of Six Peter Pan Disks: Diversity of X-Ray-driven Internal Photoevaporation Rates Does Not Explain Their Rare Longevity

We present Chandra X-ray observations of six previously identified Peter Pan objects, rare ∼40 Myr systems with evidence of primordial disk retention. We observe X-ray luminosities (0.8–3.0 keV) ranging from log Lx ∼ 27.7–29.1. We find that our Peter Pan sample exhibits X-ray properties similar to that of weak-lined T Tauri stars and do not exhibit evidence of stellar accretion induced X-ray suppression. Our observed Peter Pan X-ray luminosities are consistent with that measured for field dM stars of similar spectral type and age, implying their long primordial disk lifetimes are likely not a consequence of unusually faint X-ray host stars. Our derived X-ray photoevaporative mass-loss rates predict our systems have passed the point of rapid gas dispersal and call into question the impact of this internal mechanism for primordial disk dispersal around dM stars. Our qualitative assessment of the surrounding Peter Pan environments also does not predict unusually low levels of external photoevaporation relative to other respective moving group members. Overall, our results suggest Peter Pan disks may be a consequence of the low far-UV flux incident on the disk in low-mass dM stars given their relatively lower levels of accretion over the course of their pre-main-sequence evolution.

Stefan Laos↗

NASA NTRS2023

Combined Experimental and Modeling Study of the Interactions of Acid Gas with Common Spacecraft Surfaces for Fire Safety Applications

A fire in a spacecraft poses detrimental consequences and risks mission success in addition to crew safety. This is compounded during long-duration missions when the crew has limited options to recover from a fire. A common spacecraft fire concern is the smoldering of wire insulation, typically made from Polyvinyl chloride (PVC) or Polytetrafluoroethylene (PTFE). This creates acid gases such as Hydrogen Chloride (HCl), Hydrogen Fluoride (HF) and Hydrogen Cyanide (HCN). These poisonous gases are hazardous to the crew. They also interact with common surfaces within the spacecraft more than dominant combustion products such as CO2 and H2O. This makes them more difficult to track for potential fire detection techniques, or for postfire clean-up. It is imperative to be able to understand and predict the fate of these poisonous species in a microgravity environment in order to design a safe vehicle. HCl interacts with a number of materials inside a spacecraft. Primary among these materials is aluminum, which is abundantly used due to its strong and light weight nature. Aluminum has a natural oxide layer that protects it from corrosion but is typically treated to enhance this oxide layer. Among these treatments is a chromate conversion coating (CCC), which provides a thin enough protective oxide layer to still conduct electricity, and a traditional anodized material that has a thicker oxide layer that does not conduct electricity. Nomex is another common material found inside a spacecraft. It is a flame-resistant woven polymer that is related to nylon. This commercially available material is used for cargo storage bags and as a fire barrier. Physics-based models were developed to predict the uptake of HCl by these materials. The ultimate objective of these models is to predict the fate of HCl within the spacecraft so that sensors can be placed in meaningful locations in future missions based on the model predictions. To support these modeling efforts, experiments were performed in a cast acrylic test cell that measured the difference between the inlet and outlet concentration of HCl after inserting a sample rod of the test material. Different uptake capacities were realized for each type of sample tested. A computational fluid dynamics model (CFD) model of the reactor was then constructed that used a one-step global reaction rate with calibratable reaction (or kinetic) constants. These constants were calibrated to match the HCl uptake on the CCC aluminum samples, and the same kinetic constants were then tested for the stock and anodized aluminum samples. Model predictions matched the experimental data for the stock aluminum, and to a much lesser extent, the anodized aluminum. The model was additionally validated at different flow rates, sample surface areas, and inlet concentrations, and showed good agreement for all stock and CCC samples. The model did not accurately predict the HCl uptake in the anodized samples compared to the other two types of aluminum. Adjusting the kinetic constants and transport properties did little to improve the prediction. X-Ray Photoelectron Spectroscopy (XPS) was used to determine that the oxide layer thickness of anodized aluminum is approximately 5,000 nm, compared to 250 nm for CCC and 50 nm for stock. XPS also revealed presence of chlorine further down in the aluminum oxide layer in anodized samples than CCC and stock samples after the samples were saturated with HCl, indicating that accounting for diffusion of HCl into the oxide layer is important for accurate prediction of HCl uptake onto anodized aluminum. Consequently, a multi-scale model was developed and tested. First, a single pore inside the anodized aluminum oxide layer was modeled and is referred to as the pore-scale model. In this model, HCl diffused through the pore and reacted with the aluminum oxide pore wall to create aluminum chloride. The sample was then saturated when the mass transfer resistance through the growing aluminum chloride layer became too large for the HCl to reach the aluminum oxide wall and continue the reaction. This pore-scale model was coupled to the reactor-scale model using a concentration-dependent diffusion coefficient, resulting in much more accurate predictions (approximately half the sum square error of the aforementioned reactor-scale model that produced good agreement for stock and CCC) for a variety of operating conditions. The amount of water vapor or relative humidity (RH) in the flow during a reactor experiment was determined to influence HCl uptake. Experiments were performed to understand the interaction of gaseous HCl with aluminum surfaces in the presence of water vapor. The results show that increasing levels of RH increased the capacity of aluminum to adsorb HCl but decreased the capacity of Nomex to uptake HCl. A series of tests were performed on individual aluminum samples after they had been saturated with a fixed concentration of HCl in dry air conditions with the goal of determining how their HCl uptake capacity changes after various treatments with water relative to the original saturation tests. HCl-saturated aluminum samples subjected to a second dry air flow at the same HCl concentration as the original test had an uptake of 23.5% of the original sample with no treatment in between. Saturated aluminum samples subjected to an air flow with a RH of 90% in between tests had an uptake of 35.6% of the original. Saturated aluminum samples submerged in distilled water for 12 hours in between tests had an uptake of 82.2% of the original sample. Previously saturated aluminum tested with HCl and a 50% RH air flow resulted in similar uptake characteristics in multiple repeated tests. The experiments show the profound effect water vapor has on HCl uptake onto aluminum surfaces. In the samples subjected to water vapor or liquid water, capillary condensation and capillary diffusion alters the transport of HCl significantly. A model was proposed that developed a relationship between RH and the coefficient of HCl diffusion in aluminum chloride. This produced an “S-shaped” curve with diffusion coefficient as a function of RH, with 45% RH represented as the point where the diffusion coefficient is halfway between no water saturation and 100% water saturation in the aluminum chloride product layer. No difference in uptake characteristics for the experiment or model were realized between 50% and 62% RH. The results from the large-scale microgravity experiment, Saffire, are discussed as they pertain to the fate of HCl throughout a spacecraft. HCl was released, both as a standalone event, and in concurrence with the burning of a structured cloth. These events only produced a small response in the far field HCl sensor, while a PMMA burn that did not produce HCl had a significantly greater response. A ground-based large-scale facility was constructed to flow acid gas at the scale and configuration realized in the Saffire experiments. A CFD model of this duct was constructed to test kinetic parameters developed in this work at a larger scale and different geometric configuration and to predict the results of the large-scale facility. The models developed in this work were used to interpret the results of the microgravity tests and lead the discussion on what further experiments and models are needed in order to predict the fate of acid gas in a spacecraft environment. To summarize, the major contributions of this work are as follows: the capacity to uptake HCl, with and without the presence of water vapor, was measured for a variety of real spacecraft surfaces. Several different models (single reactor-scale, multiscale, spacecraft-scale) were developed and with the aid of modeling, the rate of uptake for those surfaces was also predicted and validated. The kinetic parameters determined from the small-scale reactor experiments and models were used to predict large-scale and microgravity tests. Conclusions from this research will be used in the design of spacecraft vehicles and large-scale microgravity fire safety experiments. The models built by this work will aid designers in sensor placement and could be used to predict acid gas transport from fires in partial gravity, as would be seen in Lunar and Martian habitats.

fire safety↗

NASA NTRS2023

What’s That Supposed to Mean? Capturing Micro-Behaviors in Teams

Future long-duration space exploration (LDSE) crews will require extensive coordination, cooperation, and team functioning as they face a myriad of challenges rooted in both taskwork and teamwork (Bell et al., 2015; Landon et al., 2018). While exposed to extreme conditions, crew members must navigate living and working together in prolonged confinement. Moreover, astronaut teams are becoming increasingly diverse, introducing significant variability in team composition. This increasing diversity, alongside traditional constraints of LDSE, introduces additional challenges into effective team functioning. To date, most methods for capturing team functioning rely on self-report measures. Such measures are prone to several limitations, including but not limited to social desirability bias, halo effect, and leniency effects (Trull & Ebner-Priemer, 2013), which skew data and limit nuanced understandings of phenomena at play. Self-report measures broadly capture team functioning, lending the nature of such methods to identifying underlying “macro”-behaviors (i.e., behaviors that are long-standing and last over time). However, team functioning is far more complex than a series of macro-behaviors, rendering reliance on self-report data deficient for accurate measurement. Recent research demonstrates the potential of alternative methods for capturing team functioning, such as speech and physiological data (Chaffin et al., 2017; Murray & Oertel, 2018). Consequently, these methods are more suitable for capturing micro-behaviors: brief, often unconscious expressions that affect the extent to which an individual feels included by others around them (Paletz et al., 2013). Micro-behaviors can be further classified into micro-aggressions (i.e., subtle, negative exchanges; Keller & Galgay, 2010) or micro-affirmations (i.e., subtle, positive exchanges; Kyte et al. 2020), both of which influence team functioning. Due to the subtle nature of micro-behaviors, contextual factors have a significant impact when determining if it is aggressive or affirmative. Additionally, several iterations of micro-behaviors can have lingering effects on team interactions. For example, the use of “mm-hmm” by a crew member can function as both a micro-affirmation and micro-aggression. Specifically, it can be indication of active listening (i.e., micro-affirmation) or as an expression of annoyance (i.e., aggression) depending on the context in which it occurs. Auditory features (e.g., tone, frequency) can help delineate between the two forms; however, the contextual factors (e.g., previous interactions between team members, crew demographics) add a layer of complexity that render auditory features alone as insufficient to capture micro-behaviors. Consequently, this paper seeks to provide a novel approach in which multi-modal data (i.e., auditory features and contextual features) are used in a random-forest model to better identify distinguishing characteristics between micro-affirmations and micro-aggressions. In turn, detected micro-behaviors are used to predict team performance, thereby demonstrating the value of capturing micro-behaviors as supplemental data to macro-behaviors.

Sydney Begerowski↗

NASA NTRSDate not supplied

Nonlinear Acoustic Propagation in Low-Density Media

Nonlinear acoustic propagation in the atmosphere is usually modeled using an augmented Burgers equation accounting for atmospheric absorption and weak nonlinearity. However, the weak-nonlinearity assumption may not apply to acoustic signals propagating from the lower atmosphere that are subsequently refracted downward from the upper atmosphere (e.g., stratosphere and thermosphere) due to the decreasing air density with increasing altitude [Lonzaga, et al., Geophysical Journal International, 200(3), pp.1347-1361]. Consequently, this paper discusses the effects of a strong nonlinearity that lead to an amplitude-dependent increase in signal propagation speed. This propagation speed is obtained using a perturbation expansion where the leading-order term is simply the small-amplitude sound speed while the first-order term is the existing expression that gives rise to waveform steepening and stretching. Furthermore, the second-order term is proportional to the spectral density of the acoustic signal and is inversely proportional to the local density of the medium. Consequently, for an impulsive signal such as a sonic boom or an infrasound, the second-order effect causes a dispersion of the signal similar to the observed dispersion of acoustic signals from supersonic Concorde as well as from large explosions. This paper also discusses the extension of these results in general low-density propagation media.

sonic booms↗

NASA NTRS2023

IMPACTing Medical System Design with a Risk Analysis Tool [“IMPACT” sur la Conception du Système Médical avec un Outil d'Analyse des Risques]

Background: Following the success of Artemis I, NASA is preparing for human extended duration missions. Ongoing efforts are focused on mitigating mission-related risks, including those affecting crew health and performance. Communication latency, logistics of resupply and time frame of medical evacuation are barriers to provision of healthcare for these missions, especially with respect to constraints in mass, volume, and crew training. An in-depth assessment of medical risks, capabilities and resources for a specific mission design is necessary to determine an optimal balance that maximizes likelihood of mission success. Overview: IMPACT (Informed Mission Planning via Analysis of Complex Tradespaces) is a dynamic tool designed to estimate medical risk and outcomes for a specific mission design. In its current iteration, a list of medical conditions selected based on likelihood of occurrence and/or consequence was linked to a set of clinical capabilities and resources necessary for diagnosis and management. A probabilistic risk analysis tool was then used to identify and estimate the likelihood and consequence of risks through the following outcome metrics: loss of crew life (inflight mortality due to medical conditions), need for medical evacuation (return to definitive care), and crew disability (task time affected based on how medical conditions influence the ability to perform specific exploration mission crew tasks). Finally, the model’s optimization algorithm provides recommendations for medical capabilities that maximize risk mitigation relative to mass and volume constraints. In the Spring of 2023, IMPACT was utilized to estimate outcome metrics for a design reference mission that would be representative of an extended duration Artemis mission. Notional data generated were then used to determine a recommended set of medical capabilities and resources relative to user-defined mass and volume constraints. A multidisciplinary team has also been updating IMPACT to strengthen the model’s fidelity. Figure 1 shows how updates to outcome metric inputs for the conditions resulted in different capability and resource allocation recommendations. Discussion: This presentation will discuss the IMPACT tool and share the latest data generated for a representative extended duration Artemis mission. Efforts to improve the fidelity of data generated by the model’s algorithm will also be discussed.

K A Shair↗

NASA NTRSDate not supplied

Aerosols Delay the Emergence of Greenhouse Gas Forcing on 21st Century South Asian Monsoon Precipitation By Several Decades

Anthropogenic aerosols (AERs) affect several aspects of the climate system across the world through radiative forcing and microphysical effects. These influences are particularly strong across South Asia, where AER concentrations are highest and further projected to increase in coming decades. Using large ensemble experiments from Earth system model, we examine how AERs shape the evolution of seasonal precipitation over South Asia inlate 20th century and 21st century climate in the presence of rising greenhouse gases (GHGs) concentrations. We find that AERs strongly reduce monsoon precipitation, moderately reduce post-monsoon precipitation, and negligibly influence pre-monsoon precipitation. Consequently, AERs delay the emergence of GHG-forced increases in precipitation by ~5 decades in the monsoon season and ~1 decade in the post-monsoon season. However, GHGs are projected to outpace the influence of AERs by mid 21st century, causing a steep intensification of monsoon and post-monsoon precipitation. We further show that local AERs have the strongest influence on precipitation in the monsoon and post monsoon seasons in the near-future (2020-2049). However, the contribution from remote AERs changes is also important in shaping the monsoon precipitation changes over northwestern South Asia. Further, the influence of local AERs monsoon precipitation remains stationary throughout the 21st century, indicating the insensitivity of relationship between local AOD and precipitation to the projected warming. A better understanding of aerosol-climate interactions and associated precipitation responses in is pertinent for policymakers to address the critical aspect of regional consequences over South Asia induced by externally forced climate change.

Aerosols↗

NASA NTRS2023

Is the Global MHD Modeling of the Magnetosphere Adequate for GIC Prediction: the May 27–28, 2017 Storm

Practical steps taken by the international community to reduce the damage to technological systems from space weather include the development of numerical models capable of real-time predictions of electromagnetic disturbances at the Earth’s surface. Here we examine the feasibility of a version of the Space Weather Modeling Framework (SWMF) global MHD simulation code similar to that used by the NOAA Space Weather Prediction Center to predict the level of geomagnetic field variability, and consequently geomagnetically induced currents (GICs). We consider the contribution of geomagnetic disturbances to the bursts of GIC in the electric power line of the Kola Peninsula during the May 27–28, 2017 storm and compare the observations with results of the global MHD model. During the maximal disturbance magnetic field variations at East Scandinavian stations become more irregular, as intense Pi3 pulsations are superposed on the magnetic bay. These pulsations are not quasi-sinusoidal waves like typical Pc5 pulsations, but they are rather a quasi-periodic sequence of magnetic impulses with time scales ~5–15 min. During this period with elevated Pi3 activity very high values of GIC were recorded (variations >100 A) in the electric power transmission line. The SWMF modeling reasonably well reproduces the global magnetospheric parameters, such as SYM-H index or cross-polar potential. However, the magnetic field variability dB/dt in the East Scandinavia predicted by the modeling has turned out to be more than order of magnitude less than that observed. Thus, the version of SWMF with the grid used by NOAA SWPC still cannot adequately predict for the May 27–28 event the fine structure of the storm/substorm—Pi3 geomagnetic disturbances, and consequently the magnitude of the GIC that they drive.

geomagnetically induced currents↗

NASA NTRS2023

How Have Hydrological Extremes Changed Over the Past 20 Years?

Severe floods and droughts, including their back-to-back occurrences (weather whiplash), have been increasing in frequency and severity around the world. Improved understanding of systematic changes in hydrological extremes is essential for preparation and adaptation. In this study, we identified and quantified extreme wet and dry events globally by applying a clustering algorithm to terrestrial water storage (TWS) data from the Gravity Recovery and Climate Experiment (GRACE) and GRACE Follow-On (FO). The most intense events, ranked using an intensity metric, often reflect impacts of large-scale oceanic oscillations such as El Niño–Southern Oscillation and consequences of climate change. The severity of both wet and dry events, represented by standardized TWS anomalies, increased significantly in most cases, likely associated with intensification of wet and dry weather regimes in a warmer world, and consequently, exhibited strongest correlation with global temperature. In the Dry climate, the number of wet events decreased while the number of dry events increased significantly, suggesting a drying trend that may be attributed to climate variability and possible increases in irrigation and reliance on groundwater. In the Continental climate where temperature has risen faster than global average, dry events increased significantly. Characteristics of extreme events often showed strong correlations with global temperature, especially when averaged over all climates. These results suggest changes in hydrological extremes and underscore the importance of quantifying total water storage changes when studying hydrological extremes. Extending the GRACE/FO record, which spans 2002 to the present, is essential to continuously tracking changes in TWS and hydrological extremes.

Bailing Li↗

NASA NTRSDate not supplied

IMPACTing Medical System Design with a Risk Analysis Tool

K A Shair↗

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↗