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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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All sourcesNASA NTRSDOE OSTI
DOE OSTI2026

Human Factors and Technologies Design to Improve User Acceptance of Pooled Rideshare for Increasing Transportation System Energy Efficiency

This multi-year project delivered a comprehensive, human-factors-driven framework to understand, model, and improve pooled rideshare (PR) adoption in the United States. Through three large-scale national survey studies involving more than 16,000 participants across multiple cities and demographic groups, the research established one of the most extensive datasets to date on user perceptions, behavioral barriers, and service expectations related to pooled rideshare. These data revealed key human factors barriers of user acceptance of PR and suggested potential actionable experience optimizations that could lead to increased PR usage. This foundational knowledge guided the development of novel human-factors models and behavioral choice models that quantify how psychological, demographic, and trip-level factors influence willingness to pool. Building on these empirical insights, the project developed advanced behavioral modeling tools, including mixed logit and integrated choice and latent variable models, to capture both observable and latent influences on PR adoption. These models significantly improved the ability to predict riders’ acceptance of pooled trips, explaining choice heterogeneity through latent constructs such as safety, service experience, privacy concerns, time sensitivity, and environmental attitudes. Together, these models provide a robust analytical foundation for designing PR systems that more effectively meet user needs. The project translated human-factors insights and behavioral models into actionable technology innovations by extending POLARIS—an agent-based, activity-based travel simulation platform—into a fully functional pooled rideshare simulation environment. New PR modules, acceptance models, and regional scenarios were implemented for Greenville, SC and Austin, TX, enabling high-fidelity validation of algorithmic strategies under realistic demand and traffic conditions. The simulation platform supported the development and evaluation of adaptive discount-based assignment algorithms, enhanced willingness-to-pay formulations, demographic-aware incentive mechanisms, and a proactive joint assignment and repositioning strategy. Simulation results demonstrated substantial gains in pooling uptake, average vehicle occupancy, energy efficiency, and fleet profitability. In Greenville, pooling adoption more than doubled, while reductions in vehicle-miles traveled and energy consumption were significant. In Austin, pooling improvements were achieved with minimal service-quality trade-offs, and profitability increased across all fleet sizes. Through this research, we developed a comprehensive understanding of the human factors barriers that limit user acceptance of pooled rideshare services. These insights enabled the design of human-factors-aware pooled rideshare technologies that more effectively address user concerns and improve adoption rates. By integrating these models into an advanced agent-based simulation framework, we demonstrated that higher adoption of pooled rideshare can lead to measurable improvements in energy efficiency and system performance. Together, these contributions establish a validated pathway from human-centered analysis to technology development and energy-saving outcomes, supporting national goals for more sustainable and efficient mobility systems.

Jia, Yunyi↗
NASA NTRS2009

Reaction Wheel Disturbance Model Extraction Software - RWDMES

The RWDMES is a tool for modeling the disturbances imparted on spacecraft by spinning reaction wheels. Reaction wheels are usually the largest disturbance source on a precision pointing spacecraft, and can be the dominating source of pointing error. Accurate knowledge of the disturbance environment is critical to accurate prediction of the pointing performance. In the past, it has been difficult to extract an accurate wheel disturbance model since the forcing mechanisms are difficult to model physically, and the forcing amplitudes are filtered by the dynamics of the reaction wheel. RWDMES captures the wheel-induced disturbances using a hybrid physical/empirical model that is extracted directly from measured forcing data. The empirical models capture the tonal forces that occur at harmonics of the spin rate, and the broadband forces that arise from random effects. The empirical forcing functions are filtered by a physical model of the wheel structure that includes spin-rate-dependent moments (gyroscopic terms). The resulting hybrid model creates a highly accurate prediction of wheel-induced forces. It accounts for variation in disturbance frequency, as well as the shifts in structural amplification by the whirl modes, as the spin rate changes. This software provides a point-and-click environment for producing accurate models with minimal user effort. Where conventional approaches may take weeks to produce a model of variable quality, RWDMES can create a demonstrably high accuracy model in two hours. The software consists of a graphical user interface (GUI) that enables the user to specify all analysis parameters, to evaluate analysis results and to iteratively refine the model. Underlying algorithms automatically extract disturbance harmonics, initialize and tune harmonic models, and initialize and tune broadband noise models. The component steps are described in the RWDMES user s guide and include: converting time domain data to waterfall PSDs (power spectral densities); converting PSDs to order analysis data; extracting harmonics; initializing and simultaneously tuning a harmonic model and a wheel structural model; initializing and tuning a broadband model; and verifying the harmonic/broadband/structural model against the measurement data. Functional operation is through a MATLAB GUI that loads test data, performs the various analyses, plots evaluation data for assessment and refinement of analysis parameters, and exports the data to documentation or downstream analysis code. The harmonic models are defined as specified functions of frequency, typically speed-squared. The reaction wheel structural model is realized as mass, damping, and stiffness matrices (typically from a finite element analysis package) with the addition of a gyroscopic forcing matrix. The broadband noise model is realized as a set of speed-dependent filters. The tuning of the combined model is performed using nonlinear least squares techniques. RWDMES is implemented as a MATLAB toolbox comprising the Fit Manager for performing the model extraction, Data Manager for managing input data and output models, the Gyro Manager for modifying wheel structural models, and the Harmonic Editor for evaluating and tuning harmonic models. This software was validated using data from Goodrich E wheels, and from GSFC Lunar Reconnaissance Orbiter (LRO) wheels. The validation testing proved that RWDMES has the capability to extract accurate disturbance models from flight reaction wheels with minimal user effort.

Blaurock, Carl↗
NASA NTRS2019

Acoustic Analysis of Sensor Ports

Acquiring data in rocket engines that is representative of the actual dynamic environment can often be difficult due to a multitude of influences. One source of contamination that is often not considered entirely is the response associated with the acoustic cavity created by a sensor offset. It is common to offset a sensor due to various reasons such as for mounting accessibility, thermal isolation, shock reduction, or prevention of debris impingement. While estimating the natural frequency of the acoustic cavity is straightforward, limited analysis has been described on the determination of the overall frequency response. The sensor port design approach usually attempts to ensure the port is short enough such that the acoustic response is negligible near the frequency-of-interest, but this requires knowledge of the frequency response and simple rules-of-thumb are not always guaranteed. Data correction and/or data interpretation is also often desired for an unsatisfactory response. The limited response analysis in the literature only offers approximations or neglects important contributions. A new approach is devised theoretically and computationally that captures the true acoustic response of a sensor port. This paper summarizes the acoustics background, the port response theoretical development, and provides comparisons of a port acoustic response using an analytical model and computational acoustics. The effects of nonlinear acoustics are also examined. Additionally, the paper summarizes the design of a specialized filter using the predicted sensor port response that can be applied to data for correction.

Casiano, M. J.↗
NASA NTRSDate not supplied

Probabilistic Blast Damage Modeling Uncertainties and Sensitivities

Blast overpressure is the predominant source of ground damage posed by potentially hazardous asteroid strikes. Estimates of the extent, severity, and likelihoods of potential blast damage regions will be one of the key metrics needed to mount civil defense or disaster response plans in the face of an impending impact. However, there are many inherent sources of uncertainty in evaluating the damage, both in characterizing the properties of the incoming object and in the approaches used to model the entry/impact and resulting damage, which make it difficult to produce a single ‘accurate’ or ‘best guess’ prediction of ground damage. The current 2021 PDC hypothetical impact scenario poses a particular challenge due to its short warning time. The need for rapid disaster response to prepare for an immanent impact, combined with lack of observational opportunities to refine basic knowledge about the object’s basic size and properties, make understanding the range and relative likelihood of consequences particularly critical. The potential damage caused by these blasts can be evaluated using a range of modeling and simulation approaches and levels of fidelity. Fast-running engineering-level models can be used to run large numbers of probabilistically sampled cases covering wide variations of uncertain properties or parameters. High-fidelity simulations, on the other hand, can capture more detailed/accurate blast physics, but can only be performed for a small selection of specific cases, requiring many assumptions to be made about the initial object and its unpredictable entry/breakup characteristics. In order to provide a more complete picture of the potential threat for effective disaster response, both types of analysis need to be employed together. In this approach, high-fidelity simulations are used to refine and anchor engineering models, and the probabilistic engineering models are used to evaluate broad parameters spaces and guide selection of the most pertinent simulation cases for a given scenario. This presentation expands upon the probabilistic asteroid impact risk assessments being performed as part of the 2021 PDC hypothetical impact exercise, focusing on key aspects of blast damage modeling uncertainties and sensitivities. We review the current modeling and simulation approaches employed in the current assessment, compare the relative levels of uncertainty stemming from each main element of the problem (i.e., knowledge of the asteroid properties, modeling of the atmospheric entry/breakup and airburst, and estimates of the ground damage from the resulting blasts waves), and highlight any notable trends and sensitivities for the current scenario case.

SMD↗
DOE OSTI2025

Neutron diffraction reveals protonation states in pyridoxal‐5′‐phosphate‐free and glycine external aldimine‐bound serine hydroxymethyltransferase

Serine hydroxymethyltransferase (SHMT) is a critical enzyme in the one-carbon (1C) metabolism pathway catalyzing the reversible conversion of L-Ser into Gly and concurrent transfer of 1C unit to tetrahydrofolate (THF) to give 5,10-methylene-THF (5,10-MTHF), which is used in the downstream syntheses of biomolecules critical for cell proliferation. The cellular 1C metabolism is hijacked by many cancer types to support cancer cell proliferation, making SHMT a promising target for the design and development of novel small-molecule antimetabolite chemotherapies. To advance structure-assisted drug design, knowledge of SHMT catalysis is crucial, but can only be fully realized when the atomic details of each reaction step governed by the acid–base catalysis are elucidated by visualizing active site hydrogen atoms. Here, we used room-temperature neutron crystallography to directly determine protonation states in Thermus thermophilus SHMT (TthSHMT), capturing protomer A in the apo form lacking the coenzyme pyridoxal 5′-phosphate (PLP), and protomer B as a ternary complex with PLP–Gly-external aldimine and (6S)-5-methyltetrahydrofolate (5MTHF). We observed protonation of the Schiff base nitrogen in PLP–Gly and neutrality of the catalytic Lys226 side chain in the ternary complex, whereas Lys226 is protonated and positively charged in the apo-active site. Furthermore, we obtained an X-ray structure of TthSHMT in complex with the substrate THF, which binds identically as 5MTHF at the peripheral binding site. In conclusion, the unique structural and functional information provided by neutron crystallography, in combination with X-ray structures, can be employed in the rational design of SHMT inhibitors.

X-ray crystallography↗
NASA NTRS1991

An examination of coherent structures in a lobed mixer using multifractal measures in conjunction with the proper orthogonal decomposition

A 'lobed mixer' device that enhances mixing through secondary flows and streamwise vorticity is presently studied within the framework of multifractal-measures theory, in order to deepen understanding of velocity time trace data gathered on its operation. Proper orthogonal decomposition-based knowledge of coherent structures has been applied to obtain the generalized fractal dimensions and multifractal spectrum of several proper eigenmodes for data samples of the velocity time traces; this constitutes a marked departure from previous multifractal theory applications to self-similar cascades. In certain cases, a single dimension may suffice to capture the entire spectrum of scaling exponents for the velocity time trace.

Ukeiley, L.↗
NASA NTRS2007

Recommendations for Exploration Space Medicine from the Apollo Medical Operations Project

Introduction: A study was requested in December, 2005 by the Space Medicine Division at the NASA-Johnson Space Center (JSC) to identify Apollo mission issues relevant to medical operations that had impact to crew health and/or performance. The objective was to use this new information to develop medical requirements for the future Crew Exploration Vehicle (CEV), Lunar Surface Access Module (LSAM), Lunar Habitat, and Advanced Extravehicular Activity (EVA) suits that are currently being developed within the exploration architecture. Methods: Available resources pertaining to medical operations on the Apollo 7 through 17 missions were reviewed. Ten categories of hardware, systems, or crew factors were identified in the background research, generating 655 data records in a database. A review of the records resulted in 280 questions that were then posed to surviving Apollo crewmembers by mail, face-to-face meetings, or online interaction. Response analysis to these questions formed the basis of recommendations to items in each of the categories. Results: Thirteen of 22 surviving Apollo astronauts (59%) participated in the project. Approximately 236 pages of responses to the questions were captured, resulting in 107 recommendations offered for medical consideration in the design of future vehicles and EVA suits based on the Apollo experience. Discussion: The goals of this project included: 1) Develop or modify medical requirements for new vehicles; 2) create a centralized database for future access; and 3) take this new knowledge and educate the various directorates at NASA-JSC who are participating in the exploration effort. To date, the Apollo Medical Operations recommendations are being incorporated into the exploration mission architecture at various levels and a centralized database has been developed. The Apollo crewmembers input has proved to be an invaluable resource, prompting ongoing collaboration as the requirements for the future exploration missions continue to evolve and be refined.

Scheuring, R. a.↗
NASA NTRS2012

Autonomous Onboard Science Data Analysis for Comet Missions

Coming years will bring several comet rendezvous missions. The Rosetta spacecraft arrives at Comet 67P/Churyumov-Gerasimenko in 2014. Subsequent rendezvous might include a mission such as the proposed Comet Hopper with multiple surface landings, as well as Comet Nucleus Sample Return (CNSR) and Coma Rendezvous and Sample Return (CRSR). These encounters will begin to shed light on a population that, despite several previous flybys, remains mysterious and poorly understood. Scientists still have little direct knowledge of interactions between the nucleus and coma, their variation across different comets or their evolution over time. Activity may change on short timescales so it is challenging to characterize with scripted data acquisition. Here we investigate automatic onboard image analysis that could act faster than round-trip light time to capture unexpected outbursts and plume activity. We describe one edge-based method for detect comet nuclei and plumes, and test the approach on an existing catalog of comet images. Finally, we quantify benefits to specific measurement objectives by simulating a basic plume monitoring campaign.

comets↗
DOE OSTI2025

Demonstrate new plasticity models for doped UO 2 that capture dislocation mechanisms

In light water reactors, fuel vendors are investigating the use of dopants to modify the properties of UO 2 pellets, with the goal of improving pellet-cladding mechanical interactions during operation. Dopants are expected to ‘soften’ the pellets; that is, the doped pellets have higher plastic deformation than conventional UO 2 . This leads to a reduction in the severity of mechanical pellet-cladding interactions, helping to reduce the hoop strain on the cladding. By minimizing the strain exerted by the pellet on the cladding, it is anticipated that cladding performance under accident conditions can be enhanced (i.e., lowering the risk of burst during a LOCA). Dopants such as chromium (Cr) promote grain growth during pellet fabrication, leading to larger grains; therefore, understanding the link between chemistry, microstructure and mechanical deformation (enhanced creep rates) behavior of UO 2 is critical to helping operators further substantiate the benefits of doping UO 2 . Historically, the nuclear energy industry has relied on empirical models to make assessments of performance. Compared to empirical models, mechanistic physics-based models provide benefits, such as, fewer data points for validation and better extrapolation where experimental data is scarce or non-existent. In this report, Bayesian inference techniques have been applied to a previously developed lower length-scale-informed diffusional creep model. The objective is to i) infer lower-length-scale parameter distributions from available experiment and then ii) determine the uncertainties in the measurable quantity (in this case creep rates) after propagating the inferred lower length scale parameter uncertainties. The approach requires many evaluations of the model, which becomes computationally insurmountable; therefore, a neural-network model is trained to data obtained by sampling the full model over the most important parameters. This neural-network is then used in the Bayesian inference approach to determine probability distributions in the parameter values that represent the uncertainty in the model given what is known from the experiments (posterior). A significant reduction compared to conservative initial (prior) uncertainties is achieved through inference against the experimental data, demonstrating the efficacy of this approach. Furthermore, by accounting for uncertainties in the experimental conditions and sample non-stoichiometry, it is possible to resolve apparent discrepancies in experimental measurements within a self-consistent grain boundary (Coble) creep model that is sensitive to chemistry. This work has been written up and submitted to Nuclear Technology for a special issue on accelerated fuel qualification (AFQ). This uncertainty quantification (UQ) work not only improves the diffusional model, while accounting for uncertainty, but also establishes a framework which can readily be applied to the mechanistic models of dislocation deformation developed in this study. The most likely values from the Bayesian analysis are incorporated into our UO 2 diffusional creep model and a lower length scale-informed irradiation UO 2 creep mechanistic model to generate a dataset. This dataset has been provided to our INL collaborators for training an artificial neural network surrogate model, which will be implemented in the BISON fuel performance code to assess how the results differ from those currently obtained using a fully empirical model and that of using the nominal (uncalibrated) atomic scale parameters in our mechanistic model. Plastic deformation (creep and glide) in UO 2 is a complex phenomenon, governed by multiple underlying processes such as local defect concentrations, applied stresses, and microstructural characteristics. Consequently, there is a need for a meso-scale model with polycrystalline resolution capable of extrapolating to large grain sizes applicable to doped UO 2 , where data is limited and the model can help bridge the knowledge gap. By integrating atomistic data into the polycrystal LApx code, it becomes possible to predict dislocation climb and glide plasticity that simple analytical models cannot accurately represent. The application of atomic-scale data within LApx demonstrated the importance of climb and glide mechanisms in reproducing high-stress UO 2 behavior. Behaviors such as this are crucial to capture and implement in BISON, as parts of the fuel pellet can reach temperatures where glide can occur before pellet cracking. This model which captures dislocation based mechanisms for UO 2 is then used to stand up the doped model accounting for larger grain sizes. It was found that larger grain sizes can lead to enhanced deformation rates in the glide regime, and therefore can help with the pellet cladding mechanical interaction. Therefore if the fuel pellet reaches conditions (stress/temperature) where glide is active, the enhanced creep rates for larger grains in the glide regime (doped UO 2 ) can help with pellet cladding mechanical interactions. Plastic deformation in UO 2 involves multiple mechanisms, including diffusional creep, dislocation climb, and glide. This milestone contains two parts: (1) UQ of a pre-existing lower length scale informed mechanistic diffusional creep model, and (2) development of a new LApx based model for dislocation-mediated creep mechanisms in UO 2 , with application to large-grain doped UO 2 .

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2024

Contradictory Ambiguous Revocable Assertion Tracker (CARAT) Encoding

How data is encoded in a knowledge graph directly influences what can be done with that data. A common problem with many encodings is that they have difficulty representing ambiguity and evolution inherent in many real-world data sets. The data encoding represented in this paper (called CARAT) is a graph-level description of our attempt to capture data that is contradictory, ambiguous and evolves over time (including deleting information). The data encoding relies on tracking assertions about subjects rather than directly tracking states. This encoding decision resolves many issues our team had experienced using other data encodings but produces a a larger graph. This is a preliminary presentation of our experience with CARAT.

Cottam, Joseph A. [BATTELLE (PACIFIC NW LAB)]↗
NASA NTRS2005

Development of a Work Control System for Propulsion Testing at NASA Stennis

In 1996 Stennis Space Center was given management authority for all Propulsion Testing for NASA. Over the next few years several research and development (R&D) test facilities were completed and brought up to full operation in what is known as the E-Complex Test Facility at Stennis Space Center. To construct, activate and operate these test facilities, a manual paper-based work control system was created. After utilizing this paper-based work control system for approximately three years, it became apparent that the research and development test area needed a better method to execute, monitor, and report on tasks required to further propulsion testing. The paper based system did not provide the engineers adequate visibility into work tasks or the tracking of testing or hardware discrepancies. This system also restricted the engineer s ability to utilize and access past knowledge and experiences given the severe schedule limitations for most R&D propulsion testing projects. Therefore a system was developed to meet the growing need of Test Operations called the Propulsion Test Directorate (PTD) Work Control System. This system is used to plan, perform, and track tasks that support testing and also to capture lessons learned while doing so.

Messer, Elizabeth A.↗
DOE OSTI2025

Convective potential and fuel availability complement near-surface weather in regulating global wildfire activity

Wildfires are favored by hot, dry, windy, rainless conditions—this knowledge about fire weather informs both short-term forecast and long-term prediction of wildfire activity. Yet, wildfires rely on the availability of ignition and fuel, which are underrepresented in fire forecast and prediction practices. By analyzing satellite measurements and atmospheric reanalysis, here we show that near-surface weather only partially captures wildfire occurrence and intensity across the daily to seasonal timescales. Beyond near-surface weather, convection and fuel abundance play a complementary role in regulating burning processes. Specifically, enhanced atmospheric convection is identified for over 40% of the low-human-impact regions and 61% of global burnable areas during wildfire ignition and spreading periods. Meanwhile, 56% of shrublands and 54% of grasslands see higher fuel load with actual occurrence of fire. Our results highlight the role of convection and fuel in wildfire forecast, prompting a revisit of wildfire prediction under intertwined atmospheric and terrestrial changes.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS2010

Project Management Using Modern Guidance, Navigation and Control Theory

The idea of control theory and its application to project management is not new, however literature on the topic and real-world applications is not as readily available and comprehensive in how all the principals of Guidance, Navigation and Control (GN&C) apply. This paper will address how the fundamental principals of modern GN&C Theory have been applied to NASA's Constellation Space Suit project and the results in the ability to manage the project within cost, schedule and budget. A s with physical systems, projects can be modeled and managed with the same guiding principles of GN&C as if it were a complex vehicle, system or software with time-varying processes, at times non-linear responses, multiple data inputs of varying accuracy and a range of operating points. With such systems the classic approach could be applied to small and well-defined projects; however with larger, multi-year projects involving multiple organizational structures, external influences and a multitude of diverse resources, then modern control theory is required to model and control the project. The fundamental principals of G N&C stated that a system is comprised of these basic core concepts: State, Behavior, Control system, Navigation system, Guidance and Planning Logic, Feedback systems. The state of a system is a definition of the aspects of the dynamics of the system that can change, such as position, velocity, acceleration, coordinate-based attitude, temperature, etc. The behavior of the system is more of what changes are possible rather than what can change, which is captured in the state of the system. The behavior of a system is captured in the system modeling and if properly done, will aid in accurate system performance prediction in the future. The Control system understands the state and behavior of the system and feedback systems to adjust the control inputs into the system. The Navigation system takes the multiple data inputs and based upon a priori knowledge of the input, will develop a statistical-based weighting of the input to determine where the system currently is located. Guidance and Planning logic of the system with the understanding of where it is (provided by the navigation system) will in turn determine where it needs to be and how to get there. Lastly, the system Feedback system is the right arm of the control system to allow it to affect change in the overall system and therefore it is critical to not only correctly identify the system feedback inputs but also the system response to the feedback inputs. And with any systems project it is critical that the objective of the system be clearly defined for not only planning but to be used to measure performance and to aid in the guidance of the system or project.

Hill, Terry↗
NASA NTRS2020

X-HAB 2020: AR Field Treks Summary and Conclusions

As part of the FY20 X-Hab Challenge, BLiSS sought to create an Augmented Reality (AR) toolkit to help with analog field trek operations under the supervision of the Solar System Exploration Research Virtual Institute (SSERVI). These treks are operational and technical demonstrations at space-like destinations on Earth to test current extra-vehicular activity (EVA) techniques. While BLiSS as an organization has experience studying operational tasks such as this, it has never developed AR software at this scale. For that reason, another team at the University was brought on to work in parallel. The Collaborative Lab for Advancing Work in Space (CLAWS) is a veteran group of the NASA Spacesuit User Interface Technologies for Students (SUITS) challenge in which Hololens displays for astronauts are created within a year. The operational and technological pairing was ideally suited for tackling this problem. The team divided its responsibilities so that BLiSS would handle the research required to shape the project. As this deliverable had an end user, it was decided that interviewing these field geologists and operations specialists would provide the best insight. These interviews paired with literature review would reveal niche applications for AR that remained within feasible bounds. These science-driven EVAs in unknown terrain require more flexible tools than the current generation of EVA assistants. Rather than focus on sequential instructions, there instead needs to be a broad toolkit that's only called upon in specific instances. This AR Toolkit for Lunar Astronauts and Scientists (ATLAS) became the development goal of the project: create a non-intrusive assembly of tools that could be accessed in AR on the field. The current ATLAS design makes use of a geospatially and temporally annotated eld note system called GeoNotes. This allows for data to be collected and coordinated in a way that's synchronized across time, space, and different users. A Mission Control Center (MCC) and Mobile Support Equipment (MSE) were all needed to transport the AR headset into the field with the user. A network infrastructure was designed and set up within the University to enable this functionality. The software is based on a Protocol-Module structure that allows for modular development of each capability. A Protocol Manager coordinates different protocols that make use of modules. Each module tackles a different individual task while the protocol puts each one to use. The protocol manager coordinates when these are called to be used. This software is hosted on a head-mounted display (HMD) with the MCC acting as support from afar. While the software would be unit-tested at each level and each hardware component verified, a final demonstration would serve to prove the system's capabilities: an analog field trek. The team would prepare to support a user in a remote location from the MCC back at the University. A local area near campus would be tested before going out to do sample field geology further away. This unfortunately became impossible with the arrival of COVID-19. Access to all of the facilities to complete the project as planned were shut down. Our team was scattered across the globe and forced to complete the rest virtually. Adjustments were made to produce a small virtual concept in Adobe XD in the meantime. Even digital surveys were created based on the NASA task-load index (TLX) originally intended for testing actual users. The goal shifted towards completing software and getting feedback on the user interfaces (UI) and user experiences (UX). This team has reformed in response to COVID and its focus has shifted to what can be done remotely. There is still an intention to finish the original deliverable described in this report. The work has been expanded beyond the original X-Hab challenge and has instead become its own research e ort to be continued afterwards. This report collects the processes and knowledge gained from a year of studying and working at this problem with two teams. It should preserve it for the time until the world returns to normal and work can resume. CLAWS will be taking over full responsibility from that point forward, eventually surpassing the original needs of the project. While this document captures the work done towards an eventual end, the CLAWS team has written their own proposal alongside it. It outlines a new future for ATLAS beyond X-Hab, BLiSS, and hopefully beyond COVID-19. This project began as a vague goal hoping to place a new technology into the unique setting of exploration science. The project has since comfortably taken root and will hopefully bloom over the next year.

Alex Sena↗
NASA NTRS2021

Exploration Medical Capability Medical Scenarios

Medical systems supporting exploration class missions to cislunar space, the lunar surface, and the vicinity of Mars require an evolution in medical capability beyond that available for today’s low Earth orbit centric paradigm. Progress in developing more capable medical systems will be driven by the requirements of prolonged mission duration, increasing distance from Earth, and the realities of orbital mechanics, all necessitating a concomitant need for progressively Earth independent medical decision-making capabilities. These medical systems (which include the crewmembers) are expected to be capable of evaluating, diagnosing, treating and managing a defined list of medical conditions as well as addressing unanticipated medical conditions that may arise. The prioritized medical capabilities and associated resources needed to treat these medical conditions and support anticipated inflight medical events provide robust content that informs system designers and allows for a more complete evaluation of both medical and overall mission risk. Communication of these medical capabilities to system, vehicle, and mission designers can be enhanced using scenarios that characterize the system’s operations. Carefully considered scenarios provide the context needed to explore expected human and system interfaces, roles of ground and inflight crew (including periods of interrupted or delayed communications), identify training needs, assess data needs, etc. Mission-based scenario content varies dependent upon the needs, medical capabilities, conditions and context they are intended to illustrate. This document explicitly seeks to capture and codify those scenarios that have been useful to the Exploration Medical Capability Element of the Human Research Program in defining the enhanced medical systems required for future space exploration. It is expected that this document will continue to evolve through the refinement and characterization of current and future scenarios, respectively, as our knowledge grows, and requirements increasingly focus on Earth independent spaceflight operations.

Derek M Nusbaum↗
NASA NTRSDate not supplied

Harnessing Artificial Intelligence for Medical Diagnosis and Treatment During Space Exploration Missions

From May 8th to June 9th, 2023, I had the opportunity to participate in an experiential learning experience at Johnson Space Center in Houston, TX with Exploration Medical Capability (ExMC), an element of the NASA Human Research Program. During this research experience, I was not only able to work on the above titled research project, but also gain an immense exposure to the field of aerospace medicine, make numerous connections within the field, tour NASA facilities, as well as travel to the Aerospace Medical Association Annual Conference (AsMA) in New Orleans. To briefly introduce my project, it is well understood that the medical capabilities available to crew medical officers (CMOs) on the International Space Station will be different than the capabilities available and needed during deep space exploration missions to the Moon, Mars, and beyond. Ground support is particularly limited due to distance, communication delays (or lack of communication), and lack of resupply. Therefore, to support medical care by CMOs on these missions, robust clinical decision support systems (CDSSs) must be designed. The recent publication and public launch of generative artificial intelligence (AI) tools based upon large language models (LLM) such as ChatGPT provides the opportunity to create a smart assistant for onboard triage, diagnosis, and treatment of medical conditions. Ultimately, the overall purpose of the project was to research what AI tools currently exist or are in development, and to see how they might be implemented onboard during exploration class spaceflights of the future. The ExMC element is actively developing several tools to be used in preparation for and during deep space exploration missions. One of those tools, known as IMPACT, is a probabilistic risk assessment model which can be used to propose a desired medical system (based on mass and volume) and suggest the clinical outcomes likely to occur for a design reference mission (DRM). The group recently presented the IMPACT model and a DRM of interest titled “Modified Long Duration Lunar Orbital and Lunar Surface” (mLDLOLS) at the recent AsMA conference. The mLDLOLS mock mission is a 9 month and 6-day deep space exploration mission consisting of time in Moon’s orbit (3 months on the Gateway space station), on the lunar surface (3 months within habitat), and another 3 months on Gateway before return to Earth. For this DRM, IMPACT ultimately outlined a preferred medical system that was then associated with medical conditions considered to be most likely based on frequency, most likely to cause astronaut task time loss (TTL), most likely to cause return to definitive care (RTDC), and most likely cause loss of crew life (LOCL). IMPACT also highlighted the medical capabilities/skills that would be required to care for those medical conditions, such as performing a history of present illness or musculoskeletal exam with ultrasound. The primary objective of the project was to perform a survey of the AI tools and systems applicable to the conditions outlined for the proposed mLDLOLS mission. Using PubMed (including most relevant MeSH terms) and Google Scholar, we then created a robust annotated bibliography organized by condition. The 56-page and over 500 reference annotated bibliography was subsequently used to create a review outline that would become the basis for drafting of a future publication. For the review outline, we took those medical conditions researched within the annotated bibliography (condition-based approach) and deployed a systems-based approach, combining those medical conditions and related tools into ten categories. These categories included general/all-purpose CDSSs, tools to diagnose or manage respiratory, dermatologic, neurologic, auditory and vestibular, ophthalmic, musculoskeletal, infection-associated, and gynecologic conditions, as well as tools that could be deployed in the setting of trauma/emergency. With the completion of the 30-page outline, we then began drafting the review paper. To conclude the research experience, I presented the findings from our survey to the ExMC Clinical and Science team. With these objectives, I ultimately learned about the number of AI tools that exist today to assist medical professionals with the triage, diagnosis, and management of several medical conditions. These tools can span from chatbot assistants to help triage knee pain to vision transformer models that can identify ophthalmic conditions based on ocular surface images captured with a cell phone. We also highlighted the current gaps that exist in the literature alongside the advancements that are needed to make the desired CDSS for deep space exploration missions. With this experience, I certainly confirmed an existing career goal and identified several additional skills needed to become an aerospace medical doctor including knowledge of critical care in an extreme medicine setting, aerospace engineering and human integration systems, artificial intelligence, machine learning, and risk models. I also identified numerous transferable skills for this career goal including the basic knowledge of medicine (MD), deployment of the scientific method for critical thought about new scientific questions (PhD), review of published literature, including creating an annotated bibliography (PhD), as well as detailed scientific writing (PhD). The results of my research will likely guide the design of an all-encompassing onboard medical assistant for use during deep space exploration missions of the future. I plan on sharing the outcomes from this experience with my peers at a student seminar in the Fall semester on August 30th. During the seminar, I will detail the project, my experience at NASA and AsMA, as well as offer best practice guidelines for students entertaining similar experiences or careers. In conclusion, I would like to thank the WVU School of Medicine, Research and Graduate Education office, as well as NASA ExMC for the unwavering support of this life-changing experience.

Ryan A. Lacinski↗
DOE OSTI2024

High-throughput measurements of CO 2 permeance and solubility in ionic liquid reveal a synergistic role of ionic interactions and void fractions

The factors that govern CO 2 solubility in ionic liquids (ILs) are of great interest for the development of new materials for CO 2 capture and utilization. The cationic functional group (i.e., imidazolium, pyrrolidinium, pyridinium, etc.), alkyl chain length of cation, degree of fluorination of anion, anion size, and the void fraction in IL are known to influence CO 2 solubility. However, a comprehensive explanation of how these factors collectively affect CO 2 solubility has not been developed yet. This knowledge gap is largely attributed to the lack of CO 2 solubility data for IL structures other than imidazolium based ILs. We report here an automated high-throughput (HT) setup for the measurement of CO 2 solubility in room-temperature ILs (RTILs) combining six different anions and nine different cations for a total of 19 different specific ranges of RTILs. The HT setup first dispenses up to 200 µL of RTILs in a 96-well microtiter plate and then utilizes a robotic arm to measure cyclic voltammogram (CV) in each well using maneuverable Ag electrodes. The Cottrell analysis of the CO 2 reduction CV peak provides a direct measurement of CO 2 permeance in RTILs, which yields Henry’s constant from the estimated diffusion coefficient of CO 2 . Henry’s constants thus obtained are in very good agreement with those reported earlier. The measured CO 2 permeance and Henry’s constant of all RTILs seem to follow a first-order dependence on void fraction and a second-order dependence on electrostatic interaction between anion and cation of IL, with some synergistic dependence on the product of a void fraction and electrostatic interaction, making them two important descriptors for the design of novel ILs.

CO2 Solubility↗
DOE OSTI2026

Mutation of active site glutamate in serine hydroxymethyltransferase allows trapping a reactive intermediate: a combined neutron and X-ray crystallography study

Serine hydroxymethyltransferase (SHMT) is a pyridoxal-5′-phosphate (PLP) dependent enzyme that catalyzes a chemical transformation essential for the one-carbon (1C) metabolism. SHMT reversibly converts L-Ser into Gly and transfers a 1C unit to tetrahydrofolate (THF) to give 5,10-methylene-THF (5,10-MTHF). 5,10-MTHF, a 1C-unit donor, plays a crucial role in the downstream biomolecular syntheses required for the cell homeostasis and proliferation. SHMT is a prominent target for the drug discovery to battle bacterial and parasitic infections, and to treat various types of cancer. SHMT-catalyzed chemistry is governed by the general acid-base catalysis. Knowledge of the catalytic mechanism can aid drug design but can only be achieved when the atomic details of each reaction step are mapped, including accurate determination of hydrogen atom positions. Here we utilized the inactive E53Q mutant of Thermus thermophilus ( Tth ) SHMT to directly determine protonation states with room-temperature neutron crystallography and to capture a reactive intermediate containing the PLP-L-Ser external aldimine and THF in the enzyme active site. We observed protonation of the Schiff base nitrogen (N SB ) in the PLP internal aldimine but no change in the protonation states of other ionizable PLP groups and active site residues compared to wild-type Tth SHMT. X-ray structural analysis of the ternary intermediate complex E53Q-Ser-THF that eluded previous structural characterization shows the strategic positioning of the E53Q side chain in close proximity to the external aldimine and THF and reinforces the proposed role for E53 as the driver of proton transfer events along the reaction pathway.

Drago, Victoria N. [Oak Ridge National Laboratory ↗