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NASA NTRSDate not supplied

Habitability Assessments And Lessons-learned From 3-day And 11-day Enriched Oxygen Hypobaric Chamber Tests At NASA Johnson Space Center

INTRODUCTION: Decompression sickness (DCS) is a risk to the health and performance of astronauts and high-altitude aircrew. Tolerance to flammability, hypoxia, prebreathe duration, and DCS risk varies across different organizations, vehicles, suits, and destinations, necessitating a variety of DCS risk mitigation approaches. Existing models of altitude DCS risk are often insufficient to enable accurate risk-informed decisions during hardware development, mission planning, and flight operations. METHODS: NASA completed outfitting of a dedicated facility at Johnson Space Center to support testing of up to eight human subjects for multiple days in hypobaric and enriched oxygen atmospheres. The primary purpose of the testing capability is validation of DCS risk mitigation protocols for Artemis missions to the Moon; however, it will also support development and validation of a generalizable altitude DCS risk estimation tool. A 3-day and an 11-day prebreathe validation test were completed in 2022, each with 8 human subjects living at 56.5 kPa (8.2 psia), 34% O2, 66% N2, with 5 simulated EVAs performed on masks at 29.6 kPa (4.3 psi), 85% O2, 15% N2. Facility and organizational lessons-learned and process improvements were recorded during and following the tests, and subjective habitability ratings were recorded daily during the 11-day test. Hypoxia and DCS-related physiological and cognitive outcome measures were recorded during both tests and are reported in companion presentations. RESULTS & DISCUSSION: All subjects completed each of the tests. Primary habitability issues related to mask discomfort during simulated EVAs and poor sleep quality due to thin mattresses. Polybenzimidazole (PBI) clothing was worn by all subjects due to the increased fire risk and may be required for Artemis missions; clothing was found to be acceptable overall with the worst ratings being due to poor fit and inelasticity. Chamber O2 and CO2 sensor inconsistency was observed that did not result in test termination but required post-test follow-up. Forward plans include additional hypobaric testing and integration of existing and future physiological outcome data into an open-source Aerospace Estimation Tool for Hypobaric Exposure Risk (AETHER). NASA is also working to make the testing capability available to commercial companies.

Andrew F J Abercromby↗

NASA NTRSDate not supplied

Utilizing Tissue Engineering and 3D Models to Address Space Exploration Risks

Explore the source record for details and available documents.

Kristin Fabre↗

NASA NTRSDate not supplied

Habitability Assessments And Lessons-learned From 3-day And 11-day Enriched Oxygen Hypobaric Chamber Tests At NASA Johnson Space Center

Andrew Abercromby↗

NASA NTRSDate not supplied

Active Swarm Resiliency in the HelioSwarm Mission

Designed to observe plasma turbulence dynamics in solar wind over a distributed volume of space, the HelioSwarm mission comprises a primary chief spacecraft and eight smaller deputy satellites in uniquely assigned “loops” of periodic relative motion in a P/2 lunar resonant orbit. If one or more deputies fail, this multi-satellite architecture facilitates resiliency for science goals through repositioning of satellites to contingency loops. This strategy of Active Swarm Resiliency mitigates risk by modeling quantitative results ahead of time for mission operators to make informed decisions. Responsive actions meet minimum science objectives based on past and predicted system performance, an approach with applications to future missions with similar architecture and requirements.

Fault Management↗

NASA NTRSDate not supplied

Active Swarm Resiliency in the HelioSwarm Mission

Fault Management↗

NASA NTRSDate not supplied

Assessing Crew Medical Officer Preparedness for International Space Station Missions

INTRODUCTION Astronaut crew medical officers (CMO) undergo additional, specialized training to provide medical support onboard the International Space Station (ISS). CMO training focuses on utilizing resources on-station and optimizing communication with ground-based expertise to manage both common minor conditions as well as emergency/trauma situations. As NASA moves towards future Artemis and exploration class missions, we sought CMO perspectives on past, present, and future CMO training and medical resourcing to help inform mission planners regarding medical risk mitigation considerations. We present an interview-based qualitative assessment of CMO preparedness for the International Space Station with the aim to help iterate future training flows for Low Earth Orbit, Artemis, and exploration-class missions. METHODS A semi-structured interview tool was developed to assess CMO experience and their recommendations for future mission training considerations. Participants were recruited from former or current US astronauts who were designated as CMO and subsequently flew to the International Space Station. 10 former CMOs took part in the study. Interview transcripts were deidentified and evaluated for qualitative thematic analysis by two independent coders with NVivo Software suite (Lumivero, Denver, CO), and emergent themes were compiled. RESULTS Former CMO crew expressed appropriate preparedness for current ISS medical capabilities and requirements. They identified the role of the CMO as serving as a healthcare extender to ground-based flight surgeons for ISS and other LEO missions. Individuals with prior medical experience were preferred though not felt to be necessary for LEO missions. For exploration class missions with limitations in ground communication, a physician-as-CMO and more rigorous training curricula for both the CMO and astronaut crew were desired. DISCUSSION Former NASA astronaut crew were interviewed to retrospectively assess their preparedness as ISS crew medical officers and hypothesize future medical knowledge, skill, and ability needs. Along with medical operations subject matter expert opinion and advanced probabilistic risk assessment modeling, past CMO experience can help inform future CMO training considerations and responsibilities for future Artemis and exploration class missions.

M A Labarbera↗

NASA NTRS2026

Turbofan Engine Power Extraction Demonstration Final Report

As GE Aerospace advances toward a revolutionary step change in propulsion efficiency, the integration and demonstration of new engine architectures and technology systems are essential. The NASA Turbofan Engine Power Extraction Demonstration (PEx), conducted through the Hybrid Thermally Efficient Core (HyTEC) project, aims to develop and demonstrate megawatt-class hybrid electric capability on a modern commercial turbofan engine. The hybrid electric system is critical to meeting the needs of the U.S. aviation industry for next-generational propulsion systems with greater efficiency, durability, and range. This supports energy independence and helps ensure the security and resilience of one of America's largest export industries. The PEx project specifically targets three key objectives: mechanically integrating hybrid electric capability into a commercial turbofan engine, integrating electric machine control with turbofan control for advanced power management, and de-risking performance modeling of future hybrid electric architectures. To mature these technologies to Technology Readiness Level (TRL) 6, a series of electric power system component tests and a baseline engine performance test campaign were conducted. These efforts culminated in an integrated hybrid electric turbofan test campaign demonstrating power extraction, power insertion, and power transfer between spools. Tests of the electric power system were completed at GE Aerospace’s Electrical Power Integrated Systems Center in Dayton, Ohio and engine tests were completed at Peebles Test Operation in Peebles, Ohio. Hybrid electric trade studies extended the demonstrated capability to altitude using the validated cycle model from the PEx test campaigns, allowing for comments on expanded mission benefits not demonstrated in the ground campaign. The knowledge gained from PEx also supports GE Aerospace’s Compact Core Demonstrator as part of HyTEC Phase 2 and ultimately informs the implementation of hybrid electric systems in the next generation of GE Aerospace commercial engine products. This report provides a summary of the program background, test campaigns, trade studies, and insights into the technical maturation required to support future commercial products.

Hybrid Electric↗

NASA NTRS2017

Assessing Inter-Sectoral Climate Change Risks: The Role of ISIMIP

The aims of the Inter-Sectoral Impact Model Intercomparison Project (ISIMIP) are to provide a framework for the intercomparison of global and regional-scale risk models within and across multiple sectors and to enable coordinated multi-sectoral assessments of different risks and their aggregated effects. The overarching goal is to use the knowledge gained to support adaptation and mitigation decisions that require regional or global perspectives within the context of facilitating transformations to enable sustainable development, despite inevitable climate shifts and disruptions. ISIMIP uses community-agreed sets of scenarios with standardized climate variables and socioeconomic projections as inputs for projecting future risks and associated uncertainties, within and across sectors. The results are consistent multi-model assessments of sectoral risks and opportunities that enable studies that integrate across sectors, providing support for implementation of the Paris Agreement under the United Nations Framework Convention on Climate Change.

Regional-scale risk models↗

NASA NTRS2010

Ablative Rocket Deflector Testing and Computational Modeling

A deflector risk mitigation program was recently conducted at the NASA Stennis Space Center. The primary objective was to develop a database that characterizes the behavior of industry-grade refractory materials subjected to rocket plume impingement conditions commonly experienced on static test stands. The program consisted of short and long duration engine tests where the supersonic exhaust flow from the engine impinged on an ablative panel. Quasi time-dependent erosion depths and patterns generated by the plume impingement were recorded for a variety of different ablative materials. The erosion behavior was found to be highly dependent on the material s composition and corresponding thermal properties. For example, in the case of the HP CAST 93Z ablative material, the erosion rate actually decreased under continued thermal heating conditions due to the formation of a low thermal conductivity "crystallization" layer. The "crystallization" layer produced near the surface of the material provided an effective insulation from the hot rocket exhaust plume. To gain further insight into the complex interaction of the plume with the ablative deflector, computational fluid dynamic modeling was performed in parallel to the ablative panel testing. The results from the current study demonstrated that locally high heating occurred due to shock reflections. These localized regions of shock-induced heat flux resulted in non-uniform erosion of the ablative panels. In turn, it was observed that the non-uniform erosion exacerbated the localized shock heating causing eventual plume separation and reversed flow for long duration tests under certain conditions. Overall, the flow simulations compared very well with the available experimental data obtained during this project.

Allgood, Daniel C.↗

DOE OSTI2024

An Integrated Assessment of a G3 GMD Event on Large-Scale Power Grids: From Magnetometer Data to Geomagnetically Induced Current Analysis

Solar activities can cause geomagnetic disturbances (GMDs) that give rise to geomagnetically induced currents (GICs) which may compromise the reliability of the power system. In order to build more reliable models representing GMD interactions with the power grid, the power system’s detailed electrical model must be considered along with fluctuations in the earth’s magnetic and induced surface electric fields. Here, this study investigates the impact of incorporating spatially varying magnetic fields into surface electric field models on GMD risk metrics. A spatially independent magnetic field model and a spatially varying model are compared through simulations. To perform this analysis, the earth’s magnetic field disturbances are transformed into surface electric fields using respective one-dimensional earth conductivity models. Then, the modeling impact of these electric fields is studied using a 2,000-bus grid for Texas and a 25,000-bus grid for the northeast and mid- Atlantic regions of the United States. Simulation results reveal that the inclusion of spatially varying magnetic fields results in considerable differences in GMD risk metrics, highlighting the importance of accounting for spatial variability when assessing GMD risks in the power system.

24 POWER TRANSMISSION AND DISTRIBUTION↗

NASA NTRSDate not supplied

In-Depth Modeling and Simulation Analysis of Artemis Missions Using the Impact Probabilistic Risk Assessment Tool

BACKGROUND The Artemis campaign is a Moon exploration program with a series of six planned missions, five of which will be crewed. These five crewed missions will contain a single mission segment (space flight), or multiple mission segments involving space flight (Orion), lunar landing (LTV) and/or space habitat (Gateway). Each crewed segment faces the risk of unique medical conditions, necessitating medical sets/kits tailored to those specificities. To support and enable a data-driven and evidence-based decision-making process through out a mission’s life cycle, a software tool called IMPACT was developed. Using probabilistic risk assessment (PRA) methodologies, IMPACT (Informing Mission Planning via Analysis of Complex Tradespaces) is a novel tool built for analyzing the possibility of encountering complex medical risks during space flight, and for identifying the medical resources and capabilities needed to treat those potential at-risk medical conditions. IMPACT achieves this by performing hundreds of thousands of Monte Carlo simulations of missions to build aggregate pictures of medical risk. During an extended simulation modeling phase, IMPACT generated analytical results for medical risks, and the medical resources and capabilities to address those risks, for every segment of every crewed Artemis mission. This presentation will highlight the reliability, consistency and validity of IMPACT’s computational modeling techniques and will showcase the library of analytical outcomes generated for the Artemis missions. OVERVIEW During the early stages of IMPACT’s design, architecture and technical requirements collection, “scenarios” (use cases) - achievement goals required for acceptance testing, were identified by stakeholders. IMPACT successfully completed the scenario testing requirements and undertook an extensive operational run phase utilizing a wide range of input combinations with a goal of delivering a cohesive, trustworthy, reliable, vast, and diverse body of evidence. The intent of these modeling runs was to validate consistency in output, ensure solidity of executable operations and to streamline processes by identifying areas requiring efficiency improvements. Using the many missions of Artemis, IMPACT ran variations of operational runs to assess the output for acceptable, as well as unusual characteristics. This rigorous long-term “shakedown” analysis was implemented to help build a collective body of evidence to aid in securing a high level of confidence, reliability, and validity in the output, whether from the applicational components of IMPACT, or the entirety of the operational process. ANTICIPATED ANALYSIS AND CONCLUSION This presentation will discuss the various categories of input criteria; the comparisons in the application of these input criteria to various Artemis missions; the preparation and collection of the body of evidence, and reliability of the computational modeling techniques. This paper serves as an initial analytical overview of IMPACT’s probabilistic risk assessment (PRA) medical risk outputs covering Artemis missions and is not intended to be deemed the official medical response for the Artemis campaign.

Crew Composition↗

NASA NTRS2005

Distributed Web-Based Expert System for Launch Operations

The simulation and modeling of launch operations is based on a representation of the organization of the operations suitable to experiment of the physical, procedural, software, hardware and psychological aspects of space flight operations. The virtual test bed consists of a weather expert system to advice on the effect of weather to the launch operations. It also simulates toxic gas dispersion model, and the risk impact on human health. Since all modeling and simulation is based on the internet, it could reduce the cost of operations of launch and range safety by conducting extensive research before a particular launch. Each model has an independent decision making module to derive the best decision for launch.

Bardina, Jorge E.↗

NASA NTRS2007

Resilient Propulsion Control Research for the NASA Integrated Resilient Aircraft Control (IRAC) Project

Gas turbine engines are designed to provide sufficient safety margins to guarantee robust operation with an exceptionally long life. However, engine performance requirements may be drastically altered during abnormal flight conditions or emergency maneuvers. In some situations, the conservative design of the engine control system may not be in the best interest of overall aircraft safety; it may be advantageous to "sacrifice" the engine to "save" the aircraft. Motivated by this opportunity, the NASA Aviation Safety Program is conducting resilient propulsion research aimed at developing adaptive engine control methodologies to operate the engine beyond the normal domain for emergency operations to maximize the possibility of safely landing the damaged aircraft. Previous research studies and field incident reports show that the propulsion system can be an effective tool to help control and eventually land a damaged aircraft. Building upon the flight-proven Propulsion Controlled Aircraft (PCA) experience, this area of research will focus on how engine control systems can improve aircraft safe-landing probabilities under adverse conditions. This paper describes the proposed research topics in Engine System Requirements, Engine Modeling and Simulation, Engine Enhancement Research, Operational Risk Analysis and Modeling, and Integrated Flight and Propulsion Controller Designs that support the overall goal.

Guo, Ten-Huei↗

NASA NTRS2014

Conceptual Launch Vehicle and Spacecraft Design for Risk Assessment

One of the most challenging aspects of developing human space launch and exploration systems is minimizing and mitigating the many potential risk factors to ensure the safest possible design while also meeting the required cost, weight, and performance criteria. In order to accomplish this, effective risk analyses and trade studies are needed to identify key risk drivers, dependencies, and sensitivities as the design evolves. The Engineering Risk Assessment (ERA) team at NASA Ames Research Center (ARC) develops advanced risk analysis approaches, models, and tools to provide such meaningful risk and reliability data throughout vehicle development. The goal of the project presented in this memorandum is to design a generic launch 7 vehicle and spacecraft architecture that can be used to develop and demonstrate these new risk analysis techniques without relying on other proprietary or sensitive vehicle designs. To accomplish this, initial spacecraft and launch vehicle (LV) designs were established using historical sizing relationships for a mission delivering four crewmembers and equipment to the International Space Station (ISS). Mass-estimating relationships (MERs) were used to size the crew capsule and launch vehicle, and a combination of optimization techniques and iterative design processes were employed to determine a possible two-stage-to-orbit (TSTO) launch trajectory into a 350-kilometer orbit. Primary subsystems were also designed for the crewed capsule architecture, based on a 24-hour on-orbit mission with a 7-day contingency. Safety analysis was also performed to identify major risks to crew survivability and assess the system's overall reliability. These procedures and analyses validate that the architecture's basic design and performance are reasonable to be used for risk trade studies. While the vehicle designs presented are not intended to represent a viable architecture, they will provide a valuable initial platform for developing and demonstrating innovative risk assessment capabilities.

Launch Vehicle↗

NASA NTRS2019

Predictive Modeling for Differential Diagnosis and Mortality Risk Assessment

The prevalence of electronic health record (EHR) systems has brought prodigious biomedical informatics opportunity. Automated machine learning methods can effectively utilize such data and have become common tools for healthcare predictive modeling. Researches in medical informatics have explored the potential of deep learning and classical models in emergent care scenarios. In particular, predicting differential diagnoses for admissions have proven useful in decreasing unnecessary lab tests and improving inpatient triage decision-making. Moreover, identification of high-risk patients for in-hospital mortality is vitally important to maximize allocation of medical resources.The Medical Information Mart for Intensive Care (MIMIC-III) database, containing de-identified critical care inpatient was used in our study. This data set captures hospital patient laboratory measurements, pharmacologic prescriptions, diagnostic data and procedure event recordings. When considering adult patients and discounting admissions with ICU length of stay less than 24 hours, there were 37,787 unique admissions and 30,414 total patients. We examined the top 25 most prevalent ICD-9 group-level disease specificities in MIMIC-III using a multi-label classification model. In-hospital mortality was modeled as binary classification with 4,155 (13%) adult patients that expired, of which 3,138 (75.5%) were in the ICU setting. The metrics AUC, F1 score, sensitivity and specificity values calculated for each disease label measured prediction performance.The usage of ICD-9 group codes reduced feature dimension from 14,567 to 942 and greatly improved distribution of patient diagnostic categories. Disease temporal patterns were captured by considering the most frequently sampled 6 vital signs and 13 laboratory values. Missing data were imputed at each time-stamp. Time-series raw hourly average values were converted into 5 summary features (mean, standard deviation, number of observations, min & max values). Patient demographic variables such as age, gender, marital status and ethnicity were also factored into the modeling. Choi et al showed that contextual embedding of medical data, diagnostic and procedural codes alone can predict future diagnoses with sensitivity as high as 0.79. We utilized an embedding technique called word2vec which allowed sparse representations of medical history to be transformed into dense word vectors. The mappings captured contextual information by treating each admission as a sentence and learning the most likely neighboring words in a sliding window fashion. Binary and multi-label classification was achieved via collapse models, which do not consider temporal information, as well as recurrent neural networks with regularization, Softmax output layer activation together with categorical cross-entropy as the loss function.

US Army collaboration↗

NASA NTRSDate not supplied

Radiation Transport Models in Space: from Supernovae to Cells

Humans embarking on deep space exploration missions will encounter persistent exposure to galactic cosmic rays (GCR) - an energetic and highly complex radiation field that is unlike anything found on Earth. Exposure to such radiation fields is attributed to various adverse health effects, including cancer, cardiovascular disease, and cognitive impairment and is identified by NASA as one of the five main hazards of human spaceflight. It is therefore critical to be able to fully characterize the exposure received by humans behind shielding in space and project consequent health risks. A wide variety of computational models have been developed over the years to help meet this requirement. In this talk, an overview of the GCR environment in deep space is provided. Methods of propagating GCR fields through the shielding that protects humans in space are described along with simulation tools used to assess biological damage at the cellular scale. Finally, the NASA cancer risk model is briefly described, and risk projections are provided for various mission scenarios. Radiation transport models and solution methods pervade many aspects of this talk. For example, the GCR spectrum impinging on spacecraft is determined by solving the Fokker-Planck transport equation to propagate cosmic rays (believed to originate from supernovae) from the edge of the heliosphere to the vicinity of Earth. The Boltzmann transport equation is solved to transport this GCR spectrum through shielding and human tissue. Monte Carlo methods are used to simulate the transport of low energy electrons that dominate biological damage at the cellular scale. Progress and challenges in each of these areas will be highlighted.

Tony C. Slaba↗

DOE OSTI2026

A prototype cooling blanket for mitigating occupant overheating risk in a hot indoor environment: Modeling and assessments

Conventional ways of cooling a room or an entire house for occupant thermal comfort during summer consume a significant amount of energy and are vulnerable to overheating risk during power outages that lead to loss of cooling system operations. This study investigates a low-power cooling blanket, as a Personal Cooling System (PCS), that covers the upper human body for direct cooling during a five-day heat wave in a single-family house. A modeling framework is developed for evaluating the thermal and energy performance of the cooling blanket, which builds upon the co-simulation of three models: a house energy model, a personal thermal comfort model, and a cooling blanket model. Simulation results show that under the power outage scenario, the cooling blanket can greatly reduce the occupant heat stress with a reduction of daily hours of exceedance (discomfort hours defined as TSV>2) by up to 17.2 h (a 95.3 % improvement from the baseline power outage without the blanket). The cooling blanket, equipped with an innovative electrocaloric heat pump (COP as high as 10.1) consumes 6.31 W and can be operated by a portable battery for several days. The cooling blanket consumes only 0.28 % of the electricity of a central air-conditioning system running to provide cooling for the whole house during the five-day heatwave period. The findings justify further research of electrocaloric wearable PCS as low-power effective cooling to ensure thermal survivability of occupants during extreme indoor environments.

Electrocaloric heat pump↗

NASA NTRS2016

Modeling of the Orbital Debris Environment Risks in the Past, Present, and Future

Despite of the tireless work by space surveillance assets, much of the Earth debris environment is not easily measured or tracked. For every object that is in an orbit we can track, there are hundreds of small debris that are too small to be tracked but still large enough to damage spacecraft. In addition, even if we knew today's environment with perfect knowledge, the debris environment is dynamic and would change tomorrow. Therefore, orbital debris scientists rely on numerical modeling to understand the nature of the debris environment and its risk to space operations throughout Earth orbit and into the future. This talk will summarize the ways in which modeling complements measurements to help give us a better picture of what is occurring in Earth orbit, and helps us to better conduct current and future space operations.

Matney, Mark↗