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NASA NTRS2009

Benefits of Using a Mars Forward Strategy for Lunar Surface Systems

This paper identifies potential risk reduction, cost savings and programmatic procurement benefits of a Mars Forward Lunar Surface System architecture that provides commonality or evolutionary development paths for lunar surface system elements applicable to Mars surface systems. The objective of this paper is to identify the potential benefits for incorporating a Mars Forward development strategy into the planned Project Constellation Lunar Surface System Architecture. The benefits include cost savings, technology readiness, and design validation of systems that would be applicable to lunar and Mars surface systems. The paper presents a survey of previous lunar and Mars surface systems design concepts and provides an assessment of previous conclusions concerning those systems in light of the current Project Constellation Exploration Architectures. The operational requirements for current Project Constellation lunar and Mars surface system elements are compared and evaluated to identify the potential risk reduction strategies that build on lunar surface systems to reduce the technical and programmatic risks for Mars exploration. Risk reduction for rapidly evolving technologies is achieved through systematic evolution of technologies and components based on Moore's Law superimposed on the typical NASA systems engineering project development "V-cycle" described in NASA NPR 7120.5. Risk reduction for established or slowly evolving technologies is achieved through a process called the Mars-Ready Platform strategy in which incremental improvements lead from the initial lunar surface system components to Mars-Ready technologies. The potential programmatic benefits of the Mars Forward strategy are provided in terms of the transition from the lunar exploration campaign to the Mars exploration campaign. By utilizing a sequential combined procurement strategy for lunar and Mars exploration surface systems, the overall budget wedges for exploration systems are reduced and the costly technological development gap between the lunar and Mars programs can be eliminated. This provides a sustained level of technological competitiveness as well as maintaining a stable engineering and manufacturing capability throughout the entire duration of Project Constellation.

Mulqueen, Jack↗

NASA NTRSDate not supplied

Development and Initial Validation of HFBP-EM Short-Form Surveys

The Human Factors and Behavioral Performance Exploration Measures (HFBP-EM) suite includes self-report surveys designed to assess Behavioral Medicine (BMed) and Team risks for future exploration class missions. Survey data was collected during the Human Exploration Research Analog (HERA) Campaign 4 (C4), HERA Campaign 5 (C5), and during SIRIUS19 missions in the Russian Ground Based Experiment Complex, NEK. Crew time in spaceflight analogs and in spaceflight is typically limited. Extensive self-report surveys can be a significant burden to participants and are not operationally acceptable for spaceflight. The purpose of this project was to comprehensively assess the reliability and validity of the standard-length HFBP-EM surveys, identify acceptable short forms to administer during HERA C6, examine initial validation evidence for the proposed short form measures, and identify key measurement gaps in HFBP-EM coverage. In this presentation, we will report reliability and validity metrics of standard form data, describe the proposed new short forms, and present initial psychometric analyses supporting the use of these short forms.

S T Bell↗

DOE OSTI2024

GeoThermalCloud: Cloud Fusion of Big Data and Multi-Physics Models using Machine Learning for Discovery, Exploration, and Development of Hidden Geothermal Resources

The primary goals of this project are exploring hidden geothermal resources in the U.S.A. and designing profitable enhanced geothermal systems (EGS). Many processes and parameters control geothermal exploration and energy production from geothermal fields. Diverse datasets (e.g., geology, geochemistry, geophysics, satellite, airborne geophysics) are available to help characterize subsurface geothermal conditions. Sparse and multi-scale characteristics of these datasets prohibit properly leveraging these datasets for geothermal exploration and profitable EGS design. Recent advancements in machine learning (ML) promise to resolve these issues. The tremendous challenges and risks of geothermal exploration and production bring the demand for novel ML methods and tools that can (1) analyze large field datasets, (2) assimilate model simulations (large inputs and outputs), (3) process sparse datasets, (4) perform transfer learning (between sites with different exploratory levels), (5) extract hidden geothermal signatures in the field and simulation data, (6) label geothermal resources and processes, (7) identify high-value data acquisition targets, and (8) guide geothermal exploration and production by selecting optimal exploration, production, and drilling strategies. To address these necessities, ML-based geothermal resources exploration and enhanced geothermal systems (EGS) design tools have been developed. The exploration tool is called GeoThermalCloud and EGS design tool is called GeoDT-ML. GeoThermalCloud (https://github.com/SmartTensors/GeoThermalCloud.jl) utilizes a LANL unsupervised ML platform called SmartTensors (https://tensors.lanl.gov/) to automate data analyses and interpretations by extracting hidden signatures to identify geothermal prospects. Also, it enables the identification of critical measurements needed to identify geothermal resource signatures. Alternatively, GeoDT-ML (https://github.com/SmartTensors/GeoThermalCloud.jl/tree/master/EGS) is an ML-based alternative to GeoDT (https://github.com/GeoDesignTool/GeoDT.git), a fast, simplified multi-physics solver to evaluate EGS project designs in uncertain geologic systems. GeoDT-ML leverages recent advances in deep learning and high-performance computing. It is a faster and simpler version of GeoDT. To make this project a success, we used capabilities of LANL, PNNL, Google, Stanford, and Julia Computing. We analyzed eight datasets of the U.S.A. using GeothermalCloud and demonstrated potential highly prospective geothermal resources and identified key factors defining highly prospective sites. The first data set includes 44 locations in southwest New Mexico and 18 geological, hydrogeological, geophysical, geothermal, geochemical attributes. We defined low- and medium-temperature hydrothermal systems and discovered a new highly prospective site. The second data set analyzed 18 shallow water chemistry attributes at 14,342 locations in the Great Basin. It demarcated modestly, moderately, and highly prospective sites including key attributes for each type of prospectivity. The third data set analyzed Utah FORGE data including satellite (InSAR), geophysical (gravity, seismic), geochemical, and geothermal attributes. Here, we performed prospectivity analysis to identify future drilling locations using geological, geochemical, and geophysical attributes. Maps of temperature at depth and heat flow are constructed based on the available data. Prospectivity maps were generated, and drilling locations were proposed for future geothermal field exploration. The fourth data set analyzed 21 attributes at 120 locations in Tularosa Basin, New Mexico; data comes from past play fairway analyses in this region. ML analyses identified geothermal signatures associated with modestly, moderately, and highly hydrothermal systems. We also defined dominant attributes and spatial distribution of the geothermal signatures. The fifth, sixth, seventh, and eighth datasets include Tohatchi Springs, New Mexico, Hawaii, Brady site, Nevada, and EGS Collab, respectively. Moreover, we coupled GeothermalCloud and magnetotellurics data to pinpoint drilling locations for developing geothermal projects in the Tularosa Basin, New Mexico. GeothermalCloud found potential prospective locations for geothermal resources near White Sands Missile Range and McGregor Range at Fort Bliss. Magnetotellurics data determined the potential depth (~1800m) of geothermal prospects at McGregor Range based on apparent resistivity structures/layers in the subsurface. The McGregor Range consists of three resistivity layers and two resistivity structures. Magnetotellurics data also helps identify that the western portion of the McGregor Range has thick and low-resistivity earth materials. The low resistivity to the west is most likely for a fault system. Assuming temperature is consistent with a geothermal reservoir, the west-central part of the McGregor Range has the highest geothermal potential because of the increase in porosity and associated permeability attributed to the interpreted fault system. Also, we devised a coupling strategy between a process model and GeothermalCloud to characterize hydrogeological conditions and geothermal conditions, respectively. The process model characterizes hydrogeological and geothermal conditions on highly prospective geothermal sites provided by GeothermalCloud. We developed a physics-informed neural network (PINN) version of the Burns equation that can be easily coupled with GeothermalCloud. Furthermore, we performed an optimal design decision maximizing the economic value of an EGS power plant. This study optimized the range of well spacing between injection and production wells maximizing net present value in dollars (NPV). For this task, we used the GeoDT to simulate the Utah FORGE EGS development cycle from the initial well design to the end of production. Next, we accomplished another crucial task, which is predicting permeability of geothermal reservoirs. Predicting permeability of geothermal reservoirs is a non-trivial task because of huge computational runtime of simulation and lack of measurements. To avoid these limitations, we used easy-to-measure chemical concentrations in the subsurface as measurement data and convolutional neural network based ML model of a high-fidelity model. Next, we predicted permeability using Markov chain Monte Carlo simulation. We found that Markov chain Monte Carlo simulation predicts permeability with a high certainty if the prediction zone in the simulation area has chemical concentration data. Finally, we analyzed the DOE funded INGENIOUS and GeoDAWN projects data. For discovering hidden geothermal systems in the Great Basin, the INGENIOUS project accumulated old data, collected new data, and released them in 2022. The dataset includes a total of 24 geological, geophysical, and geochemical attributes. Data resolution and scale significantly vary prohibiting an appropriate usage. To avoid such limitations, we brought all data in the same resolution and scale by applying the inverse distance weighting interpolation technique for predicting data in unsampled locations. Subsequently, we analyzed LiDAR data of the GeoDAWN project. We received data in tiles format. The DOE’s overarching goal is to use ML on LiDAR data for finding favorable geological structures (e.g., step up faults in Brady, Nevada). To serve the purpose, we need to label favorable geologic structures that correspond to LiDAR data. We wrote an algorithm to label the LiDAR data with the favorable geologic structures.

15 GEOTHERMAL ENERGY↗

NASA NTRSDate not supplied

Teams in Space: Knowledge Gained, but More to Explore

NASA’s Human Research Program oversees the Team Risk (i.e., Risk of Performance and Behavioral Health Decrements due to Inadequate Cooperation, Coordination, Communication and Psychosocial Adaptation within a Team). Research in this area informs all aspects of an astronaut’s career, from hiring to training to mission support, and works to address new challenges related to lunar and Mars missions. NASA’s astronaut selection process creates an astronaut corps of highly qualified, team-oriented individuals, which allows mission planners much flexibility in composing small crews for specific missions. These crews are further developed and supported through extensive training, including team skills training, and countermeasures available to the crew throughout the mission. However, in the high consequence environment of long-duration missions, team composition is complex and is not a one-time concern to be addressed pre-mission. Team factors such as team cohesion, dyadic relationships, and shared team cognition are likely to change dynamically in response to each interaction and event experienced by the individuals and the team as a whole. Thus, monitoring and optimizing team composition at a more micro level (e.g., per task) is one way to support team functioning and performance. Spaceflight teams research also includes the multi-team system of Mission Control and coordination between space-to-ground, adding another avenue in which risk might be introduced, particularly under exploration missions that experience significant communication delays. Spaceflight teams research has recently experienced a concentrated flurry of analog research over the past decade, shedding light on the many unique challenges and potential solutions to mitigate the team risk in long-duration exploration missions. However, questions still remain about how to, for example, create unobtrusive operational measures and how to advance interdisciplinary teams research and countermeasure development. We present an overview of the challenges facing teams in space, our current knowledge, and the next steps for research and spaceflight operations.

Lauren Blackwell Landon↗

NASA NTRS2009

Space Radiation and Exploration - Information for the Augustine Committee Review

Space radiation presents significant health risks including mortality for Exploration missions: a) Galactic cosmic ray (GCR) heavy ions are distinct from radiation that occurs on Earth leading to different biological impacts. b) Large uncertainties in GCR risk projections impact ability to design and assess mitigation approaches and select crew. c) Solar Proton Events (SPEs) require new operational and shielding approaches and new biological data on risks. Risk estimates are changing as new scientific knowledge is gained: a) Research on biological effects of space radiation show qualitative and quantitative differences with X- or gamma-rays. b) Expert recommendations and regulatory policy are changing. c) New knowledge leads to changes in estimates for the number of days in space to stay below Permissible Exposure Limits (PELS).

Cucinotta, Francis↗

NASA NTRSDate not supplied

IMPACT - Information for the Development of Human Health and Performance Systems

IMPACT is a suite of computational and systems engineering tools. Currently being developed for NASA Exploration Medical Capabilities (ExMC) and could be extended to other Human Research Program (HRP) elements. The purpose is to provide a data-driven means to inform human health and performance risk mitigation during exploration missions considering resource constraints in the medical system. IMPACT enables systematic trade studies to evaluate options. IMPACT uses Probabilistic Risk Assessment (PRA) as a systematic methodology to evaluate risks. IMPACT is currently under development to inform decision-makers the risks involved with trade-options that have likelihoods and consequences backed by scientific research in a medical evidence library. IMPACT supports multi-segment analysis to determine probabilities and risks in different mission segments. There are currently 122 medical conditions and 900 resources in the IMPACT Medical Database. IMPACT modeling is using mission segments and multiple vehicles for the NASA Artemis campaign and could support future complex missions in deep space.

IMPACT PRA↗

NASA NTRS2024

NASA's Human Research Program: Evolving Collaborations to Enable the Future of Human Spaceflight

Since its formation in 2007, the NASA Human Research Program’s (HRP) mission has been to reduce human health and performance risks for spaceflight exploration missions. The program has achieved this mission primarily through work in ground analogs and on the International Space Station. Over the last three years, NASA overall has seen transformative changes with the flight of Artemis I, formation of the Commercial LEO Destinations Program, commercial flights to the ISS, and new International Partners participating in human spaceflight. NASA’s HRP has embraced these new opportunities and is collaborating on all these fronts to collect biomedical research data. Artemis I marked the arrival of NASA’s new human spaceflight exploration missions. NASA has developed a Moon-to-Mars Architecture to map out how it will use the moon to de-risk and enable Mars missions. NASA’s HRP is a critical component to develop and deliver research and technologies for future Artemis Crew Health and Performance (CHP) Systems. The program is working closely with NASA’s Moon-to-Mars Office to ensure CHP deliverables are ready to demonstrate on the moon, as we also look toward Mars, and is developing the partnership strategies required to support these deliverables. Commercial space flights, both free flyer and suborbital missions and private astronaut missions to the ISS, are providing broader opportunities and subjects to characterize the space-induced changes to the human system and to test countermeasures. To better use these opportunities to achieve its mission, HRP has been working to understand the commercial spaceflight companies’ needs and then partner with them on aspects of mutual interest. In addition, NASA HRP continues to engage in long-standing relationships with its international partners through the International Space Life Sciences Working Group (ISLSWG) and other joint international groups. The Program is now also interested in sharing its knowledge and ability to collaborate on projects of mutual interest with new countries developing capabilities for human spaceflight. The next 10 years will shape how humanity partners on exploration missions to Mars. NASA’s HRP is committed to enabling and developing collaborative strategies with commercial and international partners to keep humans safe and productive as we explore longer and further into space.

Jancy McPhee↗

NASA NTRS2015

Risk Informed Philosophy: Using What We Fear to Lose to Guide Us to Success

When an organization sets out on a new effort, program, or project, one of the first steps undertaken is to understand the related requirements. Most often, these requirements come in the form of standards, directives, or other organizational processes, and are derived to meet a broad range of efforts, programs, and projects. The net result is that organizations or teams are forced to start with a maximum set of requirements and expend time and energy tailoring the set of requirements down to what is more appropriate for the effort, program, or project at hand. This presentation will present an alternate method for the application of requirements or best practices that is based upon the actual risks to the safety, performance, or success of the effort. This additive route for applying best practices and requirements also encourages an early exploration of the risks, thus yielding a better understanding of where resources should be applied. This presentation also extends this concept of risk-based application of best practices and requirements to the selection of organization-wide improvement or standardization efforts, such as Lean, Six Sigma, and Quality Management Systems.

Darpel, Scott↗

NASA NTRS2002

Software risk estimation and management techniques at JPL

In this talk we will discuss how uncertainty has been incorporated into the JPL software model, probabilistic-based estimates, and how risk is addressed, how cost risk is currently being explored via a variety of approaches, from traditional risk lists, to detailed WBS-based risk estimates to the Defect Detection and Prevention (DDP) tool.

software risk↗

NASA NTRSDate not supplied

Validation of Fitness for Duty Standards Using Pre- and Post-Flight Capsule Egress and Suited Functional Performance Tasks in Simulated Reduced Gravity

The transition between gravity environments will involve one of the most complex, high-risk phases of exploration missions. The reduced functional capacity caused by physiological deconditioning adaptations in microgravity coupled with the stressors of re-entry into partial gravity environments will increase risks to crew, even with rigorous adherence to inflight countermeasures. Specifically, two high-risk scenarios may be required to be performed soon after gravity transitions: 1) nominal and/or emergency unassisted capsule egress task after return to Earth, and 2) planetary extravehicular activity (EVA) soon after landing on Mars or the Moon. Quantification of crewmember’s functional performance after long-duration spaceflight is necessary to inform concepts of operations for future exploration missions. The overarching aim of this study is to quantify post-landing functional performance with deconditioning after long-duration ISS missions. This study is broken down into two phases. Phase 1 includes a pilot study to assess the overall feasibility and demonstrate the capability to perform mission-like tasks shortly after landing. Phase 2, the Egress Fitness study, which is part of the Complement of Integrated Protocols for Human Exploration Research (CIPHER), uses a task-based approach to characterize functional performance in long-duration ISS crewmembers before flight and shortly after return to Earth. The pilot and full Egress Fitness study includes pre-flight and post-flight testing of simulated emergency egress out of a functional capsule mockup and a Mars gravity EVA simulation at the Active Response Gravity Offload System (ARGOS) facility. The EVA simulation tasks include suit donning, hatch egress, ladder descent, task board cable operations, baggage transfer over sand/rocky regolith, alignment with a rear entry port, and suit egress. The post-flight simulated capsule egress test occurs 1–4 h after landing and the planetary EVA simulation occurs 18–36 h after landing. The full CIPHER Egress Fitness study has additional pre-flight sessions, longer EVA tasks that include traverse and geology sampling, and post-flight sessions on R+1, 4, and 8 to characterize the timeframe of recovery. The Pilot Egress Fitness study has completed baseline and post-flight testing on four crewmembers. All subjects were able to complete the post-flight simulated planetary EVA; three subjects were able to complete the postflight capsule egress simulation. CIPHER study data collection is ongoing. This study will quantify post-landing functional performance in operationally relevant simulations to help inform future planetary concepts of operations shortly after landing.

egress↗

NASA NTRSDate not supplied

CIPHER: Egress Fitness

The transition between gravity environments will involve one of the most complex, high-risk phases of exploration missions. The reduced functional capacity caused by physiological deconditioning adaptations in microgravity coupled with the stressors of re-entry into partial gravity environments will increase risks to crew, even with rigorous adherence to inflight countermeasures. Specifically, two high-risk scenarios may be required to be performed soon after gravity transitions: 1) nominal and/or emergency unassisted capsule egress task after return to Earth, and 2) planetary extravehicular activity (EVA) soon after landing on Mars or the Moon. Quantification of crewmember’s functional performance after long-duration spaceflight is necessary to inform concepts of operations for future exploration missions. The overarching aim of this study is to quantify post-landing functional performance with deconditioning after long-duration ISS missions. This study is broken down into two phases. Phase 1 includes a pilot study to assess the overall feasibility and demonstrate the capability to perform mission-like tasks shortly after landing. Phase 2, the Egress Fitness study, which is part of the Complement of Integrated Protocols for Human Exploration Research (CIPHER), uses a task-based approach to characterize functional performance in long-duration ISS crewmembers before flight and shortly after return to Earth. The pilot and full Egress Fitness study includes pre-flight and post-flight testing of simulated emergency egress out of a functional capsule mockup and a Mars gravity EVA simulation at the Active Response Gravity Offload System (ARGOS) facility. The EVA simulation tasks include suit donning, hatch egress, ladder descent, task board cable operations, baggage transfer over sand/rocky regolith, alignment with a rear entry port, and suit egress. The post-flight simulated capsule egress test occurs 1–4 h after landing and the planetary EVA simulation occurs 18–36 h after landing. The full CIPHER Egress Fitness study has additional pre-flight sessions, longer EVA tasks that include traverse and geology sampling, and post-flight sessions on R+1, 4, and 8 to characterize the timeframe of recovery. Pilot Egress Fitness has completed baseline and post-flight testing on four crewmembers. That study remains open. Originally this was to cover the Boeing CFT mission, but now also includes private astronauts on commercial spaceflights. CIPHER study data collection is ongoing with 2 subjects completed and 4 additional subjects consented. This study will quantify post-landing functional performance in operationally relevant simulations to help inform fitness for duty standards and future planetary concepts of operations shortly after landing.

Jason Norcross↗

NASA NTRS2016

Exploration Laboratory Analysis

The Exploration Laboratory Analysis (ELA) project supports the Exploration Medical Capability (ExMC) risk to minimize or reduce the risk of adverse health outcomes and decrements in performance due to in-flight medical capabilities on human exploration missions. To mitigate this risk, the availability of inflight laboratory analysis instrumentation has been identified as an essential capability for manned exploration missions. Since a single, compact space-ready laboratory analysis capability to perform all exploration clinical measurements is not commercially available, the ELA project objective is to demonstrate the feasibility of emerging operational and analytical capability as a biomedical diagnostics precursor to long duration manned exploration missions. The initial step towards ground and flight demonstrations in fiscal year (FY) 2015 was the downselection of platform technologies for demonstrations in the space environment. The technologies selected included two Small Business Innovation Research (SBIR) performers: DNA Medicine Institute's rHEALTH X and Intelligent Optical System's lateral flow assays combined with Holomic's smartphone analyzer. The selection of these technologies were based on their compact size, breadth of analytical capability and favorable ability to process fluids in a space environment, among several factors. These two technologies will be advanced to meet ground and flight demonstration success criteria and requirements. The technology demonstrations and metrics for success will be finalized in FY16. Also, the downselected performers will continue the technology development phase towards meeting prototype deliverables in either late 2016 or 2017.

In-Flight laboratory↗

NASA NTRS2016

Exploration Laboratory Analysis

The Exploration Laboratory Analysis (ELA) project supports the Exploration Medical Capability (ExMC) risk to minimize or reduce the risk of adverse health outcomes and decrements in performance due to in-flight medical capabilities on human exploration missions. To mitigate this risk, the availability of inflight laboratory analysis instrumentation has been identified as an essential capability for manned exploration missions. Since a single, compact space-ready laboratory analysis capability to perform all exploration clinical measurements is not commercially available, the ELA project objective is to demonstrate the feasibility of emerging operational and analytical capability as a biomedical diagnostics precursor to long duration manned exploration missions. The initial step towards ground and flight demonstrations in fiscal year (FY) 2015 was the down selection of platform technologies for demonstrations in the space environment. The technologies selected included two Small Business Innovation Research (SBIR) performers: DNA Medicine Institutes rHEALTH X and Intelligent Optical Systems later flow assays combined with Holomics smartphone analyzer. The selection of these technologies were based on their compact size, breadth of analytical capability and favorable ability to process fluids in a space environment, among several factors. These two technologies will be advanced to meet ground and flight demonstration success criteria and requirements that will be finalized in FY16. Also, the down selected performers will continue the technology development phase towards meeting prototype deliverables in either late 2016 or 2017.

Laboratory analysis↗

NASA NTRS2015

Coordination of International Risk-Reduction Investigations by the Multilateral Human Research Panel for Exploration

Effective use of the unique capabilities of the International Space Station (ISS) for risk reduction on future deep space missions involves preliminary work in analog environments to identify and evaluate the most promising techniques, interventions and treatments. This entails a consolidated multinational approach to biomedical research both on ISS and in ground analogs. The Multilateral Human Research Panel for Exploration (MHRPE) was chartered by the five ISS partners to recommend the best combination of partner investigations on ISS for risk reduction in the relatively short time available for ISS utilization. MHRPE will also make recommendations to funding agencies for appropriate preparatory analog work. In 2011, NASA's Human Research Program (HRP) and the Institute of Biomedical Problems (IBMP) of the Russian Academy of Science, acting for MHRPE, developed a joint US-Russian biomedical program for the 2015 one-year ISS mission (1YM) of American and Russian crewmembers. This was to evaluate the possibilities for multilateral research on ISS. An overlapping list of 16 HRP, 9 IBMP, 3 Japanese, 3 European and 1 Canadian investigations were selected to address risk-reduction goals in 7 categories: Functional Performance, Behavioral Health, Visual Impairment, Metabolism, Physical Capacity, Microbial and Human Factors. MHRPE intends to build on this bilateral foundation to recommend more fully-integrated multilateral investigations on future ISS missions commencing after the 1YM. MHRPE has also endorsed an on-going program of coordinated research on 6-month, one-year and 6-week missions ISS expeditions that is now under consideration by ISS managers. Preparatory work for these missions will require coordinated and collaborative campaigns especially in the psychological and psychosocial areas using analog isolation facilities in Houston, Köln and Moscow, and possibly elsewhere. The multilateral Human Analogs research working group (HANA) is the focal point of those planning discussions, with MHRPE coordinating between the national programs and then supporting implementation on ISS. Experience gained during preparations for the 1YM has identified improvements in both American and Russian processes to enable well-integrated investigations on all subsequent ISS expeditions. Among those is that the greatest efficiency is to be gained with investigations that are fully integrated from their conception, with co-principal investigators, a consolidated proposal and integrated plans for crewmember time and other flight-related resources. Analog investigations preceding future ISS expeditions will employ these lessons in efficiency to evaluate the techniques and tools to be validated aboard ISS. In this way, the resources and capabilities of ISS can be applied most efficiently to solving the problems facing astronauts of all nations in missions deep into the solar system.

Charles, John B.↗

NASA NTRS2017

Medical Data Architecture Project Status

Exploration medical system↗

NASA NTRS2017

Medical Data Architecture Project Status

Data management↗

NASA NTRS2002

Exploration of the Mars Radiation Environment Using MARIE

One of three science instruments onboard Mars Odyssey is the Mars Radiation Environment Experiment (MARIE), which is described here. MARIE is an energetic particle spectrometer which will characterize the space radiation environment of Mars and determine its risk to human exploration. Additional information is contained in the original extended abstract.

Cucinotta, F.↗

NASA NTRS2020

Medical Data Architecture Platform and Recommended Requirements for a Medical Data System for Exploration Missions

The Medical Data Architecture (MDA) project supports the Exploration Medical Capability (ExMC) risk to minimize or reduce the risk of adverse health outcomes and decrements in performance due to in-flight medical capabilities on human exploration missions. To mitigate this risk, the ExMC MDA project addresses the technical limitations identified in ExMC Gap Med 07: We do not have the capability to comprehensively process medically- relevant information to support medical operations during exploration missions. This gap identifies that the current in-flight medical data management includes a combination of data collection and distribution methods that are minimally integrated with on-board medical devices and systems. Furthermore, there are a variety of data sources and methods of data collection. For an exploration mission, the seamless management of such data will enable a more medically autonomous crew than the current paradigm of medical data management on the International Space Station. ExMC has recognized that in order to make informed decisions about a medical data architecture framework, current methods for medical data management must not only be understood, but an architecture must also be identified that provides the crew with actionable insight to medical conditions. This medical data architecture will provide the necessary functionality to address the challenges of executing a self-contained medical system that approaches crew health care delivery without assistance from ground support. Hence, the products derived from the third MDA prototype development will directly inform exploration medical system requirements for Level of Care IV in Gateway missions. In fiscal year 2019, the MDA project developed Test Bed 3, the third iteration in a series of prototypes, that featured integrations with cognition tool data, ultrasound image analytics and core Flight Software (cFS). Maintaining a layered architecture design, the framework implemented a plug-in, modular approach in the integration of these external data sources. An early version of MDA Test Bed 3 software was deployed and operated in a simulated analog environment that was part of the Next Space Technologies for Exploration Partnerships (NextSTEP) Gateway tests of multiple habitat prototypes. In addition, the MDA team participated in the Gateway Test and Verification Demonstration, where the MDA cFS applications was integrated with Gateway-in-a-Box software to send and receive medically relevant data over a simulated vehicle network. This software demonstration was given to ExMC and Gateway Program stakeholders at the NASA Johnson Space Center Integrated Power, Avionics and Software (iPAS) facility. Also, the integrated prototypes served as a vehicle to provide Level 5 requirements for the Crew Health and Performance Habitat Data System for Gateway Missions (Medical Level of Care IV). In the upcoming fiscal year, the MDA project will continue to provide systems engineering and vertical prototypes to refine requirements for medical Level of Care IV and inform requirements for Level of Care V.

Krihak, M.↗