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All sourcesNASA NTRSDOE OSTI
NASA NTRSDate not supplied

PersEIDS: A Biomedical Decision Support System for Extravehicular Operations Under Significant Communication Latency

Humanity hopes to perform extravehicular activities (EVAs) on the surface of Mars; however, several technical and operational challenges must first be overcome. Foremost among these challenges is managing a significant communication latency between Earth and Mars. Current and historical paradigms of EVA operations have required near-real-time communication between the crewmember(s) and Earth-based mission control. Nextgeneration operational paradigms for supporting deep space exploration will necessitate a distributed decision authority system, including delayed Earth-based mission control, the onplanet extravehicular crewmember(s), and intermediate mission support from intravehicular (IV) crewmember(s) within real-time communication range. This latter group is of particular interest: they must provide operations support without the plentiful resources available to mission control on Earth. Thus, NASA is developing the Personalized EVA Informatics and Decision Support (PersEIDS) software platform. PersEIDS is designed to bolster operator situational awareness and offload operator workload by automatically tracking and projecting consumables usage over an EVA timeline, providing real-time probabilistic safety assessments and recommending alternative EVA timeline(s) when the active timeline is not expected to be completed under consumables limits. The PersEIDS concept of operations, use cases, and models will be presented. A limited version of PersEIDS was demonstrated during a three-day-long study where each day a roughly four-hour-long simulated Martian EVA was performed in virtual reality at the NASA Johnson Space Center. The first day was a control trial without PersEIDS support; the second and third days represented different levels of decision support provided by PersEIDS to the IV crewmember acting as mission control. With PersEIDS support, the IV crewmember was able to manage the mission to completion faster and with more remaining consumables; however, additional testing is required to understand confounding factors, e.g., training bias.

Mars↗
NASA NTRSDate not supplied

Kinematic Sensors Evaluation for Spaceflight Exercise Data Collections

INTRODUCTION: On the International Space Station (ISS), exercise feedback from astronauts is very important to diagnose and mitigate any form-related injuries and ensure efficacious exercise prescriptions and systems. Going forward, exploration exercise efforts seek to gain further quantitative data of human and system performance. Currently, methods of collecting in-flight exercise data on the ISS are limited to marker-based motion capture (MoCap) where astronauts must wear reflective markers over their clothes and specialized cameras are used. The main objective of this work was to investigate the following alternative tracking options: markerless video-based MoCap and inertial measurement units (IMUs). These were compared against traditional marker-based MoCap to evaluate kinematic accuracy and inform feasible methods for future exercise data collections on the ISS, especially in support of future Vibration Isolation and Stabilization (VIS) system development. METHODS: Three test subjects performed a variety of flight-like resistance and aerobic exercises using the Miniature Exercise Device (MED-2), Concept-2 rowing ergometer, barbell mockup, bench (e.g., for bench press, hip thruster, and cycling), and a custom structure for dips. These were intended also to represent exercises which could be performed on the multi-modality European Enhanced Exploration Exercise Device (E4D) [1]. The marker-based MoCap data, collected through a 16-camera OptiTrack MoCap system, was regarded as the gold standard to compare the data against. Passive markers were affixed to each subject according to a modified full body Plug-in Gait marker set [2] with 46 total markers. The markerless MoCap data was collected using two GoPro Hero7 cameras and one GoPro Hero11 camera. For the IMU data, a full body set of 17 Xsens DOTs were placed on the subject: 10 upper body and 7 lower body IMUs. Biomechanical modeling and evaluation was conducted through OpenSim [3] (MoCap), OpenSense [4] (IMU), OpenCap [5] (markerless), ENABLE [6] (markerless), and other modeling software. Secondary objectives included comparing the volume of equipment, reducing mass and crew set-up time. RESULTS AND DISCUSSION: While there were issues with initial processing for the IMUs and markerless MoCap, the results aided in the understanding of each sensor, developing end-to-end processes, and identifying future needs. Some observed concerns with the markerless MoCap approaches included being cognizant of a cluttered background, number of people in field of view, camera number and placement. Some challenges with the IMUs included possible sliding, early deactivation possibly due to exercise pose, and large quantity sensor synchronization. Overall, the markerless MoCap option may be the preferred method of data collection and processing as it provides a solution for certain IMU shortcomings and may be least in equipment volume, upmass, and crew setup time. CONCLUSIONS: While this work was mainly focused on ISS data collection, these sensor data along with continued evaluation and development efforts will help to establish best methods for exercise data collection on Gateway, for other Artemis missions, and beyond. Details on the latest end-to-end processing of the data and results will be presented, along with lessons learned and recommended sensor selection and methods.

S. Faragalla↗
NASA NTRSDate not supplied

Architectural Framework for Conceptualizing Exploration Class Medical Operations

Currently, discrete projects within NASA’s Human Research Program (HRP) take aim at providing future exploration missions with the capabilities necessary to operate within a progressively Earth-independent operative environment. Realizing an entire ecosystem that can accomplish these goals requires a clear visualization on how each project contributes to the overall objectives of Human Health and Performance (HH&P) in that context. The Exploration Medical Capability (ExMC) Element has developed an architectural framework for exploration class medical operations by utilizing a systems engineering approach using model-based systems engineering (MBSE). This model, a System of Systems Architecture (SoSA), captures a means of integrating various independent but related efforts into a comprehensive view associated with HRP’s goal of providing progressively Earth-Independent Medical Operations (EIMO). This level of visibility is realized by identifying interfaces between development efforts and existing programs that contribute to the overall mission of EIMO even if those extend past the traditional boundary of HRP. Potential interfaces that are considered important when constructing an architecture include program/project Needs, Goals, and Objectives (NGOs), capabilities, envisioned use cases/scenarios, and system/subsystem structure. This presentation will focus on the processes that were used to generate the SoSA along with a means to realize its utility amongst other MBSE products from ExMC. Evaluation of the best architecture moving forward can then be achieved that promotes cohesion between various functional areas of HH&P. Additionally, the SoSA is developed with a long-term vision for the dynamic integration of novel technological developments that may be implemented in the future. The SoSA is intended to enable Stakeholders the ability to view the broader interconnections that exist and begin to create avenues of communication between various efforts. The benefits of a SoSA provide an essential step towards addressing the unique challenges of attaining the goals of broader exploration class medical missions of the future.

Systems engineering↗
NASA NTRSDate not supplied

The Human Research Program Grant Lifecycle & Data Integration Schedule: Infographic

The Human Research Program (HRP) Grant Lifecycle process can be described using information from several government authoritative sources with overlapping generalizations. It is the responsibility of the HRP Program Planning & Control (PP&C) Office and the Data Management Integration Office (DMIO)to interpret this information into a cohesive process that can be communicated to the human research organization. PP&C and DMIO have been exploring training opportunities to facilitate understanding through the form of infographics. This communication tool combines eye-catching visuals and text making complex information and data more digestible and shareable. The infographic poster tells a short story about a federally awarded grant and is intended to help both the new and experienced HRP workforce understand the timeline for a research procurement and where their specific tasks fall within the 4 phases of the grant lifecycle. The Pre-Award, Award, Post-Award, and Closeout phases are overlayed with business swimlanes so HRP stakeholders can see where they fit into the timeline rather than working in an isolated part. This includes the Chief Scientist Office (CSO), PP&C, the Data Management Integration Office (DMIO), the Principal Investigator (PI), the Element stakeholders, the LSDA Archivists, and the Research & Operations Integration (ROI) team along with the stakeholders in the Human Health and Performance Directorate. Additionally, the poster introduces (1) the HRP Data Integration Schedule identified in the HRP Data Management Plan HRP-48047, Table 8-2 and (2) a Smartsheet Solution to automate the grants tracking business process. Emphasis is given to the Data Integration Schedule which is the basis for the milestone tasks that are to be completed during the Post-Award phase in the grant lifecycle. The poster is also an opportunity to present the Smartsheet Solution, a software collaboration and work management tool used to assign tasks and track project progress. This PP&C FY24 effort will facilitate an end-to-end solution to track grants and provide insight to the health of HRP grant research procurements using metrics, reports, and dashboards.

J Peace↗
NASA NTRS2023

Earth Independent Medical Operations (EIMO) Training Technical Interchange Meeting, 26th October 2023: Background and Summary of Discussion

On 26th October 2023, ExMC convened a panel of Subject Matter Experts (SMEs) from NASA, broadly representing Headquarters, the Human Research Program, Medical Operations, the Human Health and Performance Directorate at JSC, the Health and Medical Technical Authority, the Flight Operations Directorate, and representation from other Centers including: Ames Research Center (ARC), and Glenn Research Center (GRC). Representatives from the Canadian Space Agency also participated in this TIM. In addition, SMEs from industry included representation from the following entities: Axiom Space, Space Exploration Technologies Corporation, Level Ex, Shiny Box Interactive. Additional SMEs from academia included: University of Houston, Touro University, Weill Cornell Medical College and the Translational Research Institute for Space Health at Baylor College of Medicine. This group of stakeholders discussed the training issues related to facilitating EIMO. Sub-topics for this discussion included the following: - Pre-launch medical curriculum development - Ground-based training on medical hardware - Dental health - Behavioral health - Telemedicine - Just-in-time training - Simulation-based training (extended reality)

CMO Training↗
NASA NTRS2024

Kinematic Sensors Evaluation for Spaceflight Exercise Data Collections

INTRODUCTION: On the International Space Station (ISS), exercise feedback from astronauts is very important to diagnose and mitigate any form-related injuries and ensure efficacious exercise prescriptions and systems. Going forward, exploration exercise efforts seek to gain further quantitative data of human and system performance. Currently, methods of collecting in-flight exercise data on the ISS are limited to marker-based motion capture (MoCap) where astronauts must wear reflective markers over their clothes and specialized cameras are used. The main objective of this work was to investigate the following alternative tracking options: markerless video-based MoCap and inertial measurement units (IMUs). These were compared against traditional marker-based MoCap to evaluate kinematic accuracy and inform feasible methods for future exercise data collections on the ISS, especially in support of future Vibration Isolation and Stabilization (VIS) system development. METHODS: Three test subjects performed a variety of flight-like resistance and aerobic exercises using the Miniature Exercise Device (MED-2), Concept-2 rowing ergometer, barbell mockup, bench (e.g., for bench press, hip thruster, and cycling), and a custom structure for dips. These were intended also to represent exercises which could be performed on the multi-modality European Enhanced Exploration Exercise Device (E4D) [1]. The marker-based MoCap data, collected through a 16-camera OptiTrack MoCap system, was regarded as the gold standard to compare the data against. Passive markers were affixed to each subject according to a modified full body Plug-in Gait marker set [2] with 46 total markers. The markerless MoCap data was collected using two GoPro Hero7 cameras and one GoPro Hero11 camera. For the IMU data, a full body set of 17 Xsens DOTs were placed on the subject: 10 upper body and 7 lower body IMUs. Biomechanical modeling and evaluation was conducted through OpenSim [3] (MoCap), OpenSense [4] (IMU), OpenCap [5] (markerless), ENABLE [6] (markerless), and other modeling software. Secondary objectives included comparing the volume of equipment, reducing mass and crew set-up time. RESULTS AND DISCUSSION: While there were issues with initial processing for the IMUs and markerless MoCap, the results aided in the understanding of each sensor, developing end-to-end processes, and identifying future needs. Some observed concerns with the markerless MoCap approaches included being cognizant of a cluttered background, number of people in field of view, camera number and placement. Some challenges with the IMUs included possible sliding, early deactivation possibly due to exercise pose, and large quantity sensor synchronization. Overall, the markerless MoCap option may be the preferred method of data collection and processing as it provides a solution for certain IMU shortcomings and may be least in equipment volume, upmass, and crew setup time. CONCLUSIONS: While this work was mainly focused on ISS data collection, these sensor data along with continued evaluation and development efforts will help to establish best methods for exercise data collection on Gateway, for other Artemis missions, and beyond. Details on the latest end-to-end processing of the data and results will be presented, along with lessons learned and recommended sensor selection and methods.

S Faragalla↗
NASA NTRS2024

Architectural Framework for Conceptualizing Exploration Class Medical Operations

Currently, discrete projects within NASA’s Human Research Program (HRP) take aim at providing future exploration missions with the capabilities necessary to operate within a progressively Earth-independent operative environment. Realizing an entire ecosystem that can accomplish these goals requires a clear visualization on how each project contributes to the overall objectives of Human Health and Performance (HH&P) in that context. The Exploration Medical Capability (ExMC) Element has developed an architectural framework for exploration class medical operations by utilizing a systems engineering approach using model-based systems engineering (MBSE). This model, a System of Systems Architecture (SoSA), captures a means of integrating various independent but related efforts into a comprehensive view associated with HRP’s goal of providing progressively Earth-Independent Medical Operations (EIMO). This level of visibility is realized by identifying interfaces between development efforts and existing programs that contribute to the overall mission of EIMO even if those extend past the traditional boundary of HRP. Potential interfaces that are considered important when constructing an architecture include program/project Needs, Goals, and Objectives (NGOs), capabilities, envisioned use cases/scenarios, and system/subsystem structure. This presentation will focus on the processes that were used to generate the SoSA along with a means to realize its utility amongst other MBSE products from ExMC. Evaluation of the best architecture moving forward can then be achieved that promotes cohesion between various functional areas of HH&P. Additionally, the SoSA is developed with a long-term vision for the dynamic integration of novel technological developments that may be implemented in the future. The SoSA is intended to enable Stakeholders the ability to view the broader interconnections that exist and begin to create avenues of communication between various efforts. The benefits of a SoSA provide an essential step towards addressing the unique challenges of attaining the goals of broader exploration class medical missions of the future.

Systems engineering↗
NASA NTRSDate not supplied

ExMC Digital Engineering

Future missions beyond Artemis II will become increasingly complex as multiple vehicles (e.g., Gateway, Human Landing System (HLS), and Extravehicular Activity and Human Surface Mobility Program (EHP)), each having their own Program requirements and other associated documentation, which will need to be integrated into a single mission. Currently, the Human Health and Performance Directorate (HHPD)Program Support Teams mostly use documents to manage, perform, and archive their analyses. Identifying an opportunity for efficiency, ExMC demonstrated the ability to utilize MagicDraw, a Model-Based Systems Engineering (MBSE) tool, as a requirements database with traceability, dependencies, and relationships in one place. Rather than existing in documents, emails, and historical knowledge, ExMC pursued a Digital Engineering (DE) effort in coordination with HHPD by combining MBSE tools with other digital platforms to manage and develop user-defined databases and interfaces. This DE approach is aimed to simplify processes and reduce risk through the unification of requirements into a centralized digital network, improving collaboration, decision-making, and transparency compared to isolated documents and knowledge. However, manipulating data views and content in MagicDraw requires a steep learning curve not needed by all users and even the user-friendly web view comes with downsides due to the static views. To provide a more dynamic user interface, ExMC investigated the use of Microsoft Power Platform which does not require as steep of a learning curve to become proficient. This introduces analytics to the DE infrastructure, offering customizable and dynamic data dashboards. ExMC continues developing these dashboards and tailoring the DE infrastructure in alignment with HHPD workforce needs.

M Krihak↗
DOE OSTI2011

CHAMPION: Intelligent Hierarchical Reasoning Agents for Enhanced Decision Support

We describe the design and development of an advanced reasoning framework employing semantic technologies, organized within a hierarchy of computational reasoning agents that interpret domain specific information. Designed based on an inspirational metaphor of the pattern recognition functions performed by the human neocortex, the CHAMPION reasoning framework represents a new computational modeling approach that derives invariant knowledge representations through memory-prediction belief propagation processes that are driven by formal ontological language specification and semantic technologies. The CHAMPION framework shows promise for enhancing complex decision making in diverse problem domains including cyber security, nonproliferation and energy consumption analysis.

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2012

Occupancy Simulation in Three Residential Research Houses

Three houses of similar floor plan are being compared for energy consumption. The first house is a typical builder house of 2400 ft2 (223 m2) in east Tennessee. The second house contains retrofits available to a home owner such as energy efficient appliances, windows and HVAC, as well as an insulated attic which contains HVAC duct work. The third house was built using optimum-value framing construction with photovoltaic modules and solar water heating. To consume energy researchers have set up appliances, lights, and plug loads to turn on and off automatically according to a schedule based on the Building America Research Benchmark Definition. As energy efficiency continues to be a focus for protecting the environment and conserving resources, experiments involving whole house energy consumption will be done. In these cases it is important to understand how to simulate occupancy so that data represents only house performance and not human behavior. The process for achieving automated occupancy simulation will be discussed. Data comparing the energy use of each house will be presented and it will be shown that the third house used 66% less and the second house used 36% less energy than the control house in 2010. The authors will discuss how energy prudent living habits can further reduce energy use in the third house by 23% over the average American family living in the same house.

Boudreaux, Philip R↗
DOE OSTI2014

Integrated fiducial sample mount and software for correlated microscopy

A novel design sample mount with integrated fiducials and software for assisting operators in easily and efficiently locating points of interest established in previous analytical sessions is described. The sample holder and software were evaluated with experiments to demonstrate the utility and ease of finding the same points of interest in two different microscopy instruments. Also, numerical analysis of expected errors in determining the same position with errors unbiased by a human operator was performed. Based on the results, issues related to acquiring reproducibility and best practices for using the sample mount and software were identified. Overall, the sample mount methodology allows data to be efficiently and easily collected on different instruments for the same sample location.

36 MATERIALS SCIENCE↗
DOE OSTI2016

Energetic Light Fragment Production Capability in MCNP6

Monte Carlo Methods, Codes, and Applications group within the Computational Physics Division at Los Alamos National Laboratory has led the development of the transport code MCNP6 (Monte Carlo N-Particle transport code, version 6). MCNP6 is a general-purpose, continuous energy, generalized-geometry, time-dependent, Monte-Carlo radiation-transport code designed to track many particle types over broad ranges of energies. It is used around the world in applications ranging from radiation protection and dosimetry, nuclear-reactor design, nuclear criticality safety, detector design and analysis, decontamination and decommissioning, accelerator applications, medical physics, space research, and beyond. At lower energies, the code uses tables of evaluated nuclear data, while for higher energies (> 150 MeV), MCNP6 uses the cascade-exciton model, version 03.03 (CEM03.03), and the Los Alamos quark-gluon string model, version 03.03 (LAQGSM03.03) to model nuclear reactions. Emission of energetic heavy clusters heavier than {sup 4}He from nuclear reactions play a critical role in several applications, including electronics performance in space, human radiation dosages in space or other extreme radiation environments, proton- and hadron-therapy in medical physics, accelerator and shielding applications, and more. None of the available models are able to accurately predict emission of light fragments (LF) from arbitrary reactions. The CEM and LAQGSM event generators in MCNP6 describe quite well the spectra of fragments with sizes up to {sup 4}He across a broad range of target masses and incident energies (up to ∼ 5 GeV for CEM and up to ∼ 1 TeV/A for LAQGSM). However, they do not predict the high-energy tails of LF spectra heavier than {sup 4}He well. Most LF with energies above several tens of MeV are emitted during the precompound stage of a reaction. The 03.03 versions of CEM and LAQGSM do not account for precompound emission of LF larger than {sup 4}He. The goal of this research is to enable MCNP6 to produce high-energy light fragments. These energetic LF may be emitted by our models through three processes: Fermi breakup, preequilibrium, and coalescence. We explore the emission of light fragments through each of these mechanisms and demonstrate an improved agreement with experimental data achieved by extending precompound models to include emission of fragments heavier than {sup 4}He. (authors)

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
NASA NTRS2015

Capability and Technology Performance Goals for the Next Step in Affordable Human Exploration of Space

The capability for living off the land, commonly called in-situ resource utilization, is finally gaining traction in space exploration architectures. Production of oxygen from the Martian atmosphere is called an enabling technology for human return from Mars, and a flight demonstration to be flown on the Mars 2020 robotic lander is in development. However, many of the individual components still require technical improvements, and system-level trades will be required to identify the best combination of technology options. Based largely on work performed for two recent roadmap activities, this paper defines the capability and technology requirements that will need to be achieved before this game-changing capability can reach its full potential.

Mars exploration↗
NASA NTRS2015

The Effects of Long Duration Bed Rest as a Spaceflight Analogue on Resting State Sensorimotor Network Functional Connectivity and Neurocognitive Performance

Long duration spaceflight has been associated with detrimental alterations in human sensorimotor systems and neurocognitive performance. Prolonged exposure to a head-down tilt position during long duration bed rest can resemble several effects of the microgravity environment such as reduced sensory inputs, body unloading and increased cephalic fluid distribution. The question of whether microgravity affects other central nervous system functions such as brain functional connectivity and its relationship with neurocognitive performance is largely unknown, but of potential importance to the health and performance of astronauts both during and post-flight. The aims of the present study are 1) to identify changes in sensorimotor resting state functional connectivity that occur with extended bed rest exposure, and to characterize their recovery time course; 2) to evaluate how these neural changes correlate with neurocognitive performance. Resting-state functional magnetic resonance imaging (rsfMRI) data were collected from 17 male participants. The data were acquired through the NASA bed rest facility, located at the University of Texas Medical Branch (Galveston, TX). Participants remained in bed with their heads tilted down six degrees below their feet for 70 consecutive days. RsfMRI data were obtained at seven time points: 7 and 12 days before bed rest; 7, 50, and 65 days during bed rest; and 7 and 12 days after bed rest. Functional connectivity magnetic resonance imaging (fcMRI) analysis was performed to measure the connectivity of sensorimotor networks in the brain before, during, and post-bed rest. We found a decrease in left putamen connectivity with the pre- and post-central gyri from pre bed rest to the last day in bed rest. In addition, vestibular cortex connectivity with the posterior cingulate cortex decreased from pre to post bed rest. Furthermore, connectivity between cerebellar right superior posterior fissure and other cerebellar regions decreased from pre bed rest to the last day in bed rest. In contrast, connectivity within the default mode network remained stable over the course of bed rest. We also utilized a battery of behavioral measures including spatial working memory tasks and measures of functional mobility and balance. These behavioral measurements were collected before, during, and after bed rest. We will report the preliminary findings of correlations observed between brain functional connectivity and behavioral performance changes. Our results suggest that sensorimotor brain networks exhibit decoupling with extended periods of reduced usage. The findings from this study could aid in the understanding and future design of targeted countermeasures to alleviate the detrimental health and neurocognitive effects of long-duration spaceflight.

Cassady, K.↗
NASA NTRS1993

Piloting Vertical Flight Aircraft: A Conference on Flying Qualities and Human Factors

This document contains papers from a specialists' meeting entitled "Piloting Vertical Flight Aircraft. A Conference on Flying Qualities and Human Factors." The conference was co-sponsored by the American Helicopter Society--San Francisco Bay Chapter, and the NASA Ames Research Center. It was held January 20-22, 1993 at the Sheraton Hotel Fisherman's Wharf, San Francisco, California. Vertical flight aircraft, including helicopters and a variety of Vertical Takeoff and Landing (VTOL) concepts, place unique requirements on human perception, control, and performance for the conduct of their design missions. The intent of this conference was to examine, for these vehicles, advances in: (1) design of flight control systems for ADS-33C standards; (2) assessment of human factors influences of cockpit displays and operational procedures; (3) development of VTOL design and operational criteria; and (4) development of theoretical methods or models for predicting pilot-vehicle performance and mission suitability. Recognizing that human capabilities and limitations form an integral aspect of the operations for these classes of vehicles, a secondary goal of the conference was to provide an initial venue for enhanced interaction between human factors and handling qualities specialists.

Helicopter↗