Search NASA⌕ Search

SEARCH · Search NASA

Results for “EVA simulation”

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

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 163 records · Page 9

Validation of Decompression Sickness Risk Mitigation Protocols for Planetary Spaceflight Missions

BACKGROUND: Apollo missions used a 100% O2 cabin atmosphere which effectively eliminated the risk of decompression sickness (DCS) during extravehicular activity (EVA) on the moon. NASA’s future missions to the moon and Mars are expected to use nitrox gas mixtures of up to 34% O2, 66% N2, which will reduce flammability risk compared with Apollo, but will necessitate Oxygen prebreathe prior to EVA to reduce DCS risk to acceptable levels. Prebreathe protocols used on the space shuttle and International Space Station are validated for microgravity EVAs, but the significantly increased risk of DCS during equivalent ambulatory EVAs make these protocols inapplicable to planetary EVA. An “exploration atmosphere” of 56.5 kPa (8.2 psia), 34% O2, 66% N2 has been recommended by NASA as a compromise that balances prebreathe duration, hypoxia, and flammability risk, assuming a 29.6 kPa (4.3 psi) spacesuit. However, this atmosphere may not be used for vehicles that do not support frequent EVA, and with commercial providers and international providers expected to provide landers, pressurized rovers, habitats, and spacesuits, different combinations of vehicle and spacesuit atmospheres are possible and will each require validated prebreathe protocols. OVERVIEW: Key components of a multi-year strategic roadmap include: 1) Establish hypobaric chamber facility capable of supporting 8-person EVA prebreathe validation tests at saturation atmospheres up to 36% O2; 2) validate an EVA physical workload simulation for use during prebreathe validation testing; 3) validate the recommended “exploration atmosphere” prebreathe protocol; 4) validate prebreathe protocols for additional atmospheric combinations that bound the most likely potential operating ranges of future vehicles and spacesuits; and 5) update DCS risk estimation models based on results of prebreathe validation studies. DISCUSSION: Details and data from completion of the first two steps of the strategic roadmap will be presented; the third step is currently underway, with pilot results provided in a companion presentation. Steps four and five will require a multi-year series of chamber tests; collaborations are being pursued.

Andrew F. J. Abercromby↗

Appetite and Food Intake During 11 Days of Mild Hypobaric Hypoxia

Introduction Reduced food consumption and loss of body mass and muscle mass have been observed during spaceflight. Hypoxic conditions that astronauts may encounter on exploration missions may further implicate satiety signals and dietary intake. Appetite, food intake, and satiety hormones were investigated under the conditions of mild hypoxia and high energy output during simulated extravehicular activity (EVA) to determine the adequacy of a mission relevant space food system to support energy balance and body composition. Methods Foods realistic to early Artemis missions was packed by meal for each subject for the 11-day test based on estimated energy requirements (EER) and estimated EVA caloric requirements. No hot water or food warmer was provided and only room temperature water was available to rehydrate food and beverages in-mission, mimicking plans for early Artemis missions. Measures included food records (pre-mission, in-mission); fasted body weight (pre-mission, in-mission); Dual-energy X-ray absorptiometry (DXA) (pre-mission, post-mission); subjective ratings and feedback of food acceptability, mealtime and meal preparation sufficiency, appetite, and nausea (in-mission); and circulating ghrelin and leptin concentration in fasted blood samples (pre-mission, in-mission: pre-post EVA). Results All subjects consumed fewer calories in-mission than predicted. On average, subjects consumed 341 calories less on EVA days compared to non-EVA days in-mission (p=0.0511). The total weight loss estimate from daily weight measurements (-1.1 kg, p=0.0028) is consistent with underconsumption and supported by DXA measurements (-1.3 kg total body mass, p=0.0123 and -1.6 kg fat mass, p=0.0016). In general, most foods that were consumed were given acceptable scores, but subject comments indicated that the most acceptable foods were those not intended to be heated. Comments also indicated that subjects found their favorite foods early in the mission and avoided the foods that they did not like throughout the mission. Habitability scores indicated that overall aspects of the food system were considered borderline or unacceptable over the length of this mission. Foods that caused gas were avoided pre-EVA to prevent discomfort during pressure changes. Average fruit and vegetable intake decreased during the mission, dropping from 4.8 servings/d pre-mission to 3.4 servings/d on non-EVA days in-mission (p=0.0872) and 2.3 servings on EVA days (p=0.0020). Fasting ghrelin concentrations tended to be lower pre-EVA and on non-EVA days when exposed to mild hypoxia compared to normoxic conditions pre-mission and post-EVA (p=0.0136). Fasting levels of leptin did not change. Discussion Food intake was reduced in-mission, resulting in a caloric deficit and weight loss for most subjects. Crew food and appetite ratings and comments indicated this was due to a combination of food choices, lack of preference, lack of preparation capability, lack of time for meal preparation, consumption, and cleanup, and physiological challenges with the changing pressure. The regulation of appetite stimulating hormone ghrelin, but not the appetite suppressor leptin, appeared to be sensitive to hypoxic conditions. Conclusions Food preparation capabilities and time for meals are important for promoting adequate food intake. Reduced appetite and food intake during missions may further be aggravated under hypoxic conditions through the suppression of ghrelin. Lack of time for meals on EVA days, and avoidance of potential gas-causing foods (e.g., health promoting fruits and vegetables) prior to EVAs, demonstrate the importance of scheduling ample recovery time between EVA days.

Grace L Douglas↗

Appetite and Food Intake During 11 Days of Mild Hypobaric Hypoxia

Introduction Reduced food consumption and loss of body mass and muscle mass have been observed during spaceflight. Hypoxic conditions that astronauts may encounter on exploration missions may further implicate satiety signals and dietary intake. Appetite, food intake, and satiety hormones were investigated under the conditions of mild hypoxia and high energy output during simulated extravehicular activity (EVA) to determine the adequacy of a mission relevant space food system to support energy balance and body composition. Methods Foods realistic to early Artemis missions was packed by meal for each subject for the 11-day test based on estimated energy requirements (EER) and estimated EVA caloric requirements. No hot water or food warmer was provided and only room temperature water was available to rehydrate food and beverages in-mission, mimicking plans for early Artemis missions. Measures included food records (pre-mission, in-mission); fasted body weight (pre-mission, in-mission); Dual-energy X-ray absorptiometry (DXA) (pre-mission, post-mission); subjective ratings and feedback of food acceptability, mealtime and meal preparation sufficiency, appetite, and nausea (in-mission); and circulating ghrelin and leptin concentration in fasted blood samples (pre-mission, in-mission: pre-post EVA). Results All subjects consumed fewer calories in-mission than predicted. On average, subjects consumed 341 calories less on EVA days compared to non-EVA days in-mission (p=0.0511). The total weight loss estimate from daily weight measurements (-1.1 kg, p=0.0028) is consistent with underconsumption and supported by DXA measurements (-1.3 kg total body mass, p=0.0123 and -1.6 kg fat mass, p=0.0016). In general, most foods that were consumed were given acceptable scores, but subject comments indicated that the most acceptable foods were those not intended to be heated. Comments also indicated that subjects found their favorite foods early in the mission and avoided the foods that they did not like throughout the mission. Habitability scores indicated that overall aspects of the food system were considered borderline or unacceptable over the length of this mission. Foods that caused gas were avoided pre-EVA to prevent discomfort during pressure changes. Average fruit and vegetable intake decreased during the mission, dropping from 4.8 servings/d pre-mission to 3.4 servings/d on non-EVA days in-mission (p=0.0872) and 2.3 servings on EVA days (p=0.0020). Fasting ghrelin concentrations tended to be lower pre-EVA and on non-EVA days when exposed to mild hypoxia compared to normoxic conditions pre-mission and post-EVA (p=0.0136). Fasting levels of leptin did not change. Discussion Food intake was reduced in-mission, resulting in a caloric deficit and weight loss for most subjects. Crew food and appetite ratings and comments indicated this was due to a combination of food choices, lack of preference, lack of preparation capability, lack of time for meal preparation, consumption, and cleanup, and physiological challenges with the changing pressure. The regulation of appetite stimulating hormone ghrelin, but not the appetite suppressor leptin, appeared to be sensitive to hypoxic conditions. Conclusions Food preparation capabilities and time for meals are important for promoting adequate food intake. Reduced appetite and food intake during missions may further be aggravated under hypoxic conditions through the suppression of ghrelin. Lack of time for meals on EVA days, and avoidance of potential gas-causing foods (e.g., health promoting fruits and vegetables) prior to EVAs, demonstrate the importance of scheduling ample recovery time between EVA days.

Lichar Dillon↗

A Preliminary Assessment of Cognition and Fatigue During Simulated Lunar Surface Extravehicular Activities

Introduction: Artemis astronauts will be required to complete more rigorous Extravehicular Activity (EVA) schedules than during ever before. While new spacesuits are designed to sustain high physical workloads during exploration EVAs (xEVA), crewmembers must also sustain cognitive performance throughout xEVA timelines. It is therefore necessary to characterize the effects of surface xEVA tasks and timelines on cognition and fatigue. Methods: This study utilized NASA Johnson Space Center’s Active Response Gravity Offload System (ARGOS) to simulate lunar gravity and assess xEVA tasks and cognitive performance. Two subjects completed two ~5-hour EVAs in a pressurized Mark III spacesuit, completing simulated lander operations, cable routing, crew rescue, geology, payload relocation, and traverses. Subjects completed two cognitive assessments (Digit-Symbol Substitution Task (DSST) and Psychomotor Vigilance Task (PVT)) before the first and after the second simulated EVA to assess effects of xEVA tasks on processing speed and vigilant attention. Additionally, sleep (e.g., quality, duration, and efficiency) was monitored (Oura Ring) for ≥7 days prior to the simulated EVAs, as well as between each EVA, to account for possible effects of sleep decrements on cognitive metrics. Results: Cognitive performance changed minimally from pre to post EVA for both DSST (response time (RT): S1 Δ129.1ms, S2 Δ40.7ms; Accuracy: S1 preEVA = 1.0, S1 postEVA = 0.98, S2 preEVA = 1.0, S2 postEVA = 1.0) and PVT (S1 PVT RT Δ17.7 ms, S2 PVT RT Δ-2.7 ms). Subjects’ sleep duration immediately prior to EVA showed minimal deviation from baseline (Δhrs; S1 preEVA1= + 0.67, S1 preEVA2 = -.03, S2 preEVA1 = - 1.1, S2 preEVA2 = -1.39) and efficiency (Δ%; S1 preEVA1 = 0.09, S1 preEVA2 = 9.54, S2 preEVA1 = 0, S2 preEVA2= 12). Notably, sleep waketime shifted earlier for one subject by ~1 hr which may have impacted performance. Conclusion: Understanding the impacts of xEVA workloads on cognitive performance will be instrumental to future exploration mission planning and success. Future work will expand the subject pool and test new spacesuit designs to better characterize cognitive performance and impacts of sleep during simulated xEVA and inform modeling and prediction capabilities for future Artemis xEVA planning.

Taylor E. Schlotman↗

Wissler Simulations of a Liquid Cooled and Ventilation Garment (LCVG) for Extravehicular Activity (EVA)

In order to provide effective cooling for astronauts during extravehicular activities (EVAs), a liquid cooling and ventilation garment (LCVG) is used to remove heat by a series off tubes through which cooling water is circulated. To better predict the effectiveness of the LCG and determine possible modifications to improve performance, computer simulations dealing with the interaction of the cooling garment with the human body have been run using the Wissler Human Model. Simulations have been conducted to predict the heat removal rate for various liquid cooled garment configurations. The current LCVG uses 48 cooling tubes woven into a fabric with cooling water flowing through the tubes. The purpose of the current project is to decrease the overall weight of the LCVG system. In order to achieve this weight reduction, advances in the garment heat removal rates need to be obtained. Currently, increasing the fabric s thermal conductivity along with also examining an increase in the cooling tube conductivity to more efficiently remove the excess heat generated during EVA is being simulated. Initial trials varied cooling water temperature, water flow rate, garment conductivity, tube conductivity, and total number of cooling tubes in the LCVG. Results indicate that the total number of cooling tubes could be reduced to 22 and still achieve the desired heat removal rate of 361 W. Further improvements are being made to the garment network used in the model to account for temperature gradients associated with the spacing of the cooling tubes over the surface of the garment

Kesterson, Matthew↗

The Instrumented Walking and Turning Test to Evaluate Suited Gait Dynamics and Performance in Extravehicular Activity Training Environments

Background and aims: Walking will be required for many exploration tasks on the Moon during the Artemis program. Walking in a straight line on the confined floorspace of a testing area, and repetitive treadmill walking that requires no change in direction may not adequately reflect the balance and coordination required during ambulation. Also, performance of turning maneuvers may be affected differently in different extravehicular activity (EVA) training facilities that simulate partial gravity. For example, the Neutral Buoyancy Lab (NBL) simulates lunar gravity by adding weight to underwater subjects to alter buoyancy and achieve the equivalent ground reaction force of 1/6 of Earth’s gravity (1/6G), whereas the Active Response Gravity Offload System (ARGOS) uses a computer controlled overhead suspension system programmed to continuously offload a percentage of a subject’s weight to simulate 1/6G. The degree to which dynamic movements such as turning are comparable across these EVA training facilities has not yet been evaluated. The instrumented gait test helps NASA scientists and engineers evaluate gait dynamics and performance in suited conditions, and this test demonstrates the unique characteristics and limitations of EVA training facilities. We developed an instrumented walking and turning test using inertial measurement units (IMUs) and conducted the test at NASA’s EVA training facilities. Results were used to compare suited walking and turning characteristics in the ARGOS and the NBL. Methods: Subjects donned the Mark III space suit during offloading with the ARGOS spreader bar gimbal and donned the Z2.5 space suit while underwater in the NBL with weights and floatation added to achieve realistic suit center of gravity. The test team securely attached three Opal (APDM, OR, USA) wireless IMUs on the space suit for each test run: one on the middle of the hard upper torso, and one on the left and on the right ankle bearings. During the NBL tests, the IMUs were encased in a waterproof housing (GoPro) with foam added to create a tighter fit. At both testing facilities, 6.3 m x 1.0 m (LxW) walking lines were marked, and a cone for turning or walking around was located at the end of the walking path with another line on the other side of the cone to indicate the stopping point after walking around the cone. Under simulated 1/6G, subjects began by standing at the marked line with their arms folded across the chest, they then walked at a preferred speed along the straight walking path until they reached the end, turned 180 degrees around the cone, and finally stopped at the marked stopping point. All IMU data recorded during testing were automatically saved to the internal memory. Then, raw IMU signals were processed using custom MATLAB (Mathworks, MA, USA) code to compare gait parameters during both the walking and the turning components of the task. These parameters included time (s), speed (m/s for walking and rad/s for turning), step number (n) and walk:turn time ratio (% time spent straight walking versus turning). Results: Less time, faster gait, fewer steps, and higher walk:turn ratio during both walking and turning components were exhibited during tests performed at the ARGOS versus those performed at the NBL. During the NBL tests, the slower walking speed continued at the same rate throughout a U-shape turn. During the ARGOS tests, the subjects performed shorter and tighter turns at 4 times the speed of the NBL turns because they walked 30% faster and the vertical offloading system gave them more support. Conclusion: Our data show that the differences in walking and turning parameters during the NBL tests may be due to the high viscosity in the water environment where the motion of the lower limbs was slow and did not reach full flexion and extension. These tests improve the current knowledge of testing environments in preparation for EVAs on the lunar surface.

Kyoung Jae Kim↗

Analog Testing of Operations Concepts for Mitigation of Communication Latency During Human Space Exploration

OBJECTIVES: NASA Extreme Environment Mission Operations (NEEMO) is an underwater spaceflight analog that allows a true mission‐like operational environment and uses buoyancy effects and added weight to simulate different gravity levels. Three missions were undertaken from 2014‐2015, NEEMO's 18‐20. All missions were performed at the Aquarius undersea research habitat. During each mission, the effects of varying operations concepts and tasks type and complexity on representative communication latencies associated with Mars missions were studied. METHODS: 12 subjects (4 per mission) were weighed out to simulate near‐zero or partial gravity extravehicular activity (EVA) and evaluated different operations concepts for integration and management of a simulated Earth‐based science backroom team (SBT) to provide input and direction during exploration activities. Exploration traverses were planned in advance based on precursor data collected. Subjects completed science‐related tasks including presampling surveys, geologic‐based sampling, and marine‐based sampling as a portion of their tasks on saturation dives up to 4 hours in duration that were to simulate extravehicular activity (EVA) on Mars or the moons of Mars. One‐way communication latencies, 5 and 10 minutes between space and mission control, were simulated throughout the missions. Objective data included task completion times, total EVA times, crew idle time, translation time, SBT assimilation time (defined as time available for SBT to discuss data/imagery after it has been collected, in addition to the time taken to watch imagery streaming over latency). Subjective data included acceptability, simulation quality, capability assessment ratings, and comments. RESULTS: Precursor data can be used effectively to plan and execute exploration traverse EVAs (plans included detailed location of science sites, high‐fidelity imagery of the sites, and directions to landmarks of interest within a site). Operations concepts that allow for presampling surveys enable efficient traverse execution and meaningful Mission Control Center (MCC) interaction across long communication latencies and can be done with minimal crew idle time. Imagery and information from the EVA crew that is transmitted real‐time to the intravehicular (IV) crewmember(s) can be used to verify that exploration traverse plans are being executed correctly. That same data can be effectively used by MCC (across comm latency) to provide further instructions to the crew from a SBT on sampling priorities, additional tasks, and changes to the plan. Text / data capabilities are preferred over voice capabilities between MCC and IV when executing exploration traverse plans over communication latency. Autonomous crew planning tools can be effective at modifying existing plans if the objectives and constraints are clearly defined.

Chappell, Steven P.↗

Effects of Varying Surface Inclines and Suit Pressure: Implications on Space Suit Design

Suited human performance studies in reduced gravity environments to date include limited observations from Apollo Lunar surface Extravehicular Activities (EVA) and from previous studies conducted in partial gravity simulation environments. The Constellation Program EVA Systems Project office has initiated tests to develop design requirements for the next generation Lunar EVA suit. Theses studies were conducted in the Space Vehicle Mock-Up Facility (SVMF) at Johnson Space Center from which the results provided recommendations for suit weight, mass, center of gravity, pressure, and suit kinematic constraints that optimize human performance in partial gravity environments.

Clowers, Kurt↗

NEEMO 18-20: Analog Testing for Mitigation of Communication Latency During Human Space Exploration

NASA Extreme Environment Mission Operations (NEEMO) is an underwater spaceflight analog that allows a true mission-like operational environment and uses buoyancy effects and added weight to simulate different gravity levels. Three missions were undertaken from 2014-2015, NEEMO's 18-20. All missions were performed at the Aquarius undersea research habitat. During each mission, the effects of communication latencies on operations concepts, timelines, and tasks were studied. METHODS: Twelve subjects (4 per mission) were weighed out to simulate near-zero or partial gravity extravehicular activity (EVA) and evaluated different operations concepts for integration and management of a simulated Earth-based science team (ST) to provide input and direction during exploration activities. Exploration traverses were preplanned based on precursor data. Subjects completed science-related tasks including pre-sampling surveys, geologic-based sampling, and marine-based sampling as a portion of their tasks on saturation dives up to 4 hours in duration that were designed to simulate extravehicular activity (EVA) on Mars or the moons of Mars. One-way communication latencies, 5 and 10 minutes between space and mission control, were simulated throughout the missions. Objective data included task completion times, total EVA times, crew idle time, translation time, ST assimilation time (defined as time available for ST to discuss data/imagery after data acquisition). Subjective data included acceptability, simulation quality, capability assessment ratings, and comments. RESULTS: Precursor data can be used effectively to plan and execute exploration traverse EVAs (plans included detailed location of science sites, high-fidelity imagery of the sites, and directions to landmarks of interest within a site). Operations concepts that allow for pre-sampling surveys enable efficient traverse execution and meaningful Mission Control Center (MCC) interaction across communication latencies and can be done with minimal crew idle time. Imagery and contextual information from the EVA crew that is transmitted real-time to the intravehicular (IV) crewmember(s) can be used to verify that exploration traverse plans are being executed correctly. That same data can be effectively used by MCC (across comm latency) to provide meaningful feedback and instruction to the crew regarding sampling priorities, additional tasks, and changes to the EVA timeline. Text / data capabilities are preferred over voice capabilities between MCC and IV when executing exploration traverse plans over communication latency.

Chappell, Steven P.↗

Performance Characterization and Simulation of Amine-Based Vacuum Swing Sorption Units for Spacesuit Carbon Dioxide and Humidity Control

Controlling carbon dioxide (CO2) and water (H2O) vapor concentrations in a space suit is critical to ensuring an astronauts safety, comfort, and capability to perform extra-vehicular activity (EVA) tasks. Historically, this has been accomplished using lithium hydroxide (LiOH) and metal oxide (MetOx) canisters. Lithium hydroxide is a consumable material that requires priming with water before it becomes effective at removing carbon dioxide. MetOx is regenerable through a power-intensive thermal cycle but is significantly heavier on a volume basis than LiOH. As an alternative, amine-based vacuum swing beds are under aggressive development for EVA applications. The vacuum swing units control atmospheric concentrations of both CO2 and H2O through fully-regenerative process. The current concept, referred to as the rapid cycle amine (RCA), has resulted in numerous laboratory prototypes. Performance of these prototypes have been assessed experimentally and documented in previous reports. To support developmental e orts, a first principles model has also been established for the vacuum swing sorption technology. For the first time in several decades, a major re-design of Portable Life Support System (PLSS) for the extra-vehicular mobility unit (EMU) is underway. NASA at Johnson Space Center built and tested an integrated PLSS test bed of all subsystems under a variety of simulated EVA conditions of which the RCA prototype played a significant role. The efforts documented herein summarize RCA test performance and simulation results for single and variable metabolic rate experiments in an integrated context. In addition, a variety of off-nominal tests were performed to assess the capability of the RCA to function under challenging circumstances. Tests included high water production experiments, degraded vacuum regeneration, and deliberate valve/power failure and recovery.

Swickrath, Michael J.↗

EVA manipulation and assembly of space structure columns

Assembly techniques and hardware configurations used in assembly of the basic tetrahedral cell by A7LB pressure-suited subjects in a neutral bouyancy simulator were studied. Eleven subjects participated in assembly procedures which investigated two types of structural members and two configurations of attachment hardware. The assembly was accomplished through extra-vehicular activity (EVA) only, EVA with simulated manned maneuvering unit (MMU), and EVA with simulated MMU and simulated remote manipulator system (RMS). Assembly times as low as 10.20 minutes per tetrahedron were achieved. Task element data, as well as assembly procedures, are included.

Loughead, T. E.↗

Life Sciences Implications of Lunar Surface Operations

The purpose of this report is to document preliminary, predicted, life sciences implications of expected operational concepts for lunar surface extravehicular activity (EVA). Algorithms developed through simulation and testing in lunar analog environments were used to predict crew metabolic rates and ground reaction forces experienced during lunar EVA. Subsequently, the total metabolic energy consumption, the daily bone load stimulus, total oxygen needed, and other variables were calculated and provided to Human Research Program and Exploration Systems Mission Directorate stakeholders. To provide context to the modeling, the report includes an overview of some scenarios that have been considered. Concise descriptions of the analog testing and development of the algorithms are also provided. This document may be updated to remain current with evolving lunar or other planetary surface operations, assumptions and concepts, and to provide additional data and analyses collected during the ongoing analog research program.

Chappell, Steven P.↗

Modeling and Simulation Credibility Assessments of Musculoskeletal Computational Models for Simulating Astronaut Injuries Due to a Poor Spacesuit Fit

The musculoskeletal (MS) system of astronauts is subject to physiological changes, potentially leading to injuries due to the exposure to different gravitational environments experienced during spaceflight. These injuries can occur while an astronaut is performing an Extravehicular Activity (EVA) in space, on lunar or planetary surfaces or while wearing a spacesuit during terrestrial training for an EVA. The OpenSim MS modeling software can assess EVA induced MS injury mechanisms such as muscle strains, ligament injuries and joint injuries. One area of concern, since there are only a few different spacesuit sizes with limited adjustability, is the possibility of a poorly fitting spacesuit. This can cause unnatural joint motions and torques resulting in various MS injuries. A credibility assessment of the OpenSim modeling and simulation procedures is performed per NASA-STD-7009A to provide information on the credibility of the model’s use in simulating EVA related injury mechanisms. The credibility assessment evaluated various OpenSim models against the following eight credibility factors: data pedigree, input pedigree, code verification, solution verification, conceptual validation, referent validation, results uncertainty and results robustness (sensitivity). The models evaluated for EVA injuries will require additional credibility factor analysis and upgrades to the model features, such as adding ligaments to a whole-body model, to reliably predict and analyze the EVA injuries expected to occur due to a poor spacesuit fit. The degree of elevation strategy required to increase the credibility assessment scores will depend on the model complexity and the injury mechanism.

Christopher A. Gallo↗

Modeling and Simulation Credibility Assessments of Musculoskeletal Computational Models for Simulating Astronaut Injuries Due to a Poor Spacesuit Fit

The musculoskeletal (MS) system of astronauts is subject to physiological changes, potentially leading to injuries due to the exposure to different gravitational environments experienced during spaceflight. These injuries can occur while an astronaut is performing an Extravehicular Activity (EVA) in space, on lunar or planetary surfaces or while wearing a spacesuit during terrestrial training for an EVA. The OpenSim MS modeling software can assess EVA induced MS injury mechanisms such as muscle strains, ligament injuries and joint injuries. One area of concern, since there are only a few different spacesuit sizes with limited adjustability, is the possibility of a poorly fitting spacesuit. This can cause unnatural joint motions and torques resulting in various MS injuries. A credibility assessment of the OpenSim modeling and simulation procedures is performed per NASA-STD-7009A to provide information on the credibility of the model’s use in simulating EVA related injury mechanisms. The credibility assessment evaluated various OpenSim models against the following eight credibility factors: data pedigree, input pedigree, code verification, solution verification, conceptual validation, referent validation, results uncertainty and results robustness (sensitivity). The models evaluated for EVA injuries will require additional credibility factor analysis and upgrades to the model features, such as adding ligaments to a whole-body model, to reliably predict and analyze the EVA injuries expected to occur due to a poor spacesuit fit. The degree of elevation strategy required to increase the credibility assessment scores will depend on the model complexity and the injury mechanism.

Christopher A Gallo↗

Machine-learning Solution for Automatic Spacesuit Motion Recognition and Measurement from Conventional Video

Extravehicular Activity (EVA) spacesuits exhibit unique movement patterns due to their design characteristics. Mobility assessments using traditional motion capture systems are cost prohibitive and not feasible for some training conditions (e.g., simulated lunar outdoor terrain). This paper aims to present the ongoing development of machine learning solutions to quantify suit motions from conventional videos without special sensors or hardware. Preliminary work into this field was promising but given the fast growth in deep/machine learning technologies, external expertise was sought from open-source communities. Partnerships were formed with the NASA JSC Center of Excellence for Collaborative Innovation (CoCEI) and an execution crowdsourcing platform partner to solicit machine learning framework developments from external contenders. NASA provided contenders with images and video clips of spacesuits with simultaneously measured motion capture data during EVA simulation tasks. The contenders used this data to train and develop generalized algorithms to predict motions. At the end of the crowdsourcing event, the top five solutions were selected from 250 submissions. Each submission was tested and scored using video clips not previously disclosed to the contenders. The weighted scoring metrics measured how well the algorithm detected the suit shape, the 2D suit joint detection accuracy, and 3D joint detection accuracy. The winning solution was able to achieve roughly 85% prediction accuracy. Overall, the algorithms could efficiently detect various types of spacesuits and motions across different EVA environments such as the NASA Active Response Gravity Offload System (ARGOS). After continued improvements and validation, the fully developed system will enable EVA stakeholders to quantify suit kinematic patterns, which can help optimize suit, hardware, and task designs.

Linh Vu↗

Metabolic Costs and Biomechanics of Inclined Ambulation and Exploration Tasks in a Planetary Suit

Observations from Apollo lunar surface extravehicular activities (EVAs) and a few studies conducted in partial-gravity simulation environments have helped us understand suited human performance in reduced-gravity environments. The Constellation Program EVA Systems Project Office initiated a series of tests aimed at increasing our understanding of human performance and suit kinematics under various simulated lunar EVA conditions, including matched unsuited controls, to identify the specific metabolic costs and biomechanics of the prototype Mark III Advanced Spacesuit Technology Demonstrator. A primary goal of the series is to provide evidence-based recommendations for suit mass, center of gravity, pressure, and suit kinematic constraints that optimize human performance in partial-gravity environments. Results will be combined with studies in other lunar analogs to evaluate the effectiveness and limitations of these environments. As our understanding of suited human performance matures, different combinations of variables can be evaluated to determine whether significant interactions exist between parameters. This report provides an overview of key findings of Integrated Suit Test (IST)-2. As future tests are completed, focusing on other suit factors, analog environments, or different suits, study results will be combined and reevaluated. The series of tests comprising IST-2 was conducted from June 13, 2007 through October 24, 2007.

Aerospace environments↗