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NASA NTRS2010

A Near-Term Concept for Trajectory Based Operations with Air/Ground Data Link Communication

An operating concept and required system components for trajectory-based operations with air/ground data link for today's en route and transition airspace is proposed. Controllers are fully responsible for separation as they are today, and no new aircraft equipage is required. Trajectory automation computes integrated solutions to problems like metering, weather avoidance, traffic conflicts and the desire to find and fly more time/fuel efficient flight trajectories. A common ground-based system supports all levels of aircraft equipage and performance including those equipped and not equipped for data link. User interface functions for the radar controller's display make trajectory-based clearance advisories easy to visualize, modify if necessary, and implement. Laboratory simulations (without human operators) were conducted to test integrated operation of selected system components with uncertainty modeling. Results are based on 102 hours of Fort Worth Center traffic recordings involving over 37,000 individual flights. The presence of uncertainty had a marginal effect (5%) on minimum-delay conflict resolution performance, and windfavorable routes had no effect on detection and resolution metrics. Flight plan amendments and clearances were substantially reduced compared to today s operations. Top-of-descent prediction errors are the largest cause of failure indicating that better descent predictions are needed to reliably achieve fuel-efficient descent profiles in medium to heavy traffic. Improved conflict detections for climbing flights could enable substantially more continuous climbs to cruise altitude. Unlike today s Conflict Alert, tactical automation must alert when an altitude amendment is entered, but before the aircraft starts the maneuver. In every other failure case tactical automation prevented losses of separation. A real-time prototype trajectory trajectory-automation system is running now and could be made ready for operational testing at an en route Center in 1-2 years.

McNally, David↗

NASA NTRS2019

Method for Tracking and Communicating Aggregate Risk Through the Use of Model-Based Systems Engineering (MBSE) Tools

Large, complex projects can identify a significant number and variety of risks, throughout the project life cycle. These risks are analyzed, mitigated, closed or accepted as independent uncertainties. Once closed or accepted, it is easy for projects to lose awareness of their impact. In reality, each of these risks contributes some amount to the overall risk posture of the project. The ability to track and effectively communicate this aggregate risk has represented a challenge to project management. There have been previous attempts to create a schema to communicate the aggregate effect of risks, without notable success. Most of these attempts have centered on some additive metric derived from the scoring of likelihood and consequence values. This, in and of itself, is a logical approach, but all too often the scores were then aggregated to a level where all context was lost. One weakness has been a lack of attempt to create linkages or logical groups of the risks upon which useful aggregation could then occur. The overall move to model-based (systems) engineering (MBSE) has opened up a vast frontier of opportunities to better integrate all project data. MBSE provides an underlying layer that links data items to each other. Objectives link to requirements, which then link to functions, functions to physical architecture items, and so on, as far down as projects want to model. While it started with a focus on modeling requirements based on things like use cases, efforts are now underway to integrate safety and mission assurance (S&MA) information and analyses, such as risks. This effort, called Model Based Mission Assurance (MBMA), is yielding models that are more useful and are a more accurate representations of the systems. MBSE models, with this ability to link related items, provide a new means of tracking and communicating aggregate risks. In the proposed method, risks are added into the models as distinct items, having attributes that communicate a scoring derived from the likelihood and consequence values as charted on the standard NASA 5x5 risk matrix. Like earlier efforts, each box in the 5x5 has an associated scoring, which may include both a current score and potential post-mitigation/control score. The risk items are then linked to elements of the model, such as system objectives/goals, requirements, functions, or physical architecture items, with "Risk to" relationships. These risks will then be communicated by use of reports generated from the model, detailing all risks and/or hazards linked to model elements. These reports can include aggregate impacts, including a current scoring and potential future state scoring based on the planned mitigations and/or controls. These reports will show all risks, open, accepted, and closed, linked to project objectives or requirements. When run as part of an upcoming risk acceptance discussion, these reports will serve to remind the team of all previous risks that relate to the effected portion of the system. When included as part of periodic program or project reviews, risk reviews, and safety reviews, this method can improve the overall understanding of the system's true risk posture. This proposed method takes full advantage of the advances that modern modeling techniques provide, with a minimal investment of additional time. Utilizing the model environment also enables a near constant access to current state of aggregate risks.

model based mission assurance↗

NASA NTRSDate not supplied

Lunar Transport Vehicle Ocupant Protection Requirements

INTRODUCTION The National Aeronautics and Space Administration (NASA) is preparing for future Artemis missions that will return humans to the lunar surface. A critical piece of these future missions is the Lunar Transport Vehicle (LTV), a transportation device to be used on the lunar surface. A vehicular method of transportation will allow for longer duration missions with increased capabilities to conduct research and transport soil, geological samples, or other materials of interest. The objective of this project is to provide occupant protection guidance for the design of the LTV. METHODS At the time of writing of occupant protection requirements, much of the LTV design is unknown. However, several general assumptions have been established. It is assumed that the LTV will be an unpressurized crewed rover with the occupant(s) wearing an EVA suit. Additionally, the occupant must be protected using established health limits as governing criteria to protect the occupant from hazardous levels of acceleration, jerk, and vibration. In addition to the health limits, it is expected that the LTV shall provide a comfortable transportation solution to Lunar operations. Several restraint configurations have been considered to allow for seated and standing operation of the vehicle. RESULTS Preliminary recommendations and metrics were put forward by a cross functional working group with members from Johnson Space Center and Ames Research Center. Exposure to acceleration, vibration, and jerk metrics above the proposed limits could create a risk of occupant injury. In addition to satisfying crew health needs, these limits permit the occupant to meet performance objectives including operating the vehicle and reading displays while traversing the Lunar surface. Initial guidance was refined during a Technical Interchange Meeting with external subject matter experts in industry, academia, and United States Air Force. CONCLUSION Operating a crewed vehicle in a lunar environment is a novel problem with few analogs to provide data. Based on terrestrial data from ISO & MIL Standards, occupant protection recommendations have been identified with several assumptions made about reduced gravity and deconditioned occupants. If the design of the vehicle attenuates energetics to levels below those put forward, there is high confidence the occupant will be able to repetitively operate the vehicle without physical harm or operational issues.

K Dolick↗

NASA NTRS2018

NASA ESDIS Employs the Latest Generation Web Analytics Tool

Under the auspices of NASA's Earth Observing System Data and Information System (EOSDIS), The Earth Science Data and Information System (ESDIS) Project distributes science data to a wide community of users through its Distributed Active Archive Centers (DAACs). Much of this data is made available via interactive websites - which involve links, downloads, on page interaction, and referrals to additional online pages. To meet the earth science data and information needs of many data users representing numerous different science domains, over 80 specialized websites are supported by multiple distributed organizations under the ESDIS umbrella.

Web Metrics↗

NASA NTRS2026

PROTECT: Production and Reuse of Thermally Efficient Ceramic Thermal Protection Systems

PROTECT (Production and Reuse Of Thermally Efficient Ceramic TPS) is a NASA Early Career Initiative focused on developing the next generation of reusable ceramic thermal protection systems (TPS). This project addresses key challenges in TPS design, including temperature capability, thermal stability, and refurbishment time, by integrating novel material development with predictive modeling. Leveraging enhanced capabilities in NASA’s Porous Microstructure Analysis (PuMA) software, PROTECT introduces new modeling tools to predict the thermal and mechanical behavior of fibrous ceramic materials. These tools enable accurate prediction of performance metrics such as thermal conductivity and structural integrity, reducing reliance on costly physical testing. Preliminary advances in these areas will be presented. To support model validation, PROTECT is building a comprehensive database of raw material properties using advanced characterization techniques, including micro computed tomography (CT) scanning in collaboration with the University of Illinois Urbana-Champaign (UIUC). The presentation will detail the sampling workflows and analysis methods used to generate this detailed microstructural data and how it is used to develop improved models in PuMA. This multi-center collaboration, spanning NASA (JSC, ARC, KSC, GRC), Oak Ridge National Laboratory, UIUC, and SpaceX, is developing tailored TPS solutions for LEO, lunar, and Martian missions. By bridging heritage systems with the demands of modern spaceflight, PROTECT contributes to the advancement of reusable TPS technologies for future exploration missions.

Propulsion, Refractory, and Coating Materials↗

NASA NTRS2026

PROTECT: Production and Reuse of Thermally Efficient Ceramic Thermal Protection Systems

Propulsion, Refractory, and Coating Materials↗

NASA NTRS1984

An experimental evaluation of the Sternberg task as a workload metric for helicopter Flight Handling Qualities (FHQ) research

The objective was to determine whether the Sternberg item-recognition task, employed as a secondary task measure of spare mental capacity for flight handling qualities (FHQ) simulation research, could help to differentiate between different flight-control conditions. FHQ evaluations were conducted on the Vertical Motion Simulator at Ames Research Center to investigate different primary flight-control configurations, and selected stability and control augmentation levels for helicopters engaged in low-level flight regimes. The Sternberg task was superimposed upon the primary flight-control task in a balanced experimental design. The results of parametric statistical analysis of Sternberg secondary task data failed to support the continued use of this task as a measure of pilot workload. In addition to the secondary task, subjects provided Cooper-Harper pilot ratings (CHPR) and responded to workload questionnaire. The CHPR data also failed to provide reliable statistical discrimination between FHQ treatment conditions; some insight into the behavior of the secondary task was gained from the workload questionnaire data.

Hemingway, J. C.↗

NASA NTRS2011

2008 GEM Modeling Challenge: Metrics Study of the Dst Index in Physics-Based Magnetosphere and Ring Current Models and in Statistical and Analytic Specifications

In this paper the metrics-based results of the Dst part of the 2008-2009 GEM Metrics Challenge are reported. The Metrics Challenge asked modelers to submit results for 4 geomagnetic storm events and 5 different types of observations that can be modeled by statistical or climatological or physics-based (e.g. MHD) models of the magnetosphere-ionosphere system. We present the results of over 25 model settings that were run at the Community Coordinated Modeling Center (CCMC) and at the institutions of various modelers for these events. To measure the performance of each of the models against the observations we use comparisons of one-hour averaged model data with the Dst index issued by the World Data Center for Geomagnetism, Kyoto, Japan, and direct comparison of one-minute model data with the one-minute Dst index calculated by the United States Geologic Survey (USGS).

Rastaetter, L.↗

NASA NTRSDate not supplied

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↗

NASA NTRS1984

The Sternberg Task as a Workload Metric in Flight Handling Qualities Research

The objective of this research was to determine whether the Sternberg item-recognition task, employed as a secondary task measure of spare mental capacity for flight handling qualities (FHQ) simulation research, could help to differentiate between different flight-control conditions. FHQ evaluations were conducted on the Vertical Motion Simulator at Ames Research Center to investigate different primary flight-control configurations, and selected stability and control augmentation levels for helicopers engaged in low-level flight regimes. The Sternberg task was superimposed upon the primary flight-control task in a balanced experimental design. The results of parametric statistical analysis of Sternberg secondary task data failed to support the continued use of this task as a measure of pilot workload. In addition to the secondary task, subjects provided Cooper-Harper pilot ratings (CHPR) and responded to a workload questionnaire. The CHPR data also failed to provide reliable statistical discrimination between FHQ treatment conditions; some insight into the behavior of the secondary task was gained from the workload questionnaire data.

Hemingway, J. C.↗

NASA NTRS2013

Preliminary Assessment of the Mars Science Laboratory Entry, Descent, and Landing Simulation

On August 5, 2012, the Mars Science Laboratory rover, Curiosity, successfully landed inside Gale Crater. This landing was only the seventh successful landing and fourth rover to be delivered to Mars. Weighing nearly one metric ton, Curiosity is the largest and most complex rover ever sent to investigate another planet. Safely landing such a large payload required an innovative Entry, Descent, and Landing system, which included the first guided entry at Mars, the largest supersonic parachute ever flown at Mars, and a novel and untested Sky Crane landing system. A complete, end-to-end, six degree-of-freedom, multibody computer simulation of the Mars Science Laboratory Entry, Descent, and Landing sequence was developed at the NASA Langley Research Center. In-flight data gathered during the successful landing is compared to pre-flight statistical distributions, predicted by the simulation. These comparisons provide insight into both the accuracy of the simulation and the overall performance of the vehicle.

Way, David W.↗

NASA NTRSDate not supplied

Flight Testing of In-Time Safety Assurance Technologies for UAS Operations

Ongoing research at NASA is driven by a strategic plan defined by the Aeronautics Research Mission Directorate and a vision for future In-Time Aviation Safety Management Systems (IASMS) as described by the National Academies. In both visions, system safety awareness and provision are expanded through increased access to relevant data; integrated analysis and predictive capabilities; improved real-time detection and alerting of domain-specific hazards; decision support, and in some cases, automated risk mitigation strategies. One primary research focus is to develop means by which more timely (i.e., “in-time”) actions may be taken to mitigate precursors, anomalies, or trends that are observed during operations. In this paper, we describe such means as a collection of Services, Functions, and Capabilities (SFCs) that are supported by an underlying information system. For example, an integrated risk assessment capability is envisioned that continuously monitors safety-related metrics and margins and recommends timely operational changes. Assessment functions and/or services can be based on data analytics and predictive models derived from heterogeneous data sets that span relevant indicator metrics and their time histories. Likewise, on-board functions can identify and reduce susceptibility to precursor conditions that have led (and can lead) to aircraft loss-of-control or out-of-control accidents. This paper summarizes development and testing of such an information system tailored to hazards anticipated for future highly autonomous flight missions near and over densely populated areas. Testing is accomplished via simulation and by using small, unmanned aircraft operating over a test range at NASA’s Langley Research Center. Flight plans and test scenarios are defined to emulate several use-cases, including package delivery; reconnaissance; fire management; and urban air taxi vertiport operations. Two test phases are summarized with Phase 1 occurring in (2019-2020) and Phase 2 ongoing (2021-present). Results focus on SFC performance, technology readiness level assessment, and requirements discovery/validation. Companion papers are cited throughout for additional details on the recent testing.

safety management↗

NASA NTRS2022

Identification of Best Practices for Predicting Inlet Performance Using FUN3D Part 2: Installed Inlets.

A series of studies were performed to assess the impacts of boundary condition type and placement, grid reﬁnement, and modeling parameters such as turbulence model and ﬂux limiter on the predicted inlet performance for installed inlet conﬁgurations using the FUN3D ﬂow solver. Two conﬁgurations were considered for the study; a wall-mounted Boundary Layer Ingestion (BLI) inlet and the C607 propulsion model tested in the 8x6 Supersonic Wind Tunnel at the NASA Glenn Research Center. The results of the studies were to be used to recommend best practices, as well as to assess the accuracy of FUN3D for inlet predictions. The results of BLI inlet stud-ies showed a minimal impact of grid reﬁnement on the predicted inlet performance for a constant mass ﬂow rate through the inlet. For the C607 propulsion model, the results showed that while the FUN3D predictions at the Aerodynamic Inter-face Plane (AIP) qualitatively agree with the experimental data, FUN3D showed a tendency to overpredict the circumferential distortion metric (IDCmax) and un-derpredict both the radial distortion metric (IDRmax) and the pressure recovery at the AIP (PRAIP ), with the diﬀerences between FUN3D and the experimental data increasing with increasing grid reﬁnement and Mach number. Additionally, the outﬂow boundary location studies performed for both geometries showed that the solution at the AIP was not signiﬁcantly impacted by the outﬂow boundary location as long as it was not placed at the location of the AIP. The modeling parameter studies did not indicate a path forward for improved predictions for either inlet con-ﬁguration. Finally, comparisons between the mass ﬂow plug and outﬂow geometry versions of the C607 propulsion model illustrated favorable agreement, which indi-cates that the diﬀerences observed are not caused by the outﬂow boundary model for this problem. This problem poses signiﬁcant challenges to Reynolds-averaged Navier-Stokes (RANS) solvers due to the presence of shocks and ﬂow separation in the inlet.

FUN3D↗

NASA NTRS2013

Assessment of the Mars Science Laboratory Entry, Descent, and Landing Simulation

On August 5, 2012, the Mars Science Laboratory rover, Curiosity, successfully landed inside Gale Crater. This landing was only the seventh successful landing and fourth rover to be delivered to Mars. Weighing nearly one metric ton, Curiosity is the largest and most complex rover ever sent to investigate another planet. Safely landing such a large payload required an innovative Entry, Descent, and Landing system, which included the first guided entry at Mars, the largest supersonic parachute ever flown at Mars, and a novel and untested Sky Crane landing system. A complete, end-to-end, six degree-of-freedom, multi-body computer simulation of the Mars Science Laboratory Entry, Descent, and Landing sequence was developed at the NASA Langley Research Center. In-flight data gathered during the successful landing is compared to pre-flight statistical distributions, predicted by the simulation. These comparisons provide insight into both the accuracy of the simulation and the overall performance of the vehicle.

Way, David W.↗

NASA NTRSDate not supplied

Comparisons of Mixing Efficiency for the Strut Fuel Injector Obtained from Large-Eddy and Reynolds-Averaged Simulations, and Experiments

Mixing efficiency is obtained for a strut fuel injector at hypervelocity flow conditions by using large-eddy simulations (LES), Reynolds-averaged simulations (RAS), and experiments. The injector and flow conditions have been previously investigated by using RAS and experiments as a part of the Enhanced Injection and Mixing Project (EIMP) at the NASA Langley Research Center (LaRC). Because the fidelity of LES is a strong function of the grid, the mixing efficiency is obtained on two grids, the coarser of which is a factor of two coarser in each of the three dimensions with respect to the fine grid. The RAS uses the two-equation linear eddy viscosity and diffusivity modeling of Menter. In RAS, the species diffusivity model exhibits a strong dependence on the turbulent Schmidt number, which is often adjusted until some metric of engineering interest, such as the mixing efficiency, matches the experimental data. In the absence of experimental data, scale-resolving simulations, such as LES, have been proposed as surrogates for experiments that could provide the data needed to “calibrate” the turbulent Schmidt number in the RAS models. This approach is followed because LES requires significantly more computational resources (CPU, data storage, and time) than RAS, making it prohibitive for use in many engineering applications and specifically for parameter exploration or optimization. Here we examine the mixing efficiency obtained from several RAS with different values of the turbulent Schmidt number, and compare the results with those obtained from the LES and experiments. In addition, the least squares fitting approach was used to demonstrate how to obtain an estimate for the turbulent Schmidt number from LES analytically. These estimates were then used together with prior knowledge about RAS model sensitivity to select a turbulence model that was expected to best match the LES data.

LES↗

NASA NTRSDate not supplied

Comparisons of Mixing Efficiency for the Strut Fuel Injector Obtained from Large-Eddy and Reynolds-Averaged Simulations, and Experiments

LES↗

NASA NTRS2023

Characterization of Errors in Satellite-Based HCHO/NO 2 Tropospheric Column Ratios With Respect to Chemistry, Column-to-PBL Translation, Spatial Representation, and Retrieval Uncertainties

The availability of formaldehyde (HCHO) (a proxy for volatile organic compound reactivity) and nitrogen dioxide (NO 2 ) (a proxy for nitrogen oxides) tropospheric columns from ultraviolet–visible (UV–Vis) satellites has motivated many to use their ratios to gain some insights into the near-surface ozone sensitivity. Strong emphasis has been placed on the challenges that come with transforming what is being observed in the tropospheric column to what is actually in the planetary boundary layer (PBL) and near the surface; however, little attention has been paid to other sources of error such as chemistry, spatial representation, and retrieval uncertainties. Here we leverage a wide spectrum of tools and data to quantify those errors carefully. Concerning the chemistry error, a well-characterized box model constrained by more than 500 h of aircraft data from NASA's air quality campaigns is used to simulate the ratio of the chemical loss of HO 2 + RO 2 (LRO x ) to the chemical loss of NO x (LNO x ). Subsequently, we challenge the predictive power of HCHO/NO 2 ratios (FNRs), which are commonly applied in current research, in detecting the underlying ozone regimes by comparing them to LRO x /LNO x . FNRs show a strongly linear (R 2 =0.94) relationship with LRO x /LNO x , but only on the logarithmic scale. Following the baseline (i.e., ln(LRO x /LNO x ) = −1.0 ± 0.2) with the model and mechanism (CB06, r2) used for segregating NO x -sensitive from VOC-sensitive regimes, we observe a broad range of FNR thresholds ranging from 1 to 4. The transitioning ratios strictly follow a Gaussian distribution with a mean and standard deviation of 1.8 and 0.4, respectively. This implies that the FNR has an inherent 20 % standard error (1σ) resulting from not accurately describing the RO x –HO x cycle. We calculate high ozone production rates (PO 3 ) dominated by large HCHO × NO 2 concentration levels, a new proxy for the abundance of ozone precursors. The relationship between PO 3 and HCHO × NO 2 becomes more pronounced when moving towards NO x -sensitive regions due to nonlinear chemistry; our results indicate that there is fruitful information in the HCHO × NO 2 metric that has not been utilized in ozone studies. The vast amount of vertical information on HCHO and NO 2 concentrations from the air quality campaigns enables us to parameterize the vertical shapes of FNRs using a second-order rational function permitting an analytical solution for an altitude adjustment factor to partition the tropospheric columns into the PBL region. We propose a mathematical solution to the spatial representation error based on modeling isotropic semivariograms. Based on summertime-averaged data, the Ozone Monitoring Instrument (OMI) loses 12 % of its spatial information at its native resolution with respect to a high-resolution sensor like the TROPOspheric Monitoring Instrument (TROPOMI) (> 5.5 × 3.5 km 2 ). A pixel with a grid size of 216 km 2 fails at capturing ∼ 65 % of the spatial information in FNRs at a 50 km length scale comparable to the size of a large urban center (e.g., Los Angeles). We ultimately leverage a large suite of in situ and ground-based remote sensing measurements to draw the error distributions of daily TROPOMI and OMI tropospheric NO 2 and HCHO columns. At a 68 % confidence interval (1σ), errors pertaining to daily TROPOMI observations, either HCHO or tropospheric NO 2 columns, should be above 1.2–1.5 × 10 16 molec. cm −2 to attain a 20 %–30 % standard error in the ratio. This level of error is almost non-achievable with the OMI given its large error in HCHO. The satellite column retrieval error is the largest contributor to the total error (40 %–90 %) in the FNRs. Due to a stronger signal in cities, the total relative error (< 50 %) tends to be mild, whereas areas with low vegetation and anthropogenic sources (e.g., the Rocky Mountains) are markedly uncertain (> 100 %). Our study suggests that continuing development in the retrieval algorithm and sensor design and calibration is essential to be able to advance the application of FNRs beyond a qualitative metric.

Amir H. Souri↗

NASA NTRSDate not supplied

In-Depth Analysis of Subject Functional Performance and Subjective Feedback Data for Evaluating Argos Simulation Quality

Mechanical offloading systems such as the Active Response Gravity Offload System (ARGOS) at NASA Johnson Space Center (JSC) are used to simulate various partial gravity environments. ARGOS offloads pressurized suited subjects through a gimbaling pivot point system attached to a volumetric Portable Life Support System (PLSS). The pivot point can be configured to multiple locations with respect to the human-suit system center of gravity (CG). Previous work has tested and documented the interaction between different pivot point locations and measured CG. Observations indicated that small changes in pivot point location substantially affect the stability and functional performance (simulation quality) of a subject. This led to the development of a standardized gimbal assessment protocol to assess the functional performance of a pressurized suited subject as a function of the pivot point location, using the data obtained from a variety of planetary suit mobility tasks. As a result, an expansive repository of CG-related task metrics was generated from numerous ARGOS spacesuit test events, for different gimbal configurations and different test subjects. Based on the evaluation metrics and observed trends, several pivot point locations were iteratively identified to determine an “appropriate/optimal” configuration. This study thus describes the in-depth analysis of the CG evaluation metrics to better quantify trends and determine if specific factors are strongly associated with appropriate/optimal configurations. Quantitative and qualitative variables relating to subject task performance, subjective feedback, and anthropometry will be evaluated via probabilistic methods. The results from this study are expected to improve our understanding of optimal ARGOS gimbal settings, which will better inform the gimbal configuration identification process and improve simulation quality for extravehicular activity (EVA) training.

Joseph Yao↗