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At least 595 records · Page 33
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NASA NTRS2025

Identifying Cognitive Capabilities Required for Optimal Exploration EVA Performance: A Cognitive Task Analysis

BACKGROUND Extravehicular activity (EVA) is one of the most dangerous and cognitively demanding actions that astronauts can execute, and the cognitive demands associated with future exploration EVA on the Moon and Mars are expected to be higher compared to EVA currently conducted from the International Space Station (ISS). Decrements in cognitive performance present an important risk to crew safety during exploration mission class EVA. Yet there is currently insufficient characterization of the cognitive capabilities required prior to, during, and following EVA. Furthermore, it is unclear which cognitive domains are most important for conducting mission critical decisions with crew safety implications. To address this gap, we conducted a cognitive task analysis of exploration EVA to characterize the cognitive capabilities, critical safety decisions, and contributing factors (e.g., lunar communications delay) important to monitor for optimal performance in future exploration EVA. This cognitive task analysis was conducted through interviews with astronauts and subject matter experts in EVA research and operations. Interviews focused on exploration EVA and elicited feedback on the cognitive capabilities required for specific EVA tasks and subtasks. The information from this cognitive task analysis will help close the gap in our understanding of the key cognitive capabilities required for safe decision-making during exploration mission class EVA on the Moon and Mars. METHOD We used an applied cognitive task analysis method1 over the course of interviews with a total of 15 NASA astronauts and subject matter experts in EVA. Each interview was led by a scientist with expertise in cognitive neuroscience from the Behavioral Health & Performance (BHP) Laboratory at NASA Johnson Space Center. Notes were taken by a research coordinator in the BHP Laboratory and interviews were recorded on Microsoft Teams to ensure the accuracy of notetaking. In the first interview protocol, participants were asked about the specific tasks and cognitive demands associated with EVA. This provided a high-level overview of the steps involved in the major tasks conducted during exploration EVA, as well as which of the steps require the most cognitive skill. Next, participants completed a knowledge audit, which employs a set of probes designed to describe types of domain knowledge of skill and elicit appropriate examples. In the second interview protocol, completed with a separate set of subject matter experts, interviewees were asked to complete a simulated incapacitated crew rescue (ICR) scenario2, which provided specific context that allowed probing around relevant issues such as situational awareness and potential errors. Experts were then asked to identify the knowledge, skills, and abilities (KSAs) underlying each EVA task and to provide ratings on the importance and cognitive demand of each KSA. Finally, participants also described the most likely and consequential critical safety incidents related to decrements in cognitive performance during exploration EVA and assessed the impact of lunar communication delay on cognitive performance. RESULTS & DISCUSSION Interviews for this cognitive task analysis are nearly complete and results will be presented in full at IWS 2025. Results will include a summary of all expert ratings of EVA tasks and subtasks, qualitative summaries of content from each interview part, and a discussion of future directions for products addressing cognitive performance monitoring and cognitive domain mapping in exploration EVA.

S R Anderson↗
NASA NTRS2024

PALMO: An OVERFLOW Machine Learning Airfoil Performance Database

The OVERFLOW Machine Learning Airfoil Performance (PALMO) database has been created to enable robust modeling of airfoil performance in a variety of applications. The database uses OVERFLOW simulation data second-order accurate in time and fourth-order accurate in space with Spalart-Allmaras turbulence closure. The foundation of the in-development PALMO database is the airfoil base cube. Each base cube includes simulation data parametrized over a range of Mach numbers, Reynolds numbers, and angles-of-attack. This first release of the database includes the NACA 4-series airfoils, with parametrization in airfoil thickness and camber from an NACA 0006 to an NACA 4424. In total, 52,480 NACA 4-series calculations were run on the NASA High-End Compute Capability (HECC) supercomputer and the corresponding airfoil performance coefficients are embedded in the Appendix of this document for public distribution. This provides high-order-accurate simulation data covering a wide range of aerospace design applications, which enables users to develop OVERFLOW-quality airfoil performance look-up tables without additional high-performance computing. In addition to engineering design and analysis of aerospace vehicles, PALMO is well suited to be a benchmark dataset for the development and testing of machine learning methods in aerospace engineering. Downstream surrogate models enable OVERFLOW- quality airfoil performance predictions for any arbitrary combination of camber, thickness, Mach number, Reynolds number, and angle-of-attack within the bounds of the database.

Database↗
NASA NTRS2026

Performance Optimization for Lunar Extravehicular Activity Readiness (POLAR) Study: Methods Paper

To better understand which aspects of physical fitness may be most related to performance during Lunar surface operations and thereby help to inform the current NASA fitness standards, much can be learned from fields encompassing the “tactical athlete.” Other physically demanding professions such as law enforcement, military, or rescue professionals often require candidates to meet occupationally-relevant fitness standards. The determination of such standards is a multistep process, including both objective and subjective measures, to determine tasks essential to occupational performance and identify the minimal fitness profile needed to meet physical demands of the job. Notably, fitness is only one component which may contribute to the demands of astronaut selection, flight assignment, and occupational performance. Utilizing a framework to systematically determine which domains of fitness most contribute to relevant job tasks can aid in the refinement of current NASA-STD-3001 fitness standards. Therefore, NASA’s Exercise Physiology & Countermeasures Laboratory conducted the Performance Optimization for Lunar Extravehicular Activity Readiness (POLAR) study to identify and examine a comprehensive list of fitness tests (including NASA-STD-3001 assessments: 1-Repetition Maximum [1-RM] bench press and deadlift) and determine preliminary relationships between identified fitness parameters and novel Artemis-relevant tasks to help inform future investigations for the continued development of aerobic and muscular fitness standards for surface EVAs. This was accomplished through 1) a review of the literature relating fitness assessments to simulated or real EVA performance to identify fitness tests that are most correlated with simulated EVA task performance; 2) a task analysis following a modified framework for physical employment standards development to down select mission critical tasks; and 3) development and pilot testing of a novel, portable Artemis-relevant EVA task circuit to relate to a battery of fitness assessments. The current report describes the methodology used to complete the task analysis, EVA task circuit development, and the pilot study.

Nicole C Strock↗
NASA NTRS2026

Predicting Operational Performance of xEMU Boot at Lunar South Pole Temperatures using Thermal Desktop ®

The spacesuit boots that will be used on Artemis lunar south pole surface missions will be exposed to extremely cold temperatures (down to ~50 K). To assess the performance of the government’s Exploration Extravehicular Mobility Unit (xEMU) lunar boot in these permanently shadowed regions, testing was performed at the Jet Propulsion Lab (JPL) in the Cryogenic Ice Transfer, Acquisition Development, and Excavation Laboratory (CITADEL) thermal vacuum (TVAC) chamber. This paper documents the data analysis, thermal boot model correlation, and operational predictions conducted using data from the xEMU CITADEL TVAC test. Expected thermal conductances within the boot and between the boot and environment were calculated from test data, which was then used as an initial guess for conductances within a Thermal Desktop (TD) model. Correlation of the TD model using the internal SOLVER feature was performed across 10 different test points which varied external temperature, internal boot ventilation flowrate, and contact pressure. Operational performance at the lunar south pole was then predicted using results from the correlated model. While the predictions provide evidence for acceptable performance of the boots at the 100K environment test point, there is still substantial uncertainty in performance, especially at the 48K test point. This uncertainty is due in part to testing limitations such as contacting the foot to a hard metal plate rather than granular regolith, and model limitations such as the lack of a realistic foot model. These limitations and their impacts are addressed in detail in this paper. The results of this test series and model correlation underscore the importance of additional improved testing and modeling for characterizing the expected thermal resistance between the outside of the boot and the lunar surface.

Spacesuit↗
NASA NTRS1993

Performance and mood-state parameters during 30-day 6 degrees head-down bed rest with exercise training

The study was designed to determine if performance and mood impairments occur in bed-rested subjects, and if different exercise-training regimens modify or prevent them. Eighteen normal, healthy men were divided on the basis of age, peak oxygen uptake, and maximal isometric knee extension strength into three similar groups: no exercise (NOE), isotonic exercise (ITE), and isokinetic exercise (IKE). A 15-min battery of 10 performance tests and 8 mood and 2 sleep scales were administered daily during ambulatory control, 30 d of absolute bed rest (BR), and 4 d of ambulatory recovery. Performance test proficiency increased (p < 0.05) for all three groups during BR in 7 of 10 tests and there were no consistent significant differences between the three groups. However, during BR, the ITE group was distinguished from the other groups by a decline (p < 0.05) in the activation mood dimension and in two of its constituent scales (motivation and concentration), and by improvement (p < 0.05) in the trouble-falling-asleep and psychological-tension scales. Since few deleterious changes in performance and mood occurred in the three groups and did not exceed baseline ambulatory levels, we conclude that mood and performance did not deteriorate in response to prolonged BR and were not altered by exercise training. However, the decline in activation mood scales in the ITE group may reflect overtraining or excess total workload in this group.

NASA Center ARC↗
NASA NTRS2003

Effects of a psychophysiological system for adaptive automation on performance, workload, and the event-related potential P300 component

The present study examined the effects of an electroencephalographic- (EEG-) based system for adaptive automation on tracking performance and workload. In addition, event-related potentials (ERPs) to a secondary task were derived to determine whether they would provide an additional degree of workload specificity. Participants were run in an adaptive automation condition, in which the system switched between manual and automatic task modes based on the value of each individual's own EEG engagement index; a yoked control condition; or another control group, in which task mode switches followed a random pattern. Adaptive automation improved performance and resulted in lower levels of workload. Further, the P300 component of the ERP paralleled the sensitivity to task demands of the performance and subjective measures across conditions. These results indicate that it is possible to improve performance with a psychophysiological adaptive automation system and that ERPs may provide an alternative means for distinguishing among levels of cognitive task demand in such systems. Actual or potential applications of this research include improved methods for assessing operator workload and performance.

Task Performance and Analysis↗
NASA NTRS2005

Circadian rhythms, sleep, and performance in space

Maintaining optimal alertness and neurobehavioral functioning during space operations is critical to enable the National Aeronautics and Space Administration's (NASA's) vision "to extend humanity's reach to the Moon, Mars and beyond" to become a reality. Field data have demonstrated that sleep times and performance of crewmembers can be compromised by extended duty days, irregular work schedules, high workload, and varying environmental factors. This paper documents evidence of significant sleep loss and disruption of circadian rhythms in astronauts and associated performance decrements during several space missions, which demonstrates the need to develop effective countermeasures. Both sleep and circadian disruptions have been identified in the Behavioral Health and Performance (BH&P) area and the Advanced Human Support Technology (AHST) area of NASA's Bioastronautics Critical Path Roadmap. Such disruptions could have serious consequences on the effectiveness, health, and safety of astronaut crews, thus reducing the safety margin and increasing the chances of an accident or incident. These decrements oftentimes can be difficult to detect and counter effectively in restrictive operational environments. NASA is focusing research on the development of optimal sleep/wake schedules and countermeasure timing and application to help mitigate the cumulative effects of sleep and circadian disruption and enhance operational performance. Investing research in humans is one of NASA's building blocks that will allow for both short- and long-duration space missions and help NASA in developing approaches to manage and overcome the human limitations of space travel. In addition to reviewing the current state of knowledge concerning sleep and circadian disruptions during space operations, this paper provides an overview of NASA's broad research goals. Also, NASA-funded research, designed to evaluate the relationships between sleep quality, circadian rhythm stability, and performance proficiency in both ground-based simulations and space mission studies, as described in the 2003 NASA Task Book, will be reviewed.

Review↗
NASA NTRS2007

A Covariance Analysis Tool for Assessing Fundamental Limits of SIM Pointing Performance

This paper presents a performance analysis of the instrument pointing control system for NASA's Space Interferometer Mission (SIM). SIM has a complex pointing system that uses a fast steering mirror in combination with a multirate control architecture to blend feed forward information with feedback information. A pointing covariance analysis tool (PCAT) is developed specifically to analyze systems with such complexity. The development of PCAT as a mathematical tool for covariance analysis is outlined in the paper. PCAT is then applied to studying performance of SIM's science pointing system. The analysis reveals and clearly delineates a fundamental limit that exists for SIM pointing performance. The limit is especially stringent for dim star targets. Discussion of the nature of the performance limit is provided, and methods are suggested to potentially improve pointing performance.

pointing control↗
NASA NTRS2013

Performance Measurement of Advanced Stirling Convertors (ASC-E3)

NASA Glenn Research Center (GRC) has been supporting development of the Advanced Stirling Radioisotope Generator (ASRG) since 2006. A key element of the ASRG project is providing life, reliability, and performance testing data of the Advanced Stirling Convertor (ASC). The latest version of the ASC (ASC-E3, to represent the third cycle of engineering model test hardware) is of a design identical to the forthcoming flight convertors. For this generation of hardware, a joint Sunpower and GRC effort was initiated to improve and standardize the test support hardware. After this effort was completed, the first pair of ASC-E3 units was produced by Sunpower and then delivered to GRC in December 2012. GRC has begun operation of these units. This process included performance verification, which examined the data from various tests to validate the convertor performance to the product specification. Other tests included detailed performance mapping that encompassed the wide range of operating conditions that will exist during a mission. These convertors were then transferred to Lockheed Martin for controller checkout testing. The results of this latest convertor performance verification activity are summarized here.

Stirling Cycle↗
NASA NTRS2016

Wind Tunnel and Hover Performance Test Results for Multicopter UAS Vehicles

There is currently a lack of published data for the performance of multicopter unmanned aircraft system (UAS) vehicles, such as quadcopters and octocopters, often referred to collectively as drones. With the rapidly increasing popularity of multicopter UAS, there is interest in better characterizing the performance of this type of aircraft. By studying the performance of currently available vehicles, it will be possible to develop models for vehicles at this scale that can accurately predict performance and model trajectories. This paper describes a wind tunnel test that was recently performed in the U.S. Army's 7- by 10-ft Wind Tunnel at NASA Ames Research Center. During this wind tunnel entry, five multicopter UAS vehicles were tested to determine forces and moments as well as electrical power as a function of wind speed, rotor speed, and vehicle attitude. The test is described here in detail, and a selection of the key results from the test is presented.

Multicopter UAS↗
NASA NTRS2016

NAS-Wide Fast-Time Simulation Study for Evaluating Performance of UAS Detect-and-Avoid Alerting and Guidance Systems

This presentation contains the analysis results of NAS-wide fast-time simulations with UAS and VFR traffic for a single day for evaluating the performance of Detect-and-Avoid (DAA) alerting and guidance systems. This purpose of this study was to help refine and validate MOPS alerting and guidance requirements. In this study, we generated plots of all performance metrics that are specified by RTCA SC-228 Minimum Operational Performance Standards (MOPS): 1) to evaluate the sensitivity of alerting parameters on the performance metrics of each DAA alert type: Preventive, Corrective, and Warning alerts and 2) to evaluate the effect of sensor uncertainty on DAA alerting and guidance performance.

DAA Alerting Performance↗
NASA NTRS2015

Integrating Human Performance Measures into Space Operations: Beyond Our Scheduling Capabilities?

Current planning and scheduling software tools for International Space Station (ISS) support different flight controller teams as they plan daily space operations. Planning and scheduling tools capabilities include integrating digitized ISS state inputs, evaluating their expected future states, and propagating them over time. Extensive, custom-made computational models of operations, of objectives, and of operational constraints help ISS flight controllers identify where scheduled events violate constraints. Based on the current capabilities of these tools, this paper proposes how human performance measures could be better integrated into planning and scheduling tools for space mission operations. Future integration of human performance measures could be applied to state inputs (in this case, the astronaut’s state) and to modeling human performance operational constraints & operational objectives (i.e., assigned activities) with parameters that are relevant to human performance measures. Gaps between the state-of-the-art for human performance modeling and planning tools for future exploration missions are identified.

space operations↗
NASA NTRS2020

Model Rotor Hover Performance at Low Reynolds Number

Hover performance data from four key experiments has been analyzed in detail to shed some light on model rotor hover performance at low Reynolds number. Each experiment used the simplest blade geometry. The blades were constant chord and untwisted. Three experiments used blades with the NACA 0012 airfoil from root to tip. The NACA 0015 was used in the earliest test. The four experiments provide data spanning a Reynolds number range of 136,500 to 548,700. The specific objective of this report is to ask and answer two questions: 1. Does blade aspect ratio influence hover performance or is rotor solidity the fundamental rotor geometry parameter for practical engineering purposes? ANSWER: Rotor solidity is the fundamental rotor geometry parameter for practical engineering purposes. Any effect of blade aspect ratio appears to be such a secondary variable that its effect lies within the range of experimental error. 2. Is Reynolds number a significant factor in scaling up hover performance to full-scale rotor performance? The answer is twofold. ANSWER: (a) Reynolds number effects on the increase of power with thrust do not appear to be a significant factor for practical engineering purposes, and (b) Reynolds number effects on minimum profile power at or very near zero rotor thrust could not be clearly established primarily because the low torque levels could not be accurately measured with the test equipment used. This has led to significant data scatter. A number of other observations can be made based on the analysis provided herein. For instance: 1. The test matrices used in the four key references contained far too few data points. A collective pitch variation of four or five data points is insufficient to establish experimental accuracy and data repeatability. 2. A common property of the power-versus-thrust (raised to the 3/2 exponent) graphs was that this curve was linear below the onset of blade stall. 3. The blade-to-blade interference at or near zero thrust may, in fact, be creating a turbulent flow field such that the effective Reynolds number at a blade element is considerably greater than what theories using two-dimensional (2D) airfoil properties at a blade element would calculate. 4. Definitive experiments answering the two key questions have yet to be made.

Model Rotor Hover Performance↗
NASA NTRSDate not supplied

Performance and Portability of a Linear Solver Across Emerging Architectures

A linear solver algorithm used by a large-scale unstructured-grid computational fluid dynamics application is examined for a broad range of familiar and emerging architectures. Efficient implementation of a linear solver is challenging on recent CPUs offering vector architectures. Vector loads and stores are essential to effectively utilize available memory bandwidth on CPUs, and maintaining performance across different CPUs can be difficult in the face of varying vector lengths offered by each. A similar challenge occurs on GPU architectures, where it is essential to have coalesced memory accesses to utilize memory bandwidth effectively. In this work, we demonstrate that restructuring a computation, and possibly data layout, with regard to architecture is essential to achieve optimal performance by establishing a performance benchmark for each target architecture in a low level language such as vector intrinsics or CUDA. In doing so, we demonstrate how a linear solver kernel can be mapped to Intel® Xeon™ and Xeon Phi™, Marvell® ThunderX2®, NEC® SX-Aurora™ TSUBASA Vector Engine, and NVIDIA® and AMD® GPUs. We further demonstrate that the required code restructuring can be achieved in higher level programming environments such as OpenACC, OCCA, and Intel® OneAPI™/SYCL, and that each generally results in optimal performance on the target architecture. Relative performance metrics for all implementations are shown, and subjective ratings for ease of implementation and optimization are suggested.

Programming models↗
NASA NTRSDate not supplied

Precision Landing Performance of a Human-Scale Lunar Lander Using a Generalized Simulation Framework

NASA has established goals of returning humans to Moon with an initial landing by 2024 and a subsequent sustained presence by 2028, which will require technological advances in spacecraft navigation to enable precision landing. The ability to assess the navigation performance of these new and existing technologies is critical to identifying areas of risk reduction and investment. To that end, the Safe and Precise Landing Integrated Capabilities Evolution (SPLICE) project has demonstrated that a detailed six degree-of-freedom integrated performance simulation framework can provide information on and assessment of expected navigation performance. This framework incorporates engineering models of the on-board spacecraft guidance, navigation, and control systems at varying levels of fidelity. Recent advances in the development of this integrated performance simulation permit running these systems “in-the-loop,” rather than assuming perfect knowledge of the spacecraft states. This development, coupled with fast simulation time and modularization of the various system models, enables a wide variety of system trades to be assessed at once. This paper presents a summary of the advances in the SPLICE simulation framework, updates to the spacecraft navigation models, and an application of the framework to characterize the precision landing performance of a human-scale lunar lander. A series of trade studies examining effects of ground state update qualities shows that given all other assumptions, sufficiently accurate Deep Space Network (DSN) measurements can enable safe and precise human-scale Lunar landings.

Spacecraft navigation↗
NASA NTRSDate not supplied

Normative Baseline Oculomotor Performance

Future missions to the moon or Mars will require the crew to monitor and assess their health and performance more autonomously, necessitating approaches that are easily useable and interpretable by non-clinicians. The eye-movement-based performance metrics (oculometrics) obtained from NASA-patented technology developed at the Visuomotor Control Laboratory can reliably detect and discriminate the source of mild neural impairment relative to an individual’s baseline visual and sensorimotor performance and can predict performance in manual control tasks. This study aims to develop a database of normative performance that can be used to enable the detection of impairment without a within-subject baseline and to facilitate power analyses for the design of future studies.

eye movements↗
NASA NTRS1972

Effect of continuous gamma-ray exposure on performance of learned tasks and effect of subsequent fractionated exposures on blood-forming tissue

Sixteen monkeys trained to perform continuous and discrete-avoidance and fixed-ratio tasks with visual and auditory cues were performance-tested before, during, and after 10-day gamma-ray exposures totaling 0, 500, 750, and 1000 rads. Approximately 14 months after the performance-test exposures, surviving animals were exposed to 100-rad gamma-ray fractions at 56-day intervals to observe injury and recovery patterns of blood-forming tissues. The fixed-ratio, food-reward task performance showed a transient decline in all dose groups within 24 hours of the start of gamma-ray exposure, followed by recovery to normal food-consumption levels within 48 to 72 hours. Avoidance tasks were performed successfully by all groups during the 10-day exposure, but reaction times of the two higher dose-rate groups in which animals received 3 and 4 rads per hour or total doses of 750 and 1000 rads, respectively, were somewhat slower.

Spalding, J. F.↗
NASA NTRS1972

A study of the effect of selected material properties on the ablation performance of artificial graphite

Eighteen material properties were measured on 45 different, commercially available, artificial graphites. Ablation performance of these same graphites were also measured in a Mach 2 airstream at a stagnation pressure of 5.6 atm. Correlations were developed, where possible, between pairs of the material properties. Multiple regression equations were then formulated relating ablation performance to the various material properties, thus identifying those material properties having the strongest effect on ablation performance. These regression equations reveal that ablation performance in the present test environment depends primarily on maximum grain size, density, ash content, thermal conductivity, and mean pore radius. For optimization of ablation performance, grain size should be small, ash content low, density and thermal conductivity high, and mean pore radius large.

Maahs, H. G.↗