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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.

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At least 1,189 records · Page 66

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NASA NTRS2003

Prediction of muscle performance during dynamic repetitive movement

BACKGROUND: During long-duration spaceflight, astronauts experience progressive muscle atrophy and often perform strenuous extravehicular activities. Post-flight, there is a lengthy recovery period with an increased risk for injury. Currently, there is a critical need for an enabling tool to optimize muscle performance and to minimize the risk of injury to astronauts while on-orbit and during post-flight recovery. Consequently, these studies were performed to develop a method to address this need. METHODS: Eight test subjects performed a repetitive dynamic exercise to failure at 65% of their upper torso weight using a Lordex spinal machine. Surface electromyography (SEMG) data was collected from the erector spinae back muscle. The SEMG data was evaluated using a 5th order autoregressive (AR) model and linear regression analysis. RESULTS: The best predictor found was an AR parameter, the mean average magnitude of AR poles, with r = 0.75 and p = 0.03. This parameter can predict performance to failure as early as the second repetition of the exercise. CONCLUSION: A method for predicting human muscle performance early during dynamic repetitive exercise was developed. The capability to predict performance to failure has many potential applications to the space program including evaluating countermeasure effectiveness on-orbit, optimizing post-flight recovery, and potential future real-time monitoring capability during extravehicular activity.

Physical Endurance/physiology↗

NASA NTRSDate not supplied

Strategies for Automation of Model Tuning in Multifidelity Trajectory Uncertainty Propagation

Multi-model Monte Carlo methods are efficient strategies to perform forward uncertainty quantification studies in entry, descent, and landing (EDL) applications. These multi-model methods are based on the classical Monte Carlo estimator, but fuse predictions from several low-fidelity models to obtain estimators with greater precision given a prescribed computational budget. The effectiveness of these approaches relies on the magnitudes of correlations between the low-fidelity models and the high-fidelity model, as well as the relative computational costs of all models. Identifying and exploiting the best trade-off between correlation and cost, which ultimately depends on the selection of hyperparameters in the low-fidelity models, is a task often performed by hand or simply inspired by the deterministic understanding available for a specific application. This work extends a preliminary effort,

Marten Thompson↗

NASA NTRS1996

Maintaining safety and high performance on shiftwork

This review of the shiftwork area focuses on aspects of safety and productivity. It discusses the situations in which shiftworker performance is critical, the types of problem that can develop and the reasons why shiftworker performance can be impaired. The review ends with a discnssion of the various advantages and disadvantages of several shift rotation systems, and of other possible solutions to the problem.

Review↗

NASA NTRSDate not supplied

Accuracy of Center of Pressure Determination via Motion Capture

BACKGROUND: This study was conducted to support the stability assessment for tasks in lunar gravity and exercises on a Vibration Isolation and Stabilization (VIS) system in microgravity based on the dynamic feasibility criterion of whether the calculated position of the center of pressure (COP) falls within the base of support (BOS) which outlines the subject’s feet. Motion capture data combined with biomechanical modeling and simulation allows the forces and moments between the human and the VIS platform to be computed and the position of the COP as well as the location and shape of the BOS to be determined. The goal of this study was to assess the accuracy of the COP trajectory calculated using motion capture-based data. METHODS AND RESULTS: To obtain the dynamic quantities from which COP is calculated, motion capture data is first collected in the 1g lab environment by recording the trajectories of passive retroreflective markers placed on a subject during exercise or performance of a given task. The OpenSim [1] inverse kinematics (IK) tool is used to fit a scaled subject model to recorded marker trajectories while minimizing marker error to obtain joint angles. Then, a custom OpenSim plugin [2] is used to determine the subject’s time-varying moment of inertia and its time derivative, center of mass (CM) position, velocity, and acceleration, as well as the angular momentum and its time derivative relative to the subject’s CM. Some of these quantities are not needed for modeling tasks performed on a stationary lunar surface but, due to the moving exercise platform, are needed to model VIS response to the subject’s motion. Hand positions, used in calculating a cable force if present, are recorded as well. These quantities are used to calculate the total force (F ⃗^((plate) )) and moment (M ⃗^((plate) )) exerted by the lunar surface or the VIS plate on the subject’s shoe soles. COP is then calculated from the following equations: r_x^((cop) )= M_z^((plate) )/F_y^((plate) ) and r_z^((cop) )= 〖-M〗_x^((plate) )/F_y^((plate) ), where the y axis is normal to the surface. COP accuracy for feasibility assessments is then determined by whether it falls within the BOS, which is also computed by the plugin. To study the accuracy of COP calculated from motion capture, we first investigated whether COP remained within the BOS, as it must, for exercises performed in the 1g lab environment. Standard exercises such as back squat and deadlift were analyzed, as well as more explosive exercises including hang clean and press. Cases in which the COP exited the BOS indicated that COP accuracy required further investigation. In this study, an exercise device with cables was used, so cable force modeling accuracy should also be considered. In a separate study, we collected motion capture and force plate data for twenty-seven motions not involving an exercise device. About a third were genuine countermeasures exercises (e.g., hang clean and press), some were relevant for lunar tasks (e.g., object pick up), and the rest were of a “unit test” nature (e.g., swaying back and forth or side to side). Motion capture-based COP positions were compared with force plate measured COP. We found that while force plate measured COP remained within the BOS, motion capture-based COP was observed to briefly exit the BOS on occasion. Techniques to mitigate IK artifacts and filtering of calculated data could be used to improve the agreement of calculated and measured results, resolving excursions from the BOS within this dataset. The mean error between calculated and measured COP was found to be less than 6 mm. Additionally, we derived and investigated equations for the COP in terms of the cable force, cable location, as well as the human CM position, acceleration, and angular momentum with respect to the CM, and analyzed them for sensitivity to errors in individual quantities. Several were found, but the most significant one was that when the vertical force on the feet approaches zero, indicating a near-detachment or ‘jump off’ condition, errors are amplified. This is consistent with the observation that in the absence of pressure, the concept of the center of pressure would become meaningless.

C A Bell↗

NASA NTRS1991

Perception of linear acceleration in weightlessness

Tests of the perception and use of linear acceleration sensory information were performed on the science crews of the Spacelab 1 (SL-1) and D-1 missions using linear 'sleds' in-flight (D-1) and pre-post flight. The time delay between the acceleration step stimulus and the subjective response was consistently reduced during weightlessness, but was neither statistically significant nor of functional importance. Increased variability of responses when going from one environment to the other was apparent from measurements on the first day of the mission and in the first days post-flight. Subjective reports of perceived motion during sinusoidal oscillation in weightlessness were qualitatively similar to reports on earth. In a closed-loop motion nulling task, enhanced performance was observed post-flight in all crewmembers tested in the Y or Z axes.

Arrott, Anthony P.↗

NASA NTRS1990

Perception of linear acceleration in weightlessness

Tests of the perception and use of linear acceleration sensory information were performed on the science crews of the Spacelab 1 (SL-1) and D-1 missions using linear "sleds" in-flight (D-1) and pre-post flight. The time delay between the acceleration step stimulus and the subjective response was consistently reduced during weightlessness, but was neither statistically significant nor of functional importance. Increased variability of responses when going from one environment to the other was apparent from measurements on the first day of the mission and in the first days post-flight. Subjective reports of perceived motion during sinusoidal oscillation in weightlessness were qualitatively similar to reports on earth. In a closed-loop motion nulling task, enhanced performance was observed post-flight in all crewmembers tested in the Y or Z axes.

NASA Discipline Number 16-10↗

NASA NTRS1986

Evaluating space station applications of automation and robotics technologies from a human productivity point of view

The role that automation, robotics, and artificial intelligence will play in Space Station operations is now beginning to take shape. Although there is only limited data on the precise nature of the payoffs that these technologies are likely to afford there is a general consensus that, at a minimum, the following benefits will be realized: increased responsiveness to innovation, lower operating costs, and reduction of exposure to hazards. Nevertheless, the question arises as to how much automation can be justified with the technical and economic constraints of the program? The purpose of this paper is to present a methodology which can be used to evaluate and rank different approaches to automating the functions and tasks planned for the Space Station. Special attention is given to the impact of advanced automation on human productivity. The methodology employed is based on the Analytic Hierarchy Process. This permits the introduction of individual judgements to resolve the confict that normally arises when incomparable criteria underly the selection process. Because of the large number of factors involved in the model, the overall problem is decomposed into four subproblems individually focusing on human productivity, economics, design, and operations, respectively. The results from each are then combined to yield the final rankings. To demonstrate the methodology, an example is developed based on the selection of an on-orbit assembly system. Five alternatives for performing this task are identified, ranging from an astronaut working in space, to a dexterous manipulator with sensory feedback. Computational results are presented along with their implications. A final parametric analysis shows that the outcome is locally insensitive to all but complete reversals in preference.

Bard, J. F.↗

NASA NTRS1985

Automated Portable Test (APT) System: overview and prospects

The Automated Portable Test (APT) System is a notebook-sized, computer-based, human-performance and subjective-status assessment system. It is now being used in a wide range of environmental studies (e.g., simulator aftereffects, flight tests, drug effects, and hypoxia). Three questionnaires and 15 performance tests have been implemented, and the adaptation of 30 more tests is underway or is planned. The APT System is easily transportable, is inexpensive, and has the breadth of expansion options required for field and laboratory applications. The APT System is a powerful and expandable tool for human assessment in remote and unusual environments.

Aerospace Medicine/instrumentation↗

DOE OSTI2024

Predicting seismic amplitudes with machine learning

The accurate estimation of seismic wave amplitude is vital to precisely determine the yield, magnitude, and event discrimination possible for a given network – a critical element in nuclear explosion monitoring. This task is complicated by several factors, including but not limited to radiation pattern, scattering effects, and crustal variations, which can lead to the attenuation or amplification of amplitude along a given raypath. In this report, we explore the novel application of machine learning to the task of seismic amplitude estimation by training a simple Artificial Neural Network (ANN) on an S-wave amplitude dataset from Lai et al. (2019). Attributes from this dataset used as input to the ANN included event-station distances, station locations (latitude, longitude), event locations (latitude, longitude), event depths, event magnitudes, radiation patterns, signal-to noise ratio (SNR) measurements (average-amplitude, peak-to-trough, maximum peak), and signal periods. We find that the trained ANN predicts S-wave amplitudes with a modest tendency toward underestimating the actual values, as indicated by a linear regression between predicted and actual data (slope: 0.892, intercept: -0.651). These results suggest that an ANN can perform this task, with potential for significant improvements through improved datasets, architectures, and parameter tuning.

45 MILITARY TECHNOLOGY, WEAPONRY, AND NATIONAL DEF↗

NASA NTRS2008

Engineering America's Future in Space: Systems Engineering Innovations for Sustainable Exploration

The National Aeronautics and Space Administration (NASA) delivers space transportation solutions for America's complex missions, ranging from scientific payloads that expand knowledge, such as the Hubble Space Telescope, to astronauts and lunar rovers destined for voyages to the Moon. Currently, the venerable Space Shuttle, which has been in service since 1981, provides U.S. capability for both crew and cargo to low-Earth orbit to construct the International Space Station, before the Shuttle is retired in 2010, as outlined in the 2006 NASA Strategic Plan. I In the next decade, NASA will replace this system with a duo of launch vehicles: the Ares I Crew Launch Vehicle/Orion Crew Exploration Vehicle and the Ares V Cargo Launch Vehicle/Altair Lunar Lander. The goals for this new system include increased safety and reliability, coupled with lower operations costs that promote sustainable space exploration over a multi-decade schedule. This paper will provide details of the in-house systems engineering and vehicle integration work now being performed for the Ares I and planned for the Ares V. It will give an overview of the Ares I system-level test activities, such as the ground vibration testing that will be conducted in the Marshall Center's Dynamic Test Stand to verify the integrated vehicle stack's structural integrity against predictions made by modern modeling and simulation analysis. It also will give information about the work in progress for the Ares I-X developmental test flight planned in 2009 to provide key data before the Ares I Critical Design Review. Activities such as these will help prove and refine mission concepts of operation, while supporting the spectrum of design and development tasks being performed by Marshall's Engineering Directorate, ranging from launch vehicles and lunar rovers to scientific spacecraft and associated experiments. Ultimately, the work performed will lead to the fielding of a robust space transportation solution that will carry international explorers and essential payloads for sustainable scientific discovery beyond planet Earth.

Dumbacher, Daniel L.↗

NASA NTRS2023

Developing a Hybrid Spacesuit Simulator as a Research Tool for Assessing Extravehicular Activity Relevant Workload

Conducting human tests in a pressurized spacesuit is limited by availability, cost, and manpower; however, pressurized spacesuits are not always needed depending on the objectives of testing, including the development and testing of new informatics capabilities. The Human Physiology, Performance, Protection & Operations Laboratory (H-3PO) at NASA is developing a Hybrid Spacesuit Simulator (HS3) to support testing and characterization of human performance during analog planetary exploration extravehicular activities (EVAs). The goal of HS3 is to create a low-cost, modular, and unpressurized spacesuit simulator as a research tool that provides relevant physical and cognitive workload approximations with EVA-like immersion. HS3 consists of a soft outer suit, thermal control, gloves, boots, helmet, and integrated bioinformatics and communications. Baseline HS3 assessments were performed during 3-hour EVA simulations in two different subjects (DEMO1 and DEMO2) that included traverses at variable resistances and geological sampling activities. Liquid cooling garment (LCG) temperature, mean skin temperature, heart rate, motion capture, and metabolic rate were collected during each 3-hour simulated EVA. During DEMO1 and DEMO2, baseline metabolic rates at rest were 836 ± 327 BTU/hr and 869 ± 207 BTU/hr and increased to 2124 ± 548 BTU/hr and 2269 ± 559 BTU/hr, respectively, during 500m traverse. Average inlet LCG temperatures were 29.57 ± 6.62 °C and 25.63 ± 6.48 °C for DEMO1 and DEMO2 with increased outlet LCG temperatures of 33.53 ± 6.62 °C and 29.21 ± 4.79 °C, respectively. Overall, HS3 will enable future studies to characterize EVA tasks, human performance, and test future EVA capabilities in analog test environments without the need for pressurized suited environments.

Monica Hew↗

NASA NTRSDate not supplied

Developing A Hybrid Spacesuit Simulator as A Research Tool for Assessing Extravehicular Activity Relevant Workload

Suit simulator↗

DOE OSTI2024

Artificial Neural Network-based State Estimation for Low Observable, Unbalanced Microgrids for Microgrid Building Blocks

The microgrid building blocks (MBB) were proposed as microgrid components with combined sub-components with power conversion, communication, and microgrid control capability, or a subset of such sub-components. This work addresses the microgrid controller, present in an MBB, which requires accurate state estimation to perform its tasks, including for monitoring, power flow (dispatch), fault detection, etc. In this paper, an artificial neural network (ANN)-based framework for state estimation is proposed for an MBB, especially for unbalanced and low observable microgrids. To overcome the challenge of low observability in unbalanced systems, a concept of extended adjacent matrix is introduced to reduce the required number of measurements for state estimation. Addressing the challenges, a feed forward neural network (FNN) is utilized to enhance estimation accuracy and reliability with the reduced number of measurements. The proposed state estimation is validated through extensive simulations on a microgrid, which was achieved from the modified IEEE 34-bus distribution test feeder with multiple distributed energy resources (DERs) and demonstrated superior performance in estimation accuracy and low observability.

Choi, Jongchan↗

DOE OSTI2020

Magnetic fluctuations and the spin–orbit interaction in Mott insulating CoO

Motivated by the presence of an unquenched orbital angular momentum in CoO, a team at Chalk River, including a recently hired research officer Roger Cowley, performed the first inelastic neutron scattering experiments on the classic Mott insulator. Despite identifying two magnon modes at the zone boundary, the team was unable to parameterise the low energy magnetic excitation spectrum below TN using conventional pseudo-bosonic approaches, instead achieving only qualitative agreement. It would not be for another 40 years that Roger, now at Oxford and motivated by the discovery of the high-Tc cuprate superconductors, would make another attempt at the parameterisation of the magnetic excitation spectrum that had previously alluded him at the start of his career. Upon his return to CoO, Roger found a system embroiled in controversy, with some of its most fundamental parameters still remaining undetermined. Faced with such a formidable task, Roger performed a series of inelastic neutron scattering experiments in the early 2010s on both CoO and a magnetically dilute structural analogue Mg 0.97 Co 0.03 O. These experiments would prove instrumental in the determination of both single-ion and cooperative magnetic parameters for CoO. Both these sets of parameters would eventually be used in a spin–orbit exciton model, developed by his longtime friend and collaborator Bill Buyers, to successfully parameterise the complex spectrum that both measured at Chalk River almost 50 years prior. The story of CoO is of one that has come full circle, one filled with both spectacular failures and intermittent, yet profound, little victories.

36 MATERIALS SCIENCE↗

NASA NTRS2025

A Preliminary Study on the Feasibility of Large Language Models for Detecting Micro-Behaviors Among Team Members in Space Missions

Large-language models (LLMs) have been recently used for spoken language understanding (SLU) to infer meaning and semantics from speech in tasks such as speaker intent and sentiment classification. Due to being trained on large amounts of data, and their ability to understand context and relationships between words, LLMs are competent, enabling them to generalize across tasks without requiring many task-specific training samples. This research examines the feasibility of few-shot learning in LLMs for detecting subtle, brief, and possibly unconscious interactions between team members, called ``micro-behaviors," and provides insights into the appropriate design of LLMs for this task. Our data came from 5 teams participating in a 45-day mission at the US National Aeronautics and Space Administration’s (NASA) Human Exploration Research Analog (HERA). More specifically we used data collected from team interaction battery (TIB) tasks teams performed five times in-mission which comprise an average 1.5 hours of conversation data per day. Micro-behaviors were coded according to an adapted version of Smith & Griffins (2022) theoretical framework in terms of Violation (i.e., presence of valenced behavior, uplifting/positive or discouraging/negative), Intensity (i.e., force of behavior in terms of how uplifting or discouraging is the behavior), and Intent (i.e., motive of the behavior in terms of whether it was deliberate or unintentional). We explore the ability of LLMs to detect the presence and intensity of micro-behaviors. We examine employing and fine-tuning readily available LLMs (i.e., RoBERTa, DistilBERT), as well as prompting state-of-the-art sequence classification models (i.e., Llama-2, Llama-3). In a total of 13,058 conversational turns (17.8% uplifting, 3.3% discouraging, 75.76% neutral, 3.14% nulls), we compute the macro F1-score of the 3-way micro-behavior classification task (i.e., classifying among uplifting, discouraging, and neutral; 33% chance). Results indicate that the RoBERTa model achieves a F1-score of 36.2% (uplift: 43.3% precision (P), 15.1% recall (R); discourage: 20% P, 0.5% R). These results significantly improve when we augment the data via paraphrasing in the RoBERTa model, reaching a 41.2% macro F1-score (uplift: 37.7% P, 86.3% R; discourage: 3.5% P, 1.8% R). Finally, the Llama-2 model with 3-shot prompting yields 38% macro F1-score (uplift: 28.7% P, 20% R; discourage: 7.2% P, 18% R), which is slightly better compared to the RoBERTa model without data augmentation, highlighting the effectiveness of sequence classification models in detecting minority classes with a small sample size. Findings indicate that LLMs hold potential to detect subtle behaviors in conversations, which could be valuable in assessing team behavior in space exploration missions. Future studies will evaluate the performance of different LLM prompting strategies or fine-tuning methods.

Ankush Raut↗

NASA NTRS2017

Human-Autonomy Teaming in a Flight Following Task

The NATO HFM-247 Working Group is creating a summary report of the group's activities on human-autonomy teaming. This chapter is a summary of our at NASA Ames work toward developing a framework for human-autonomy teaming (HAT) in aviation. The purpose of this project was to demonstrate and evaluate proposed tenets of HAT. The HAT features were derived from three tenets and were built into an automated recommender system on a ground station. These tenets include bi-directional communication, automation transparency, and operator directed interface. This study focused primarily on interactions with one piece of automation, the Autonomous Constrained Flight Planner (ACFP). The ACFP is designed to support rapid diversion decisions for commercial pilots in off-nominal situations. Much effort has gone into enhancing this tool not only in capability but also in transparency. In this study, participants used the ACFP at a ground station designed to aid dispatchers in a flight following role to reroute aircraft in situations such as inclement weather, system failures and medical emergencies. Participants performed this task both with HAT features enabled and without and provided feedback. We examined subjective and behavioral indicators of HAT collaborations using a proof-of-concept demonstration of HAT tenets. The data collected suggest potential advantages and disadvantages of HAT.

bi-directional communication↗

NASA NTRS2004

Proposing an International Collaboration on Lightweight Autonomous Vehicles to Conduct Scientific Traverses and Surveys over Antarctica and the Surrounding Sea Ice

We have continued to develop a concept for use of autonomous rovers, originally developed for use in planetary exploration, in polar science on Earth; the concept was the subject of a workshop, and this report summarizes and extends that workshop. The workshop on Antarctic Autonomous Scientific Vehicles and Traverses met at the National Geographic Society on February 14 and 15, 2001 to discuss scientific objectives and benefits of the use of autonomous rovers. The participants enthusiastically viewed rovers as being uniquely valuable for such tasks as data taking on tedious or repetitive routes, traverses in polar night, difficult or hazardous routes, extremely remote regions, routes requiring only simple instrumentation, traverses that must be conducted at low speed, augments of manned traverses, and scientific procedures not compatible with human presence or combustion engines. The workshop has concluded that instrumented autonomous vehicles, of the type being developed for planetary exploration, have the potential to contribute significantly to the way science in conducted in Antarctica while also aiding planetary technology development, and engaging the public's interest. Specific objectives can be supported in understanding ice sheet mass balance, sea ice heat and momentum exchange, and surface air chemistry processes. In the interval since the workshop, we have concluded that organized program to employ such rovers to perform scientific tasks in the Fourth International Polar Year would serve the objectives of that program well.

polar science↗

NASA NTRS2001

Use of Human Modeling Simulation Software in the Task Analysis of the Environmental Control and Life Support System Component Installation Procedures

Virtual reality and simulation applications are becoming widespread in human task analysis. These programs have many benefits for the Human Factors Engineering field. Not only do creating and using virtual environments for human engineering analyses save money and time, this approach also promotes user experimentation and provides increased quality of analyses. This paper explains the human engineering task analysis performed on the Environmental Control and Life Support System (ECLSS) space station rack and its Distillation Assembly (DA) subsystem using EAI's human modeling simulation software, Jack. When installed on the International Space Station (ISS), ECLSS will provide the life and environment support needed to adequately sustain crew life. The DA is an Orbital Replaceable Unit (ORU) that provides means of wastewater (primarily urine from flight crew and experimental animals) reclamation. Jack was used to create a model of the weightless environment of the ISS Node 3, where the ECLSS is housed. Computer aided drawings of the ECLSS rack and DA system were also brought into the environment. Anthropometric models of a 95th percentile male and 5th percentile female were used to examine the human interfaces encountered during various ECLSS and DA tasks. The results of the task analyses were used in suggesting modifications to hardware and crew task procedures to improve accessibility, conserve crew time, and add convenience for the crew. This paper will address some of those suggested modifications and the method of presenting final analyses for requirements verification.

Estes, Samantha↗