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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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All sourcesNASA NTRSDOE OSTI
NASA NTRS1994

Teleoperator performance with varying force and visual feedback

An experimental study was conducted to determine the effects of various forms of visual and force feedback on human performance for several 'peg-in-hole'-type telemanipulation tasks. Each of six human test subjects used a master/slave manipulator during two experimental sessions. In one session the subjects performed the tasks with direct vision, where subtended visual angle, force feedback, task difficulty, and the interaction of subtended visual angle and force feedback made signigicant differences in task completion times. During the other session the tasks were performed using a video monitor for visual feedback, and video frame rate, force feedback, task difficulty and the interaction of frame rate and force feedback were found to make significant differences in task times. An analysis between the direct and video viewing environments showed that apart from subtended visual angle and reduced frame rate, the video medium itself did not significantly affect task times relative to direct viewing.

Massimino, Michael J.↗
DOE OSTI2025

Overcoming sparse datasets with multi-task learning as applied to high entropy alloys

Abstract The design of novel High Entropy Alloys for use in high-temperature applications is an area of active interest due to their potential to provide exceptional properties compared to conventional alloys. Since the increased popularity of machine learning, an important cog in the design process has been training surrogate models on alloy properties. However, these Single-Task models are trained on individual mechanical properties and do not take advantage of the relatedness between properties. Multi-Task models can capture the interdependencies between tasks, leading to potentially more accurate predictions for all tasks. In this paper, we investigate if Multi-Task models can show improvement over Single-Task models when used for predicting the mechanical properties of these alloys. To ensure fair evaluation between the models, we apply L 0 regularization and skip connections to the models, which allows them to adjust the number of model parameters and depth for optimal performance. We find that the Multi-Task models can leverage task relationships to perform better than Single-Task models, especially for high amounts of missing data in the tasks. Furthermore, adding simple auxiliary targets can boost Multi-Task performance even further despite not being effective as input descriptors to single-task models themselves. We anticipate that the proposed strategies can achieve more accurate predictions and consequently enable better design capabilities for such data-constrained domains without incurring much additional computational cost.

Debnath, Arindam (ORCID:0000000194274499)↗
NASA NTRS2001

Using EEG To Detect and Monitor Mental Fatigue

This project aims to develop EEG-based methods for detecting and monitoring mental fatigue. Mental fatigue poses a serious risk, even when performance is not apparently degraded. When such fatigue is associated with sustained performance of a single type of cognitive task it may be related to the metabolic energy required for sustained activation of cortical areas specialized for that task. The objective of this study was to adapt EEG to monitor cortical energy over a long period of performance of a cognitive task. Multielectrode event related potentials (ERPs) were collected every 15 minutes in nine subjects who performed a mental arithmetic task (algebraic sum of four randomly generated negative or positive digits). A new problem was presented on a computer screen 0.5 seconds after each response; some subjects endured for as long as three hours. ERPs were transformed to a quantitative measure of scalp electrical field energy. The average energy level at electrode P3 (near the left angular gyrus), 100-300 msec latency, was compared over the series of ERPs. For most subjects, scalp energy density at P3 gradually fell over the period of task performance and dramatically increased just before the subject was unable to continue the task. This neural response can be simulated for individual subjects using, a differential equation model in which it is assumed that the mental arithmetic task requires a commitment of metabolic energy that would otherwise be used for brain activities that are temporarily neglected. Their cumulative neglect eventually requires a reallocation of energy away from the mental arithmetic task.

Montgomery, Leslie↗
NASA NTRS1992

Telerobot control mode performance assessment

With the maturation of various developing robot control schemes, it is becoming extremely important that the technical community evaluate the performance of these various control technologies against an established baseline to determine which technology provides the most reliable robust, and safe on-orbit robot control. The Supervisory Telerobotics Laboratory (STELER) at JPL has developed a unique robot control capability which has been evaluated by the NASA technical community and found useful for augmenting both the operator interface and control of intended robotic systems on-board the Space Station. As part of the technology development and prototyping effort, the STELER team has been evaluating the performance of different control modes; namely, teleoperation under position, or rate, control, teleoperation with force reflection and shared control. Nine trained subjects were employed in the performance evaluation involving several high fidelity servicing tasks. Four types of operator performance data were collected; task completion time, average force, peak force, and number of operator successes and errors. This paper summarizes the results of this performance evaluation.

Zimmerman, Wayne↗
NASA NTRS1979

Operator performance and localized muscle fatigue in a simulated space vehicle control task

Fourier transforms in a special purpose computer were utilized to obtain power spectral density functions from electromyograms of the biceps brachii, triceps brachii, brachioradialis, flexor carpi ulnaris, brachialis, and pronator teres in eight subjects performing isometric tracking tasks in two directions utilizing a prototype spacecraft rotational hand controller. Analysis of these spectra in general purpose computers aided in defining muscles involved in performing the task, and yielded a derived measure potentially useful in predicting task termination. The triceps was the only muscle to show significant differences in all possible tests for simple effects in both tasks and, overall, was the most consistently involved of the six muscles. The total power monitored for triceps, biceps, and brachialis dropped to minimal levels across all subjects earlier than for other muscles. However, smaller variances existed for the biceps, brachioradialis, brachialis, and flexor carpi ulnaris muscles and could provide longer predictive times due to smaller standard deviations for a greater population range.

Lewis, J. L., Jr.↗
DOE OSTI2025

Sparse-Data Deep Learning Strategies for Radiographic Non-Destructive Testing

Radiography is an imaging technique used in a variety of applications, such as medical diagnosis, airport security, and nondestructive testing. We present a deep learning system for extracting information from radiographic images. We perform various prediction tasks using our system, including material classification and regression on the dimensions of a given object that is being radiographed. Our system is designed to address the sparse-data issue for radiographic nondestructive testing applications. It uses a radiographic simulation tool for synthetic data augmentation, and it uses transfer learning with a pre-trained convolutional neural network model. Using this system, our preliminary results indicate that the object geometry regression task saw an improvement of 70% in the R-squared value when using a multi-regime model. In addition, we increase the performance of the object material classification tasks by utilizing data from different imaging systems. In particular, using neutron imaging improved the material classification accuracy by 20% when compared to x-ray imaging.

convolutional neural networks↗
DOE OSTI2024

Harnessing large language models’ zero-shot and few-shot learning capabilities for regulatory research

Abstract Large language models (LLMs) are sophisticated AI-driven models trained on vast sources of natural language data. They are adept at generating responses that closely mimic human conversational patterns. One of the most notable examples is OpenAI's ChatGPT, which has been extensively used across diverse sectors. Despite their flexibility, a significant challenge arises as most users must transmit their data to the servers of companies operating these models. Utilizing ChatGPT or similar models online may inadvertently expose sensitive information to the risk of data breaches. Therefore, implementing LLMs that are open source and smaller in scale within a secure local network becomes a crucial step for organizations where ensuring data privacy and protection has the highest priority, such as regulatory agencies. As a feasibility evaluation, we implemented a series of open-source LLMs within a regulatory agency’s local network and assessed their performance on specific tasks involving extracting relevant clinical pharmacology information from regulatory drug labels. Our research shows that some models work well in the context of few- or zero-shot learning, achieving performance comparable, or even better than, neural network models that needed thousands of training samples. One of the models was selected to address a real-world issue of finding intrinsic factors that affect drugs' clinical exposure without any training or fine-tuning. In a dataset of over 700 000 sentences, the model showed a 78.5% accuracy rate. Our work pointed to the possibility of implementing open-source LLMs within a secure local network and using these models to perform various natural language processing tasks when large numbers of training examples are unavailable.

Biochemistry & Molecular Biology↗
DOE OSTI2020

Evolving Ensembles of Spiking Neural Networks for Neuromorphic Systems

Evolutionary algorithms have been proposed as a solution to overcome many of the challenges associated with training spiking neural networks. While evolutionary optimization for spiking neural networks is very flexible, its performance has difficulty scaling to complex tasks and correspondingly complex network structures. Here we propose a method for evolving ensembles of spiking neural networks. By using ensemble learning, the flexibility of evolutionary optimization is fully preserved while scaling to more challenging tasks. We test the performance of the proposed method using handwritten digit classification. We investigate multiple strategies for constructing ensembles of spiking neural networks, and demonstrate that evolving ensembles of SNNs offers significant performance advantages over evolutionary optimization.

Elbrecht, Daniel↗
DOE OSTI2024

A Multifunctional Isostructural Bilayer Oxygen Evolution Electrode for Durable Intermediate-Temperature Electrochemical Water Splitting

The overarching goal of the proposed research is to address SOEC’s degradation problem by advancing a new isostructural highly electrocatalytically active bilayer oxygen evolution reaction (OER) electrode, consisting of a LSCF (La 1-x Sr x Co 1-y Fe y O 3-δ ) core and a SCT (SrCo 0.9 Ta 0.1 O 3-δ ) shell, to achieve high and sustainable rate of oxygen evolution matching operating current densities without encountering delamination. To realize this goal, the project has adopted a combined experimental and theoretical approach to conduct research in the following six areas closely associated with SOPO tasks: 1) Development of electrocatalytically active bilayer oxygen electrodes (SOPO task-1) 2) Development of new symmetric three electrode cell (STEC) methodology to extract electrokinetic data of oxygen electrodes (SOPO task-2) 3) Quantification of electrokinetics of bilayer oxygen electrodes and correlation with degradation and delamination (SOPO task-2) 4) Performances of bilayer oxygen electrodes under fuel cells and electrolyzers modes (SOPO task-3) 5) Microscale modeling of oxygen electrode/electrolyte interface in solid oxide electrolysis cells (SOPO task-4) 6) Prediction of crack growth rate at oxygen electrode/electrolyte interface in solid oxide electrolysis cells (SOPO task-4)

08 HYDROGEN↗
NASA NTRS1974

High performance N2O4/amine elements: Data dump covering. Task 1: Literature review

The phenomenon of reactive stream separation (RSS) in the N2O4/amine earth-storable propellant combinations is reviewed. Early theoretical models of RSS are presented, as are experimental combustion data under simulated rocket conditions. N2O4/amine combustion chemistry data is also provided. More recent work in the development of a comprehensive model is described.

Hines, W. S.↗
NASA NTRS1982

Visual scanning behavior and mental workload in aircraft pilots

This paper describes an experimental paradigm and a set of preliminary results which demonstrate a relationship between the level of performance on a skilled man-machine control task, the skill of the operator, the level of mental difficulty induced by an additional task imposed on the basic control task, and visual scanning performance. During a constant, simulated piloting task, visual scanning of instruments was found to vary as a function of the level of difficulty of a verbal loading task. The average dwell time of each fixation on the pilot's primary instrument increased as a function of the loading. The scanning behavior was also a function of the estimated skill level of the pilots, with novices being affected by the loading task much more than experts. The results suggest that visual scanning of instruments in a controlled task may be an indicator of both workload and skill.

Tole, J. R.↗
NASA NTRS1981

Visual scanning behavior and pilot workload

An experimental paradigm and a set of results which demonstrate a relationship between the level of performance on a skilled man-machine control task, the skill of the operator, the level of mental difficulty induced by an additional task imposed on the basic control task, and visual scanning performance. During a constant, simulated piloting task, visual scanning of instruments was found to vary as a function of the level of difficulty of a verbal mental loading task. The average dwell time of each fixation on the pilot's primary instrument increased as a function of the estimated skill level of the pilots, with novices being affected by the loading task much more than the experts. The results suggest that visual scanning of instruments in a controlled task may be an indicator of both workload and skill.

Harris, R. L., Sr.↗
NASA NTRS1982

Visual scanning behavior and pilot workload

This paper describes an experimental paradigm and a set of results which demonstrate a relationship between the level of performance on a skilled man-machine control task, the skill of the operator, the level of mental difficulty induced by an additional task imposed on the basic control task, and visual scanning performance. During a constant, simulated piloting task, visual scanning of instruments was found to vary with the difficulty of a verbal mental loading task. The average dwell time of each fixation on the pilot's primary instrument increased with the estimated skill level of the pilots, with novices being affected by the loading task much more than experts. The results suggest that visual scanning of instruments in a controlled task may be an indicator of both workload and skill.

Harris, R. L., Sr.↗
NASA NTRS1984

Suppression of Biodynamic Interference by Adaptive Filtering

Preliminary experimental results obtained in moving base simulator tests are presented. Both for pursuit and compensatory tracking tasks, a strong deterioration in tracking performance due to biodynamic interference is found. The use of adaptive filtering is shown to substantially alleviate these effects, resulting in a markedly improved tracking performance and reduction in task difficulty. The effect of simulator motion and of adaptive filtering on human operator describing functions is investigated. Adaptive filtering is found to substantially increase pilot gain and cross-over frequency, implying a more tight tracking behavior. The adaptive filter is found to be effective in particular for high-gain proportional dynamics, low display forcing function power and for pursuit tracking task configurations.

Velger, M.↗
NASA NTRS1986

KBGIS-II: A knowledge-based geographic information system

The architecture and working of a recently implemented Knowledge-Based Geographic Information System (KBGIS-II), designed to satisfy several general criteria for the GIS, is described. The system has four major functions including query-answering, learning and editing. The main query finds constrained locations for spatial objects that are describable in a predicate-calculus based spatial object language. The main search procedures include a family of constraint-satisfaction procedures that use a spatial object knowledge base to search efficiently for complex spatial objects in large, multilayered spatial data bases. These data bases are represented in quadtree form. The search strategy is designed to reduce the computational cost of search in the average case. The learning capabilities of the system include the addition of new locations of complex spatial objects to the knowledge base as queries are answered, and the ability to learn inductively definitions of new spatial objects from examples. The new definitions are added to the knowledge base by the system. The system is performing all its designated tasks successfully. Future reports will relate performance characteristics of the system.

Smith, Terence↗
NASA NTRS2001

Grasping objects by their handles: a necessary interaction between cognition and action

Research has illustrated dissociations between "cognitive" and "action" systems, suggesting that different representations may underlie phenomenal experience and visuomotor behavior. However, these systems also interact. The present studies show a necessary interaction when semantic processing of an object is required for an appropriate action. Experiment 1 demonstrated that a semantic task interfered with grasping objects appropriately by their handles, but a visuospatial task did not. Experiment 2 assessed performance on a visuomotor task that had no semantic component and showed a reversal of the effects of the concurrent tasks. In Experiment 3, variations on concurrent word tasks suggested that retrieval of semantic information was necessary for appropriate grasping. In all, without semantic processing, the visuomotor system can direct the effective grasp of an object, but not in a manner that is appropriate for its use.

NASA Center ARC↗
NASA NTRS2009

Performance Support Tools for Space Medical Operations

The early Constellation space missions are expected to have medical capabilities very similar to those currently on the Space Shuttle and International Space Station (ISS). For Crew Exploration Vehicle (CEV) missions to ISS, medical equipment will be located on ISS, and carried into CEV in the event of an emergency. Flight Surgeons (FS) on the ground in Mission Control will be expected to direct the Crew Medical Officer (CMO) during medical situations. If there is a loss of signal and the crew is unable to communicate with the ground, a CMO would be expected to carry out medical procedures without the aid of a FS. In these situations, performance support tools can be used to reduce errors and time to perform emergency medical tasks. Human factors personnel at Johnson Space Center have recently investigated medical performance support tools for CMOs on-orbit, and FSs on the ground. This area of research involved the feasibility of Just-in-time (JIT) training techniques and concepts for real-time medical procedures. In Phase 1, preliminary feasibility data was gathered for two types of prototype display technologies: a hand-held PDA, and a Head Mounted Display (HMD). The PDA and HMD were compared while performing a simulated medical procedure using ISS flight-like medical equipment. Based on the outcome of Phase 1, including data on user preferences, further testing was completed using the PDA only. Phase 2 explored a wrist-mounted PDA, and compared it to a paper cue card. For each phase, time to complete procedures, errors, and user satisfaction were captured. Information needed by the FS during ISS mission support, especially for an emergency situation (e.g. fire onboard ISS), may be located in many different places around the FS s console. A performance support tool prototype is being developed to address this issue by bringing all of the relevant information together in one place. The tool is designed to include procedures and other information needed by a FS during an emergency, as well as procedures and information to be used after the emergency is resolved. Several walkthroughs of the prototype with FSs have been completed within a mockup of an ISS FS console. Feedback on the current tool design as well as recommendations for existing ISS FS displays were captured.

Byrne, Vicky E.↗

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