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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 1,567 records · Page 87

Zero-Fidelity Simulation: Engaging Team Coordination without Physical, Functional, or Psychological Re-Creation

Team coordination is essential across domains, enabling efficiency and safety. As technology improves, our temptation is to simulate with ever-higher fidelity, by making simulators re-create reality through their physical interfaces, functionality, and by making participants believe they are undertaking the simulated task. However, high-fidelity simulations often miss salient human-human work practices. We introduce the concept of zero-fidelity simulation (ZFS), a move away from literal high-fidelity mimesis of the concrete environment. ZFS alternatively models cooperation and communication as the basis of simulation. The ZFS Team Coordination Game (TeC) is developed from observation of fire emergency response work practice. We identify ways in which team members are mutually dependent on one another for information, and use these as the basis for the ZFS game design. The design creates a need for cooperation by restricting individual activity and requiring communication. The present research analyzes the design of interdependence in the validated ZFS TeC game. We successfully simulate interdependence between roles in emergency response without simulating the concrete environment.

Toups, Zachary O.↗

Jet Noise Research at NASA

A presentation outlining current jet noise work at NASA was given at the NAVAIR Noise Workshop. Jet noise tasks in the Supersonics project of the Fundamental Aeronautics program were highlighted. The presentation gave an overview of developing jet noise reduction technologies and noise prediction capabilities. Advanced flow and noise diagnostic tools were also presented.

Henderson, Brenda↗

Spaceport Processing System Development Lab

The Spaceport Processing System Development Lab (SPSDL), developed and maintained by the Systems Hardware and Engineering Branch (NE-C4), is a development lab with its own private/restricted networks. A private/restricted network is a network with restricted or no communication with other networks. This allows users from different groups to work on their own projects in their own configured environment without interfering with others utilizing their resources in the lab. The different networks being used in the lab have no way to talk with each other due to the way they are configured, so how a user configures his software, operating system, or the equipment doesn't interfere or carry over on any of the other networks in the lab. The SPSDL is available for any project in KSC that is in need of a lab environment. My job in the SPSDL was to assist in maintaining the lab to make sure it's accessible for users. This includes, but is not limited to, making sure the computers in the lab are properly running and patched with updated hardware/software. In addition to this, I also was to assist users who had issues in utilizing the resources in the lab, which may include helping to configure a restricted network for their own environment. All of this was to ensure workers were able to use the SPSDL to work on their projects without difficulty which would in turn, benefit the work done throughout KSC. When I wasn't working in the SPSDL, I would instead help other coworkers with smaller tasks which included, but wasn't limited to, the proper disposal, moving of, or search for essential equipment. I also, during the free time I had, used NASA's resources to increase my knowledge and skills in a variety of subjects related to my major as a computer engineer, particularly in UNIX, Networking, and Embedded Systems.

Systems Engineering↗

Technical Facilities Management, Loan Pool, and Calibration

My work at JPL for the SURF program began on June 11, 2012 with the Technical Facilities Management group (TFM). As well as TFM, I worked with Loan Pool and Metrology to help them out with various tasks. Unlike a lot of other interns, I did not have a specific project rather many different tasks to be completed over the course of the 10 weeks.The first task to be completed was to sort through old certification reports in 6 different boxes to locate reports that needed to be archived into a digital database. There were no reports within these boxes that needed to be archived but rather were to be shredded. The reports went back to the early 1980's and up to the early 2000's. I was looking for reports dated from 2002 to 2012

Technical Facilities Management group (TFM)↗

Overview of Marshall Space Flight Center Activities for the Combustion Stability Tool Development Program

This presentation covers the overall scope, schedule, and activities associated with the NASA - Marshall Space Flight Center (MSFC) involvement with the Combustion Stability Tool Development (CSTD) program. The CSTD program is funded by the Air Force Space & Missile Systems Center; it is approximately two years in duration and; and it is sponsoring MSFC to: design, fabricate, & execute multi-element hardware testing, support Air Force Research Laboratory (AFRL) single element testing, and execute testing of a small-scale, multi-element combustion chamber. Specific MSFC Engineering Directorate involvement, per CSTD-sponsored task, will be outlined. This presentation serves a primer for the corresponding works that provide details of the technical work performed by individual groups within MSFC.

Kenny, R. J.↗

Alignment and Testing of Critical Interface Fixtures for the James Webb Space Telescope

NASA's James Webb Space Telescope (JWST) is a 6.6m diameter, segmented, deployable telescope for cryogenic IR space astronomy. The JWST Observatory architecture includes the Primary Mirror Backplane Support Structure (PMBSS) and Integrated Science Instrument Module (ISIM) Electronics Compartment (IEC) which is designed to integrate to the spacecraft bus via six cup/cone interfaces. Prior to integration to the spacecraft bus the JWST observatory must undergo environmental testing, handling, and transportation. Multiple fixtures were developed to support these tasks including the vibration fixture and handling and integration fixture (HIF). This work reports on the development of the nominal alignment of the six interfaces and metrology operations performed for the JWST observatory to safely integrate them for successful environmental testing.

technology development↗

Alignment and Testing of Critical Interface Fixtures for the James Webb Space Telescope

NASAs James Webb Space Telescope (JWST) is a 6.6m diameter, segmented, deployable telescope for cryogenic IR space astronomy. The JWST Observatory architecture includes the Primary Mirror Backplane Support Structure (PMBSS) and Integrated Science Instrument Module (ISIM) Electronics Compartment (IEC) which is designed to integrate to the spacecraft bus via six cupcone interfaces. Prior to integration to the spacecraft bus the JWST observatory must undergo environmental testing, handling, and transportation. Multiple fixtures were developed to support these tasks including the vibration fixture and handling and integration fixture (HIF). This work reports on the development of the nominal alignment of the six interfaces and metrology operations performed for the JWST observatory to safely integrate them for successful environmental testing.

instrument development↗

Rise and Shine: Using Light as a Countermeasure to Sleep Inertia

INTRODUCTION: Sleep inertia describes the phenomenon of sleepiness and poor performance experienced after waking from sleep. This period of impaired alertness and performance is of significant concern to workers who nap on shift, or work on-call and are required to perform safety-critical tasks soon after waking (e.g., emergency services, healthcare, military). Light has been shown to acutely improve alertness during sleep deprivation and circadian misalignment. In this study, we assessed the efficacy of blue-enriched light to improve alertness and mood immediately after waking from SWS, i.e., during the sleep inertia period. METHODS: Twelve participants kept a sleep schedule of 8.5 h for 5 nights and 5 h for one night prior to the overnight laboratory visit (confirmed by actigraphy). Participants went to bed at their scheduled habitual bedtime in the laboratory and were monitored by standard polysomnography. After at least 5 min of SWS, participants were awoken and exposed to either red ambient light (control) or blue-enriched light (light) for 1 h. During this time, participants completed a subjective scale of alertness (Karolinska Sleepiness Scale, KSS) and visual analogue scales (VAS) of mood at 2 min, 17 min, 32 min, and 47 min after waking. Following this sleep inertia measurement period, all lights were turned off and participants were allowed to return to sleep. They were then awoken again from their subsequent SWS period and exposed to the opposite condition (control or light). A linear mixed-effects model with fixed effects of condition, time, and condition*time and a random effect of participant was used to determine the impact of light across the testing period. An average of baseline responses (pre-sleep) was included as a covariate. RESULTS: Compared to the control condition, participants exposed to blue-enriched light reported feeling more alert (KSS: F1,77=4.955, p=.029; VASalert: F1,77=8.226, p=.005), more cheerful (VAScheerful: F1,77=8.615, p=.004), less depressed (VASdepressed: F1,77=4.649, p=.034), and less lethargic (VASlethargic: F1,77=5.652, p=.020). DISCUSSION: Exposure to blue-enriched light immediately after waking from SWS may help to improve subjective alertness and mood. Future analyses will explore whether these findings extend to effects on cognitive performance. This countermeasure to sleep inertia may be suitable for implementation to alert crew members during mid-sleep emergencies but requires further testing in field settings.

alertness↗

2022 Spring Internship Exit Presentation

As efforts of the National Aeronautics and Space Administration (NASA) and the Federal Aviation Administration (FAA) continue to digitize the air traffic management (ATM) domain, there is countless times of need for downstream natural language processing (NLP) tasks such as named entity recognition, text summarization, classification, and more. Although there are a plethora of open-sourced pre-trained transformer models in the NLP field such as BERT, RoBERTa, XLNet, and GPT-3, these models are trained on general corpora and perform poorly on domain-specific terminology and phraseology seen in ATM documents such as Notice to Airmen (NOTAMs) and Letters of Agreement (LoA). Our proposed research objective will be to first gather a large corpus of air traffic management related documents, orders, notices, books, technical papers, conference papers, articles, and other miscellaneous sources of text data from the FAA, NASA, and accredited conference and publication societies. After gathering this data, many steps will have to be taken to collate and preprocess the data into a format understandable by our test transformer models. Thirdly, we will set up training pipelines to train the RoBERTa model on its unsupervised training task masked language modelling (MLM) using resources provided by the NASA Advanced Supercomputing (NAS) facilities. Finally, these fine-tuned transformer models will be evaluated on their performance on down-stream NLP tasks as mentioned above, to show whether they will be effective when working with ATM related data or not. Once complete, this model could be made open-sourced on the HuggingFace website, where the rest of the ATM community can access and utilize this tool.

NLP↗

Hazard Perception & Avoidance (HPA): Part Task 1 - Results Outbrief

n April 2022, the Human Autonomy Teaming Lab (NASA Ames Research Center) conducted a manned, human-in-the-loop (HITL) simulation. This part task HITL began the lab’s Hazard Perception and Avoidance (HPA) technical work under NASA’s Advanced Air Mobility (AAM), Automated Flight and Contingency Management (AFCM) Sub-Project. The goals were to assess levels of automation for manned, electric vertical takeoff and landing (eVTOL) aircraft. This simulation tested manual and automated Resolution Advisory (RA) responses and return-to-course (RTC) maneuvers for the first version of the Airborne Collision Avoidance System’s (ACAS) rotary-wing (Xr) variant. This was conducted on a fixed-based simulator designed to fly eVTOL aircraft while maneuvering for intruding traffic. Variables for this study included levels of autonomy (i.e., manual and automated) as well as the types of alerts at the onset of conflicts (i.e., Corrective and RA). The data collected included response times, losses of well clear, and maneuver sizes and durations as well as subjective ratings like acceptability, and perceived workload. Additional details and future anticipations are also discussed.

air taxis↗

Assured Vehicle Automation 1 Sim - Results Outbrief

In early 2022, the Human Autonomy Teaming Lab (NASA Ames Research Center) conducted a manned, human-in-the-loop (HITL) simulation. This part-task HITL began the lab’s Hazard Perception and Avoidance (HPA) technical work under NASA’s Advanced Air Mobility (AAM), Automated Flight and Contingency Management (AFCM) Sub-Project. The results of that sim guided the objectives of the current study, which were to examine pilots’ use of the Airborne Collision Avoidance System (ACAS) rotorcraft variant (Xr) v2 in multiple phases of flight with two separate Xr Modes, fully leverage Xr v2 features (e.g., use radar altimeter data to inform low altitude Resolution Advisory [RA] behavior, utilize the ability to designate “terminal-area intruders,” and display airspeed-based Detect and Avoid [DAA] guidance), emulate a “Traffic Advisory” (TA), and present Xr in a higher-fidelity environment. Therefore, this study was conducted in the Vertical Motion Simulator, and the variables included Phase of Flight (En-route, Hover, and Approach) as well as ACAS Xr Mode (TA/RA and DAA). The data collected included response times, losses of well clear, and maneuver sizes and durations as well as subjective ratings like acceptability and usability. Additional details and future anticipations are also discussed.

air taxis↗

Transcribing Air Traffic Control System Command Center Planning Telecons Using Cloud-Based Automatic Speech Recognition

This paper addresses the challenge of using Automatic Speech Recognition (ASR) technology to transcribe regular teleconferences that happen between FAA Air Traffic Control System Command Center (ATCSCC) planners, stakeholders and air users. These planning teleconferences (aka telecons or planning webinars) are an integral part of managing air traffic in the U.S. National Airspace System (NAS). In particular, the meetings facilitate the creation and modification of various traffic management initiatives (TMIs), that are used to regulate the flow of air traffic. This is typically a human intensive process, requiring specialists to listen to the entire meeting audio (10-20 minutes duration) and inferring the state of the NAS (e.g., weather phenomenon) that was discussed. It would be advantageous to have digital transcripts of the audio and have useful information (e.g., related to TMIs) automatically extracted from the transcripts. In this regard, we are exploring the adoption of state-of-the-art speech to text and Natural Language Processing (NLP) tools that will achieve our objective of digitizing the webinar audio. Unfortunately, the highly technical phraseology present in the audio and limited data availability for model building make ASR difficult. To overcome this challenge, we have taken the critical first step in creating a human transcription dataset from ~20 hours of speech in the ATCSCC audio with the help of subject matter experts. A novelty of our work is the creation of a ground truth transcription dataset for ATCSCC teleconference webinars, which is particularly important for Aviation domain-specific NLP tasks. Using Microsoft Speech Studio, a cloud-based ASR platform, we have fine-tuned the English pre-trained ASR models (available in speech studio) and achieved an average word error rate (WER) of 6.81%. The baseline ASR also provides a digital version of each planning webinar, making it accessible and text-searchable for future references. Additionally, the transcriptions can serve as a bridge between raw audio data and a range of text-based NLP tasks, such as named entity recognition (NER) and intent classification, potentially enhancing the digital footprint of the webinars and other connected data sources. Our work has several potential applications. Firstly, the transcriptions can be analyzed to understand the complex decision process of creating, implementing and modifying TMIs and may also contribute to TMI prediction services. Secondly, our dataset and model can be used to develop more accurate ASR systems for aviation-specific language, which can bring about digital communication in the aviation industry (and aid current “voice only” communications, which are inherently error-prone). Lastly, the transcriptions themselves can be used as a valuable resource for training other NLP models.

Stephen S. B. Clarke↗

Using Rule-Based Models for Weak Supervised Learning: A ChemNet for Transferable Chemical Property Prediction

With access to large datasets, deep neural networks (DNN) have achieved human-level accuracy in image and speech recognition tasks. However, in chemistry, data is inherently small and fragmented. In this work, we develop an approach of integrating rule-based knowledge into the Chemception CNN model via transfer learning techniques. The resulting model, ChemNet, is a transferable and generalizable deep neural network for chemical property prediction that learns in a semi-supervised manner from large unlabeled chemical databases. When ChemNet is further fine-tuned on 3 smaller datasets to predict chemical properties that it was not originally trained on, we show that ChemNet exceeds the accuracy of existing Chemception CNN models and other contemporary DNN models that were trained using conventional supervised learning approaches. These results indicate that pre-training ChemNet on a large diverse chemical database while incorporating chemistry domain knowledge, enables the development of more generalizable deep neural networks for the prediction of novel chemical properties.

Artificial Intelligence, Cheminformatics, Computat↗

An Effective Division of Labor Between Human and Robotic Agents Performing a Cooperative Assembly Task

NASA's Human Space Flight program depends heavily on spacewalks performed by human astronauts. These so-called extra-vehicular activities (EVAs) are risky, expensive and complex. Work is underway to develop a robotic astronaut's assistant that can help reduce human EVA time and workload by delivering human-like dexterous manipulation capabilities to any EVA worksite. An experiment is conducted to evaluate human-robot teaming strategies in the context of a simplified EVA assembly task in which Robonaut, a collaborative effort with the Defense Advanced Research Projects Agency (DARPA), an anthropomorphic robot works side-by-side with a human subject. Team performance is studied in an effort to identify the strengths and weaknesses of each teaming configuration and to recommend an appropriate division of labor. A shared control approach is developed to take advantage of the complementary strengths of the human teleoperator and robot, even in the presence of significant time delay.

Rehnmark, Fredrik↗

Lightweight and Statistical Techniques for Petascale PetaScale Debugging

This project investigated novel techniques for debugging scientific applications on petascale architectures. In particular, we developed lightweight tools that narrow the problem space when bugs are encountered. We also developed techniques that either limit the number of tasks and the code regions to which a developer must apply a traditional debugger or that apply statistical techniques to provide direct suggestions of the location and type of error. We extend previous work on the Stack Trace Analysis Tool (STAT), that has already demonstrated scalability to over one hundred thousand MPI tasks. We also extended statistical techniques developed to isolate programming errors in widely used sequential or threaded applications in the Cooperative Bug Isolation (CBI) project to large scale parallel applications. Overall, our research substantially improved productivity on petascale platforms through a tool set for debugging that complements existing commercial tools.

97 MATHEMATICS AND COMPUTING↗

Robotic Grasp Assistance for Decontamination and Decommissioning Tasks: Initial Applications with RoboGlove - 17310

RoboGlove, developed by NASA and General Motors, is a wearable robotic grasp assist device designed to augment human strength and endurance during manual tasks. Recent testing as part of the U.S. Department of Energy Office of Environmental Management's (DOE-EM's) Science of Safety Initiative has provided the opportunity to explore the glove's use within the context of decontamination and decommissioning work. Capable of providing a wearer with an additional 65-90 N (15-20 lb) of additional continuous grip strength, RoboGlove has the potential to decrease fatigue during long duration tasks, thereby reducing the risk of repetitive stress and other work related injuries. While current work at NASA focuses on integrating robotic grasp assistance with space suit gloves, the effort described herein focuses on the terrestrial application of RoboGlove to DOE-EM's cleanup mission. Following a brief technical description of RoboGlove, testing by United Steelworkers Union personnel at the Portsmouth Gaseous Diffusion Plant is described. Members of the workforce, in collaboration with NASA technologists, studied RoboGlove utility and performance while using tools common to the nuclear decontamination and decommissioning efforts at the plant. Results and feedback from this testing aim at identifying candidate activities for which RoboGlove holds particular promise as a workforce tool, in an effort to facilitate the infusion of robotic technology into routine workflow and processes across the DOE complex for the benefit of worker safety and health. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

Proof-of-concept automation of propellant processing

For space-based propellant production, automation of the process is needed. Currently, all phases of terrestrial production have some form of human interaction. A mixer was acquired to help perform the tasks of automation. A heating system to be used with the mixer was designed, built, and installed. Tests performed on the heating system verify design criteria. An IBM PS/2 personal computer was acquired for the future automation work. It is hoped that some the mixing process itself will be automated. This is a concept demonstration task; proving that propellant production can be automated reliably.

Ramohalli, Kumar↗

Making tomorrow's mistakes today: Evolutionary prototyping for risk reduction and shorter development time

In the early days of JPL's solar system exploration, each spacecraft mission required its own dedicated data system with all software applications written in the mainframe's native assembly language. Although these early telemetry processing systems were a triumph of engineering in their day, since that time the computer industry has advanced to the point where it is now advantageous to replace these systems with more modern technology. The Space Flight Operations Center (SFOC) Prototype group was established in 1985 as a workstation and software laboratory. The charter of the lab was to determine if it was possible to construct a multimission telemetry processing system using commercial, off-the-shelf computers that communicated via networks. The staff of the lab mirrored that of a typical skunk works operation -- a small, multi-disciplinary team with a great deal of autonomy that could get complex tasks done quickly. In an effort to determine which approaches would be useful, the prototype group experimented with all types of operating systems, inter-process communication mechanisms, network protocols, packet size parameters. Out of that pioneering work came the confidence that a multi-mission telemetry processing system could be built using high-level languages running in a heterogeneous, networked workstation environment. Experience revealed that the operating systems on all nodes should be similar (i.e., all VMS or all PC-DOS or all UNIX), and that a unique Data Transport Subsystem tool needed to be built to address the incompatibilities of network standards, byte ordering, and socket buffering. The advantages of building a telemetry processing system based on emerging industry standards were numerous: by employing these standards, we would no longer be locked into a single vendor. When new technology came to market which offered ten times the performance at one eighth the cost, it would be possible to attach the new machine to the network, re-compile the application code, and run. In addition, we would no longer be plagued with lack of manufacturer support when we encountered obscure bugs. And maybe, hopefully, the eternal elusive goal of software portability across different vendors' platforms would finally be available. Some highlights of our prototyping efforts are described.

Friedman, Gary↗