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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 739 records · Page 41
All sourcesNASA NTRSDOE OSTI
NASA NTRS2003

Large-scale Stratospheric Transport Processes

The PI has undertaken a theoretical analysis of the existence and nature of compact tracer-tracer relationships of the kind observed in the stratosphere, augmented with three-dimensional model simulations of stratospheric tracers (the latter being an extension of modeling work the group did during the SOLVE experiment). This work achieves a rigorous theoretical basis for the existence and shape of these relationships, as well as a quantitative theory of their width and evolution, in terms of the joint tracer-tracer PDF distribution. A paper on this work is almost complete and will soon be submitted to Rev. Geophys. We have analyzed lower stratospheric water in simulations with an isentropic-coordinate version of the MATCH transport model which we recently helped to develop. The three-dimensional structure of lower stratospheric water, in particular, attracted our attention: dry air is, below about 400K potential temperature, localized in the regions of the west Pacific and equatorial South America. We have been analyzing air trajectories to determine how air passes through the tropopause cold trap. This work is now being completed, and a paper will be submitted to Geophys. Res. Lett. before the end of summer. We are continuing to perform experiments with the 'MATCH' CTM, in both sigma- and entropy-coordinate forms. We earlier found (in collaboration with Dr Natalie Mahowald, and as part of an NSF-funded project) that switching to isentropic coordinates made a substantial improvement to the simulation of the age of stratospheric air. We are now running experiments with near-tropopause sources in both versions of the model, to see if and to what extent the simulation of stratosphere-troposphere transport is dependent on the model coordinate. Personnel Research is supervised by the PI, Prof. Alan Plumb. Mr William Heres conducts the tracer modeling work and performs other modeling tasks. Two graduate students, Ms Irene Lee and Mr Michael Ring, have been participating in the research.

Plumb, R. Alan↗
NASA NTRS2004

Formal Methods for Autonomic and Swarm-based Systems

Swarms of intelligent rovers and spacecraft are being considered for a number of future NASA missions. These missions will provide MSA scientist and explorers greater flexibility and the chance to gather more science than traditional single spacecraft missions. These swarms of spacecraft are intended to operate for large periods of time without contact with the Earth. To do this, they must be highly autonomous, have autonomic properties and utilize sophisticated artificial intelligence. The Autonomous Nano Technology Swarm (ANTS) mission is an example of one of the swarm type of missions NASA is considering. This mission will explore the asteroid belt using an insect colony analogy cataloging the mass, density, morphology, and chemical composition of the asteroids, including any anomalous concentrations of specific minerals. Verifying such a system would be a huge task. This paper discusses ongoing work to develop a formal method for verifying swarm and autonomic systems.

Rouff, Christopher↗
NASA NTRS2004

The International Space Station: A Pathway to the Future

Nearly six years after the launch of the first International Space Station element, and four years after its initial occupation, the United States and our 16 international partners have made great strides in operating this impressive Earth orbiting research facility. This past year we have done so in the face of the adversity of operating without the benefit of the Space Shuttle. In his January 14, 2004, speech announcing a new vision for America's space program, President Bush affirmed the United States' commitment to completing construction of the International Space Station by 2010. The President also stated that we would focus our future research aboard the Station on the longterm effects of space travel on human biology. This research will help enable human crews to venture through the vast voids of space for months at a time. In addition, ISS affords a unique opportunity to serve as an engineering test bed for hardware and operations critical to the exploration tasks. NASA looks forward to working with our partners on International Space Station research that will help open up new pathways for future exploration and discovery beyond low Earth orbit. This paper provides an overview of the International Space Station Program focusing on a review of the events of the past year, as well as plans for next year and the future.

Kitmacher, Gary H.↗
NASA NTRS2008

Information Presentation

The goal of the Information Presentation Directed Research Project (DRP) is to address design questions related to the presentation of information to the crew on flight vehicles, surface landers and habitats, and during extra-vehicular activities (EVA). Designers of displays and controls for exploration missions must be prepared to select the text formats, label styles, alarms, electronic procedure designs, and cursor control devices that provide for optimal crew performance on exploration tasks. The major areas of work, or subtasks, within the Information Presentation DRP are: 1) Controls, 2) Displays, 3) Procedures, and 4) EVA Operations.

Holden, Kritina↗
NASA NTRS2010

Human Factors in Training: Space Medical Proficiency Training

The early Constellation space missions are expected to have medical capabilities very similar to those currently on the Space Shuttle and the International Space Station (ISS). For Crew Exploration Vehicle (CEV) missions to the ISS, medical equipment will be located on the 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. The space medical training work is part of the Human Factors in Training Directed Research Project (DRP) of the Space Human Factors Engineering (SHFE) Project under the Space Human Factors and Habitability (SHFH) Element of the Human Research Program (HRP). This is a joint project consisting of human factors team from the Ames Research Center (ARC) with Immanuel Barshi as Principal Investigator and the Johnson Space Center (JSC). Human factors researchers at JSC have recently investigated medical performance support tools for CMOs on-orbit, and FSs on the ground, and researchers at the Ames Research Center performed a literature review on medical errors. Work on medical training has been conducted in collaboration with the Medical Training Group at the Johnson Space Center (JSC) and with Wyle Laboratories that provides medical training to crew members, biomedical engineers (BMEs), and to flight surgeons under the Bioastronautics contract. One area of research building on activities from FY08, involved the feasibility of just-in-time (JIT) training techniques and concepts for real-time medical procedures. A second area of research involves FS performance support tools. Information needed by the FS during the 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. The tool could have different uses depending on the situation and the skill of the user. An experienced flight surgeon could use it during an emergency situation as a decision and performance support tool, whereas a new flight surgeon could use it as JITT, or part of his/her regular training. The work proposed for FY10 continues to build on this strong collaboration with the Space Medical Training Group and previous research.

Byrne, Vicky E.↗
NASA NTRS2010

VLBI Data Interchange Format (VDIF)

One important outcome of the 7th International e-VLBI Workshop in Shanghai in June 2008 was the creation of a task force to study and recommend a universal VLBI data format that is suitable for both on-the-wire e-VLBI data transfer, as well as direct disk storage. This task force, called the VLBI Data Interchange Format (VDIF) Task Force, is the first part of a two-part effort, the second of which will address standardization of e-VLBI data-transmission-protocols. The formation of the VDIF Task Force was prompted particularly by increased e-VLBI activity and the difficulties encountered when data arrive at a correlator in different formats from various instruments in various parts of the world. The task force created a streaming packetized data format that may be used for real-time and non-realtime e-VLBI, as well as direct disk storage. The data may contain multiple channels of time-sampled data with an arbitrary number of channels, arbitrary #bits/sample up to 32, and real or complex data; data rates in excess of 100 Gbps are supported. Each data packet is completely self-identifying via a short header, and data may be decoded without reference to any external information. The VDIF task force has completed its work, and the VDIF standard was ratified at the 2009 e-VLBI workshop in Madrid.

Whitney, Alan↗
NASA NTRS2015

A Structural Model Decomposition Framework for Hybrid Systems Diagnosis

Nowadays, a large number of practical systems in aerospace and industrial environments are best represented as hybrid systems that consist of discrete modes of behavior, each defined by a set of continuous dynamics. These hybrid dynamics make the on-line fault diagnosis task very challenging. In this work, we present a new modeling and diagnosis framework for hybrid systems. Models are composed from sets of user-defined components using a compositional modeling approach. Submodels for residual generation are then generated for a given mode, and reconfigured efficiently when the mode changes. Efficient reconfiguration is established by exploiting causality information within the hybrid system models. The submodels can then be used for fault diagnosis based on residual generation and analysis. We demonstrate the efficient causality reassignment, submodel reconfiguration, and residual generation for fault diagnosis using an electrical circuit case study.

structural model decomposition↗
NASA NTRS2017

Obtaining and Using Planetary Spatial Data into the Future: The Role of the Mapping and Planetary Spatial Infrastructure Team (MAPSIT)

Planetary spatial data, which include any remote sensing data or derived products with sufficient positional information such that they can be projected onto a planetary body, continue to rapidly increase in volume and complexity. These data are the hard-earned fruits of decades of planetary exploration, and are the end result of mission planning and execution. Maintaining these data using accessible formats and standards for all scientists has been necessary for the success of past, present, and future planetary missions. The Mapping and Planetary Spatial Infrastructure Team (MAPSIT) is a group of planetary community members tasked by NASA Headquarters to work with the planetary science community to identify and prioritize their planetary spatial data needs to help determine the best pathways for new data acquisition, usable product derivation, and tools/capability development that supports NASA's planetary science missions.

Radebaugh, J.↗
NASA NTRS2017

Enabling Autonomous Space Mission Operations with Artificial Intelligence

For over 50 years, NASA's crewed missions have been confined to the Earth-Moon system, where speed-of-light communications delays between crew and ground are practically nonexistent. This ground-centered mode of operations, with a large, ground-based support team, is not sustainable for NASAs future human exploration missions to Mars. Future astronauts will need smarter tools employing Artificial Intelligence (AI) techniques make decisions without inefficient communication back and forth with ground-based mission control. In this talk we will describe several demonstrations of astronaut decision support tools using AI techniques as a foundation. These demonstrations show that astronauts tasks ranging from living and working to piloting can benefit from AI technology development.

Frank, Jeremy↗
NASA NTRS2018

A Novel Multi-Spacecraft Interplanetary Global Trajectory Optimization Transcription

As the frontier of space exploration continues to advance, so does the design complexity of future interplanetary missions. One avenue of this increasing complexity includes a class of designs known as "Distributed Spacecraft Missions"; missions where multiple spacecraft coordinate to perform shared objectives. Current approaches for the global trajectory optimization of these Multi-Vehicle Missions (MVMs) are prone to shortcomings including laborious iterative design, considerable human-in-the-loop effort, treatment of the multi-vehicle problem as multiple separate trajectory optimization subproblems (resulting in suboptimal solutions where the whole is less than the sum of its parts), and poor handling of coordination objectives and constraints. There are only a handful of software platforms in existence capable of fully-automated, rapid, interplanetary mission and systems global optimization including the Parallel Global Multiobjective Optimizer (PaGMO), the Gravity Assisted Low-thrust Local Optimization Program (GALLOP), and the Evolutionary Mission Trajectory Generator (EMTG). However, none of these tools is capable of performing such tasks for MVM designs. The work outlined in this paper lays the groundwork for a technique to begin addressing these shortcomings. We present a fully-automated technique which frames interplanetary MVMs as Multi-Objective, Multi-Agent Hybrid Optimal Control Problems (MOMA HOCP). First, the basic functionality of this technique is validated on the single-vehicle problem of reproducing the Cassini interplanetary cruise.

Interplanetary↗
NASA NTRS2018

A Novel Multi-Spacecraft Interplanetary Global Trajectory Optimization Transcription

As the frontier of space exploration continues to advance, so does the design complexity of future interplanetary missions. One avenue of this increasing complexity includes a class of designs known as ``Distributed Spacecraft Missions"; missions where multiple spacecraft coordinate to perform shared objectives. Current approaches for the global trajectory optimization of these Multi-Vehicle Missions (MVMs) are prone to shortcomings including laborious iterative design, considerable human-in-the-loop effort, treatment of the multi-vehicle problem as multiple separate trajectory optimization subproblems (resulting in suboptimal solutions where the whole is less than the sum of its parts), and poor handling of coordination objectives and constraints. There are only a handful of software platforms in existence capable of fully-automated, rapid, interplanetary mission and systems global optimization including the Parallel Global Multiobjective Optimizer (PaGMO), the Gravity Assisted Low-thrust Local Optimization Program (GALLOP), and the Evolutionary Mission Trajectory Generator (EMTG). However, none of these tools is capable of performing such tasks for MVM designs. The work outlined in this paper lays the groundwork for a technique to begin addressing these shortcomings. We present a fully-automated technique which frames interplanetary MVMs as Multi-Objective, Multi-Agent Hybrid Optimal Control Problems (MOMA HOCP). First, the basic functionality of this technique is validated on the single-vehicle problem of reproducing the Cassini interplanetary cruise.

Napier, Sean W.↗
NASA NTRS2014

Human Factors of Automation in the Airline Cockpit

The introduction of automation to the automobile is following an approach similar to that used to bring automation to the airline cockpit. As technologies incrementally became available to automate portions of the flying task, pilots were left to perform those portions of the task for which engineers were still working towards automating. A number of problems have resulted from this process of gradual takeover of a job once performed entirely by humans. Pilots struggle to maintain awareness of a task with which they are no longer intimately involved and of complex technologies that they do not fully understand. Particularly difficult problems arise when increasingly reliable automated systems reach the limits of their capabilities and require pilots to suddenly exercise manual control and reasoning skills that have slipped away as a result of disuse. We argue that car automation will face these problems and more. Aviation enjoys a broad system of redundancies and safety nets, and, high in the sky, more time to address any problems that arise. We review the literature describing problems that were observed as automation was introduced to the airline cockpit and invite car automation designers to consider how they might play out as technology is gradually introduced to cars and drivers.

Casner, Stephen↗
NASA NTRS2017

Analysis of San Francisco Bar Pilot Dispatch Records: Preliminary Report

Maritime pilots licensed by the San Francisco Board of Pilot Commissioners perform safety-critical tasks in a demanding environment, working in all weather and at all times of day and night. Since 1850, San Francisco maritime pilots have been known as Bar Pilots because their duties include guiding ships safely across the large sand bar that lies west of the Golden Gate. Schedules and Work Hours Records for San Francisco Bay Bar Pilots were analyzed to determine the minimum and maximum work periods, the frequency of extended work hours, the frequency of night work and the rotation of work hours. A mathematical model is being applied to predict fatigue in order to identify schedules that may have a high likelihood of fatigue. This presentation provides a progress report on the research thus far.

marine pilots↗
NASA NTRSDate not supplied

Early Assessments of Crew Timelines for the Lunar Surface Habitat

As NASA progresses towards sustained crewed space missions, crew timelines will become increasingly important to achieving mission goals. While it is desirable to spend as much time as possible during crewed space missions on science activities and experiments, there are a large number of activities that crew members must perform each day in order to maintain both crew and vehicle health and safety. The time available for science activities in space is highly dependent on mandatory tasks required for crew and vehicle health and safety. The different crewed activities need to be planned accordingly long before the start of a mission in order to optimize crew time for science. To begin assessing the potential crew time for available for science, an understanding of the requirements to maintain crew and vehicle health and safety is needed. These additional activities may include sleep, exercise, vehicle maintenance, logistics handling, crew personal time, as well as many other tasks. The remaining time outside of these required tasks, within a reasonable crew work schedule, can be dedicated to science operations. This paper will detail a collaborative effort to analyzing crew times for sustained spaceflight missions and how the results of that analysis are applied to the crew timeline for the proposed Lunar Surface Habitat (SH).To determine the crew time for all of these required activities, an analysis was conducted utilizing defined agency requirements and historical crewed mission data. Predicted crew activity times were integrated into a daily schedule in order to optimize the crew’s time during the mission. This methodology was utilized to produce expected crew timelines for NASA’s proposed Artemis Base Camp (ABC) missions. The current plans for the ABC contain two different sustained habitats, the Pressurized Rover (PR) and the Surface Habitat (SH). While the crew are separated between the two habitats, the timelines for each element are dependent on the other element’s operations, so the two element timelines are formed in conjunction with one another. The results described in this paper, however, will focus solely on the crew timeline in the SH. This paper will explain the methodology behind predicting the required crew time spent in the SH for each activity, and the process of incorporating these predicted crew times into a coherent schedule.

Crew Time↗
NASA NTRS2024

Cognitive Performance in ISS Astronauts on 6-Month Low Earth Orbit Missions

Introduction: Current and future astronauts will endure prolonged exposure to spaceflight hazards and environmental stressors that could compromise cognitive functioning, yet cognitive performance in current missions to the International Space Station remains critically under-characterized. We systematically assessed cognitive performance across 10 cognitive domains in astronauts on 6-month missions to the ISS. Methods: Twenty-five professional astronauts were administered the Cognition Battery as part of National Aeronautics and Space Administration (NASA) Human Research Program Standard Measures Cross-Cutting Project. Cognitive performance data were collected at five mission phases: pre-flight, early flight, late flight, early post-flight, and late post-flight. We calculated speed and accuracy scores, corrected for practice effects, and derived z-scores to represent deviations in cognitive performance across mission phases from the sample’s mean baseline (i.e., pre-flight) performance. Linear mixed models with random subject intercepts and pairwise comparisons examined the relationships between mission phase and cognitive performance. Results: Cognitive performance was generally stable over time with some differences observed across mission phases for specific subtests. There was slowed performance observed in early flight on tasks of processing speed, visual working memory, and sustained attention. We observed a decrease in risk-taking propensity during late flight and post-flight mission phases. Beyond examining group differences, we inspected scores that represented a significant shift from the sample’s mean baseline score, revealing that 11.8% of all flight and post-flight scores were at or below 1.5 standard deviations below the sample’s baseline mean. Finally, exploratory analyses yielded no clear pattern of associations between cognitive performance and either sleep or ratings of alertness. Conclusions: There was no evidence for a systematic decline in cognitive performance for astronauts on a 6-month missions to the ISS. Some differences were observed for specific subtests at specific mission phases, suggesting that processing speed, visual working memory, sustained attention, and risk-taking propensity may be the cognitive domains most susceptible to change in Low Earth Orbit for high performing, professional astronauts. We provide descriptive statistics of pre-flight cognitive performance from 25 astronauts, the largest published preliminary normative database of its kind to date, to help identify significant performance decrements in future samples.

Data curation↗
DOE OSTI2015

Leveraging Paraphrase Labels to Extract Synonyms from Twitter

We present an approach for automatically learning synonyms from a paraphrase corpus of tweets. This work shows improvement on the task of paraphrase detection when we substitute our extracted synonyms into the training set. The synonyms are learned by using chunks from a shallow parse to create candidate synonyms and their context windows, and the synonyms are incorporated into a paraphrase detection system that uses machine translation metrics as features for a classifier. We demonstrate a 2.29% improvement in F1 when we train and test on the paraphrase training set, providing better coverage than previous systems, which shows the potential power of synonyms that are representative of a specific topic.

Antoniak, Maria A.↗
DOE OSTI2021

Self-Supervised Anomaly Detection via Neural Autoregressive Flows with Active Learning

Many self-supervised methods have been proposed with the target of image anomaly detection. These methods often rely on the paradigm of data augmentation with predefined transformations such as flipping, cropping, and rotations. However, it is not straightforward to apply these techniques for non-image data, such as time series or tabular data, while the performance of the existing deep approaches has been under our expectation on tasks beyond images. In this work, we propose a novel active learning (AL) scheme that relied on neural autoregressive flows (NAF) for self-supervised anomaly detection, specifically on small-scale data. Unlike other generative models such as GANs or VAEs, flow-based models allow to explicitly learn the probability density and thus can assign accurate likelihoods to normal data which makes it usable to detect anomalies. The proposed NAF-AL method is achieved by efficiently generating random samples from latent space and transforming them into feature space along with likelihoods via invertible mapping. The samples with lower likelihoods are selected and further checked by outlier detection using Mahalanobis distance. The augmented samples incorporating with normal samples are used for training a better detector so as to approach decision boundaries. Compared with random transformations, NAF-AL can be interpreted as a likelihood-oriented data augmentation that is more efficient and robust. Extensive experiments show that our approach outperforms existing baselines on multiple time series and tabular datasets, and a real-world application in advanced manufacturing, with significant improvement on anomaly detection accuracy and robustness over the state-of-the-art.

Zhang, Jiaxin↗
DOE OSTI2023

Hydrogen Equipment Enclosure Risk Reduction through Earlier Detection of Component Failures

Hydrogen component reliability and the hazard associated with failure rates is a critical area of research for the successful implementation and growth of hydrogen technology across the globe. The research team has partnered to quantify system risk reduction through earlier detection of hydrogen component failures. A model of hydrogen dispersion in a hydrogen equipment enclosure has been developed utilizing experimentally quantified hydrogen component leak rates as inputs. This model provides insight into the impact of hydrogen safety sensors and ventilation on the flammable mass within a hydrogen equipment enclosure. This model also demonstrates the change in safety sensor response time due to detector placement under various leak scenarios. The team looks to improve overall hydrogen system safety through an improved understanding of hydrogen component reliability and risk mitigation methods. This collaboration fits under the work program of IEA Hydrogen Task 43 Subtask E Hydrogen System Safety.

CFD↗