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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 1,261 records · Page 70
All sourcesNASA NTRSDOE OSTI
NASA NTRS1986

Analytical techniques of pilot scanning behavior and their application

The state of the art of oculometric data analysis techniques and their applications in certain research areas such as pilot workload, information transfer provided by various display formats, crew role in automated systems, and pilot training are documented. These analytical techniques produce the following data: real-time viewing of the pilot's scanning behavior, average dwell times, dwell percentages, instrument transition paths, dwell histograms, and entropy rate measures. These types of data are discussed, and overviews of the experimental setup, data analysis techniques, and software are presented. A glossary of terms frequently used in pilot scanning behavior and a bibliography of reports on related research sponsored by NASA Langley Research Center are also presented.

Harris, R. L., Sr.↗
NASA NTRS1986

Bedrest in healthy women: Effects of menstrual function and oral contraceptives

With the development of the space shuttle program, space flight for the first time is available to individuals who have not been specially selected and trained to be astronauts. In addition, women are being actively recruited into the space program, both as mission specialists and as career astronauts. One purpose of this project was to examine some of the physiological responses of women to a simulated weightlessness program (12 day horizontal bedrest), to compare their responses to those reported in men during similar programs, and to test whether menstrual function might alter some of the physiological changes which occur during bedrest, specifically changes in the plasma volume, exercise tolerance, and venous compliance before and after bedrest.

Fortney, Suzanne M.↗
NASA NTRS1993

Anomaly detection of turbopump vibration in Space Shuttle Main Engine using statistics and neural networks

The statistical and neural networks methods have been applied to investigate the feasibility in detecting anomalies in turbopump vibration of SSME. The anomalies are detected based on the amplitude of peaks of fundamental and harmonic frequencies in the power spectral density. These data are reduced to the proper format from sensor data measured by strain gauges and accelerometers. Both methods are feasible to detect the vibration anomalies. The statistical method requires sufficient data points to establish a reasonable statistical distribution data bank. This method is applicable for on-line operation. The neural networks method also needs to have enough data basis to train the neural networks. The testing procedure can be utilized at any time so long as the characteristics of components remain unchanged.

Lo, C. F.↗
NASA NTRS1993

Denver TMA assessment

This report describes the assessment of the Traffic Management Advisor (TMA) conducted at the Denver Center and TRACON, January 11-February 5, 1993. The assessment addressed the effectiveness of TMA for supporting various traffic management activities. At the Center, traffic management coordinators (TMC's) shadowed traffic operations, using TMA to make metering time and internal release decisions. At the TRACON, TMC's accessed TMA in an advisory mode for different planning activities such as staffing, distributing the traffic load, and changing the airport acceptance rate. These different opportunities for assessing TMA provide insight into TMA as a potential communication aid and planning tool. Findings from this assessment indicate that TMA can be used to support traffic management planning and decisions. TMC's at the center were able to use information provided by TMA to determine metering times as well as internal release times. At the TRACON, TMA supported decisions on airport configuration, airport acceptance rate, load distribution, proactive coordination with the center, and staffing. While findings of TMA use are generally positive, it must be kept in mind that this assessment is a snapshot in time. Not all TMA capabilities were assessed, nor were TMC's fully trained and knowledgeable on all features. Feature use will continue to evolve and strategies emerge as the TMC's gain experience with TMA over a variety of traffic situations and their understanding of TMA capabilities broadens with continued training.

Harwood, Kelly↗
NASA NTRS1989

Intelligent hypertext manual development for the Space Shuttle hazardous gas detection system

This research is designed to utilize artificial intelligence (AI) technology to increase the efficiency of personnel involved with monitoring the space shuttle hazardous gas detection systems at the Marshall Space Flight Center. The objective is to create a computerized service manual in the form of a hypertext and expert system which stores experts' knowledge and experience. The resulting Intelligent Manual will assist the user in interpreting data timely, in identifying possible faults, in locating the applicable documentation efficiently, in training inexperienced personnel effectively, and updating the manual frequently as required.

Lo, Ching F.↗
NASA NTRS1997

AOPA Survey Summary of AGATE Concepts Demonstration October 17-19, 1996: Basic Report - Volume 1

An AGATE Concepts Demonstration was conducted at the Annual Aircraft Owners and Pilots Association (AOPA) Convention in 1996. The demonstration consisted of an interactive simulation of a single-pilot, single-engine aircraft in which the participant took off, flew a brief enroute segment and then flew a Global Positioning System (GPS) approach and landing. The participant was provided an advanced 'pathway-in-the-sky' presentation on both a head-up display and a head-down display to follow throughout the flight. A single lever power control and display concept was also provided for control of the engine throughout the flight. A second head-down, multifunction display in the instrument panel provided a moving map display for navigation purposes and monitoring of the status of the aircraft's systems. An estimated 352 people observed or participated in the demonstration, and 144 surveys were collected. The pilot ratings of the participants ranged from student to Air Transport Rating with an average of 1850 hours total flight time. The performance of the participants was surprisingly good, considering the minimal training in a completely new system concept. The overwhelming response was that technologies that simplify piloting tasks are enthusiastically welcomed by pilots of all experience levels. The increase in situation awareness and reduction in pilot workload were universally accepted and lauded as steps in the right direction.

Source record↗
NASA NTRS1997

AOPA Survey Summary of AGATE Concepts Demonstration, October 17-19, 1996: Original Survey Data - Volume 2

An AGATE Concepts Demonstration was conducted at the Annual Aircraft Owners and Pilots Association (AOPA) Convention in 1996. The demonstration consisted of an interactive simulation of a single-pilot, single-engine aircraft in which the participant took off, flew a brief enroute segment and then flew a Global Positioning System (GPS) approach and landing. The participant was provided an advanced 'pathway-in-the-sky' presentation on both a head-up display and a head-down display to follow throughout the flight. A single lever power control and display concept was also provided for control of the engine throughout the flight A second head-down, multifunction display in the instrument panel provided a moving map display for navigation purposes and monitoring of the status of the aircraft's systems. An estimated 352 people observed or participated in the demonstration, and 144 surveys were collected. The pilot ratings of the participants ranged from student to Air Transport Rating with an average of 1850 hours total flight time. The performance of the participants was surprisingly good, considering the minimal training in a completely new system concept. The overwhelming response was that technologies that simplify piloting tasks are enthusiastically welcomed by pilots of all experience levels. The increase in situation awareness and reduction in pilot workload were universally accepted and lauded as steps in the right direction.

Source record↗
NASA NTRS1998

A Real-Time Telemetry Simulator of the IUS Spacecraft

A real-time telemetry simulator of the IUS spacecraft has recently entered operation to train Flight Control Teams for the launch of the AXAF telescope from the Shuttle. The simulator has proven to be a successful higher fidelity implementation of its predecessor, while affirming the rapid development methodology used in its design. Although composed of COTS hardware and software, the system simulates the full breadth of the mission: Launch, Pre-Deployment-Checkout, Burn Sequence, and AXAF/IUS separation. Realism is increased through patching the system into the operations facility to simulate IUS telemetry, Shuttle telemetry, and the Tracking Station link (commands and status message).

Drews, Michael E.↗
NASA NTRS2006

Interfacing with USSTRATCOM and UTTR during Stardust Earth Return

The Stardust Sample Return Capsule separated from the main spacecraft four hours prior to atmospheric entry. Between this time and the time at which the SRC touched down at the Utah Test and Training Range, two organizations external to JPL were involved in tracking the Sample Return Capsule. Orbit determination for the Stardust spacecraft during deep space cruise, the encounters of asteroid Annefrank and comet Wild 2, and the final approach to Earth used X-band radio metric Doppler and range data obtained through the Deep Space Network. The SRC lacked the electronics needed for coherently transponded radio metric tracking, so the DSN was not able to track the SRC after it separated from the main spacecraft. Although the expected delivery accuracy at atmospheric entry was well within the capability needed to target the SRC to the desired ground location, it was still desirable to obtain direct knowledge of the SRC trajectory in case of anomalies. For this reason U.S. Strategic Command was engaged to track the SRC between separation and atmospheric entry. Once the SRC entered the atmosphere, ground sensors at UTTR were tasked to acquire the descending SRC and maintain track during the descent in order to determine the landing location, to which the ground recovery team was then directed. This paper discusses organizational interfaces, data products, and delivery schedules, and the actual tracking operations are described.

Utah Test and Training Range (UTTR)↗
NASA NTRS2005

Rotating Desk for Collaboration by Two Computer Programmers

A special-purpose desk has been designed to facilitate collaboration by two computer programmers sharing one desktop computer or computer terminal. The impetus for the design is a trend toward what is known in the software industry as extreme programming an approach intended to ensure high quality without sacrificing the quantity of computer code produced. Programmers working in pairs is a major feature of extreme programming. The present desk design minimizes the stress of the collaborative work environment. It supports both quality and work flow by making it unnecessary for programmers to get in each other s way. The desk (see figure) includes a rotating platform that supports a computer video monitor, keyboard, and mouse. The desk enables one programmer to work on the keyboard for any amount of time and then the other programmer to take over without breaking the train of thought. The rotating platform is supported by a turntable bearing that, in turn, is supported by a weighted base. The platform contains weights to improve its balance. The base includes a stand for a computer, and is shaped and dimensioned to provide adequate foot clearance for both users. The platform includes an adjustable stand for the monitor, a surface for the keyboard and mouse, and spaces for work papers, drinks, and snacks. The heights of the monitor, keyboard, and mouse are set to minimize stress. The platform can be rotated through an angle of 40 to give either user a straight-on view of the monitor and full access to the keyboard and mouse. Magnetic latches keep the platform preferentially at either of the two extremes of rotation. To switch between users, one simply grabs the edge of the platform and pulls it around. The magnetic latch is easily released, allowing the platform to rotate freely to the position of the other user

Riley, John Thomas↗
NASA NTRS2004

NASA Tech Briefs, June 2004

Topics covered include: COTS MEMS Flow-Measurement Probes; Measurement of an Evaporating Drop on a Reflective Substrate; Airplane Ice Detector Based on a Microwave Transmission Line; Microwave/Sonic Apparatus Measures Flow and Density in Pipe; Reducing Errors by Use of Redundancy in Gravity Measurements; Membrane-Based Water Evaporator for a Space Suit; Compact Microscope Imaging System with Intelligent Controls; Chirped-Superlattice, Blocked-Intersubband QWIP; Charge-Dissipative Electrical Cables; Deep-Sea Video Cameras Without Pressure Housings; RFID and Memory Devices Fabricated Integrally on Substrates; Analyzing Dynamics of Cooperating Spacecraft; Spacecraft Attitude Maneuver Planning Using Genetic Algorithms; Forensic Analysis of Compromised Computers; Document Concurrence System; Managing an Archive of Images; MPT Prediction of Aircraft-Engine Fan Noise; Improving Control of Two Motor Controllers; Electro-deionization Using Micro-separated Bipolar Membranes; Safer Electrolytes for Lithium-Ion Cells; Rotating Reverse-Osmosis for Water Purification; Making Precise Resonators for Mesoscale Vibratory Gyroscopes; Robotic End Effectors for Hard-Rock Climbing; Improved Nutation Damper for a Spin-Stabilized Spacecraft; Exhaust Nozzle for a Multitube Detonative Combustion Engine; Arc-Second Pointer for Balloon-Borne Astronomical Instrument; Compact, Automated Centrifugal Slide-Staining System; Two-Armed, Mobile, Sensate Research Robot; Compensating for Effects of Humidity on Electronic Noses; Brush/Fin Thermal Interfaces; Multispectral Scanner for Monitoring Plants; Coding for Communication Channels with Dead-Time Constraints; System for Better Spacing of Airplanes En Route; Algorithm for Training a Recurrent Multilayer Perceptron; Orbiter Interface Unit and Early Communication System; White-Light Nulling Interferometers for Detecting Planets; and Development of Methodology for Programming Autonomous Agents.

Source record↗
NASA NTRS2016

Data Mining and Knowledge Discover - IBM Cognitive Alternatives for NASA KSC

Skillful tools in cognitive computing to transform industries have been found favorable and profitable for different Directorates at NASA KSC. In this study is shown how cognitive computing systems can be useful for NASA when computers are trained in the same way as humans are to gain knowledge over time. Increasing knowledge through senses, learning and a summation of events is how the applications created by the firm IBM empower the artificial intelligence in a cognitive computing system. NASA has explored and applied for the last decades the artificial intelligence approach specifically with cognitive computing in few projects adopting similar models proposed by IBM Watson. However, the usage of semantic technologies by the dedicated business unit developed by IBM leads these cognitive computing applications to outperform the functionality of the inner tools and present outstanding analysis to facilitate the decision making for managers and leads in a management information system.

Cognitive computing↗
NASA NTRS2018

The Diurnal Cycle of Cloud Profiles over Land and Ocean Between 51degS and 51degN, Seen by the CATS Spaceborne Lidar from the International Space Station

We document, for the first time, how detailed vertical profiles of cloud fraction (CF) change diurnally between 51 deg S and 51 deg N, by taking advantage of 15 months of measurements from the Cloud-Aerosol Transport System (CATS) lidar on the non-sun-synchronous International Space Station (ISS). Over the tropical ocean in summer, we find few high clouds during daytime. At night they become frequent over a large altitude range (11-16 km between 22:00 and 04:00 LT). Over the summer tropical continents, but not over ocean, CATS observations reveal mid-level clouds (4-8 km above sea level or a.s.l.) persisting all day long, with a weak diurnal cycle (minimum at noon). Over the Southern Ocean, diurnal cycles appear for the omnipresent low-level clouds (minimum between noon and 15:00) and high-altitude clouds (minimum between 08:00 and 14:00). Both cycles are time shifted, with high-altitude clouds following the changes in low-altitude clouds by several hours. Over all continents at all latitudes during summer, the low-level clouds develop upwards and reach a maximum occurrence at about 2.5 km a.s.l. in the early afternoon (around 14:00). Our work also shows that (1) the diurnal cycles of vertical profiles derived from CATS are consistent with those from ground-based active sensors on a local scale, (2) the cloud profiles derived from CATS measurements at local times of 01:30 and 13:30 are consistent with those observed from CALIPSO at similar times, and (3) the diurnal cycles of low and high cloud amounts (CAs) derived from CATS are in general in phase with those derived from geostationary imagery but less pronounced. Finally, the diurnal variability of cloud profiles revealed by CATS strongly suggests that CALIPSO measurements at 01:30 and 13:30 document the daily extremes of the cloud fraction profiles over ocean and are more representative of daily averages over land, except at altitudes above 10 km where they capture part of the diurnal variability. These findings are applicable to other instruments with local overpass times similar to CALIPSO's, such as all the other A-Train instruments and the future Earth-CARE mission.

Noel, Vincent↗
NASA NTRS2020

Marshall Space Flight Center Research and Technology Report 2019

Today, our calling to explore is greater than ever before, and here at Marshall Space Flight Center—we make human deep space exploration possible. A key goal for Artemis is demonstrating and perfecting capabilities on the Moon for technologies needed for humans to get to Mars. This year’s report features 10 of the Agency’s 16 Technology Areas, and I am proud of Marshall’s role in creating solutions for so many of these daunting technical challenges. Many of these projects will lead to sustainable in-space architecture for human space exploration that will allow us to travel to the Moon, on to Mars, and beyond. Others are developing new scientific instruments capable of providing an unprecedented glimpse into our universe. NASA has led the charge in space exploration for more than six decades, and through the Artemis program we will help build on our work in low Earth orbit and pave the way to the Moon and Mars. At Marshall, we leverage the skills and interest of the international community to conduct scientific research, develop and demonstrate technology, and train international crews to operate further from Earth for longer periods of time than ever before— first at the lunar surface, then on to our next giant leap, human exploration of Mars. While each project in this report seeks to advance new technology and challenge conventions, it is important to recognize the diversity of activities and people supporting our mission. This report not only showcases the Center’s capabilities and our partnerships, it also highlights the progress our people have achieved in the past year. These scientists, researchers and innovators are why Marshall and NASA will continue to be a leader in innovation, exploration, and discovery for years to come.

Dankanich, John W.↗
NASA NTRS2020

Using Reinforcement Learning to Design Missed Thrust Resilient Trajectories

From ion thrusters to solar sails, spacecraft continue to adopt new and more efficient forms of propulsion. As these low-thrust propulsion meth- ods have become more prevalent, new challenges have arisen. Depending on the mission, low-thrust propulsion elements may need to thrust con- tinuously for days/months. During these thrusting periods, external fac- tors, such as a micro-meteoroid impact or a software glitch, may cause the spacecraft to prematurely cease its thrust stage. Half of all deep space missions enter a safe mode where they cannot thrust every four months. These missed thrust events can result in the complete loss of a space- craft for time-dependent trajectories like planetary rendezvous. This paper demonstrates how neural networks, trained using reinforcement learning, can autonomously correct for missed thrust events during an interplanetary trajectory.

Laipert, Frank E.↗
NASA NTRS2024

Soil Salinity Level Assessment and Prediction Integrating UAV-borne Hyperspectral Imaging and Machine Learning Algorithms to Combat Desertification

In response to the ongoing global food crisis, the United Nations has identified “Zero Hunger” as one of its Sustainable Development Goals. A central contributor to the crisis is the process in which agricultural lands go through desertification. Research has shown a direct correlation between soil salinity and desertification - increased salinity levels indicate a higher risk for desertification. Furthermore, researchers have explored various techniques to map soil salinity, but these methods are oftentimes inefficient and don’t address future salinity predictions. To improve desertification monitoring, soil salinity can be observed via hyperspectral imaging on unmanned aerial vehicles (UAVs) to predict the risk of agricultural desertification using artificial intelligence (AI) and machine learning (ML) techniques. A significant gap exists in past research that applies ML and imaging techniques to soil salinity: convolutional neural networks (CNNs) and regression models are rarely leveraged together, despite the efficiency and accuracy of these models. To compensate for this gap, the proposed system leverages the use of these AI and ML models to improve soil assessment and prediction techniques. This approach involves three steps - data collection, image analysis, and future prediction. Using hyperspectral cameras on UAVs to collect the data from the region, a trained CNN model will output estimated soil salinity levels at a specific time. The estimations will then be analyzed by a regression model to assess the accuracy of future soil salinity predictions. The proposed system will identify regions at risk of desertification to help farmers mitigate agricultural loss, in turn helping alleviate the food crisis.

UAV systems↗
DOE OSTI2020

Real-time sparse-sampled Ptychographic imaging through deep neural networks

Ptychography has rapidly grown in the fields of X-ray and electron imaging for its unprecedented ability to achieve nano or atomic scale resolution while simultaneously retrieving chemical or magnetic information from a sample. A ptychographic reconstruction is achieved by means of solving a complex inverse problem that imposes constraints both on the acquisition and on the analysis of the data, which typically precludes real-time imaging due to computational cost involved in solving this inverse problem. In this work we propose PtychoNN, a novel approach to solve the ptychography reconstruction problem based on deep convolutional neural networks. We demonstrate how the proposed method can be used to predict real-space structure and phase at each scan point solely from the corresponding far-field diffraction data. The presented results demonstrate how PtychoNN can effectively be used on experimental data, being able to generate high quality reconstructions of a sample up to hundreds of times faster than state-of-the-art ptychography reconstruction solutions once trained. By surpassing the typical constraints of iterative model-based methods, we can significantly relax the data acquisition sampling conditions and produce equally satisfactory reconstructions. Besides drastically accelerating acquisition and analysis, this capability can enable new imaging scenarios that were not possible before, in cases of dose sensitive, dynamic and extremely voluminous samples.

Cherukara, Mathew J↗
DOE OSTI2021

Physics-Based Feature Extraction from Bulk Time-Series PMU Datasets for Event Detection

In this work, two physics-based feature extraction techniques are developed for bulk time-series phasor measurement unit (PMU) datasets collected from the field to train the machine learning model for anomaly detection. Two approaches have been developed to extract useful features for different types of events. An admittance-based feature extraction technique is developed to detect events that involve line outages and system topology variations. The developed algorithm extracts the system equivalent admittance variation. Additionally, Fielder’s Theory is utilized to further reduce the potential computation burden by sectionalizing large-scale grids and datasets into smaller areas. Second, an oscillation-based feature extraction technique is developed to detect low-frequency oscillations in power grids. The dominant oscillation modes in the grids are extracted using energy-sorted Prony analysis. The extracted dominant oscillation modes by the developed work exhibit a high fitting resolution. Finally, the developed techniques have been validated using large-scale and real-world datasets.

24 POWER TRANSMISSION AND DISTRIBUTION↗