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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 721 records · Page 40
All sourcesNASA NTRSDOE OSTI
NASA NTRS2007

Second-Generation Electronic Nose

A report discusses the second generation of the JPL Electronic Nose (ENose), an array of 32 semi-specific chemical sensors used as an event monitor to identify and quantify contaminants released into breathing air by leaks or spills. It is designed to monitor the environment for changes in air quality, and is trained to identify and quantify selected chemical species at predetermined concentrations, ranging from sub-ppm to ppth. This system has improved reproducibility for making matched arrays, allowing use of data analysis software with minimal recalibration on sensor set replacement. The Second Generation (SG) ENose is a follow-up to the first JPL Electronic Nose that was tested on an earlier space shuttle mission (STS-95). Improvements have been made to the hardware, sensor materials, and data analysis software.

Homer, Margie↗
NASA NTRS2011

How to Grow Project Scientists: A Systematic Approach to Developing Project Scientists

The Project Manager is one of the key individuals that can determine the success or failure of a project. NASA is fully committed to the training and development of Project Managers across the agency to ensure that highly capable individuals are equipped with the competencies and experience to successfully lead a project. An equally critical position is that of the Project Scientist. The Project Scientist provides the scientific leadership necessary for the scientific success of a project by insuring that the mission meets or exceeds the scientific requirements. Traditionally, NASA Goddard project scientists were appointed and approved by the Center Science Director based on their knowledge, experience, and other qualifications. However the process to obtain the necessary knowledge, skills and abilities was not documented or done in a systematic way. NASA Goddard's current Science Director, Nicholas White saw the need to create a pipeline for developing new projects scientists, and appointed a team to develop a process for training potential project scientists. The team members were Dr. Harley Thronson, Chair, Dr. Howard Kea, Mr. Mark Goldman, DACUM facilitator and the late Dr. Michael VanSteenberg. The DACUM process, an occupational analysis and evaluation system, was used to produce a picture of the project scientist's duties, tasks, knowledge, and skills. The output resulted in a 3-Day introductory course detailing all the required knowledge, skills and abilities a scientist must develop over time to be qualified for selections as a Project Scientist.

Kea, Howard↗
NASA NTRS2020

Modeling and Simulation - Virtual

The purpose of this report is to describe the body of work I have produced as a NASA Office of Science Technology Engineering and Math (OSTEM) intern in the Fall 2020 semester. My mentor during this session was Antonio Pego and my main task was to research and develop solutions in augmented and virtual reality technologies for use in training simulations. A main focus of this project was the development of human models for use in the game engine, with the purpose of creating simulations that would help with realistic analysis of tasks that will be performed by personnel. A steep learning curve had to be tackled in order to learn and catch up with current MR technologies. Along the way I created documentation of the different techniques utilized to support future continuation of the project.

Peter Leroy Santana Rodriguez↗
NASA NTRSDate not supplied

Materials Informatics at NASA GRC: Machine Learning Surrogate Modeling, Data Management, and Integrated Toolsets for Establishing/Maintaining the Digital Thread

Integrated Computational Materials Engineering (ICME) has recently received widespread attention due to its promises in reducing dependence on physical testing for engineering design by relying on simulation, reducing both time and cost to market for various applications. ICME however requires validated multiscale material models, which heavily depend on available test data with full material and test pedigree, including material processing, test and measurement equipment, raw data collection, and analysis methodology and results that is findable and usable, along with integrated, efficient toolsets for effectively passing information across various length and time scales across such models. At the NASA Glenn Research Center under the Transformational Tools and Technologies Project, significant recent efforts have been directed towards establishing the required cyberinfrastructure to enable optimized ICME processes and the design of “fit-for-purpose” materials to achieve the goals outlined in the NASA Vision 2040 report. Such efforts include development of multiscale physics-based material models, which can be used to train highly efficient surrogate machine learning models, development of best practices and infrastructure for effective, traceable materials information management, and development of toolsets that integrate with physics-based codes, machine learning models, and an information management system to enable high throughput of materials data collection and analysis, establishment of digital twins and the digital thread, and automation of the ICME design process for material optimization.

Machine Learning↗
NASA NTRS2020

Flare Statistics for Young Stars from a Convolutional Neural Network Analysis of TESS Data

All-sky photometric time-series missions have allowed for the monitoring of thousands of young (t(age) < 800 Myr) stars in order to understand the evolution of stellar activity. Here, we developed a convolutional neural network (CNN), stella, specifically trained to find flares in Transiting Exoplanet Survey Satellite (TESS) short-cadence data. We applied the network to 3200 young stars in order to evaluate flare rates as a function of age and spectral type. The CNN takes a few seconds to identify flares on a single light curve. We also measured rotation periods for 1500 of our targets and find that flares of all amplitudes are present across all spot phases, suggesting high spot coverage across the entire surface. Additionally, flare rates and amplitudes decrease for stars t(age) > 50 Myr across all temperatures T(eff) ≥ 4000 K, while stars from 2300 ≤ T(eff) < 4000 K show no evolution across 800 Myr. Stars of T(eff) ≤ 4000 K also show higher flare rates and amplitudes across all ages. We investigate the effects of high flare rates on photoevaporative atmospheric mass loss for young planets. In the presence of flares, planets lose 4%–7% more atmosphere over the first 1 Gyr. stella is an open-source Python toolkit hosted on GitHub and PyPI.

Adina D. Feinstein↗
NASA NTRS2017

Understanding the International Space Station Crew Perspective following Long-Duration Missions through Data Analytics & Visualization of Crew Feedback

The International Space Station (ISS) first became a home and research laboratory for NASA and International Partner crewmembers over 16 years ago. Each ISS mission lasts approximately 6 months and consists of three to six crewmembers. After returning to Earth, most crewmembers participate in an extensive series of 30+ debriefs intended to further understand life onboard ISS and allow crews to reflect on their experiences. Examples of debrief data collected include ISS crew feedback about sleep, dining, payload science, scheduling and time planning, health & safety, and maintenance. The Flight Crew Integration (FCI) Operational Habitability (OpsHab) team, based at Johnson Space Center (JSC), is a small group of Human Factors engineers and one stenographer that has worked collaboratively with the NASA Astronaut office and ISS Program to collect, maintain, disseminate and analyze this data. The database provides an exceptional and unique resource for understanding the "crew perspective" on long duration space missions. Data is formatted and categorized to allow for ease of search, reporting, and ultimately trending, in order to understand lessons learned, recurring issues and efficiencies gained over time. Recently, the FCI OpsHab team began collaborating with the NASA JSC Knowledge Management team to provide analytical analysis and visualization of these over 75,000 crew comments in order to better ascertain the crew's perspective on long duration spaceflight and gain insight on changes over time. In this initial phase of study, a text mining framework was used to cluster similar comments and develop measures of similarity useful for identifying relevant topics affecting crew health or performance, locating similar comments when a particular issue or item of operational interest is identified, and providing search capabilities to identify information pertinent to future spaceflight systems and processes for things like procedure development and training. In addition, the comments were scored for sentiment using a polarity scoring algorithm to identify both positive and negative comments for particular groups and clusters, allowing the team to make analytically informed decisions regarding future hardware and operating procedures. The use of polarity scoring with time series analysis was used to provide insight into how crew health and habitability is changing throughout various spaceflight increments or the station lifecycle as a whole. Finally, a visualization framework was developed to address the needs of the end users to search for and analyze comments by user, category or mission. This paper will discuss how the use of an analytical framework in conjunction with the current human interface, improved the understanding of crew perspective and shortened the time for analysis allowing for more informed decisions and rapid development of improvements. These methods are significantly optimizing the way that this valuable data can be assessed and applied to current and future spaceflight design and development. This collaboration allows the FCI OpsHab team to effectively analyze and share data in a more automated and timely fashion. Trends are no longer derived manually and can be illustrated effectively and accurately with these evolving techniques to an ever growing group of human spaceflight end users.

Bryant, Cody↗
NASA NTRS2013

Applications of Automation Methods for Nonlinear Fracture Test Analysis

Using automated and standardized computer tools to calculate the pertinent test result values has several advantages such as: 1. allowing high-fidelity solutions to complex nonlinear phenomena that would be impractical to express in written equation form, 2. eliminating errors associated with the interpretation and programing of analysis procedures from the text of test standards, 3. lessening the need for expertise in the areas of solid mechanics, fracture mechanics, numerical methods, and/or finite element modeling, to achieve sound results, 4. and providing one computer tool and/or one set of solutions for all users for a more "standardized" answer. In summary, this approach allows a non-expert with rudimentary training to get the best practical solution based on the latest understanding with minimum difficulty.Other existing ASTM standards that cover complicated phenomena use standard computer programs: 1. ASTM C1340/C1340M-10- Standard Practice for Estimation of Heat Gain or Loss Through Ceilings Under Attics Containing Radiant Barriers by Use of a Computer Program 2. ASTM F 2815 - Standard Practice for Chemical Permeation through Protective Clothing Materials: Testing Data Analysis by Use of a Computer Program 3. ASTM E2807 - Standard Specification for 3D Imaging Data Exchange, Version 1.0 The verification, validation, and round-robin processes required of a computer tool closely parallel the methods that are used to ensure the solution validity for equations included in test standard. The use of automated analysis tools allows the creation and practical implementation of advanced fracture mechanics test standards that capture the physics of a nonlinear fracture mechanics problem without adding undue burden or expense to the user. The presented approach forms a bridge between the equation-based fracture testing standards of today and the next generation of standards solving complex problems through analysis automation.

Allen, Phillip A.↗
NASA NTRS1980

Remote sensing program activity report

Major accomplishments in an effort to encourage investigation and technology transfer for practical applications of remote sensing to solve Earth resources problems in Vermont include: (1) acquisition, installation, and operation of the ORSER digital processing system on the University's IBM 3031 computer; (2) acquisition and operation of printing and CRT computer terminals for remote access to computer facilities for analysis of remotely sensed digital tape; (3) acquisition and operation of optical interpretation and image transfer devices for use with all types of aerial photography; (4) development of audio visual and other training materials for use in presentations, workshops, and short courses to enhance technology transfer; and (5) cooperation government agencies in demonstration projects to show the feasibility of using remote sensing technology.

Whitmore, R. A., Jr.↗
NASA NTRS1983

Operation and maintenance requirements of the Army Remotely Piloted Vehicle (RPV)

The Remotely Piloted Vehicle (RPV) system is being developed to provide the Army with a target acquistion, target location, and laser designation capability that will significantly enhance the effectiveness of the artillery. Iterative analyses of the manpower, personnel, and training (MPT) requirements for an RPV system configured to accommodate both a daylight television and a forward looking infrared (FLIR) mission payload subsystem (FMPS) and related support subsystems are examined. Additionally, this analysis incorporates a 24 hour-a-day operational scenario. Therefore, the information presented was developed with a view towards delineating the differences (or deltas) imposed by the new requirements resulting from FMPS/24 hour operating day functions.

Source record↗
NASA NTRS1987

Knowledge-based vision for space station object motion detection, recognition, and tracking

Computer vision, especially color image analysis and understanding, has much to offer in the area of the automation of Space Station tasks such as construction, satellite servicing, rendezvous and proximity operations, inspection, experiment monitoring, data management and training. Knowledge-based techniques improve the performance of vision algorithms for unstructured environments because of their ability to deal with imprecise a priori information or inaccurately estimated feature data and still produce useful results. Conventional techniques using statistical and purely model-based approaches lack flexibility in dealing with the variabilities anticipated in the unstructured viewing environment of space. Algorithms developed under NASA sponsorship for Space Station applications to demonstrate the value of a hypothesized architecture for a Video Image Processor (VIP) are presented. Approaches to the enhancement of the performance of these algorithms with knowledge-based techniques and the potential for deployment of highly-parallel multi-processor systems for these algorithms are discussed.

Symosek, P.↗
NASA NTRS1989

Shuttle remote manipulator system mission preparation and operations

The preflight planning, analysis, procedures development, and operations support for the Space Transportation System payload deployment and retrieval missions utilizing the Shuttle Remote Manipulator System are summarized. Analysis of the normal operational loads and failure induced loads and motion are factored into all procedures. Both the astronaut flight crews and the Mission Control Center flight control teams receive considerable training for standard and mission specific operations. The real time flight control team activities are described.

Smith, Ernest E., Jr.↗
NASA NTRS1994

Mission Operations Centers (MOCs): Integrating key spacecraft ground data system components

In an environment characterized by decreasing budgets, limited system development time, and user needs for increased capabilities, the Mission Operations Division (MOD) at the National Aeronautics and Space Administration Goddard Space Flight Center initiated a new, cost-effective concept in developing its spacecraft ground data systems: the Mission Operations Center (MOC). In the MOC approach, key components are integrated into a comprehensive and cohesive spacecraft planning, monitoring, command, and control system with a single, state-of-the-art graphical user interface. The MOD is currently implementing MOC's, which feature a common, reusable, and extendable system architecture, to support the X-Ray Timing Explorer (XTE), Tropical Rainfall Measuring Mission (TRMM), and Advanced Composition Explorer (ACE) missions. As a result of the MOC approach, mission operations are integrated, and users can, with a single system, perform real-time health and safety monitoring, real-time command and control, real-time attitude processing, real-time and predictive graphical spacecraft monitoring, trend analysis, mission planning and scheduling, command generation and management, network scheduling, guide star selection, and (using an expert system) spacecraft monitoring and fault isolation. The MOD is also implementing its test and training simulators under the new MOC management structure. This paper describes the MOC concept, the management approaches used in developing MOC systems, the technologies employed and the development process improvement initiatives applied in implementing MOC systems, and the expected benefits to both the user and the mission project in using the MOC approach.

Harbaugh, Randy↗
NASA NTRS2000

Growth and Characterization of III-V Semiconductors for Device Applications

The research goal was to achieve a fundamental understanding of the physical processes occurring at the surfaces and interfaces of epitaxially grown InGaAs/GaAs (100) heterostructures. This will facilitate the development of quantum well devices for infrared optical applications and provide quantitative descriptions of key phenomena which impact their performance. Devices impacted include high-speed laser diodes and modulators for fiber optic communications at 1.55 micron wavelengths and intersub-band lasers for longer infrared wavelengths. The phenomenon of interest studied was the migration of indium in InGaAs structures. This work centered on the molecular beam epitaxy reactor and characterization apparatus donated to CAU by AT&T Bell Laboratories. The material characterization tool employed was secondary ion mass spectrometry. The training of graduate and undergraduate students was an integral part of this program. The graduate students received a thorough exposure to state-of-the-art techniques and equipment for semiconductor materials analysis as part of the Master''s degree requirement in physics. The undergraduates were exposed to a minority scientist who has an excellent track record in this area. They also had the opportunity to explore surface physics as a career option. The results of the scientific work was published in a refereed journal and several talks were presented professional conferences and academic seminars.

Williams, Michael D.↗
NASA NTRS2009

Satellite Proving Ground for the GOES-R Geostationary Lightning Mapper (GLM)

The key mission of the Satellite Proving Ground is to demonstrate new satellite observing data, products and capabilities in the operational environment to be ready on Day 1 to use the GOES-R suite of measurements. Algorithms, tools, and techniques must be tested, validated, and assessed by end users for their utility before they are finalized and incorporated into forecast operations. The GOES-R Proving Ground for the Geostationary Lightning Mapper (GLM) focuses on evaluating how the infusion of the new technology, algorithms, decision aids, or tailored products integrate with other available tools (weather radar and ground strike networks; nowcasting systems, mesoscale analysis, and numerical weather prediction models) in the hands of the forecaster responsible for issuing forecasts and warning products. Additionally, the testing concept fosters operation and development staff interactions which will improve training materials and support documentation development. Real-time proxy total lightning data from regional VHF lightning mapping arrays (LMA) in Northern Alabama, Central Oklahoma, Cape Canaveral Florida, and the Washington, DC Greater Metropolitan Area are the cornerstone for the GLM Proving Ground. The proxy data will simulate the 8 km Event, Group and Flash data that will be generated by GLM. Tailored products such as total flash density at 1-2 minute intervals will be provided for display in AWIPS-2 to select NWS forecast offices and national centers such as the Storm Prediction Center. Additional temporal / spatial combinations are being investigated in coordination with operational needs and case-study proxy data and prototype visualizations may also be generated from the NASA heritage Lightning Imaging Sensor and Optical Transient Detector data. End users will provide feedback on the utility of products in their operational environment, identify use cases and spatial/temporal scales of interest, and provide feedback to the developers for adjusted or new products.

Goodman, Steven J.↗
NASA NTRS2010

High Resolution ECG for Evaluation of QT Interval Variability during Exposure to Acute Hypoxia

Ventricular repolarization instability as quantified by the index of QT interval variability (QTVI) is one of the best predictors for risk of malignant ventricular arrhythmias and sudden cardiac death. Because it is difficult to appropriately monitor early signs of organ dysfunction at high altitude, we investigated whether high resolution advanced ECG (HR-ECG) analysis might be helpful as a non-invasive and easy-to-use tool for evaluating the risk of cardiac arrhythmias during exposure to acute hypoxia. 19 non-acclimatized healthy trained alpinists (age 37, 8 plus or minus 4,7 years) participated in the study. Five-minute high-resolution 12-lead electrocardiograms (ECGs) were recorded (Cardiosoft) in each subject at rest in the supine position breathing room air and then after breathing 12.5% oxygen for 30 min. For beat-to-beat RR and QT variability, the program of Starc was utilized to derive standard time domain measures such as root mean square of the successive interval difference (rMSSD) of RRV and QTV, the corrected QT interval (QTc) and the QTVI in lead II. Changes were evaluated with paired-samples t-test with p-values less than 0.05 considered statistically significant. As expected, the RR interval and its variability both decreased with increasing altitude, with p = 0.000 and p = 0.005, respectively. Significant increases were found in both the rMSSDQT and the QTVI in lead II, with p = 0.002 and p = 0.003, respectively. There was no change in QTc interval length (p = non significant). QT variability parameters may be useful for evaluating changes in ventricular repolarization caused by hypoxia. These changes might be driven by increases in sympathetic nervous system activity at ventricular level.

Zupet, P.↗
NASA NTRS2010

Assessing Operational Total Lightning Visualization Products

In May 2003, NASA's Short-term Prediction Research and Transition (SPoRT) program successfully provided total lightning data from the North Alabama Lightning Mapping Array (NALMA) to the National Weather Service (NWS) office in Huntsville, Alabama. The major accomplishment was providing the observations in real-time to the NWS in the native Advanced Weather Interactive Processing System (AWIPS) decision support system. Within days, the NALMA data were used to issue a tornado warning initiating seven years of ongoing support to the NWS' severe weather and situational awareness operations. With this success, SPoRT now provides real-time NALMA data to five forecast offices as well as working to transition data from total lightning networks at Kennedy Space Center and the White Sands Missile Range to the surrounding NWS offices. The only NALMA product that has been transitioned to SPoRT's partner NWS offices is the source density product, available at a 2 km resolution in 2 min intervals. However, discussions with users of total lightning data from other networks have shown that other products are available, ranging from spatial and temporal variations of the source density product to the creation of a flash extent density. SPoRT and the Huntsville, Alabama NWS are evaluating the utility of these variations as this has not been addressed since the initial transition in 2003. This preliminary analysis will focus on what products will best support the operational warning decision process. Data from 19 April 2009 are analyzed. On this day, severe thunderstorms formed ahead of an approaching cold front. Widespread severe weather was observed, primarily south of the Tennessee River with multiple, weak tornadoes, numerous severe hail reports, and wind. This preliminary analysis is the first step in evaluation which product(s) are best suited for operations. The ultimate goal is selecting a single product for use with all total lightning networks to streamline training and science sharing.

Stano, Geoffrey T.↗
NASA NTRS2012

Recent Upgrades to NASA SPoRT Initialization Datasets for the Environmental Modeling System

The NASA Short-term Prediction Research and Transition (SPoRT) Center has developed several products for its NOAA/National Weather Service (NWS) partners that can initialize specific fields for local model runs within the NOAA/NWS Science and Training Resource Center Environmental Modeling System (EMS). The suite of SPoRT products for use in the EMS consists of a Sea Surface Temperature (SST) composite that includes a Lake Surface Temperature (LST) analysis over the Great Lakes, a Great Lakes sea-ice extent within the SST composite, a real-time Green Vegetation Fraction (GVF) composite, and NASA Land Information System (LIS) gridded output. This paper and companion poster describe each dataset and provide recent upgrades made to the SST, Great Lakes LST, GVF composites, and the real-time LIS runs.

Case, Jonathan L.↗