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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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All sourcesNASA NTRSDOE OSTI
NASA NTRS2006

PixelLearn

PixelLearn is an integrated user-interface computer program for classifying pixels in scientific images. Heretofore, training a machine-learning algorithm to classify pixels in images has been tedious and difficult. PixelLearn provides a graphical user interface that makes it faster and more intuitive, leading to more interactive exploration of image data sets. PixelLearn also provides image-enhancement controls to make it easier to see subtle details in images. PixelLearn opens images or sets of images in a variety of common scientific file formats and enables the user to interact with several supervised or unsupervised machine-learning pixel-classifying algorithms while the user continues to browse through the images. The machinelearning algorithms in PixelLearn use advanced clustering and classification methods that enable accuracy much higher than is achievable by most other software previously available for this purpose. PixelLearn is written in portable C++ and runs natively on computers running Linux, Windows, or Mac OS X.

Mazzoni, Dominic↗
NASA NTRS1976

NASA/ESA CT-990 Spacelab simulation. Appendix A: The experiment operator

A joint NASA/ESA endeavor was established to conduct an extensive spacelab simulation using the NASA CV-990 airborne laboratory. The scientific payload was selected to perform studies in upper atmospheric physics and infrared astronomy with principal investigators from France, the Netherlands, England, and several groups from the United States. Two experiment operators from Europe and two from the U.S. were selected to live aboard the aircraft along with a mission manager for a six-day period and operate the experiments in behalf of the principal scientists. This appendix discusses the experiment operators and their relationship to the joint mission under the following general headings: selection criteria, training programs, and performance. The performance of the proxy operators was assessed in terms of adequacy of training, amount of scientific data obtained, quality of data obtained, and reactions to problems that arose in experiment operation.

Reller, J. O., Jr.↗
NASA NTRS1992

The NASA airborne astronomy program - A perspective on its contributions to science, technology, and education

The publication records from NASA's airborne observatories are examined to evaluate the contribution of the airborne astronomy program to technological development and scientific/educational progress. The breadth and continuity of program is detailed with reference to its publication history, discipline representation, literature citations, and to the ability of such a program to address nonrecurring and unexpected astronomical phenomena. Community involvement in the airborne-observation program is described in terms of the number of participants, institutional affiliation, and geographic distribution. The program utilizes instruments including heterodyne and grating spectrometers, high-speed photometers, and Fabry-Perot spectrometers with wide total spectral ranges, resolutions, and numbers of channels. The potential of the program for both astronomical training and further scientific, theoretical, and applied development is underscored.

Larson, Harold P.↗
NASA NTRS1996

NASA Specialized Center of Research and Training (NSCORT) in Gravitational Biology

The mission of our NSCORT is to investigate the effects of gravity and other environmental factors on biological function at the cellular and molecular level. The research efforts, training opportunities, and scientific exchange will promote the expansion of a scientific peer group well-educated in space-related biological issues. This will stimulate the interest of the larger scientific community and insure the continuing development of rigorous flight investigations in Gravitational Biology.

Mclntire, Larry V.↗
NASA NTRS1998

Crew Skills and Training

One of the major focus points for the workshop was the topic of crew skills and training necessary for the Mars surface mission. Discussions centered on the mix of scientific skills necessary to accomplish the proposed scientific goals, and the training environment that can bring the ground and flight teams to readiness. Subsequent discussion resulted in recommendations for specific steps to begin the process of training an experienced Mars exploration team.

Jones, Thomas↗
NASA NTRS2001

On-Board Training for US Payloads

The International Space Station (ISS) crew follows a training rotation schedule that puts them in the United States about every three months for a three-month training window. While in the US, the crew receives training on both ISS systems and payloads. Crew time is limited, and system training takes priority over payload training. For most flights, there is sufficient time to train all systems and payloads. As more payloads are flown, training time becomes a more precious resource. Less training time requires payload developers (PDs) to develop alternatives to traditional ground training. To ensure their payloads have sufficient training to achieve their scientific goals, some PDs have developed on-board trainers (OBTs). These OBTs are used to train the crew when no or limited ground time is available. These lessons are also available on-orbit to refresh the crew about their ground training, if it was available. There are many types of OBT media, such as on-board computer based training (OCBT), video/photo lessons, or hardware simulators. The On-Board Training Working Group (OBTWG) and Courseware Development Working Group (CDWG) are responsible for developing the requirements for the different types of media.

Murphy, Benjamin↗
NASA NTRSDate not supplied

Harnessing Large Language Models for Scientific Endeavors

The rapid proliferation of Large Language Models (LLMs) such as GPT, Bard, and Llama has revolutionized various sectors, including the scientific community. These models, with their potential to automate and augment tasks, are increasingly being recognized as both a valuable asset and a potential challenge in the realm of scientific research and data management. However, the current LLMs, primarily trained on general corpora, exhibit a limited understanding of scientific concepts and terminologies due to the lack of scientific corpus in their training data. Recognizing this gap, several groups are now advocating for the development of LLMs specifically tailored for scientific applications. A notable initiative in this direction is the Large Language Model effort initiated by NASA's CSDO. This endeavor aims to align LLM efforts across NASA’s Science Mission Directorate, develop a science-specific corpus and validation test set for model training, and create an encoder-only model for various downstream tasks. Moreover, the initiative also plans to develop a decoder-only model to explore the potential benefits and risks associated with a generative LLM for science. Lastly, the project aims to create a science evaluation suite, encompassing various categories of downstream scientific tasks, to serve as a benchmark for assessing the value of any LLM for future use. This presentation will provide an overview and current status of this ongoing initiative, highlighting its potential to reshape the use of LLMs in the scientific domain.

Rahul Ramachandran↗
NASA NTRS2004

DASL-Data and Activities for Solar Learning

DASL-Data and Activities for Solar Learning Data and Activities for Solar Learning (DASL) provides a classroom learning environment based on a twenty-five year record of solar magnetograms from the National Solar Observatory (NSO) at Kitt Peak, AZ. The data, together with image processing software for Macs or PCs, can be used to learn basic facts about the Sun and astronomy at the middle school level. At the high school level, students can study properties of the Sun's magnetic cycle with classroom exercises emphasizing data and error analysis and can participate in a new scientific study, Research in Active Solar Longitudes (RASL), in collaboration with classrooms throughout the country and scientists at NSO and NASA. We present a half-day course to train teachers in the scientific content of the project and its classroom use. We will provide a compact disc with the data and software and will demonstrate software installation and use, classroom exercises, and participation in RASL with computer projection.

Jones, Harrison P.↗
NASA NTRS2024

The NASA Facility for Astromaterials Research at the Johnson Space Center – A National Laboratory for Planetary Research

The Astromaterials Research and Exploration Science (ARES) Division at the NASA Johnson Space Center houses a unique combination of laboratories, instruments, infrastructure, technical expertise, and other assets for conducting broad-based world-class planetary research. These facilities have been accessed for decades by hundreds of external scientists, including faculty, post-docs, students, and interns, most at no-cost and on a collaborative basis. With funding through NASA’s Planetary Science Enabling Facilities (PSEF) program, we have established the NASA Facility for Astromaterials Research (NFAR) to expand access to and enhance these laboratories for a diverse and inclusive external user base, focusing on training of the next generation of scientists and, thus, maximizing the science return from research funded by R&A programs in NASA’s Planetary Science Division (PSD). NFAR enables new planetary sample analyses, making new scientific discoveries possible, including training the next generation of planetary scientists. NFAR laboratories are co-located with JSC Curation that houses the NASA-controlled astromaterials collections, thus enabling direct access to both research and curation expertise, to facilitate specialized sample handling and analysis of allocated samples to sample PIs, particularly those affiliated with institutions that historically have limited access to or lack in-house analytical or experimental facilities.

J. I. Simon↗
NASA NTRS2018

Reflectance-Based Imaging Spectrometer Error Budget Field Practicum at the Railroad Valley Test Site, Nevada

Calibration and validation determine the quality and integrity of the data provided by sensors and have enormous downstream impacts on the accuracy and reliabilityof the products generated by these sensors. With the imminent launch of the next generation of space borne imaging spectroscopy sensors, the IEEE Geoscience and Remote Sensing Society's (GRSS's) Geoscience Spaceborne Imaging Spectroscopy Technical Committee (GSIS TC) initiated a calibration and validation initiative.This article reports on a recent reflectance-based imaging spectrometer error budget field practicum focused on radiometric calibration of spaceborne imaging spectroscopy sensors. The field exercise, conducted at Railroad Valley in Nevada, provided valuable training for personnel in a variety of Earth observation (EO) areas, from engineers developing future sensors to calibration scientists actively working in the field. Future work in this area will focus on analyzing the data acquired as part of the training to answer numerous scientific questions, e.g., understanding the spatial and spectral homogeneity of the site being measured, identifying the optimal sampling to characterize the site, and optimizating the sampling techniques, including looking into the automation of some measurement protocol aspects. The training exercise was recorded to ensure that the knowledge can be disseminated across the GRSS and wider imaging spectroscopy community.

Ong, Cindy↗
NASA NTRS2019

Tactical Scientific Decision-Making during Crewed Astrobiology Mars Missions

The limitations placed upon human explorers on the surface of Mars will necessitate a methodology for scientific exploration that is different from standard approaches to terrestrial fieldwork and prior crewed exploration of the Moon. In particular, the data transmission limitations and communication latency between Earth and Mars create a unique situation for surface crew in contact with a terrestrial science team. The BASALT research program simulated a series of extravehicular activities (EVAs) in Mars analog terrains under various Mars-relevant bandwidth and latency conditions to investigate how best to approach this problem. Here we discuss tactical decision-making under these conditions, that is, how the crew on Mars interacts with a team of scientists and support personnel on Earth to collect samples of maximum scientific interest. We describe the strategies, protocols, and tools tested in BASALT EVAs and give recommendations on how best to conduct human exploration of Mars with support from Earth-based scientists. We find that even with scientists supporting them, the crew performing the exploration must be trained in the appropriate scientific disciplines in order to provide the terrestrial scientists with enough information to make decisions, but that with appropriate planning and structure, and tools such as a ‘‘dynamic leaderboard,’’ terrestrial scientists can add scientific value to an EVA, even under Mars communication latency

Decision-making↗
NASA NTRS2011

Development of a Multivariable Parametric Cost Analysis for Space-Based Telescopes

Over the past 400 years, the telescope has proven to be a valuable tool in helping humankind understand the Universe around us. The images and data produced by telescopes have revolutionized planetary, solar, stellar, and galactic astronomy and have inspired a wide range of people, from the child who dreams about the images seen on NASA websites to the most highly trained scientist. Like all scientific endeavors, astronomical research must operate within the constraints imposed by budget limitations. Hence the importance of understanding cost: to find the balance between the dreams of scientists and the restrictions of the available budget. By logically analyzing the data we have collected for over thirty different telescopes from more than 200 different sources, statistical methods, such as plotting regressions and residuals, can be used to determine what drives the cost of telescopes to build and use a cost model for space-based telescopes. Previous cost models have focused their attention on ground-based telescopes due to limited data for space telescopes and the larger number and longer history of ground-based astronomy. Due to the increased availability of cost data from recent space-telescope construction, we have been able to produce and begin testing a comprehensive cost model for space telescopes, with guidance from the cost models for ground-based telescopes. By separating the variables that effect cost such as diameter, mass, wavelength, density, data rate, and number of instruments, we advance the goal to better understand the cost drivers of space telescopes.. The use of sophisticated mathematical techniques to improve the accuracy of cost models has the potential to help society make informed decisions about proposed scientific projects. An improved knowledge of cost will allow scientists to get the maximum value returned for the money given and create a harmony between the visions of scientists and the reality of a budget.

Dollinger, Courtnay↗
NASA NTRS2017

Comprehensive Oculomotor Behavioral Response Assessment (COBRA)

An eye movement-based methodology and assessment tool may be used to quantify many aspects of human dynamic visual processing using a relatively simple and short oculomotor task, noninvasive video-based eye tracking, and validated oculometric analysis techniques. By examining the eye movement responses to a task including a radially-organized appropriately randomized sequence of Rashbass-like step-ramp pursuit-tracking trials, distinct performance measurements may be generated that may be associated with, for example, pursuit initiation (e.g., latency and open-loop pursuit acceleration), steady-state tracking (e.g., gain, catch-up saccade amplitude, and the proportion of the steady-state response consisting of smooth movement), direction tuning (e.g., oblique effect amplitude, horizontal-vertical asymmetry, and direction noise), and speed tuning (e.g., speed responsiveness and noise). This quantitative approach may provide fast and results (e.g., a multi-dimensional set of oculometrics and a single scalar impairment index) that can be interpreted by one without a high degree of scientific sophistication or extensive training.

Stone, Leland S.↗
NASA NTRSDate not supplied

Leveraging the 2024 Solar Eclipse to Enhance Science Learning through Citizen Science

The solar eclipse on April 8, 2024, provided a rare and compelling opportunity for educators and students to engage in hands-on citizen science. Two NASA Science Activation projects GLOBE Mission Earth (GME) and NASA Earth Science Education Collaborative (NESEC) partnered together to provide a unique professional development experience for educators interested in the eclipse. They invited educators to participate in a specialized 5-week online workshop designed to engage the educators in Global Learning and Observations to Benefit the Environment (GLOBE) citizen science about the eclipse. The workshop was designed to support their certification as GLOBE educators and develop their knowledge, skills, and confidence in conducting a GLOBE investigation. Over 60 educators from across the United States took part in this workshop, which focused on investigating the eclipse by collecting and analyzing atmospheric data. The GLOBE Program promotes environmental and scientific literacy by enabling participants to collect Earth science data and contribute it to a global database accessible for research. The 2024 GLOBE Eclipse workshop trained educators in specific GLOBE protocols—Clouds, Air Temperature, and Surface Temperature—using the GLOBE Eclipse tool integrated into the GLOBE Observer app. This training was supplemented with guidance on engaging students in authentic scientific research and creating research posters to present their findings. The workshop aimed to enhance educators’ skills and confidence in integrating GLOBE protocols into their teaching practices. It addressed several key areas outlined in the National Academies' report on Learning through Citizen Science, including scientific context, nature of participation, and project infrastructure. Educators learned about the atmospheric effects of solar eclipses and were trained to use scientific tools and data analysis methods relevant to their research. They also engaged in live sessions and asynchronous activities, practicing data collection and analysis with real-time feedback. Survey results from the workshop highlighted that participants were primarily motivated by the desire to better use data in their classrooms and improve their proficiency with the GLOBE Observer app. Post-workshop evaluations showed significant increases in educators' confidence regarding their ability to conduct and guide scientific research. Participants reported feeling well-prepared to use the GLOBE Observer app for data collection and were successful in integrating their eclipse observations into classroom activities. Participants also valued the opportunity to contribute to authentic science through GLOBE, which involved observing atmospheric changes such as air temperature fluctuations and cloud cover alterations during the eclipse. The success of the workshop is evident in the increased confidence and skill levels of educators, as well as the publication of research posters on the GLOBE Mission Earth Student Research webpage.This session will discuss how the GLOBE Eclipse workshop series effectively utilized the unique context of the solar eclipse to enhance science education through citizen science. By adhering to the principles outlined in the Learning through Citizen Science framework, the workshop successfully engaged educators and students in meaningful scientific practices, demonstrating the potential of citizen science to enrich science education and foster a deeper understanding of Earth systems.

Jessica Taylor↗
NASA NTRS1993

Advanced Technology Training System on Motor-Operated Valves

This paper describes how features from the field of Intelligent Tutoring Systems are applied to the Motor-Operated Valve (MOV) Advanced Technology Training System (ATTS). The MOV ATTS is a training system developed at Galaxy Scientific Corporation for the Central Research Institute of Electric Power Industry in Japan and the Electric Power Research Institute in the United States. The MOV ATTS combines traditional computer-based training approaches with system simulation, integrated expert systems, and student and expert modeling. The primary goal of the MOV ATTS is to reduce human errors that occur during MOV overhaul and repair. The MOV ATTS addresses this goal by providing basic operational information of the MOV, simulating MOV operation, providing troubleshooting practice of MOV failures, and tailoring this training to the needs of each individual student. The MOV ATTS integrates multiple expert models (functional and procedural) to provide advice and feedback to students. The integration also provides expert model validation support to developers. Student modeling is supported by two separate student models: one model registers and updates the student's current knowledge of basic MOV information, while another model logs the student's actions and errors during troubleshooting exercises. These two models are used to provide tailored feedback to the student during the MOV course.

Wiederholt, Bradley J.↗
NASA NTRS1994

Portable Presentation And Instruction Unit

Proposed electronic display unit reminiscent of kiosk serves as portable, interactive, multimedia information terminal. Used as traveling science exhibit, aid for teaching science in schools, or training and skill-refresher device for space flight crews. Provides interactive video and audio displays, including three-dimensional-appearing video simulations. Speeds learning and improves retention by applying principles of scientific visualization. Also helps previously trained but recently unpracticed personnel relearn special skills and procedures quickly.

Christman, L.↗
NASA NTRS1931

Aeronautical education and research at the Swiss Institute of Technology in Zurich

Progress in the scientific and practical fields of aviation has caused the Swiss Institute of Technology to organize lectures and practical training courses in all three branches of aeronautics and to found centers of scientific research, laboratories, etc., in order to supply the government and industries with scientifically and technically trained engineers.

Karner, L↗
NASA NTRSDate not supplied

Foundation AI Models for Science

Foundation Models (FM) are AI models that are designed to replace a task or an application specific model. These FM can be applied to many different downstream applications. These FM are trained using self supervised techniques and can be built on any type of sequence data. The use of self supervised learning removes the hurdle for developing a large labeled dataset for training. Most FM use transformer architecture utilizes the notion of self attention which allows the network to model the influence of distant data points to each other both in space and time. The FM models exhibit emergent properties that are induced from the data. FM can be an important tool for science. The scale of these models results in better performance for different downstream applications and these applications show better accuracy over models built from scratch. FM drastically reduces the cost of entry to build different downstream applications both in time and effort. FM for selected science datasets such as optical satellite data, can accelerate applications ranging from data quality monitoring, feature detection and prediction. FM can make it easier to infuse AI into scientific research by removing the training data bottleneck and increasing the use of science data.

Manil Maskey↗