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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 307 records · Page 17
All sourcesNASA NTRSDOE OSTI
NASA NTRS2020

Going to Extremes NEEMO Case Study

In human space flight, crew preparation is paramount. NASA employs various tools in order to best prepare its crews; simulation and simulators, training for specific extravehicular activity (EVA) tasks in its Neutral Buoyancy Laboratory, and survival training. Apollo astronauts participated in desert wilderness survival to hone their skills. NASA has a long history of using terrestrial based activities as space flight analogs to advance science, test hardware and techniques, and develop crew leadership skills and team solidarity

Lessons Learned↗
DOE OSTI2026

Hydrogen Education for a Decarbonized Global Economy (H 2 EDGE) (Final Technical Report)

The energy sector is undergoing rapid growth and transformation, creating urgent demand for a skilled workforce to support emerging technologies and resilient systems. Hydrogen is an emerging solution for “hard to abate” sectors, including heavy industry and transportation that also provides optionality for the electric system and enables long‑duration energy storage. As hydrogen scales from traditional industrial uses to new applications, success depends on knowledgeable engineers, technicians, planners, and operators safely deploying hydrogen technologies across the full value chain: production, delivery, storage, and end use. The H 2 EDGE initiative, funded by the U.S. Department of Energy’s Hydrogen and Fuel Cell Technologies Office from 2020 to 2025, was launched to prepare people for careers hydrogen and related technologies. Through its interactive approach, H 2 EDGE equipped stakeholders with knowledge and tools to build a reliable and sustainable energy future together. H 2 EDGE built a national network of academic and industry partners to deliver modular training, share open-access curricula, and engage diverse talent pipelines. The program leveraged EPRI’s extensive industry membership and expanded on the train-the-trainer model of the GridEd program to connect educators, employers, and community organizations across all regions of the U.S. New methods were introduced to more systematically map hydrogen competencies and assess curricula using traditional and AI-assisted approaches. Outcomes included delivery of professional short courses, developing university curriculum, sponsoring faculty and student projects, and engaging stakeholders through workshops, site tours, and webinars.

08 HYDROGEN↗
NASA NTRS2010

Commercial Spacewalking: Designing an EVA Qualification Program for Space Tourism

In the near future, accessibility to space will be opened to anyone with the means and the desire to experience the weightlessness of microgravity, and to look out upon both the curvature of the Earth and the blackness of space, from the protected, shirt-sleeved environment of a commercial spacecraft. Initial forays will be short-duration, suborbital flights, but the experience and expertise of half a century of spaceflight will soon produce commercial vehicles capable of achieving low Earth orbit. Even with the commercial space industry still in its infancy, and manned orbital flight a number of years away, there is little doubt that there will one day be a feasible and viable market for those courageous enough to venture outside the vehicle and into the void, wearing nothing but a spacesuit, armed with nothing but preflight training. What that Extravehicular Activity (EVA) preflight training entails, however, is something that has yet to be defined. A number of significant factors will influence the composition of a commercial EVA training program, but a fundamental question remains: 'what minimum training guidelines must be met to ensure a safe and successful commercial spacewalk?' Utilizing the experience gained through the development of NASA's Skills program - designed to qualify NASA and International Partner astronauts for EVA aboard the International Space Station - this paper identifies the attributes and training objectives essential to the safe conduct of an EVA, and attempts to conceptually design a comprehensive training methodology meant to represent an acceptable qualification standard.

Gast, Matthew A.↗
NASA NTRS2011

Balancing Training Techniques for Flight Controller Certification

Training of ground control teams has been a difficult task in space operations. There are several intangible skills that must be learned to become the steely eyed men and women of mission control who respond to spacecraft failures that can lead to loss of vehicle or crew if handled improperly. And as difficult as training is, it can also be costly. Every day, month or year an operator is in training, is a day that not only they are being trained without direct benefit to the organization, but potentially an instructor or mentor is also being paid for hours spent assisting them. Therefore, optimization of the training flow is highly desired. Recently the Expedition Division (DI) at Johnson Space Flight Center has recreated their training flows for the purpose of both moving to an operator/specialist/instructor hierarchy and to address past inefficiencies in the training flow. This paper will discuss the types of training DI is utilizing in their new flows, and the balance that has been struck between the ideal learning environments and realistic constraints. Specifically, the past training flow for the ISS Attitude Determination and Control Officer will be presented, including drawbacks that were encountered. Then the new training flow will be discussed and how a new approach utilizes more training methods and teaching techniques. We will look at how DI has integrated classes, workshops, checkouts, module reviews, scenarios, OJT, paper sims, Mini Sims, and finally Integrated Sims to balance the cost and timing of training a new flight controller.

Gosling, Christina↗
NASA NTRS1986

Interaction between workload and training - Converging evidence from psychophysiology and performance measurement

Traditionally, the domains of mental workload and training have been studied in isolation even though they share many common characteristics. The present paper integrates findings from psychophysiological and performance-based studies which address both of these issues. By augmenting traditional indices of skill acquisition such as RMS error scores, reaction times, and accuracy measures with psychophysiological measures such as the event-related brain potential, it is shown that workload effects can be assessed throughout the training process. More specifically, it is argued that the development of skill and the effects of workload on the human operator can be modeled within the framework of resource theories of attentional allocation. Also described is how converging evidence from psychophysiological and behavioral studies can be used to examine subtle changes in operator strategies during training.

Kramer, Arthur F.↗
DOE OSTI2023

A New Era of Discovery: The 2023 Long-Range Plan for Nuclear Science (V.1.2)

Nuclear science is the investigation of how protons and neutrons are formed from elementary particles and how the forces between those particles produce both nuclei and the vast variety of nuclear phenomena that occur in the universe. It has evolved into a broad field that addresses profound scientific questions: Where does the mass of visible matter come from? How do stars ignite, live, and die? How do nuclei illuminate the search for new laws of nature? This science points the way to using nuclei to build new technologies that benefit society. The 2015 Nobel Prize in physics was shared by nuclear physicists Art McDonald and Takaaki Kajita for the discovery of neutrino oscillations, which confirmed that neutrinos have mass. Our progress on big questions like this one since 2015 has been remarkable owing to new experimental tools, theoretical breakthroughs, powerful computational techniques, and the talented people who make these innovations possible. Focusing on these new tools, the Facility for Rare Isotope Beams (FRIB) at Michigan State University is already producing exciting results on decays of never-before-produced isotopes a year after it was completed on time and on budget. The energy upgrade of the Continuous Electron Beam Accelerator Facility (CEBAF) at the Thomas Jefferson National Accelerator Facility (Jefferson Lab) was also completed on schedule and on budget—new data from this facility are revealing the spectrum, structure, and dynamics of protons, neutrons, nuclei, and mesons. On the theory front, we can now calculate the distribution of quarks inside the proton from first principles. The implementation of artificial intelligence (AI) and machine learning (ML) techniques has led to improved data analysis and increased efficiency in running experiments and theoretical calculations. The impact of nuclear science goes beyond expanding the frontiers of knowledge about matter in the universe. We simultaneously develop a STEM work force that advances the security, technology, health, and wealth of our nation. Some connections are obvious. Expert scientists trained to work with radioactive nuclei are in demand in nuclear security arenas and are highly sought after by various government agencies and private industries. Graduate students and postdoctoral fellows (postdocs) obtain extensive computational, modeling, and data science skills that are similarly in high demand. Less obvious but equally important is the connection between these trained scientists and success in other professions, including medicine, energy, and entrepreneurial pursuits. The workforce that enables discovery in nuclear science also makes breakthroughs in technologies with tremendous impact on the nation’s economic advancement.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
NASA NTRS2022

FY22 X-Hab: Rochester Institute of Technology: Gamification and Performance-Based Monitoring of Sensorimotor Training Activities

Proprioception is the body’s ability to sense movement, action, and location. Proprioceptive training is crucial for astronauts because humans balance system, cognitive functions, and muscle tone heavily rely on Earth’s gravity. The goal of this project is to create a training system that strengthens those characteristics to ensure astronauts not only maintain their coordination and cognitive skills, but improve upon them as well. Furthermore, the system’s live biofeedback provides astronauts with sensorimotor feedback to correct any balance dysfunction. The completed system prototype and data collected from it will support NASA’s knowledge base about the use of gamification for sensorimotor training activities.

Griffin Brown↗
NASA NTRS1992

Helicopter training simulators: Key market factors

Simulators will gain an increasingly important role in training helicopter pilots only if the simulators are of sufficient fidelity to provide positive transfer of skills to the aircraft. This must be done within an economic model of return on investment. Although rotor pilot demand is still only a small percentage of overall pilot requirements, it will grow in significance. This presentation described the salient factors influencing the use of helicopter training simulators.

Mcintosh, John↗
NASA NTRS1989

Airline Crew Training

The discovery that human error has caused many more airline crashes than mechanical malfunctions led to an increased emphasis on teamwork and coordination in airline flight training programs. Human factors research at Ames Research Center has produced two crew training programs directed toward more effective operations. Cockpit Resource Management (CRM) defines areas like decision making, workload distribution, communication skills, etc. as essential in addressing human error problems. In 1979, a workshop led to the implementation of the CRM program by United Airlines, and later other airlines. In Line Oriented Flight Training (LOFT), crews fly missions in realistic simulators while instructors induce emergency situations requiring crew coordination. This is followed by a self critique. Ames Research Center continues its involvement with these programs.

Source record↗
DOE OSTI2024

TSQP Analysis [Slides]

The purpose of this course is to help you develop the skills necessary to complete the Analysis Phase of the Systematic Approach to Training (SAT) according to the expectations of LANL and the DOE.

96 KNOWLEDGE MANAGEMENT AND PRESERVATION↗
DOE OSTI2024

TSQP: ADDIE-Design [Slides]

The purpose of this course is to help you develop the skills necessary to complete the Design Phase of the Systematic Approach to Training according to the expectations of Los Alamos National Laboratory (LANL) and the Department of Energy (DOE).

96 KNOWLEDGE MANAGEMENT AND PRESERVATION↗
DOE OSTI2024

TSQP: ADDIE-Evaluation [Slides]

The purpose of this course is to help you develop the skills necessary to complete the Evaluation Phase of the Systematic Approach to Training according to the expectations of Los Alamos National Laboratory (LANL) and the Department of Energy (DOE).

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2025

Reliable and Efficient Machine Learning (Final Technical Report)

Modern scientific experiments generate massive amounts of data at a pace much faster than humans can manually analyze. While machine learning has revolutionized commercial data analysis (such as recommending movies or recognizing faces), applying these tools to complex scientific discovery is challenging because scientific answers must be precise, interpretable, and adhere to physical laws. The research under this project aims to develop new mathematical tools and computer algorithms specifically designed for scientific applications. Major progress has been made in automatically cleaning and deconstructing messy experimental data, analyzing the visual information of physical phenomena, determining the underlying physical variables, and providing rig orous mathematical analysis of interesting algorithms and concepts widely used in machine learning. This project addressed the critical gap between our ability to generate massive scientific data and our ability to extract interpretable information from it. We established mathematical foundations for Scientific Machine Learning (SciML) aimed at effective data analytics and automated discovery. Our work focused on three core objectives: (1) developing reliable feature extraction methods for dynamic high-dimensional data, (2) establishing mathematical foundations for discovering dynamics via neural networks, and (3) creating rigorous optimization techniques for these models. Key outcomes come from two fronts. On the practical side, they include the development of algorithms that significantly enhance the extraction of signals from field data, as well as the capability to handle situations that exhibit smooth variations or physical stretching due to temperature changes. They also include the creation of an automated framework for discovering fundamental state variables from raw experimental data, demonstrating the ability to identify intrinsic physical dimensions without prior knowledge of the governing laws. On the theoretical front, the research results in theoretical advances in Optimal Transport, a widely used notion in SciML, specifically regarding functions with fixed-size nodal sets, provide sharp bounds relevant to uncertainty quantification. Meanwhile, the outcomes also include the establishment of convergence theories for nonlocal gradient descent methods, enabling robust optimization with noisy data in high-dimensional settings commonly encountered in scientific modeling. The project also helps creating opportunities to train the next generation of researchers, equipping them with the necessary technical skills for today’s workplace and preparing them for future advances.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS1991

What makes a good LOFT scenario? Issues in advancing current knowledge of scenario design

An effort is made to ascertain which combinations of technical demands and crew coordination should be incorporated in training scenarios in order to maximize the effectiveness of training for crew members. Such high-fidelity simulation, which has come to be known as 'line-oriented flight training' or LOFT, involves the practice of both technical and crew coordination skills in a realistic setting, in conjunction with periodic reviews of performance via videotaped feedback. Attention is given to the integration of appropriate information, the measurement of objective task demands, the character of information from LOFT students, and the leeway allowed LOFT instructors.

Gregorich, Steven E.↗
NASA NTRS1995

Training for Aviation Decision Making: The Naturalistic Decision Making Perspective

This paper describes the implications of a naturalistic decision making (NDM) perspective for training air crews to make flight-related decisions. The implications are based on two types of analyses: (a) identification of distinctive features that serve as a basis for classifying a diverse set of decision events actually encountered by flight crews, and (b) performance strategies that distinguished more from less effective crews flying full-mission simulators, as well as performance analyses from NTSB accident investigations. Six training recommendations are offered: (1) Because of the diversity of decision situations, crews need to be aware that different strategies may be appropriate for different problems; (2) Given that situation assessment is essential to making a good decision, it is important to train specific content knowledge needed to recognize critical conditions, to assess risks and available time, and to develop strategies to verify or diagnose the problem; (3) Tendencies to oversimplify problems may be overcome by training to evaluate options in terms of goals, constraints, consequences, and prevailing conditions; (4) In order to provide the time to gather information and consider options, it is essential to manage the situation, which includes managing crew workload, prioritizing tasks, contingency planning, buying time (e.g., requesting holding or vectors), and using low workload periods to prepare for high workload; (5) Evaluating resource requirements ("What do I need?") and capabilities ("'What do I have?" ) are essential to making good decisions. Using resources to meet requirements may involve the cabin crew, ATC, dispatchers, and maintenance personnel; (6) Given that decisions must often be made under high risk, time pressure, and workload, train under realistic flight conditions to promote the development of robust decision skills.

Orasanu, Judith↗
NASA NTRS2008

Lunar and Mars Exploration: The Autonomy Factor

Long duration space flight crews have relied heavily on almost constant communication with ground control mission support. Ground control teams provide vehicle status and system monitoring, while offering near real time support for specific tasks, emergencies, and ensuring crew health and well being. With extended exploration goals to lunar and Mars outposts, real time communication with ground control teams and the ground s ability to conduct mission monitoring will be very limited compared to the resources provided to current International Space Station (ISS) crews. An operational shift toward more autonomy and a heavier reliance on the crew to monitor their vehicle and operations will be required for these future missions. NASA s future exploration endeavors and the subsequent increased autonomy will require a shift in crew skill composition, i.e. engineer, doctor, mission specialist etc. and lead to new training challenges and mission scenarios. Specifically, operational and design changes will be necessary in many areas including: Habitat Infrastructure and Support Systems, Crew Composition, Training, Procedures and Mission Planning. This paper will specifically address how to apply ISS lessons learned to further use ISS as a test bed to address decreased amounts of ground support to achieve full autonomous operations for lunar and Mars missions. Understanding these lessons learned and applying them to current operations will help to address the future impacts of increased crew autonomy for the lunar and Mars outposts and pave the way for success in increasingly longer mission durations.

Rando, Cynthia M.↗
DOE OSTI2023

An introduction to financial option pricing on a qudit-based quantum computer

The financial sector is anticipated to be one of the first industries to benefit from the increased computational power of quantum computers, in areas such as portfolio optimisation and risk management to financial derivative pricing. Financial mathematics, and derivative pricing in particular, are not areas quantum physicists are traditionally trained in despite the fact that they often have the raw technical skills needed to understand such topics. On the other hand, most quantum algorithms have largely focused on qubits, which are comprised of two discrete states, as the information carriers. However, discrete higher-dimensional qudits, in addition to possibly possessing increased noise robustness and allowing for novel error correction protocols in certain hardware implementations, also have logarithmically greater information storage and processing capacity. In the current NISQ era of quantum computing, a wide array of hardware paradigms are still being studied and any potential advantage a platform offers is worth exploring. Here we introduce the basic concepts behind financial derivatives for the unfamiliar enthusiast as well as outline in great detail the quantum algorithm routines needed to price a European option, the simplest derivative. This is done within the context of a quantum computer comprised of qudits and employing the natural higher-dimensional analogue of a qubit-based pricing algorithm with its various subroutines. From these pieces, one should relatively easily be able to tailor the scheme to more complex, realistic financial derivatives. Finally, the entire stack is numerically simulated with the results demonstrating how the qudit-based scheme's payoff quickly approaches that of both a similarly-resourced classical computer as well as the true payoff, within error, for a modest increase in qudit dimension.

Bornman, Nicholas↗
NASA NTRS2004

Balanced Expertise Distribution in Remote Ultrasound Imaging Aboard The International Space Station (ISS)

Astronaut training for ISS operations usually ensures independent performance. With small crew size same crews also conduct all science work onboard. With diverse backgrounds, a good "match" between the existing and required skills can only be anecdotal. Furthermore, full proficiency in most of the complex tasks can be attained only through long training and practice, which may not be justified and may be impossible given the scarcity of training time. To enable a number of operational and science advancements, authors have developed a new approach to expertise distribution in time and among the space and ground personnel. Methods: As part of NASA Operational Ultrasound Project (1998-2003) and the NASA-solicited experiment "Advanced Diagnostic Ultrasound in Microgravity-ADUM" (P.I. -S.D., ongoing), the authors have created a "Balanced Expertise Distribution" approach to perform complex ultrasound imaging tasks on ISS for both operational and science use. The four components of expertise are a) any pre-existing pertinent expertise; b) limited preflight training c) adaptive onboard proficiency enhancement tools; d) real-time ' guidance from the ground. Throughout the pre-flight training and flight time preceding the experiments, the four components are shaped in a dynamic fashion to meet in an optimum combination during the experiment sessions. Results: Procedure validation sessions and feasibility studies have given encouraging results. While several successful real-time remote guidance sessions have been conducted on ISS, Expedition 8 is the first to use an "on-orbit proficiency enhancement" tool. Conclusions: In spite of severely limited training time, daring peer-reviewed research and operational enhancements are feasible through a balanced distribution of expertise in time, as well as among the crewmembers and ground personnel. This approach shows great promise for biomedical research, but may be applicable for other areas of micro gravity-based science

Sargsyan, Ashot↗