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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 397 records · Page 22

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NASA NTRS1988

Research and development for Onboard Navigation (ONAV) ground based expert/trainer system: Preliminary user's guide

The purpose is to present procedures for preparation, operation, monitoring, and recovery of the Shuttle Entry phase expert system that is part of the Onboard Navigation (ONAV) Ground Based Expert System Trainer System for aircraft/space shuttle navigation. This user's guide is primarily intended for functional users of the system. It includes procedures for system operation in support of training activities as well as operational tasks. In addition, information is provided which enables maintenance personnel to handle updates, modifications, etc. to the system.

Bochsler, Daniel C.↗

NASA NTRS2016

Environmental Testing of Flight Hardware in the 25 ft. Space Simulator at JPL in a Manual Mode

After receiving global admiration for the Mars Science Laboratory (MSL) Curiosity rover, the Jet Propulsion Laboratory (JPL) is planning to embark upon another mobile mission to the red planet in the year 2020. Currently, the working name given to this sophisticated next-generation rover is Mars 2020. Mars 2020 will boast a multitude of newly developed instruments to aid in the scientific study of Mars. This paper will describe the process of testing one of the Mars 2020 instruments in the 25 ft. Space Simulator. The testing was performed at Mars CO2 atmospheric pressure of 7 Torr and consisted of multiple chamber evacuations and backfills. The Programmable Logic Control (PLC) system for the chamber was in the middle of a major overhaul that resulted in utilizing the manual Hand/Off/Auto switches to operate the chamber. Accomplishing this challenging task required the meticulous development of new operating procedures and thorough training of the chamber’s operators.

Ovcharenko, Anton↗

NASA NTRSDate not supplied

Neo – Mars Adaptive Training Integrative Knowledge System (MATRIKS) to Improve Operational Performance and its Neural Basis for Spaceflight

With prolonged mission durations, spaceflight crews will become increasingly dependent on onboard technologies for knowledge acquisition and maintenance. It is expected that not all skills and knowledge required for these missions can be retained and retrieved based on pre-mission training alone. Limited and delayed communication will significantly constrain support from Mission Control and crews will increasingly rely on autonomous onboard technologies to successfully perform post-landing operations. With the present project we will target NASA’s particular interest in developing and assessing an adaptive, just-in-time countermeasure that will consolidate and improve skills that are most relevant to space flight operations. To achieve this aim, NASA established a Virtual NASA Specialized Center of Research (VNSCOR)referred to as “Mars Adaptive Training Integrative Knowledge System (MATRIKS)”, comprising the following three projects: (1) “Trinity–Multi-Environment Virtual Training for Long Duration Exploration Missions”, PI: A. Anderson (UC Boulder); (2) “Morpheus–A Haptic Sensory Supplement to Optimize In-Flight Adaptive Training for Human Control of Spacecraft Robotic Arms”, PI: S. Robinson, UC Davis); and the present project “Neo–Adaptive Training integrative knowledge System to Improve Operational Performance and its Neural Basis for Spaceflight” (UPenn, PI: A.C. Stahn). Neo leverages a validated workstation called 6DF that simulates a rendezvous and docking maneuver using real spacecraft flight dynamics. It is designed to (1) train and improve sensorimotor skills relevant for inflight and post-landing operational tasks; (2) feature an autonomous and adaptive training approach that does not rely on feedback from flight operations on the ground; (3) maximize the transfer of mission-relevant motor skills; (4) allow the assessment of the neural circuitry underlying the task; and (5) deliver the training in a motivating and meaningful way to astronauts. Neocomprises two overarching aims: First, we will identify the neural circuitry underlying spaceflight relevant tasks by performing a subset of the 6DFtaskduring functional magnetic resonance imaging (MRI)in a total of up to N=30 subjects with varying levels of 6DF training experience. Second, as part of the above-mentioned VNSCOR MATRIKS the proposed 6DF autonomous intelligent tutor system will be integrated in an additive manner with a haptic feedback intervention (Morpheus), and a multi-environment virtual trainer(Trinity).It is expected that Neo, Morpheus and Trinity mutually complement each other to facilitate an effective countermeasure tool to acquire and retain operational skills that are critical for exploration class missions. To assess the efficacy of this combined effort, the VNSCOR MATRIKS will collect data inN=16 crew members in one HERA campaign of 45 days duration with N=16 crew members(four missions with N=4 crew member seach).The primary goal is to identify changes in operational performance as assessed by NASA’s simulator of Canadarm2 operations, i.e., Robotic On-board Trainer (ROBoT-r) in response to MATRIKS. As part of Neo we will also identify if, and to what extent MATRIKS will promote transfer to general cognitive performance (Cognition battery), distinctive visuo-spatial tasks critical for telerobotic tasks (Spatial Cognition battery), and affect brain structural changes and the neural circuitry of key brain networks expected to be relevant for spaceflight-related performance. At the conclusion of the research, we will have defined and demonstrated the use of a neuroscience-based, adaptive training integrative knowledge system to potentially mitigate visuo-spatial and sensorimotor brain changes associated with prolonged isolation and confinement to reduce the likelihood or impact of potential decrements in human performance capabilities during long-duration space missions. The expected significance of this 4-year project relates to its relevance for facilitating effective countermeasure tools to acquire and retain operational skills that are critical for exploration class missions. This will support the development of necessary countermeasures and technologies in support of human space exploration, focusing on mitigating operational performance risks.

A C Stahn↗

NASA NTRS1993

The use of high fidelity CAD models as the basis for training on complex systems

During the design phases of large and complex systems such as NASA's Space Station Freedom (SSF), there are few, if any physical prototypes built. This is often due to their expense and the realization that the design is likely to change. This poses a problem for training, maintainability, and operations groups who are tasked to lay the foundation of plans for using these systems. The Virtual Reality and Visualization Laboratory at the Boeing Advanced Computing Group's Huntsville facility is supporting the use of high fidelity, detailed design models that are generated during the initial design phases, for use in training, maintainability and operations exercises. This capability was used in its non-immersive form to great effect at the SSF Critical Design Review (CDR) during February, 1993. Allowing the user to move about within a CAD design supports many efforts, including training and scenario study. We will demonstrate via a video of the Maintainability SSF CDR how this type of approach can be used and why it is so effective in conveying large amounts of information quickly and concisely. We will also demonstrate why high fidelity models are so important for this type of training system and how it's immersive aspects may be exploited as well.

Miller, Kellie↗

NASA NTRS1967

Stable superconducting magnet

Operation of a superconducting magnet is considered. A method is described for; (1) obtaining a relatively high current in a superconducting magnet positioned in a bath of a gas refrigerant; (2) operating a superconducting magnet at a relatively high current level without training; and (3) operating a superconducting magnet containing a plurality of turns of a niobium zirconium wire at a relatively high current level without training.

Boom, R. W.↗

NASA NTRS1977

Network functions and facilities

Objectives, functions, and organization of the Deep Space Network are summarized. A deep space station, ground communication, and network operations control capabilities are described. Data system configurations for testing, training, and network operations control functions are outlined.

Renzetti, N. A.↗

NASA NTRS1981

Traveling-wave maser, closed cycle refrigerator automation

At the present time all traveling-wave maser and closed-cycle refrigerator system (TWM-CCR) and their power supply and helium compressor assemblies are operated manually. Many man-hours are required of highly trained and experienced operators, resulting in high operator cost. Of greater importance are the problems of unpredictable failure and long downtimes. Since field performance is not monitored, system degradation is detected only when it has progressed to the point of catastrophic failure. Without the aid of performance histories, failure diagnosis is arduous and slow. Rational and functional requirements for the TWM-CCR Automation project are the following: (1) to improve reliability and reduce downtime by providing unattended monitor and control, alarm and fault location, failure prediction and self-corrective action; (2) to reduce operator cost by providing automatic tuning and cooldown procedures; and (3) to improve system operations and development by providing the needed engineering data.

Mcneil, J. A.↗

DOE OSTI2024

Towards maintaining canine training aid integrity: Effects of environmental factors and operational use on the triacetone triperoxide polymer odor capture‐and‐release system

Abstract There are many factors that may affect the longevity of or guide the use of canine training aids. Literature to date has mainly focused on identifying the headspace volatiles associated with training aids or odors and only minimal research exists into how different variables may alter those volatiles. The current study examines several factors affecting canine training aids: humidity, air flow, transportation, and operational deployment, using the triacetone triperoxide polymer odor capture‐and‐release canine training aid (TATP POCR) as the target. The TATP POCR is an absorption‐based canine training aid developed to be used to safely train canines to detect the odor of the explosive TATP in operational settings. Comparisons of the TATP POCR to neat TATP are made throughout the manuscript. First, humidity increased the background components of the POCR matrix, as well as the amount of TATP recovered was above the POCR. Humidity thus affected the amount of TATP detected but did not prevent detection. Second, air flow lessened the lifetime of the TATP POCR. Third, the practice of using primary and secondary containment successfully prevented contamination, cross‐contamination, and significant target loss, thereby maintaining kit integrity. Finally, the absorption of background odors from training environments was not observed. TATP headspace concentrations between a Deployed and Control POCR kit were not significantly different at time 0 (i.e., upon opening), which suggests that the operational use does not affect the function of the TATP POCR system. This information provides pivotal evidence for explosives detection canine handlers or trainers who utilize the TATP POCR.

Legal Medicine↗

NASA NTRS1989

An intelligent tutor for a high performance domain

The use of intelligent tutoring systems based on the apprenticeship approach to training is explored as a possible solution to the problem of training individuals to operate and maintain complex devices, such as those used in the aerospace industry. A general approach to the development of such a system is presented, and a specific intelligent tutoring system designed for training mission control console operators is described as an example.

Fink, Pamela K.↗

DOE OSTI2021

Artificial Intelligence for Data Center Operations (AI Ops)

HPC data centers such as the one at NREL's ESIF will increasingly need to rely on automation to keep pace with exascale growth in compute capability and to manage and optimize the data center environment and facility resources. Artificial intelligence (AI) and machine learning (ML) approaches provide the means to improve HPC data center efficiency (energy, operational, and managerial efficiency) and resiliency by learning historical trends and training models to operate on real-time data collected from both IT and facilities sources. The goal of coupled improvement of data center resiliency and energy efficiency through automated data collection and AI has led to a multi-year, multi-staged collaboration between NREL and Hewlett-Packard Enterprise's Advanced Technology Group, referred to as Artificial Intelligence for Data Center Operations (AIOps). The extended efforts within the AIOps project include a common goal of building capabilities for an advanced smart facility and demonstration of data collection and AI modeling techniques in the ESIF data center.

97 MATHEMATICS AND COMPUTING↗

NASA NTRS1985

STS flight operations - Concept versus reality

The NASA Lyndon B. Johnson Space Center Mission Operations Directorate (MOD) has the responsibility for planning, training, and implementing of flight operations in support of the National Space Transportation System (STS) Program. In this role, MOD has responsibility for the operational interface with customers and the translation of customer requirements into operating plans to satisfy their objectives. The basic objectives of flight operations are to maximize mission success, to minimize risks to the Orbiter and the crew, to decrease operating costs, and to achieve an effective balance in the application of all operational resources. In the National STS Program, to date, 20 missions have been flown and the process for planning, training, and flight operations has been thoroughly exercised. In this paper, MOD's performance is assessed, and those areas in which our initial operating concepts have been successful as well as those in which significant additional work is required are identified.

Kranz, E. F.↗

DOE OSTI2022

Throughput-Oriented and Accuracy-Aware DNN Training with BFloat16 on GPU

Deep Neural Networks (DNNs) have transformed the field of artificial intelligence and achieved extraordinary success in many areas. The training of DNNs is commonly compute and memory-intensive, which has resulted in several optimizations in the training phase. Among them, reduced precision is a typical and widely used technique to accelerate DNN training and reduce memory requirements. However, applying a widely adopted reduced precision format such as Float16 to all involved operations in DNN training is not optimal as the use of Float16 in some operations can hurt model accuracy. Meanwhile, additional optimizations including loss scaling and autocast techniques can mitigate the accuracy loss but lead to inherent overhead and inadequate use of reduced precision. In this work, we leverage another reduced precision format, BFloat16, and introduce a throughput-oriented and accuracy-aware approach to maximize the performance potential of DNN training. Since the high throughput provided by BFloat16 format is accompanied by low precision of the floating-point representation, this approach achieves high throughput by using BFloat16 on all DNN operations and avoids the accuracy loss through a customized accuracy-aware normalization. Results show that our approach outperforms the state-of-the-art mixed-precision training by 1.21x on an NVIDIA A100 GPU.

Xie, Zhen↗

NASA NTRSDate not supplied

What Can We Learn From Resilient Pilot Behaviors? The Case of Energy Management While Flying a Star

Recently, there has been increased interest in documenting flightcrew behaviors that contribute to safe operations. Instead of only capturing errors, new efforts are attempting to understand how pilots manage complexity and variability in the operational environment to ensure a safe mission. This approach highlights pilot responses to events and conditions that fall outside typical TEM threats; e.g., revised ATC clearances. This approach presents a two-sided coin: characterize flightcrew resilience /or/ generate insights regarding complexity in the operational environment that is not adequately managed by current flight deck interface designs, procedures, and training. To capture operational complexity, we have been analyzing flight path management tied to flying an RNAV STAR. Because ATC often requests revisions—e.g., descend late—and because RNAV STARs may not align with airplane performance limits, flightcrews need to monitor, anticipate threats to RNAV STAR compliance, and devise ways to accommodate unexpected challenges. In this paper, we identify general strategies that can support response adaptation and explore methods to facilitate training these strategies.

flight operations↗

DOE OSTI2023

Volume 9: Critical Facility with Add-On Ion Beam

Completion of the originally planned critical facility has been considered as part of the High Flux Isotope Reactor (HFIR) Sustaining and Enhancing Neutron Science Initiative at Oak Ridge National Laboratory (ORNL). A working group of ORNL staff members was formed to develop the idea and to recommend one or more configurations to best support future HFIR operations and scientific capacities. HFIR was designed with a critical pool in the reactor bay that was projected to be outfitted as a critical facility. The primary purpose of the planned critical facility was to measure the subcritical worth of fresh fuel elements to support startup requirements. However, the Y-12 National Security Complex already housed a critical facility that was used for this purpose. This report presents the working group’s efforts, including determination of the proposed critical facility’s high-impact benefits. A generic low-power critical facility would be employed for reactor physics measurements, code and data validation, reactor operator and staff training, and education. This facility would be instrumental in supporting current HFIR operations, conversion of HFIR to low-enriched uranium, existing light water reactor operations, and advanced reactor development and deployment.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

NASA NTRS1973

Mariner Mars 1971 project. Volume 3: Mission operations system implementation and standard mission flight operations

The Mariner Mars 1971 mission which was another step in the continuing program of planetary exploration in search of evidence of exobiological activity, information on the origin and evolution of the solar system, and basic science data related to the study of planetary physics, geology, planetology, and cosmology is reported. The mission plan was designed for two spacecraft, each performing a separate but complementary mission. However, a single mission plan was actually used for Mariner 9 because of failure of the launch vehicle for the first spacecraft. The implementation is described, of the Mission Operations System, including organization, training, and data processing development and operations, and Mariner 9 spacecraft cruise and orbital operations through completion of the standard mission from launch to solar occultation in April 1972 are discussed.

Source record↗

NASA NTRS1986

NOSL experiment support

An optical lightning detector was constructed and flown, along with Vinton cameras and a Fairchild Line Scan Spectrometer, on a U-2 during the summer of 1979. The U-2 lightning data was obtained in daylight, and was supplemented with ground truth taken at Langmuir Laboratory. Simulations were prepared as required to establish experiment operating procedures and science training for the astronauts who would operate the Night/Day Optical Survey of Thunderstorm Lightning (NOSL) equipment during the STS-2 NOSL experiment on the Space Shuttle. Data was analyzed and papers were prepared for publication.

Brook, M.↗

NASA NTRS1994

International Space Station Alpha user payload operations concept

International Space Station Alpha (ISSA) will accommodate a variety of user payloads investigating diverse scientific and technology disciplines on behalf of five international partners: Canada, Europe, Japan, Russia, and the United States. A combination of crew, automated systems, and ground operations teams will control payload operations that require complementary on-board and ground systems. This paper presents the current planning for the ISSA U.S. user payload operations concept and the functional architecture supporting the concept. It describes various NASA payload operations facilities, their interfaces, user facility flight support, the payload planning system, the onboard and ground data management system, and payload operations crew and ground personnel training. This paper summarizes the payload operations infrastructure and architecture developed at the Marshall Space Flight Center (MSFC) to prepare and conduct ISSA on-orbit payload operations from the Payload Operations Integration Center (POIC), and from various user operations locations. The authors pay particular attention to user data management, which includes interfaces with both the onboard data management system and the ground data system. Discussion covers the functional disciplines that define and support POIC payload operations: Planning, Operations Control, Data Management, and Training. The paper describes potential interfaces between users and the POIC disciplines, from the U.S. user perspective.

Schlagheck, Ronald A.↗

NASA NTRS2001

STS-108 Crew Training Clip

This video shows the crew of STS-108, Commander Dominic Gorie, Pilot Mark Kelly, and Mission Specialists Linda Godwin and Daniel Tani, during various parts of their training, including T-38 operations at Ellington, bail-out training (with the Expedition 4 crew: Commander Yuri Onufrienko and Flight Engineers Carl Walz and Daniel Bursch) in CCT2, extravehicular activity (EVA) preparations, Space Station Mockup and Test/Training Facility (SSMTF) transfer and hands-on familiarization (also with E4), Remote Manipulator System training, EVA training in the Neutral Buoyancy Laboratory, and in a payload training class.

Source record↗