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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
DOE OSTI2017

Initial Site-Specific De-Inventory Report for Trojan

This report has been developed to satisfy solicitation number 6400014223 under subcontract number 4000146712 issued by UT-Battelle, LLC, managing contractor of Oak Ridge National Laboratory (ORNL) to AREVA Federal Services (AFS). The purpose of this report is to assist the United States (U.S.) Department of Energy (DOE) in laying the groundwork for implementing an integrated waste management system. This includes preparing for future large-scale transport of Spent Nuclear Fuel (SNF), High-Level Radioactive Waste (HLW), and Greater Than Class C (GTCC) Low Level Radioactive Waste (LLW). This report addresses the tasks, equipment, and interfaces necessary for the complete de-inventory of the Trojan independent spent fuel storage installation (ISFSI) located in northwestern Oregon along the Columbia River at river mile 72.5 and approximately 42 miles north of Portland, OR. As such, this report is intended to provide information useful for planning options within the integrated waste management system.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2017

Initial Site-Specific De-Inventory Report for Maine Yankee

This report has been developed to satisfy solicitation number 6400014223 under subcontract number 4000146712 issued by UT-Battelle, LLC, managing contractor of Oak Ridge National Laboratory (ORNL) to AREVA Federal Services (AFS). The purpose of this report is to assist the United States (U.S.) Department of Energy (DOE) in laying the groundwork for implementing an integrated waste management system. This includes preparing for future large-scale transport of Spent Nuclear Fuel (SNF), High-Level Radioactive Waste (HLW), and Greater Than Class C (GTCC) Low Level Radioactive Waste (LLW). This report addresses the tasks, equipment, and interfaces necessary for the complete de-inventory of the Maine Yankee (MY) independent spent fuel storage installation (ISFSI) site located in the mid-coast region of Maine approximately 25 miles south of Augusta, ME and 45 miles northeast of Portland, ME. As such, this report is intended to provide information useful for planning options within the integrated waste management system.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
NASA NTRS1973

En route position and time control of aircraft using Kalman filtering of radio aid data

Fixed-time-of-arrival (FTA) guidance and navigation is investigated as a possible technique capable of operation within much more stringent en route separation standards and offering significant advantages in safety, higher traffic densities, and improved scheduling reliability, both en route and in the terminal areas. This study investigated the application of FTA guidance previously used in spacecraft guidance. These FTA guidance techniques have been modified and are employed to compute the velocity corrections necessary to return an aircraft to a specified great-circle reference path in order to exercise en route time and position control throughout the entire flight. The necessary position and velocity estimates to accomplish this task are provided by Kalman filtering of data from Loran-C, VORTAC/TACAN, Doppler radar, radio or barometric altitude,and altitude rate. The guidance and navigation system was evaluated using a digital simulation of the cruise phase of supersonic and subsonic flights between San Francisco and New York City, and between New York City and London.

Mcgee, L. A.↗
NASA NTRS1991

Acquisition, representation and rule generation for procedural knowledge

Current research into the design and continuing development of a system for the acquisition of procedural knowledge, its representation in useful forms, and proposed methods for automated C Language Integrated Production System (CLIPS) rule generation is discussed. The Task Analysis and Rule Generation Tool (TARGET) is intended to permit experts, individually or collectively, to visually describe and refine procedural tasks. The system is designed to represent the acquired knowledge in the form of graphical objects with the capacity for generating production rules in CLIPS. The generated rules can then be integrated into applications such as NASA's Intelligent Computer Aided Training (ICAT) architecture. Also described are proposed methods for use in translating the graphical and intermediate knowledge representations into CLIPS rules.

Ortiz, Chris↗
NASA NTRS1991

Extensions to the Parallel Real-Time Artificial Intelligence System (PRAIS) for fault-tolerant heterogeneous cycle-stealing reasoning

Extensions to an architecture for real-time, distributed (parallel) knowledge-based systems called the Parallel Real-time Artificial Intelligence System (PRAIS) are discussed. PRAIS strives for transparently parallelizing production (rule-based) systems, even under real-time constraints. PRAIS accomplished these goals (presented at the first annual C Language Integrated Production System (CLIPS) conference) by incorporating a dynamic task scheduler, operating system extensions for fact handling, and message-passing among multiple copies of CLIPS executing on a virtual blackboard. This distributed knowledge-based system tool uses the portability of CLIPS and common message-passing protocols to operate over a heterogeneous network of processors. Results using the original PRAIS architecture over a network of Sun 3's, Sun 4's and VAX's are presented. Mechanisms using the producer-consumer model to extend the architecture for fault-tolerance and distributed truth maintenance initiation are also discussed.

Goldstein, David↗
NASA NTRS1993

Lithium D-cell study

The purpose of this contract is to evaluate parametrically the effects of various factors including the electrolyte type, electrolyte concentration, depolarizer type, and cell configuration on lithium cell electrical performance and safety. This effort shall allow for the selection and optimization of cell design for future NASA applications while maintaining close ties with WGL's continuous improvements in manufacturing processes and lithium cell design. Taguchi experimental design techniques are employed in this task, and allow for a maximum amount of information to be obtained while requiring significantly less cells than if a full factorial design were employed. Acceptance testing for this task is modeled after the NASA Document EP5-83-025, Revision C, for cell weights, OCV's and load voltages. The performance attributes that are studied in this effort are fresh capacity and start-up characteristics evaluated at two rates and two temperatures, shelf-life characteristics including start-up and capacity retention, and iterative microcalorimetry measurements. Abuse testing includes forced over discharge at two rates with and without diode protection, temperature tolerance testing, and shorting tests at three rates with the measurement of heat generated during shorting conditions.

Size, P.↗
NASA NTRS2010

Recent Status of SIM Lite Astrometric Observatory Mission: Flight Engineering Risk Reduction Activities

The SIM Lite Astrometric Observatory is a mission concept for a space-borne instrument to perform micro-arc-second narrow-angle astrometry to search 60 to 100 nearby stars for Earth-like planets, and to perform global astrometry for a broad astrophysics program. The instrument consists of two Michelson stellar interferometers and a telescope. The first interferometer chops between the target star and a set of reference stars. The second interferometer monitors the attitude of the instrument in the direction of the target star. The telescope monitors the attitude of the instrument in the other two directions. The main enabling technology development for the mission was completed during phases A & B. The project is currently implementing the developed technology onto flight-ready engineering models. These key engineering tasks will significantly reduce the implementation risks during the flight phases C & D of the mission. The main optical interferometer components, including the astrometric beam combiner, the fine steering optical mechanism, the path-length-control and modulation optical mechanisms, focal-plane camera electronics and cooling heat pipe, are currently under development. Main assemblies are built to meet flight requirements and will be subjected to flight qualification level environmental testing (random vibration and thermal cycling) and performance testing. This paper summarizes recent progress in engineering risk reduction activities.

astrometry↗
NASA NTRSDate not supplied

Analytical Framework for Rodent/NHP Data Set Utilization to Inform Human CNS Risk Estimation

Objectives Review and inform on tactics to analyze & communicate data from animal research (e.g., rodents, mini-pigs, NHPs, et al) exposed to single and combinations of spaceflight hazards, using NASA’s Human System Risk Board (HSRB) process for the Behavioral Medicine Risk - To quantitatively inform Behavioral Medicine Risk posture - i.e., likelihood (L) and consequence (C) - To help inform estimation of crew health standards for operational task performance (i.e., Fitness For Duty, Space Permissible Exposure Levels, Permissible Operational Limits).

Brain↗
NASA NTRS2023

Developing a Hybrid Spacesuit Simulator as a Research Tool for Assessing Extravehicular Activity Relevant Workload

Conducting human tests in a pressurized spacesuit is limited by availability, cost, and manpower; however, pressurized spacesuits are not always needed depending on the objectives of testing, including the development and testing of new informatics capabilities. The Human Physiology, Performance, Protection & Operations Laboratory (H-3PO) at NASA is developing a Hybrid Spacesuit Simulator (HS3) to support testing and characterization of human performance during analog planetary exploration extravehicular activities (EVAs). The goal of HS3 is to create a low-cost, modular, and unpressurized spacesuit simulator as a research tool that provides relevant physical and cognitive workload approximations with EVA-like immersion. HS3 consists of a soft outer suit, thermal control, gloves, boots, helmet, and integrated bioinformatics and communications. Baseline HS3 assessments were performed during 3-hour EVA simulations in two different subjects (DEMO1 and DEMO2) that included traverses at variable resistances and geological sampling activities. Liquid cooling garment (LCG) temperature, mean skin temperature, heart rate, motion capture, and metabolic rate were collected during each 3-hour simulated EVA. During DEMO1 and DEMO2, baseline metabolic rates at rest were 836 ± 327 BTU/hr and 869 ± 207 BTU/hr and increased to 2124 ± 548 BTU/hr and 2269 ± 559 BTU/hr, respectively, during 500m traverse. Average inlet LCG temperatures were 29.57 ± 6.62 °C and 25.63 ± 6.48 °C for DEMO1 and DEMO2 with increased outlet LCG temperatures of 33.53 ± 6.62 °C and 29.21 ± 4.79 °C, respectively. Overall, HS3 will enable future studies to characterize EVA tasks, human performance, and test future EVA capabilities in analog test environments without the need for pressurized suited environments.

Monica Hew↗
NASA NTRSDate not supplied

Developing A Hybrid Spacesuit Simulator as A Research Tool for Assessing Extravehicular Activity Relevant Workload

Conducting human tests in a pressurized spacesuit is limited by availability, cost, and manpower; however, pressurized spacesuits are not always needed depending on the objectives of testing, including the development and testing of new informatics capabilities. The Human Physiology, Performance, Protection & Operations Laboratory (H-3PO) at NASA is developing a Hybrid Spacesuit Simulator (HS3) to support testing and characterization of human performance during analog planetary exploration extravehicular activities (EVAs). The goal of HS3 is to create a low-cost, modular, and unpressurized spacesuit simulator as a research tool that provides relevant physical and cognitive workload approximations with EVA-like immersion. HS3 consists of a soft outer suit, thermal control, gloves, boots, helmet, and integrated bioinformatics and communications. Baseline HS3 assessments were performed during 3-hour EVA simulations in two different subjects (DEMO1 and DEMO2) that included traverses at variable resistances and geological sampling activities. Liquid cooling garment (LCG) temperature, mean skin temperature, heart rate, motion capture, and metabolic rate were collected during each 3-hour simulated EVA. During DEMO1 and DEMO2, baseline metabolic rates at rest were 836 ± 327 BTU/hr and 869 ± 207 BTU/hr and increased to 2124 ± 548 BTU/hr and 2269 ± 559 BTU/hr, respectively, during 500m traverse. Average inlet LCG temperatures were 29.57 ± 6.62 °C and 25.63 ± 6.48 °C for DEMO1 and DEMO2 with increased outlet LCG temperatures of 33.53 ± 6.62 °C and 29.21 ± 4.79 °C, respectively. Overall, HS3 will enable future studies to characterize EVA tasks, human performance, and test future EVA capabilities in analog test environments without the need for pressurized suited environments.

Suit simulator↗
DOE OSTI2024

Machine Learning for DUNE Supernova Trigger

One of the major scientific goals of the Deep Underground Neutrino Experiment (DUNE) is to detect and measure the neutrino flux originating from galactic core-collapse supernovae. These neutrinos provide an opportunity to study the end of life evolution of massive stars, and reveal information about the structure of core-collapse that is not visible in observations of the electromagnetic spectrum. Because of the rarity of these events, it is crucial that DUNE is able to detect supernova neutrino interactions when they occur. However, this will require sifting through a large quantity of data, motivating the development of a trigger algorithm to identify significant events and discard irrelevant data. Machine learning provides a potential approach to building this trigger. This project generates ADC and ground truth images of simulated neutrino interactions in a LArTPC detector to be used for machine learning, and uses them to train a sparse Convolutional Neural Network (C NN). The performance of this model when applied to the task of pixel classification based on interaction type is examined. This project found that the sparse CNN approach has the potential to have high accuracy in pixel classification, meaning it may be highly relevant to the development of a supernova neutrino trigger for the DUNE far detector.

Damish, S.↗
NASA NTRS1993

Airborne Visible/Infrared Imaging Spectrometer (AVIRIS): Recent Improvements to the Sensor and Data Facility

AVIRIS operations at the Jet Propulsion Laboratory consist primarily of a sensor task and a data facility task. The sensor task is responsible for AVIRIS sensor meaintenance, laboratory calibration, and field operations. The AVIRIS data facility is responsible for data archiving, data calibration, quality monitoring and distribution. In this paper we describe recent improvements in these two primary AVIRIS tasks.

Airborne↗
NASA NTRS1980

Software development tools: A bibliography, appendix C.

A bibliography containing approximately 200 citations on tools which help software developers perform some development task (such as text manipulation, testing, etc.), and which would not necessarily be found as part of a computing facility is given. The bibliography comes from a relatively random sampling of the literature and is not complete. But it is indicative of the nature and range of tools currently being prepared or currently available.

Riddle, W. E.↗
NASA NTRS1980

The Lockheed OSO-8 program. Task 2: Analysis of data from the high resolution ultraviolet spectrometer experiment

The complete set of C 4 time sequences generated by the University of Colorado high resolution ultraviolet spectrometer experiment on OSO-8 were examined in a comprehensive and systematic fashion. As a result a new limit is placed on the acoustic flux passing through the transition zone of the Sun's atmosphere. It is found to be three orders of magnitude too small to heat the corona, and is consistent with zero. In collaborative efforts, the properties of transient C 4 brightenings were examined in considerable detail.

Bruner, E. C., Jr.↗
DOE OSTI2017

Machine Learning-Based Temperature Prediction for Runtime Thermal Management Across System Components

Elevated temperatures limit the peak performance of systems because of frequent interventions by thermal throttling. Non-uniform thermal states across system nodes also cause performance variation within seemingly equivalent nodes leading to significant degradation of overall performance. In this paper we present a framework for creating a lightweight thermal prediction system suitable for run-time management decisions. We pursue two avenues to explore optimized lightweight thermal predictors. First, we use feature selection algorithms to improve the performance of previously designed machine learning methods. Second, we develop alternative methods using neural network and linear regression-based methods to perform a comprehensive comparative study of prediction methods. We show that our optimized models achieve improved performance with better prediction accuracy and lower overhead as compared with the Gaussian process model proposed previously. Specifically we present a reduced version of the Gaussian process model, a neural network-based model, and a linear regression-based model. Using the optimization methods, we are able to reduce the average prediction errors in the Gaussian process from 4: 2 degrees C to 2: 9 degrees C. We also show that the newly developed models using neural network and Lasso linear regression have average prediction errors of 2: 9 degrees C and 3: 8 degrees C respectively. The prediction overheads are 0.22, 0.097, and 0.026 ms per prediction for reduced Gaussian process, neural network, and Lasso linear regression models, respectively, compared with 0.57 ms per prediction for the previous Gaussian process model. We have implemented our proposed thermal prediction models on a two-node system configuration to help identify the optimal task placement. The task placement identified by the models reduces the average system temperature by up to 11: 9 degrees C without any performance degradation. Furthermore, these models respectively achieve 75, 82.5, and 74.17 percent success rates in correctly pointing to those task placements with better thermal response, compared with 72.5 percent success for the original model in achieving the same objective. Lastly, we extended our analysis to a 16-node system and we were able to train models and execute them in real time to guide task migration and achieve on average 17 percent reduction in the overall system cooling power.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2014

Fault-tolerant dynamic task graph scheduling

In this paper, we present an approach to fault tolerant execution of dynamic task graphs scheduled using work stealing. In particular, we focus on selective and localized recovery of tasks in the presence of soft faults. We elicit from the user the basic task graph structure in terms of successor and predecessor relationships. The work stealing-based algorithm to schedule such a task graph is augmented to enable recovery when the data and meta-data associated with a task get corrupted. We use this redundancy, and the knowledge of the task graph structure, to selectively recover from faults with low space and time overheads. We show that the fault tolerant design retains the essential properties of the underlying work stealing-based task scheduling algorithm, and that the fault tolerant execution is asymptotically optimal when task re-execution is taken into account. Experimental evaluation demonstrates the low cost of recovery under various fault scenarios.

fault tolerance↗
DOE OSTI2018

ECP Milestone Memo for 2.3.1.04.16

The DARMA many-task framework provides asynchronous communication and load balancing functionality. This functionality is embedded in standard, modern C++ through the use of the template wrapper classes similar to futures. DARMA codes previously could not interoperate with Kokkos or OpenMP since each runtime assumed sole ownership of thread resources. The most recent version now allows for the use of Kokkos/OpenMP within DARMA tasks, allowing for better performance through thread-level parallelism or use of accelerators.

97 MATHEMATICS AND COMPUTING↗