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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 145 records · Page 8
All sourcesNASA NTRSDOE OSTI
NASA NTRS1976

Hard X-ray imaging facility for space shuttle: A scientific and conceptual engineering study

A shuttle-accommodated instrument for imaging hard X-rays in the study of nonthermal particles and high temperature particles in various solar and cosmic phenomena was defined and its feasibility demonstrated. The imaging system configuration is described as well as the electronics, aspect systems, mechanical and thermal properties and the ground support equipment.

Peterson, L. E.↗
NASA NTRS1978

HEAO-B and -C engineering design and scientific objectives

The HEAO-B observatory will be launched in late 1978 for a one-year mission to analyze individual X-ray objects and extended sources in detail using a high precision X-ray telescope. The energy range of the telescope is 0.1 keV to 4 keV. Four interchangeable instruments are at the focal plane; a high resolution imaging instrument, an imaging proportional counter, a focal plane crystal spectrometer, and a solid state spectrometer. A monitor proportional counter will collect data independently of the telescope. The HEAO-C observatory is a scanning mission and will be launched in 1979 for six months operation. It will contain two cosmic ray experiments and a gamma ray spectrometer.

Dailey, C. C.↗
NASA NTRS2010

Reconciling Scientific Aspirations and Engineering Constraints for a Lunar Mission via Hyperdimensional Interpolation

Virtually every NASA space-exploration mission represents a compromise between the interests of two expert, dedicated, but very different communities: scientists, who want to go quickly to the places that interest them most and spend as much time there as possible conducting sophisticated experiments, and the engineers and designers charged with maximizing the probability that a given mission will be successful and cost-effective. Recent work at NASA's Jet Propulsion Laboratory (JPL) seeks to enhance communication between these two groups, and to help them reconcile their interests, by developing advanced modeling capabilities with which they can analyze the achievement of science goals and objectives against engineering design and operational constraints. The analyses conducted prior to this study have been point-design driven. Each analysis has been of one hypothetical case which addresses the question: Given a set of constraints, how much science can be done? But the constraints imposed by the architecture team-e.g., rover speed, time allowed for extravehicular activity (EVA), number of sites at which science experiments are to be conducted- are all in early development and carry a great deal of uncertainty. Variations can be incorporated into the analysis, and indeed that has been done in sensitivity studies designed to see which constraint variations have the greatest impact on results. But if a very large number of variations can be analyzed all at once, producing a table that includes virtually the entire trade space under consideration, then we have a tool that enables scientists and mission architects to ask the inverse question: For a given desired level of science (or any other objective), what is the range of constraints that would be needed? With this tool, mission architects could determine, for example, what combinations of rover speed, EVA duration, and other constraints produce the desired results. Further, this tool would help them identify which technology-improvement investments would be likely to produce the largest or most important return. However, the number of variations that need to be considered for such analysis quickly balloons to an unwieldy size. If three variations are considered for each of six constraints-a very modest example-there are a total of 243 variations to consider. If it takes 40 minutes to compute each variation, as it does with HURON, our automated optimization system, then it would take 162 hours or nearly 7 days of round-the-clock computing to calculate the results. Adding further constraints or variations exponentially increases the amount of time that is needed.

Weisbin, Charles R.↗
NASA NTRS1974

AIROscope: Ames infrared balloon-borne telescope

A balloon-borne telescope system designed for astronomical observations at infrared wavelengths is discussed. The telescope is gyro-stabilized with updated pointing information derived from television, star tracker, or ground commands. The television system furnishes both course and fine acquisition after initial orientation using a pair of fluxgate servo compasses. Command and control is by a UHF link with 256 commands available. Scientific and engineering data are telemetered to the ground station via narrow band F.M. in the L band. The ground station displays all scientific, engineering and status information during the flights and records the command and telemetry digital bit stream for detailed analysis. The AIROscope telescope has a 28-inch diameter primary mirror and Dall-Kirkham optics. The beam is modulated by oscillating a secondary mirror at 11 or 25 Hz with provision for left or right beam fixed positions by command.

Koontz, O. L.↗
DOE OSTI2023

Bayesian, Multifidelity Operator Learning for Complex Engineering Systems–A Position Paper

Abstract Deep learning has significantly improved the state-of-the-art in computer vision and natural language processing, and holds great potential to design effective tools for predicting and simulating complex engineering systems. In particular, scientific machine learning seeks to apply the power of deep learning to scientific and engineering tasks, with operator learning (OL) emerging as a particularly effective tool. OL can approximate nonlinear operators arising in complex engineering systems, making it useful for simulating, designing, and controlling those systems. In this position paper, we provide a comprehensive overview of OL, including its potential applications to complex engineering domains. We cover three variations of OL approaches: deterministic OL for modeling nonautonomous systems, OL with uncertainty quantification (UQ) capabilities, and multifidelity OL. For each variation, we discuss drawbacks and potential applications to engineering, in addition to providing a detailed explanation. We also highlight how multifidelity OL approaches with UQ capabilities can be used to design, optimize, and control engineering systems. Finally, we outline some potential challenges for OL within the engineering domain.

Computer Science↗
NASA NTRS1990

Fundamental research in artificial intelligence at NASA

This paper describes basic research at NASA in the field of artificial intelligence. The work is conducted at the Ames Research Center and the Jet Propulsion Laboratory, primarily under the auspices of the NASA-wide Artificial Intelligence Program in the Office of Aeronautics, Exploration and Technology. The research is aimed at solving long-term NASA problems in missions operations, spacecraft autonomy, preservation of corporate knowledge about NASA missions and vehicles, and management/analysis of scientific and engineering data. From a scientific point of view, the research is broken into the categories of: planning and scheduling; machine learning; and design of and reasoning about large-scale physical systems.

Friedland, Peter↗
NASA NTRS2008

Spatial Coverage Planning and Optimization for Planetary Exploration

We are developing onboard planning and scheduling technology to enable in situ robotic explorers, such as rovers and aerobots, to more effectively assist scientists in planetary exploration. In our current work, we are focusing on situations in which the robot is exploring large geographical features such as craters, channels or regional boundaries. In to develop valid and high quality plans, the robot must take into account a range of scientific and engineering constraints and preferences. We have developed a system that incorporates multiobjective optimization and planning allowing the robot to generate high quality mission operations plans that respect resource limitations and mission constraints while attempting to maximize science and engineering objectives. An important scientific objective for the exploration of geological features is selecting observations that spatially cover an area of interest. We have developed a metric to enable an in situ explorer to reason about and track the spatial coverage quality of a plan. We describe this technique and show how it is combined in the overall multiobjective optimization and planning algorithm.

autonomy↗
DOE OSTI2015

LHC: The Large Hadron Collider

The Large Hadron Collider (or LHC) is the world’s most powerful particle accelerator. In 2012, scientists used data taken by it to discover the Higgs boson, before pausing operations for upgrades and improvements. In the spring of 2015, the LHC will return to operations with 163% the energy it had before and with three times as many collisions per second. It’s essentially a new and improved version of itself. In this video, Fermilab’s Dr. Don Lincoln explains both some of the absolutely amazing scientific and engineering properties of this modern scientific wonder.

42 ENGINEERING↗
NASA NTRS2003

The devil that we know: lead (Pb) replacement policies under conditions of scientific uncertainty

Engineering and economic considerations are typical driving forces behind the selection of specific chemicals used in the manufacture of consumer products. Only recently has post-consumer environmental impact become part of the major considerations during the initial phases of product design. Therefore, reactive, rather than proactive strategies have dominated the consideration of environmental and health issues in product design.

Pb-free↗
DOE OSTI2020

Dual Purpose Canister Reactivity and Groundwater Absorption Analyses

The current spent nuclear fuel (SNF) management strategy includes reliance on dry storage. Utilities are meeting their interim storage needs on an individual basis with use of large-capacity dry storage casks, with a current focus on meeting existing storage and transportation requirements, as disposal requirements are not currently available. These casks are commonly known as dual-purpose (i.e., storage and transportation) canisters (DPCs). However, a small percentage of single-purpose (storage only) systems is also being used to meet storage needs. These are included under the “DPC” heading. This report investigates the postclosure criticality safety aspects of DPCs. Placing large, heavy waste packages containing DPCs into a repository for direct disposal has not yet been implemented domestically or internationally. Therefore, direct disposal of DPCs represents new engineering and scientific challenges. Some of the engineering challenges that have already been addressed include handling and placement, use of ramps vs. shafts, use of hoists, use of transport equipment, and thermal management. Additionally, some studies have been conducted in the past regarding the feasibility of direct disposal from a criticality analysis perspective and have concluded that while possible, demonstrating subcriticality over the disposal time period is a challenge. The alternative to direct disposal of DPCs into a repository is to repackage the SNF into different canisters. The direct disposal of DPCs without cutting them open and repackaging is appealing because it could be more cost-effective, reduce the complexity of fuel management operations both in and outside reactor facilities, and result in less cumulative worker dose during interim storage and handling before eventual disposal in a deep geologic repository.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2022

Dual Purpose Canister Reactivity and Groundwater Absorption Analyses

The current spent nuclear fuel (SNF) management strategy includes reliance on dry storage. Utilities are meeting their interim storage needs on an individual basis with use of large-capacity dry storage casks, with a current focus on meeting existing storage and transportation requirements, as disposal requirements are not currently available. These casks are commonly known as dual-purpose (i.e., storage and transportation) canisters (DPCs). However, a small percentage of single-purpose (storage only) systems is also being used to meet storage needs. These are included under the “DPC” heading. This report investigates the postclosure criticality safety aspects of DPCs. Placing large, heavy waste packages containing DPCs into a repository for direct disposal has not yet been implemented domestically or internationally. Therefore, direct disposal of DPCs represents new engineering and scientific challenges. Some of the engineering challenges that have already been addressed include handling and placement, use of ramps vs. shafts, use of hoists, use of transport equipment, and thermal management. Additionally, some studies have been conducted in the past regarding the feasibility of direct disposal from a criticality analysis perspective and have concluded that while possible, demonstrating subcriticality over the disposal time period is a challenge. The alternative to direct disposal of DPCs into a repository is to repackage the SNF into different canisters. The direct disposal of DPCs without cutting them open and repackaging is appealing because it could be more cost-effective, reduce the complexity of fuel management operations both in and outside reactor facilities, and result in less cumulative worker dose during interim storage and handling before eventual disposal in a deep geologic repository.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗