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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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34 records · Page 2

Spinoff 1977

The National Aeronautics & Space Administration has many missions but they can all be reduced to a common denominator: to explore Earth and its surroundings, conduct aeronautical research, and put the results to work for the benefit of mankind. At times the benefit may be dimly perceived. Take, for instance, last year's monumental triumph of exploration, the landing of robot spacecraft on Mars. How, some ask, does probing a neighbor planet improve the lot of Earth's people? In two ways: scientific gain and technological advancement. Though perhaps little understood, they are concrete benefits, assets as tangible as sunshine, more valuable than gold. Technological advancement, on the other hand, offers equally important but more immediate returns. Technology is science applied. It is the ability of a society to make things that improve the quality of human existence. It is compounded of intellect and skill, which draw upon the scientific base to bring forth new ideas, inventions, materials and processes. It is, in a word, knowledge. It builds like an inverted pyramid, each level broader than the one . before as successive generations contribute to the cumulative lore. Knowledge is readily transferable. If you build a better mousetrap, you may acquire experience in the course of the project that can be applied to a need totally unrelated to mouse-traping. This transfer process has been going on since the dawn of technology. In the last two decades it has accelerated enormously, spurred by the immense flow of aerospace-stimulated technology. There have been literally thousands of spinoffs, new products and processes that owe their origins to aerospace research. Collectively, they add up to significant gain in terms of personal convenience, human welfare, industrial efficiency, and economic value.

Haggerty, James J.↗

Science Overview

This report presents an overview of the latest scientific consensus understanding of the effect of aviation emissions on the atmosphere for both local air quality and climate change in order to provide a contextual framework for raising future questions to help assess the environmental benefits of technology goals. The questions may take the form of what are the environmental benefits that would result if goals are achieved, what are the consequences for other aviation pollutants, and whether tools exist to evaluate the trade-off. In addition to this documents, presentations will be made at the meeting to illustrate current developing views on these subjects. To facilitate studies on trade-offs among environmental impacts from aviation, one must start with scientific investigations that quantify the impacts. A second step is to select representative metrics with policy relevance so that diverse impacts can be put on the same common scale. The IPCC Special Report on Aviation (IPCC, 1999) serves as an excellent example of the first step. The report was produced by IPCC's Working Group 1, whose mandate is to provide the assessment of the scientific aspects of the climate system and climate change. An example of the second step is Witt et al. (2005), a study commissioned by the Environment DG of the European Commission. Within the context of CAEP, step 1 is aligned with the responsibilities of the Research Focal Points, while step 2 is more related to activities of FESG. These steps are likely to be iterative as proposed policy options will raise new science questions, and new science will expand or limit policy options. Past experiences show that clearly defined policy-related scientific needs will help focus the scientific community to marshal their intellects to provide the needed answers.

Bruning, Claus↗

A Thinking System and Thinking Autonomy

There are many definitions of what a “Thinking System” (TS) is. The literature primarily addresses what is called “Systems Thinking.” Dr. Marie Morganelli from Southern New Hampshire University states that “Systems thinking is a holistic way to investigate factors and interactions that could contribute to a possible outcome. A mindset more than a prescribed practice, systems thinking provides an understanding of how individuals can work together in different types of teams and through that understanding, create the best possible processes to accomplish just about anything.” So, a TS is a system that is capable of “systems thinking,” as it should be able to “ … create [utilize] the best possible processes [and intelligence] to accomplish just about anything.” To achieve this capability, human-like thinking is required. A truly autonomous system must be one that is capable of human-like thinking. This paper will address “Thinking Autonomy” (TA) enabled by a “Thinking System.” It will describe an architecture with the elements required to achieve the “thinking” behavior: understanding, intellect, reason, decision, will. The paper will further describe the contents and functionality of these elements and how to implement them, including software capabilities needed. Finally, the paper will provide details of a software platform that enables TA, the NASA Platform for Autonomous Systems (NPAS), and describe implementations of thinking systems. Thinking systems will enable a fundamental change how AI and autonomy are implemented. It will change from a “brute force” approach that results in one-time implementations that are minimally intelligent or autonomous to a “thinking” approach where implementations evolve continuously and enable powerful intelligence and autonomy on systems of high complexity as well as on systems-of-systems.

Thinking systems↗

Industry Level Feasibility of LiDAR Data into Fire Modeling Using Fire Risk Investigation in 3D (FRI3D)

Many evaluation, assessment, and modeling tasks at nuclear power plants require spatial information this often requires physical visits to locations within the facility because the 2D or 3D schematics and current models do not contain enough detail or do not capture as-built and real-world conditions. These visits require extensive manual labor for not only the requesting party, but support groups such as security. LIDAR mapping is trying to solve that problem by providing very detailed 3D models for low costs. However, the use of these models can be very limited because either component reference information is missing and too costly to add, or there is no way to extract specific spatial data needed for other tools. This report presents Idaho National Lab's work with Environmental Intellect (Ei) covering two main efforts. First, to reduce the effort of "tagging" data in large 3D models. By using both existing plant database information, and artificial intelligence (AI) to find and read equipment labels. This research explores the ability of to provide a simple way for the user to tag items and verify plant data, capturing both the speed of AI and human verification. The second part of the work is the development of an interface for importing pieces needed for Modeling & Simulation. Analysis work such as that for fire, flood, or physical security all require spatial or 3D models in various levels of detail. This interface will allow for the retrieval of item location or boundaries, enabling the auto generation of models for varying tools. The application program interface (API) of the fire risk investigation in 3D (FRI3D) was used to test feasibility of exporting the LiDAR tagged spatial information. Outcomes from this work provide preliminary data to determine if the tools and methods could provide substantial industry benefit if fully matured.

97 MATHEMATICS AND COMPUTING↗