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Steinle, Frank W., Jr.

Publications and source records attributed to Steinle, Frank W., Jr..

An integrated knowledge system for wind tunnel testing - Project Engineers' Intelligent Assistant

The Project Engineers' Intelligent Assistant (PEIA) is an integrated knowledge system developed using artificial intelligence technology, including hypertext, expert systems, and dynamic user interfaces. This system integrates documents, engineering codes, databases, and knowledge from domain experts into an enriched hypermedia environment and was designed to assist project engineers in planning and conducting wind tunnel tests. PEIA is a modular system which consists of an intelligent user-interface, seven modules and an integrated tool facility. Hypermedia technology is discussed and the seven PEIA modules are described. System maintenance and updating is very easy due to the modular structure and the integrated tool facility provides user access to commercial software shells for documentation, reporting, or database updating. PEIA is expected to provide project engineers with technical information, increase efficiency and productivity, and provide a realistic tool for personnel training.

Lo, Ching F.↗

Design and validation of advanced transonic wings using CFD and very high Reynolds number wind tunnel testing

A study is presented that opens the possibility for further wing aerodynamic technology advances when the test and design environment is at a significantly higher Reynolds number than that used for previous generations of commercial transports. Early generation wings were based primarily on NACA airfoil sections integrated simply into three-dimensional designs. Recently, designs have been developed with a major influence from CFD and have depended less on iterative wind tunnel testing. It is shown that, coupled with improvements in CFD wing modeling and advances in test techniques, additional improvements in wing technology can be realized at significantly higher Reynolds numbers.

Goldhammer, Mark I.↗

Application Of Artificial Intelligence To Wind Tunnels

Report discusses potential use of artificial-intelligence systems to manage wind-tunnel test facilities at Ames Research Center. One of goals of program to obtain experimental data of better quality and otherwise generally increase productivity of facilities. Another goal to increase efficiency and expertise of current personnel and to retain expertise of former personnel. Third goal to increase effectiveness of management through more efficient use of accumulated data. System used to improve schedules of operation and maintenance of tunnels and other equipment, assignment of personnel, distribution of electrical power, and analysis of costs and productivity. Several commercial artificial-intelligence computer programs discussed as possible candidates for use.

Lo, Ching F.↗

Application of intelligent systems to wind tunnel test facilities

An approach to the application of intelligent-systems technology to the wind tunnel facilities at NASA Ames Research Center is outlined. To help fulfill the long-range goals of improving data quality and increasing personnel efficiency and management effectiveness, three major areas of intelligent systems application are recommended. The available state-of-the-art technology for developing the proposed systems is reviewed including the application of commercial software packages. The initial tasks and effort to develop these systems are recommended. A prototype expert system for selection of internal strain-gage balances has been built and is presented herein as an example model for the future systems.

Lo, Ching F.↗