论文信息 - A computational environment for exhaust nozzle design

A computational environment for exhaust nozzle design

Design Andrew Gelsey and Don Smith (gelsey@cs.rutgers.edu, dsmith@cs.rutgers.edu) Computer Science Department Rutgers University New Brunswick, NJ 08903 Computing in Aerospace 10, San Antonio, TX, March 1995 AIAA-95-1016-CP Copyright c 1995 by Andrew Gelsey and Don Smith. Published by the American Institute of Aeronautics and Astronautics, Inc. with permission. Abstract The Nozzle Design Associate (NDA) is a computational environment for the design of jet engine exhaust nozzles for supersonic aircraft. NDA may be used either to design new aircraft or to design new nozzles that adapt existing aircraft so they may be reutilized for new missions. NDA was developed in a collaboration between computer scientists at Rutgers University and exhaust nozzle designers at General Electric Aircraft Engines and General Electric Corporate Research and Development. The NDA project has two principal goals: to provide a useful engineering tool for exhaust nozzle design, and to explore fundamental research issues that arise in the application of automated design optimization methods to realistic engineering problems. Introduction The Nozzle Design Associate (NDA) is a computational environment for the design of jet engine exhaust nozzles for supersonic aircraft. NDA may be used either to design exhaust nozzles for new aircraft or to design new nozzles that adapt existing aircraft so they may be reutilized for new missions. NDA was developed in a collaboration between computer scientists at Rutgers University and design engineers at General Electric and Lockheed. The NDA project has two principal goals: to provide a useful engineering tool for exhaust nozzle design, and to explore fundamental research issues that arise in the application of automated design optimization methods to realistic engineering problems. Figure 1 shows the NDA software architecture. The search space contains the possible nozzle designs whose performance is evaluated by the simSearch Space Airframe Model Simulator Mission Integrator

[1] Jack D. Mattingly. On-design and off-design aircraft engine cycle analysis computer programs - ONX and OFFX user guide - Developed for use with Aircraft engine design, AIAA Education Series , 1990 .

[2] Eugene Bouchard. Concepts for a future aircraft design environment , 1992 .

[3] Alice M. Agogino,et al. Techniques for integrating qualitative reasoning and symbolic computation in engineering optimization , 1987 .

[4] Philip E. Gill,et al. Practical optimization , 1981 .

[5] J. E. Rogan,et al. The application of artificial intelligence technology to aeronautical system design , 1988 .

[6] D. Smith,et al. A Search Space Toolkit , 1995, Proceedings the 11th Conference on Artificial Intelligence for Applications.

[7] Sanjay Goel,et al. Integration of artificial intelligence and numerical optimization techniques for the design of complex aerospace systems , 1992 .

[8] Jonathan Cagan,et al. Activity Analysis: The Qualitative Analysis of Stationary Points for Optimal Reasoning , 1994, AAAI.

[9] Jaroslaw Sobieszczanski-Sobieski,et al. Structural optimization by multilevel decomposition , 1983 .

[10] A. Peressini,et al. The Mathematics Of Nonlinear Programming , 1988 .

[11] Andrew Gelsey,et al. Intelligent automated quality control for computational simulation , 1995, Artificial Intelligence for Engineering Design, Analysis and Manufacturing.