Advanced aerospace composite material structural design using artificial intelligent technology
Due to the complexity in the prediction of property and behavior, composite material has not substituted for metal widely yet, though it has high specific-strength and high specific-modulus that are more important in the aerospace industry. In this paper two artificial intelligent techniques, the expert systems and neural network technology, were introduced to the structural design of composite material. Expert System which has good ability in symbolic processing can helps us to solve problem by saving experience and knowledge. It is, therefore, a reasonable way to combine expert system technology to tile composite structural design. The development of a prototype expert system to help designer during the process of composite structural design is presented. Neural network is a network similar to people`s brain that can simulate the thinking way of people and has the ability of learning from the training data by adapting the weights of network. Because of the bottleneck in knowledge acquisition processes, the application of neural network and its learning ability to strength design of composite structures are presented. Some examples are in this paper to demonstrate the idea.
- National Cheng Kung Univ., Tainan (Taiwan, Province of China). Dept. of Mechanical Engineering
- Chung Shan Institute of Science and Technology, Lung-Tan (Taiwan, Province of China)
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ISBN 0-87339-251-5; TRN: IM9413%%116
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- Conference: Advanced composites `93: international conference on advanced composite materials (ICACM), Wollongong (Australia), 15-19 Feb 1993; Other Information: PBD: 1993; Related Information: Is Part Of Advanced composites 1993; Chandra, T. [ed.] [Univ. of Wollongong (Australia)]; Dhingra, A.K. [ed.] [DuPont, Wilmington, DE (United States)]; PB: 1464 p.
- Minerals, Metals and Materials Society, Warrendale, PA (United States)
- Country of Publication:
- United States
- 36 MATERIALS SCIENCE; COMPOSITE MATERIALS; FABRICATION; EXPERT SYSTEMS; TECHNOLOGY ASSESSMENT; ARTIFICIAL INTELLIGENCE