ENHANCED COMPUTATIONAL STRUCTURAL METHODS FOR AEROSPACE APPLICATIONS

TWO METHODOLOGIES FOR INCREASING THE EFFICIENCY AND EFFECTIVENESS OF COMPUTER ANALYSIS OF AEROSPACE STRUCTURES WILL BE ADDRESSED. THE APPROACH INCORPORATES FUNCTIONAL-LINK, NEURAL-NET TECHNOLOGY FOR GENERALIZATION OFQUANTITATIVE ANALYSIS RESULTS (SO AS TO CIRCUMVENT THE NEED FOR EXTENSIVE, TIME-CONSUMING REANALYSIS) AND EPISODAL ASSOCIATIVE MEMORY FOR CAPTURING DESIGN EXPERIENCE TO GUIDE CREATION OF SUBSEQUENT DESIGNS DEVELOPED BY THE FIRM. THE FUNCTIONAL-LINK NET METHODOLOGY IS A NEURAL-NET TECHNOLOGY THAT IS PARTICULARLY USEFUL FOR LEARNING FUNCTIONAL RELATIONSHIPS, PROVIDING ACCURATE QUANTITATIVE ESTIMATES IN RESPONSE TO DESIGNS, AND COVERGING IN ON OPTIMAL DESIGNS. THE EPISODAL ASSOCIATIVE MEMORY IS A COMPUTER ARCHITECTURE FOR ORGANIZING AND STORING EXPERIMENTAL KNOWLEDGE THAT CAN BE RETRIEVED ASSOCIATIVELY IN RESPONSE TO NEW TASKS. THIS ADDITIONAL FUNCTION CAN BE EFFECTIVE IN DIRECTING THE CREATION AND ANALYSIS OF A NEW DESIGN. TWO METHODOLOGIES FOR INCREASING THE EFFICIENCY AND EFFECTIVENESS OF COMPUTER ANALYSIS OF AEROSPACE STRUCTURES WILL BE ADDRESSED. THE APPROACH INCORPORATES FUNCTIONAL-LINK, NEURAL-NET TECHNOLOGY FOR GENERALIZATION OFQUANTITATIVE ANALYSIS RESULTS (SO AS TO CIRCUMVENT THE NEED FOR EXTENSIVE, TIME-CONSUMING REANALYSIS) AND EPISODAL ASSOCIATIVE MEMORY FOR CAPTURING DESIGN EXPERIENCE TO GUIDE CREATION OF SUBSEQUENT DESIGNS DEVELOPED BY THE FIRM. THE FUNCTIONAL-LINK NET METHODOLOGY IS A NEURAL-NET TECHNOLOGY THAT IS PARTICULARLY USEFUL FOR LEARNING FUNCTIONAL RELATIONSHIPS, PROVIDING ACCURATE QUANTITATIVE ESTIMATES IN RESPONSE TO DESIGNS, AND COVERGING IN ON OPTIMAL DESIGNS. THE EPISODAL ASSOCIATIVE MEMORY IS A COMPUTER ARCHITECTURE FOR ORGANIZING AND STORING EXPERIMENTAL KNOWLEDGE THAT CAN BE RETRIEVED ASSOCIATIVELY IN RESPONSE TO NEW TASKS. THIS ADDITIONAL FUNCTION CAN BE EFFECTIVE IN DIRECTING THE CREATION AND ANALYSIS OF A NEW DESIGN.