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Inducing constraint activity in innovative design

Published online by Cambridge University Press:  27 February 2009

Jonathan Cagan  and
Alice M. Agogino
Jonathan Cagan
Affiliation:
Department of Mechanical Engineering, Carnegie Mellon University, Pittsburgh, PA 15213, U.S.A.
Alice M. Agogino
Affiliation:
Department of Mechanical Engineering, University of California at Berkeley, Berkeley, CA 94720, U.S.A.
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Abstract

In this paper, a methodology for inducing trends in a first principle reasoning system for design innovation is presented. Dimensional Variable Expansion is used in 1stPRINCE (FIRST PRINciple Computational Evaluator) to create additional design variables and introduce new prototypes. Trends are observed at each generation of the prototype and induction is used to predict optimal constraint activity at the limit of the iterative procedure. The inductive mechanism is applied to a constant-radius beam under flexural load and a tapered beam of varying radius and superior performance is derived. A circular wheel is created from a primitive-prototype consisting of a rectangular, spinning block that is optimized for minimum resistance to spinning. Although presented as a technique to perform innovative design, the inductive methodology can also be utilized as an AI approach to shape optimization.

Information

Type
Research Article
Information
AI EDAM , Volume 5 , Issue 1 , February 1991 , pp. 47 - 61
Copyright
Copyright © Cambridge University Press 1991

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