Automated Design Synthesis of Structures using Growth Enhanced Evolution

Author: Nicaise, Fabien

Year: 2008

Degree: Dissertation (Ph.D.)

Advisor: Antonsson, Erik K.

Committee Members: Antonsson, Erik K.; Adami, Christoph Carl; Burdick, Joel Wakeman; Pickar, Kenneth A.

Option: Mechanical Engineering

Abstract

Engineering design is a complex problem on generating and evaluating a variety of options. In traditional methods, this typically involves evaluating up to a dozen different point designs. The limit on the process is the amount of time to generate, refine, and evaluate the various concepts. Using a computer helps to speed up the process, but human involvement still remains the weakest link.

The natural extension of this process is to continually and rapid generate, refine, and evaluate concepts entirely automatically. Evolutionary Algorithms provide such a method, by emulating natural evolution. The computer maintains a population point design, each of which is represented by a gene string that is allowed to change (mutate) and combine with other genes (crossover). At each generation, every individual is modified then evaluated and the improved solutions proceed to the next generation.

This thesis will extend the biological model by introducing a growth process to each individual. This is akin to the concept of a multi-cellular organism developing in the womb. An encoding for discrete truss structures is described that provides for such an extension. The truss grows from a few basic elements. After showing several examples demonstrating the growth process, the method is applied to a couple simple examples using evolutionary algorithms.

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