RAMANA M. PIDAPARTI
Virginia Commonwealth University, Mechanical Engineering, 601 West Main Street, Richmond, VA 23284, USA
MATHEW J. PALAKAL
Indiana University, Purdue University Indianapolis (IUPUI), Computer and Information Science, 723 W. Michigan Street, Indianapolis, IN 46202, USA
LONG FANG
Indiana University, Purdue University Indianapolis (IUPUI), Computer and Information Science, 723 W. Michigan Street, Indianapolis, IN 46202, USA

Received 14 July 2004
Revised 3 December 2004

Corrosion is one of the degrading mechanisms that greatly affect the structural integrity of aerospace components. Corrosion begins with small imperfections in the given material referred to as "pits". Over time, and with exposure to the environment and loading stresses, these pits grow into structural cracks. These cracks, under further exposure to elements and stress, will eventually lead to material failure. To better understand how corrosion growth process takes place in materials, research is being conducted to simulate corrosion pit growth process using computational intelligence methods. The objective of this study is to develop a discrete dynamic model using cellular automata to simulate the pitting corrosion growth process in aircraft materials, and see how it affects the structural integrity.

Corrosion; artificial intelligence; cellular automata; feature extraction; computational intelligence