Abstract
Self-Organizing Map (SOM) has been applied to analyze exhaust manifold design solutions obtained during multiobjective optimization using Evolutionary Algorithms. All the numerical data (design variables and the corresponding objective function values) are mapped onto the two-dimensional SOM where global tradeoffs are successfully visualized. SOM is confirmed to be a versatile datamining tool for fluid engineering.
