부산대학교 도서관

This paper deals with an experimental investigation of roughness influence on contact angle measurements and proposes a genetic algorithm to identify an empirical regression model to combine roughness and contact angles. A ns-pulsed laser was adopted to ablate different patterns on the surfaces of AISI 304 samples. During the tests, number of repetitions, hatch distance, laser scan speed and laser scanning strategy were changed. To assess the effect of these parameters on the wettability, a multilevel factorial design was developed and tested. The analysis of variance was adopted to determine which and how the laser parameters influence the roughness and the contact angle. A significant change in the wettability is due to the produced textures on the sample surfaces, with contact angles in the range 30–110°. The optimal regression model based on genetic algorithms was able to relate inputs and outputs with a mean error lower than 5%. [ABSTRACT FROM AUTHOR]