Fuzzy based models for estimating static contact angle and sliding angle of liquid drops

Abstract

Prediction of the contact angles and sliding angles of liquid drops is so difficult, because the interaction among the variables, which have impact on the angles, is so complex. Therefore, in this paper fuzzy logic was used to develop prediction models. Experimental sliding angle and contact angles of liquid drops on the metal samples with several surface treatments were divided into training data and testing data. By using the knowledge, which was extracted from the training data and experience of authors, the effective if-then rules were developed. Then, the weight of the rules was optimized by particle swarm optimization. The obtained results for testing data by using proposed Fuzzy_CA and Fuzzy_SA models showed that the regression index for the contact angles and sliding angles were 0.9970 and 0.9980, respectively. It means that the predicted angles are so close to measured angles and the proposed fuzzy based models are so reliable.