Analysis & Modification of Axial Flow Fan Blades for Improvement in Air Velocity

Abstract

Axial flow fans, while incapable of developing high pressure, they are well suited for handling large volumes of air at relatively low pressure. An attempt has been made to modify the design of fan blade by applying Computational Fluid Dynamics (CFD) analysis and Response Surface Methodology (RSM) which has been optimized by Genetic Algorithm (GA). The suitability of FLUENT for this work has been established by experimental work available in literature. Same method has been used to predict the velocity of existing fan blade. The result of which is in good agreement with the result obtained experimentally. Process parameters such as cross section, angle, hub diameter and speed of rotation of fan blade play a major role in deciding the velocity output. In present study, four factors, five level central composite design has been used to minimize number of experimental conditions. Response Surface Method (RSM) has been used to develop the second degree model. Adequacy of developed model has been calculated by statistical tool analysis of variance (ANOVA) and validated by Chi square test. Since the response surface has been derived from regression fit, conformation experiments have been performed to verify validity of model. Further velocity has been optimized using genetic algorithm (GA), which gives maximum value of air velocity and their respective optimal conditions.