Session: 10-02 Fan and System Optimisation

Paper Number: 152511

Optimization of Centrifugal Fan Design Using Genetic Algorithm and CST Method 

Centrifugal fans used in constrained spaces, particularly in civil aviation ovens, are expected to deliver high performance. Centrifugal fans operate by initially drawing air axially, then redirecting it 90 degrees before it passes through the blades, where it is guided in a spiral pattern. This redirection, coupled with centrifugal forces, significantly influences airflow direction. One notable feature is the higher total pressure they generate, making them ideal for high-pressure applications.

In traditional design approaches, meeting performance expectations often relies on trial-and-error methods and certain dogmatic assumptions. This study aims to identify and optimize the geometric and design parameters that influence the performance of centrifugal fans used in civil aviation ovens. To achieve this, the research integrates parameterization techniques based on the Class-Shape Transformation (CST) method with optimization methods grounded in Genetic Algorithms, complemented by fluid analysis.The optimization process utilized the Class-Shape Transformation (CST) method due to its precision in capturing complex geometries with fewer variables. Numerical simulations were conducted using ANSYS Fluent, and performance data was recorded for further analysis. A communication loop between MATLAB Genetic Algorithm Toolbox and ANSYS Fluent was established, and relevant parameters were defined to conduct the necessary calculations for optimizing the centrifugal fan design.

The optimization study highlights the critical impact of blade design and other parameters on the cost function. In particular, optimizing design parameters is vital for improving performance. These findings serve as a key reference for evaluating the accuracy of models and methods used in fan design, contributing to the development of more efficient systems. Moreover, examining the relationships between different parameters and design features will help to create fan systems that deliver better performance.

Presenting Author: Erkan Bicer Istanbul Technical University

Presenting Author Biography: Erkan Bicer is a Senior Design Engineer with 13 years of experience specializing in product development across aviation, automotive, and electronic industries. A graduate in Metallurgical and Materials Engineering, Erkan is currently pursuing a Master’s degree in Mechatronics Engineering at Istanbul Technical University. For the past six years, he has been a Senior Structural and Cabin Design Engineer at Turkish Airlines, contributing to critical advancements in aviation technology and design.

Authors:

Erkan Bicer Istanbul Technical University
Tufan Kumbasar Istanbul Technical University