Date of Award
Fall 12-2005
Document Type
Thesis - Open Access
Degree Name
Master of Science in Aerospace Engineering
Department
Aerospace Engineering
Committee Chair
Vladimir V. Golubev
Committee Member
Hany Nakhla
Committee Member
Eric Perrell
Abstract
The objective of the investigation is the development of more efficient design methodologies based on the applications of established design tools including Computational Fluid Dynamics (CFD) and non-linear Multidisciplinary Design Optimization (MDO) algorithms. Well known evolutionary type optimization algorithms include the Particle Swarm Optimization (PSO), Response Surface Optimization (RSO) and Genetic (GA) Algorithms. The benchmark case study is the optimal design of a low speed fan for an industrial air-conditioning application using the Response Surface Optimization (RSO) algorithm.
The optimization algorithm controls the variations of parameters that describe the three-dimensional geometry of the blade while applying performance and geometrical constraints on blade shapes that are investigated. The optimal design is defined as the blade geometry which produces the maximum total efficiency subject to specified constraints on the volume flow rate (CFM) and rotational rate (RPM) of the fan.
Scholarly Commons Citation
Idahosa, Uyi O., "An Automated Optimal Design of a Fan Blade Using an Integrated CFD/MDO Computer Environment" (2005). Master's Theses - Daytona Beach. 310.
https://commons.erau.edu/db-theses/310
