Date of Award

Spring 2011

Document Type

Thesis

Degree Name

Master of Science (MS)

Department

Mechanical & Aerospace Engineering

Program/Concentration

Mechanical Engineering

Committee Director

Miltiadis Kotinis

Committee Member

Gene J.-W. Hou

Committee Member

Sushil Chaturvedi

Call Number for Print

Special Collections; LD4331.E56 K825 2011

Abstract

The design of transonic airfoils for civil aviation applications has been a major engineering challenge in the last fifty years. This design problem arises due to the need to limit shock wave drag at a given transonic speed. In recent years, the requirement to reduce the levels of aircraft noise has started to affect the airfoil design process. The multidisciplinary aerodynamic shape optimization problem is treated in this thesis using a multi-objective approach. The objectives correspond to the design of transonic airfoil sections with low drag during cruise and low trailing edge noise levels during the approach condition. The optimization problem was solved using the ACMOPSO algorithm, which is based on swarm intelligence. Computational intelligence tools, e.g., artificial neural networks, were also utilized to create surrogate models for the objective functions and constraints of the optimization problem. The parameterization of the airfoil shape was done using cubic B-splines. The flow analysis was performed using the commercial CFD software FLUENT. The results demonstrate the effectiveness and efficiency of the proposed optimization framework when applied to multidisciplinary design optimization problems.

Rights

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DOI

10.25777/4m9j-9k97

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