Date of Award

Fall 11-2014

Access Type

Thesis - Open Access

Degree Name

Master of Science in Aerospace Engineering

Department

Aerospace Engineering

Committee Chair

Sathya Gangadharan

First Committee Member

R.R. Mankbadi

Second Committee Member

Mark Ricklick

Abstract

The main purpose of this thesis is to conduct a parametric sensitivity study on the blade design of AOC 15/50 wind turbine based on a CFD approach and optimize the blade design for maximizing the power output. The ANSYS® Fluent® flow solver using the k-ω SST turbulence model was validated by simulating the flow over two dimensional airfoils comprising the AOC 15/50 wind turbine blade. The CFD results have shown a considerable agreement with the experimental data for the airfoils. Parametric correlation study and sensitivity analysis were conducted by performing actual flow simulations over the turbine blade using ANSYS® Fluent®. This illustrates the dependence of power output on the blade design parameters. Parametric correlation study reveals that the blade design variables on the outer 40% of the blade span have a predominant effect on the power output of the blade, while the obtained scatter plots and determination matrix indicate the blade optimization problem setup as non-linear and quadratic fit. The most sensitive design parameters are used to formulate the flow optimization problem. A response surface optimization (RSO) methodology is employed for carrying out the blade shape optimization process. Design of Experiments (DoE) using the Latin Hypercube Sampling (LHS) algorithm is used to construct a robust response surface model, which is then searched for the optimized design using the Nonlinear Programming by Quadratic Lagrangian (NLPQL) technique. Two optimization routines are carried out by varying the geometric constraints on the blade. First optimization routine constrained the blade length and maximum chord occurring at a 40% span location from the hub to be fixed, yielding a design that performs marginally well up to the wind speed of 9.2 m/s with a maximum power increment of 7.55 % occurring at the 8.03 m/s wind speed. The search for the second optimization routine was initialized in the design space with the best candidate point obtained from the first optimization routine. Second optimization routine generated a design configuration that resulted in an increased blade length and surface area, thus leading to an overall lift force augmentation producing a 25.26% increase in the power output. Both the optimized candidates obtained were validated using the flow solver to verify the optimized design for maximized power output. The coefficient of pressure plots at various span locations of the blade bolster the claim that most of the mechanical power is produced in the outer 30-40% of the blade.

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