A comparative study between artificial neural network and linear regression for optimizing a hinged blade cross axis turbine

College

Gokongwei College of Engineering

Department/Unit

Mechanical Engineering

Document Type

Conference Proceeding

Source Title

8th International Conference on Humanoid, Nanotechnology, Information Technology, Communication and Control, Environment and Management, HNICEM 2015

Publication Date

1-25-2016

Abstract

In this paper a quantitative model was used to optimize the power output of a hinged blade cross axis turbine using different blade configuration. With the following parameters; number of blades, length of blades, thickness of blade, angle of blade, and foil shape. The data was collected on actual experiments using the newly design and built (RS/HTTP) River-flow simulator/ Hydrokinetic Turbine Testing Platform. The artificial Neural Network and Linear regression analysis are used to model the fitness function. In order to calculate the different blade combination resulting power output and find the optimize configuration. The result and data that was gathered between the two models was compared and analyzed. © 2015 IEEE.

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Digitial Object Identifier (DOI)

10.1109/HNICEM.2015.7393225

Disciplines

Mechanical Engineering

Keywords

Turbines—Blades; Turbines—Testing; Neural networks (Computer science)

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