Date of Award

5-2013

Degree Name

MS in Mechanical Engineering

Department/Program

Mechanical Engineering

Advisor

Patrick Lemieux

Abstract

Structural dynamics is at the center of wind turbine tower design - excessive vibrations can be caused by a wide range of environmental and mechanical sources and can lead to reduced component life due to fatigue, noise, and impaired public perception of system integrity. Furthermore, periodic turbulent wind conditions can cause system resonance resulting in significantly increased structural loads. Structural vibration issues may become exacerbated in small wind applications where the analytical and experimental resources for system verification and optimization are scarce. This study combines several structural analysis techniques and packages them into a novel and integrated form that can be readily used by the small wind community/designer to gain insight into tower/rotor dynamic interaction, system modal characteristics, and to optimize the design for reduced tower loads and cost. The finite element method is used to model the tower structure and can accommodate various configurations including fixed monopole towers, guy-wire supported towers, and gin-pole and strut supported towers. The turbine rotor is modeled using the Equivalent Hinge-Offset blade model and coupled to the tower structure through the use of Lagrange’s Equations. Standard IEC Aeroelastic load cases are evaluated and transient solutions developed using the Modal Superposition Method and Runge-Kutta 4th order numerical integration. Validation is performed through comparisons to theoretical closed form solutions, physical laboratory test results, and peer studies. Finally a case study is performed by using the tool to simulate the Cal Poly Wind Power Research Center Wind Turbine and Tower System. Included in the case study is an optimization for hypothetical guy-wire placement to minimize tower stresses and maximize the tower’s natural frequency.

Award received:

Outstanding Thesis Award

Share

COinS