Fatigue Life Prediction of a Wind Turbine Nacelle

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Exhibition poster for my dissertation to achieve my BEng (Hons) in Mechanical Engineering

Transcript of Fatigue Life Prediction of a Wind Turbine Nacelle

Fatigue Life Prediction of a Wind

Turbine Nacelle

Ryan Mahoney Department of Mechanical Engineering

Faculty of Engineering

University of Malta

Results & ConclusionsResults and Observations

Only location 4 fell short of the 20 year

benchmark which small wind turbines are

designed for. It is a non-standard

unclassified weld, thus using a standard

one would solve this problem. The new

geometry (Figure h) of the nacelle model

including the new location of the yaw

shaft, caused stresses to be more

localised on one side of the nacelle and

higher concentrations were noted.

However, at no point were either the

allowable design strength or yield stress

of the material exceeded. It was observed

that for 44% of the time, the wind turbine

would be at a standstill.

MethodologyProcedure Adopted

The locations prone to fatigue were first

established (Figures a - c). Wind data

obtained from anemometers was

interpreted in terms of fatigue loads

acting on the nacelle model and were

simulated in FEA to establish the stress-

range history for each location (Figures -

g). The results of the rainflow counter

algorithm, together with the relative S-N

curves, were used in collaboration with

Miner’s Rule to predict the fatigue life for

each location.

Project BriefOverview and Objective

Fatigue damage has been the cause of various catastrophes over the years and is often termed by

experts as ‘the silent killer’. There is therefore a huge demand for effective and feasible methods to

predict the fatigue life of structures and components. The conversion of the Chicago-type Wind Pump in

Ghammieri to a wind turbine is a project by the University of Malta. From previous dissertations, it was

concluded that a fatigue life assessment should be carried out on the nacelle structure. Due to the lack

of equipment (such as sensors) and available data at the time of this dissertation, the fatigue life

prediction had to be based solely on raw wind data.

Supervised by: Dr. Martin Muscat

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