Fatigue Life Prediction of a Wind Turbine Nacelle
1
Fatigue Life Prediction of a Wind Turbine Nacelle Ryan Mahoney Department of Mechanical Engineering Faculty of Engineering University of Malta Results & Conclusions Results 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. Methodology Procedure 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 Brief Overview 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 Old New c b a d e g f i h
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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
Old
New
cb
a
d e
gf
ih
