Posters
Come meet the poster presenters to ask them questions and discuss their work
We would like to invite you to come and see the posters at our upcoming conference. The posters will showcase a diverse range of research topics, and will give delegates an opportunity to engage with the authors and learn more about their work. Whether you are a seasoned researcher or simply curious about the latest developments in your field, we believe that the posters will offer something of interest to everyone. So please join us at the conference and take advantage of this opportunity to learn and engage with your peers in industry and the academic community.
On 9 April at 17:15, we’ll also hold the main poster session and distinguish the 7 best posters of this year’s edition with our traditional Poster Awards Ceremony. Join us at the poster area to cheer and meet the laureates, and enjoy some drinks with all poster presenters!
We look forward to seeing you there!
PO190: A sensitivity study of fatigue life of monopile foundations using long term strain measurements and SCADA data
Ahmed Mujtaba, PhD Student, Vrije Universiteit Brussel
Abstract
This research compares the convergence behavior of different temporal extrapolation techniques for estimating the fatigue life of monopile foundations. The methods analyzed include linear extrapolation, binning extrapolation (1D and 2D), and Random Forest Regression (RF), based on long-term strain measurements (>5 years) and SCADA data from an offshore wind turbine in the Belgian North Sea. Strain measurements at the tower-transition piece interface are statically extrapolated to an arbitrary fatigue critical detail. A sliding window approach with various dataset sizes is used to estimate fatigue life and assess statistical uncertainties. The results show that 2D-binning and RF with two inputs (windspeed and turbulence intensity) converge within 9 months of data, with RF outperforming binning. In contrast, linear extrapolation (0-dimensional) requires 4.5 years for convergence. The effects of starting point of measurement campaign are more prominent for smaller datasets (12 months) in fatigue life estimations. The best-performing model, RF-2D trained with 12 months of data, is used to conduct a sensitivity analysis. This analysis explores the impact of varying Weibull distributions of windspeeds and turbine availability. The results reveal that fatigue life decreases exponentially as the mean windspeed of the Weibull distribution increases. Fatigue life increases linearly with greater turbine non-availability, which is quantified by the probability that the turbine is not producing power due to Fault, Idling, or Parked (FIP) conditions above cut-in and below cut-off windspeeds. These findings offer valuable insights into how fatigue life is affected by both measured and designed windspeeds and turbine availability.
No recording available for this poster.
