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The degrees-of-freedom associated with offshore floating wind turbines (OFWTs) result in a more dynamic flow field. The resulting aerodynamic loads may be significantly influenced by these motions via perturbations in the evolving wake. This is of great interest in terms of OFWT design, placement and simulation. This study presents free vortex wake method(More)
This paper presents a mathematical approach to properly account for uncertainty in wind resource assessment and wind energy production estimation. The evaluation of a wind resource and the subsequent estimation of the annual energy production (AEP) is a highly uncertain process. Uncertainty arises at all points in the process, from measuring the wind speed(More)
A Markov model for the performance of wind turbines is developed that accounts for component reliability and the effect of wind speed and turbine capacity on component reliability. The model is calibrated to the observed performance of offshore turbines in the north of Europe, and uses wind records obtained from the coast of the state of Maine in the(More)
An overview of offshore wind turbine (OWT) foundations is presented, focusing primarily on the monopile foundation. The uncertainty in offshore soil conditions as well as random wind and wave loading is currently treated with a determin-istic design procedure, though some standards allow engineers to use a probability-based approach. Laterally loaded(More)
This paper describes a method of solving the symbolic regression problem using developmental linear genetic programming (DLGP) with an epigenetic hill climber (EHC). We propose the EHC for optimizing the epigenetic properties of the genotype. The epigenetic characteristics are then inherited through coevolution with the population. Results reveal that the(More)
  • Dnyanesh A. Digraskar, DNYANESH A. DIGRASKAR, +4 authors Michael B. Martell
  • 2014
ACKNOWLEDGMENTS I wish to thank my thesis advisor Dr. Blair Perot for all the guidance, advice and support that he has provided during this research. I am especially thankful for his valuable insights, and all his endurance in trying to make me a better researcher. I am also thankful to Dr. Jon McGowan and Dr. Matthew Lackner, for their advice and support(More)
iv ACKNOWLEDGEMENTS I would like to express my sincere gratitude to my thesis advisor, Prof. Blair Perot, for his continuous interest, support and guidance during this study. I am also thankful to Prof. Matthew Lackner and Prof. Ashwin Ramasubramaniam for their advice and help. I specially wish to thank Chris Zusi for the all the support and great(More)
iv ACKNOWLEDGEMENTS I cannot express enough gratitude to Dr. Matthew A. Lackner for all of his support and guidance throughout this research. His mentorship and friendship throughout my time at the University of Massachusetts have been invaluable to me. The impact he has had on my life goes far past academia, and I am forever indebted to him for the(More)