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A Methodology for Tuning of Computational Vessel Models Utilizing Wave Measurements From X-Band Marine Radar and Wave Buoy

Abstract

Accurate estimation of the wave field and subsequent vessel response prediction are vital for making crucial judgments on the safe and timely execution of marine operations. Decision support systems based on the Response-Based Decision-Making (RBDM) methodology are still in the early stages due to the challenges in addressing the uncertainties in the environmental conditions and vessel computational models. Therefore, this study offers a model tuning technique that utilizes the waves measured from an onboard X-band wave radar, wave buoy, and simultaneously measured vessel motions using an Inertial Measurement Unit (IMU), for applications in RBDM. For this purpose, full-scale wave and vessel response measurements were conducted using the NTNU research vessel Gunnerus on the west coast of Norway. The on-site directional wave spectra are obtained by processing the backscattered radar images using existing inversion schemes. Furthermore, the directional wave spectra are also derived from the nearby wave buoy measurements using the Maximum Entropy Method (MEM). The influential system variables in the vessel model that induce maximum variation to the response Quantities of Interest (QoIs) are quantitatively identified using probabilistic sensitivity indices. Out of the 31 system variables, only 14 were considered influential and subsequently tuned by minimizing the error between the measured and simulated response spectra. Heave, roll, and pitch modes were tuned and results exhibit superior agreement with the measured response spectra.
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Category

Academic chapter

Language

English

Author(s)

  • Gowtham Radhakrishnan
  • Bernt Johan Leira
  • Zhen Gao
  • Svein Sævik
  • Karl Erik Kaasen
  • Konstantinos Christakos
  • Johann Alexander Dirdal

Affiliation

  • SINTEF Ocean / Skip og havkonstruksjoner
  • Norwegian University of Science and Technology
  • Shanghai Jiao Tong University
  • Norwegian Meteorological Institute (MET Norway)

Year

2023

Publisher

The American Society of Mechanical Engineers (ASME)

Book

ASME 2023 42nd International Conference on Ocean, Offshore and Arctic Engineering : Volume 5 : Ocean Engineering

ISBN

9780791886878

View this publication at Norwegian Research Information Repository