Measuring and modelling towline responses using GPS aided inertial navigation

Rights statement
Awarding institution
  • University of Strathclyde
Date of award
  • 2017
Thesis identifier
  • T15304
Person Identifier (Local)
  • 200885069
Qualification Level
Qualification Name
Department, School or Faculty
  • The offshore towage of large floating structures has been the broad subject of research since the 1960’s. The selection of a tug to engage in a tow is based on rules laid down by class and marine warranty surveyors derived from years of experience but a rigorous assessment of these rules based on a comprehensive real world datasets has not been possible. This is principally due to the nature of these tows, usually employing tugs chartered at short notice from the spot market, the long towline lengths when under tow and the high value of the tow itself. Given the commercial implications in being able to better match a suitable tug to any given tow, this research lays down the requirements of an ideal dataset, i.e. one that has a record of towline tensions, complete 6DOF of both the tug and tow all recorded to a universal timeline, along with the seastate experienced by the tow at any given point. It then reviews the historical restrictions in gathering this data and that the key issue has been gathering the motions of the unpowered tow and recording the towline tensions.A methodology is then developed which requires no interference with the towline and draws upon Kalman filters for optimal state estimation of the tug and tow’s position and attitude in 3D space driving a lumped mass simulation of the towline coded in MatLab. The stiffness properties of key elements of the towline are assessed by FEA and observations made on areas where normal industry practice’s may be lacking. Observations on advances in sensor technology as well as other areas for development are then made that provide fertile areas for further research. Finally the full code base for a MatLab, lumped mass simulator is presented in an appendix for future use.
Advisor / supervisor
  • Incecik, A.
Resource Type