Adaptive meta-heuristic to predict dent depth damage in the fixed offshore structures
Issued Date
2018
Resource Type
Language
eng
Rights
Mahidol University
Rights Holder(s)
Taylor & Francis
CRC Press
CRC Press
Suggested Citation
W. Punurai, M.S. Azad, N. Pholdee, C. Sinsabvarodom (2018). Adaptive meta-heuristic to predict dent depth damage in the fixed offshore structures. doi:10.1201/9781351174664-145 Retrieved from: https://repository.li.mahidol.ac.th/handle/20.500.14594/47939
Title
Adaptive meta-heuristic to predict dent depth damage in the fixed offshore structures
Author(s)
Abstract
The jacket structures are often employed in the range of shallow-moderate water depth.
The bracing systems and jacket legs typically use the circular section in order to compromise the hydrodynamic resistance and high torsional rigidity However, under lateral impact, these tabular bracing members
are susceptible to local denting due to ship collisions or through impact of falling objects and that can
weaken overall performance of the entire platform. It is a great significance for forecasting dent depth of
these members accurately. This paper investigates the use of adaptive meta-heuristics algorithm to provide
an automatic detection of denting damage in an offshore structure. A model is developed combining with
the percentage of the dent depth of damaged member diameter and is used to assess the performance of
the method. It is demonstrated that the small changes in stiffness of individual damaged bracing members
are detectable from measurements of global structural motion.
Description
Safety and Reliability – Safe Societies in a Changing World. Proceedings of ESREL 2018, June 17-21, 2018, chapter 145 (pp. 1143-1149). Trondheim, Norway.
Sponsorship
European Union’s Horizon 2020 research and innovation
under the Marie Skłodowska-Curie grant agreement No. 730888.