STATISTICAL PARAMETERS OF STEEL TUBULAR MEMBER DESIGN FOR OFFSHORE PLATFORMS IN MALAYSIA

• Main Authors: B. Idrus, Arazi, Sambu Potty, Narayanan, Hamid, M.F.A, Nizamani, Zafarullah, J. Cossa, Nelson
• Format: Conference or Workshop Item
• Published: 2011
• Subjects: TA Engineering (General). Civil engineering (General)
• Online Access: http://eprints.utp.edu.my/6893/1/rp015-icsas11.pdf; http://eprints.utp.edu.my/6893/
• Institution: Universiti Teknologi Petronas

The exploration and production of oil and gas in offshore industry of Malaysia is conducted by, mainly, means of jacket platforms. These are tridimensional frames formed by welding steel tubular members, which support the exploration and production facilities. The design of these structures follows working stress design (WSD) methods. However, the development of reliability analysis of structures has lead to the adoption of load and resistance factors design (LRFD) of structural systems, including in the offshore structures. The globalization of the oil and gas industry, and the need to provide a harmonized code for design, resulted in the publication of the International Standard Organization (ISO) design practice, which is LRFD based. The LRFD design method introduces load and resistance factors calibrated to produce uniform reliability levels. The adoption of this code requires the calibration of the loads and resistance factors that represent the local environmental conditions. As part of an ongoing work on the reliability based calibration of load and resistance factors for design of jacket platforms in Malaysia, this paper presents the statistical parameters of the geometrical and material properties of the tubular members of platforms fabricated and installed in Malaysia. These geometrical and material properties constitute the basic variables which influence the randomness of the resistance of the members. The results were compared with the literature and validity check was also conducted. The results were checked for goodness-of-fit tests at 5 percent significance level.