Please use this identifier to cite or link to this item: https://scholarbank.nus.edu.sg/handle/10635/33370
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dc.titleSystem identification of jack-up platform
dc.contributor.authorWANG XIAOMEI
dc.date.accessioned2012-05-31T18:02:56Z
dc.date.available2012-05-31T18:02:56Z
dc.date.issued2011-07-05
dc.identifier.citationWANG XIAOMEI (2011-07-05). System identification of jack-up platform. ScholarBank@NUS Repository.
dc.identifier.urihttp://scholarbank.nus.edu.sg/handle/10635/33370
dc.description.abstractAs demands for offshore exploration and production of oil and gas continue to increase, structural health monitoring of offshore structures has become increasingly important for mainly two reasons: (a) validating modeling and analysis, and (b) providing timely information for early warning and damage detection. Implementation of system identification using the measured signals will result in significant gains in safety and cost-effectiveness of design and maintenance. However, there is no known effective strategy for global system identification of offshore structures. Thus the main objective of this research is to develop robust and effective identification strategies for offshore structures with focus on jack-up platforms that have been widely used in shallow waters. As an illustration example, system identification of jack-up platform is studied in this research. The study involves the use of substructural identification (Sub-SI) and Genetic Algorithms (GA) method. Modeled by finite element method, dynamic analysis of jack-up platform is studied. Considering the critical parts, a single leg is studied and divided into two substructures. One of the challenges is that initial conditions are not necessarily known and need to be addressed in time domain method. Alternatively, spectral analysis can be used and thus a frequency domain method is also developed. Taking a jack-up platform in the North Sea as an example, complete structural analysis and substructural analysis are carried out in time domain and in frequency domain for validation which will be needed in the forward analysis used in GA-based system identification. On the basis of Sub-SI and GA method, time domain and frequency domain identification methods are developed to address the multiple challenges involved in system identification of offshore platform, including unknown wave loading, unknown initial conditions, unknown hydrodynamic effects and unknown support fixity. The proposed strategies are developed as output-only methods and applicable to deal with unknown initial conditions. With hydrodynamic coefficients and Rayleigh damping coefficients as unknown parameters, identification of leg stiffness and spudcan fixity is the central point of this research. The numerical simulation results show that structural stiffness can be accurately identified even with noisy effects. By identifying structural stiffness changes, damage detection is also performed with good accuracy. To further substantiate the proposed methods, an experimental study is carried out for a small-scale jack-up model supported on a particular design with springs and bearings. The focus of this partial verification study is on the identification of support fixity. Preliminary tests are conducted to verify the experimental model, and dynamic tests using linear and angular sensors show that the support fixity can be well identified by the proposed methods in time domain and frequency domain. Therefore, the proposed identification strategies are effective and applicable to offshore jack-up platform which should sever as useful non-destructive methods for existing platforms in offshore industry.
dc.language.isoen
dc.subjectSystem Identification, Jack-up Platform, Genetic Algorithms, Dynamic Analysis, Time Domain, Frequency Domain
dc.typeThesis
dc.contributor.departmentCIVIL & ENVIRONMENTAL ENGINEERING
dc.contributor.supervisorKOH CHAN GHEE
dc.description.degreePh.D
dc.description.degreeconferredDOCTOR OF PHILOSOPHY
dc.identifier.isiutNOT_IN_WOS
Appears in Collections:Ph.D Theses (Open)

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