This study proposes new methods for the reliability-based design of structural systems, with emphasis on offshore mooring systems. After a brief introduction to the mooring systems, two main objectives are discussed in this dissertation.
The first objective is the calculation of the probability of failure of a structural system, which is an important input for a reliability-based design or any quantitative risk assessment. Two different methods are proposed for calculation of the probability of failure: a method based on the Monte Carlo simulations and a method based on the basic rules of probability, which is called the Progressive Reliability Method (PRM). Both methods are flexible to the definition of system failure. For example, the probability of a serviceability or ultimate-strength failure can be assessed using any of the two methods. It is shown that the two methods produce similar results, but PRM is preferred because it is exact and usually faster to implement.
The second main objective in this dissertation is to develop a method for the optimization of the design of a structural system, given a target probability of failure. In this method, using the structural analysis of a preliminary design, the ratio of the optimal to the preliminary mean capacity of each component, which is called the Optimality Factor, is determined. Two design strategies are considered. First, an optimal design is intended to achieve the maximum system integrity. System integrity is defined as the balanced contribution of system components to its reliability. To quantify the system integrity, the Integrity Index is defined, and its calculation for various systems is discussed. Second, a designated failure scenario is considered, where some components serve as a fuse to protect some other components. This design strategy is especially applicable to mooring systems with drag anchor foundations because normally, if a drag anchor is pulled out from the seabed, it can cause significant damages to nearby subsea facilities. Using the rules of probability, a method is then developed to calculate the optimality factor of each component.
Identifer | oai:union.ndltd.org:tamu.edu/oai:repository.tamu.edu:1969.1/149292 |
Date | 02 October 2013 |
Creators | Mousavi, Mir Emad |
Contributors | Gardoni, Paolo, Aubeny, Charles, Falzarano, Jeffrey, Jones, Harry, Murphy, Colleen |
Source Sets | Texas A and M University |
Language | English |
Detected Language | English |
Type | Thesis, text |
Format | application/pdf |
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