Design optimization of jacket offshore platform considering fatigue damage using Genetic Algorithm
Introduction
The steel jacket platforms are one of the most common kinds of fixed offshore structures worldwide. About 95% of the offshore platforms in the world are using jacket platforms (Fu, 2018). Due to the considerable volume of materials used in the jacket platforms, structural optimization could remarkably reduce their investment. Satisfying various constraints such as stress ratio, maximum displacement, and fatigue life, the structural optimization aims at minimizing an objective function, which is usually the weight of the structure. Since a majority of the reported failures in the lifetime of offshore structures are fatigue failures, fatigue life is one of the major concerns in the design and optimization of offshore structures.
Considering various variables and objective functions, researchers performed many studies on the optimization of diverse offshore structures (Zhang et al., 2018; Deng et al., 2020). Different methods and algorithms such as Cyclical Parthenogenesis Algorithm (CPA) (Hosseini and Zolghadr, 2017), Particle Swarm Optimization Algorithm (PSO) (Häafele and Rolfes, 2016), Colliding Bodies Optimization Algorithm (CBO) (Kaveh and Sabeti, 2018), and Enhanced Colliding Bodies Optimization (ECBO) (Kaveh and Sabeti, 2019) were also examined to optimize offshore structures. Employing the three methods of Sequential Quadratic Programming (SQP), Genetic Algorithm (GA), and Adaptive Simulated Annealing (ASA), Birk et al. (2004) studied the objective functions for the downtime of a semisubmersible and fatigue damage of Tension-Leg Platform (TLP) tethers in irregular random waves. Among different algorithms, researchers and engineers have always used the Genetic Algorithm as a powerful tool for the optimization of offshore platforms (Ni and Ge, 2019). Using a Genetic Algorithm, Nasseri et al. (2014) made an effort to optimize an offshore platform by reducing its weight to an overall minimum value. The constraints of their problem included the design criteria for stress, buckling, and displacement, while the outer diameter and thickness of the structural members of the jacket were considered as decision variables. In order to optimize offshore structures, studies have also focused on their shape optimization, including the slope of their legs (Mohammad Nejad et al., 2010). Moreover, many researchers have investigated the topology optimization of these structures over recent years (Tian et al., 2019). Abou El-Makarem et al. (2019) topologically optimized a standard jacket platform under earthquake loading in the Gulf of Suez. They did not take the other types of pre-service and in-service loading, such as environmental loading and fatigue, into consideration. Given the presence of cyclic forces caused by waves, winds, and ocean currents in the seas, the phenomenon of fatigue is of crucial importance in the design of offshore platforms, which has widely been studied in recent years (Hammerstad et al., 2016; Ju et al., 2019). In this regard, Shabakhty and Khansari (2019) obtained the failure caused by fatigue in platform connections according to the simulation of the force of linear and nonlinear random waves using the energy spectrum and Morison equation. The fatigue has also been of interest in the optimization of offshore structures. Oest et al. (2017) carried out a study on developing and implementing an effective method for gradient-based sizing optimization of a support structure for offshore wind turbines. In this method, the diameter and thickness of the structural members were optimized, considering the fatigue and ultimate limit constraints. Chew et al. (2016) proposed a gradient-based optimization method for the design of support structures in offshore wind turbines. Their method imposed a comprehensive range of design controls on different constraints, including the sizing, eigenfrequencies, extreme load, and fatigue load. Considering requirements on natural frequencies, strength, and fatigue lifetime, Stolpe and Sandal (2018) applied a structural optimization method with multiple discrete variables per part to size optimization of the tubular members in an offshore wind turbine jacket support structure.
A review of the literature revealed that despite various studies on the fatigue and optimization of offshore platforms, it is critical to examine whether considering the fatigue as a constraint in the optimization results is effective or not. In this study, two optimizations were carried out for the SPD19A platform, located in the South Pars field in the Persian Gulf. This real model was positioned in the 100-year storm conditions subjected to the environmental loads at 100-year maximum still water depth, concerning all engineering considerations mentioned in the project report (SPD19A Structural design basis, 2011). The SACS (SACS user's manual, 2010) finite element software was used for in-place and fatigue analysis of the platform against environmental loads imposed from eight geographical directions. The optimization process was conducted by a continuous Genetic Algorithm programmed in the MATLAB software.
Section snippets
Optimization problem
The goal of the problem in this research was to achieve an optimum design for the geometric properties of the sections of the SPD19A platform jacket's structural members, by taking the fatigue damage impact into account. In the following sections, the components of the optimization problem, including objective function, decision variables, constraints, and fitness function, are discussed individually.
SPD19A platform
The jacket platform studied in this paper is SPD19A. This platform is located in the 19th phase of the South Pars field in the Persian Gulf and has the overall deck dimensions of 32.5 m × 27.5 m shown in Fig. 2(a). (SPD19A Structural design basis, 2011). Various equipment, such as piping, sources, and instrumentation, along with mechanical, electrical, safety, and firefighting equipment, were included, but for simplicity, they were not modeled. However, their weights were added to the
Design optimization of the jacket platform
As fatigue analysis is time-consuming, considering fatigue damage as a constraint can substantially extend the optimization time. Therefore, it is critical to evaluate whether considering fatigue damage as a constraint is effective in the optimization results or not.
To evaluate the impact of fatigue damage in the optimization of SPD19A, two optimizations were performed using a continuous Genetic Algorithm with the same specifications shown in Table 1. The first optimization, referred as
Conclusion
In this research, a real jacket-type platform, namely SPD19A, located in the South Pars field, the Persian Gulf, was optimized by two optimizations scenarios using a continuous Genetic Algorithm. The jacket platform was positioned in the extreme storm conditions subjected to environmental forces of the sea. The outer diameter and thickness of the jacket's structural members were the two decision variables. The first optimization, WCF-Optimization, considered constraints including the stress and
CRediT authorship contribution statement
Alireza Asgari Motlagh: Writing – original draft, Software, Investigation. Naser Shabakhty: Writing – review & editing, Data curation, Methodology, Supervision. Ali Kaveh: Conceptualization, Validation.
Declaration of competing interest
The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.
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