An improved PSO method for optimal design of subsea oil pipelines. (1st September 2017)

• Record Type: Journal Article
• Authors: Zhang, Haoran; Liang, Yongtu; Ma, Jing; Shen, Yun; Yan, Xiaohan; Yuan, Meng
• Is Part Of: Ocean engineering. Volume 141(2017)
• Page Start: 154
• Page End: 163
• Publication Date: 2017-09-01
• Subjects: Subsea pipeline -- Integer optimum design -- Improved particle swarm optimization -- Monte Carlo method; Ocean engineering -- Periodicals; Ocean engineering; Periodicals; 620.4162
• DOI: 10.1016/j.oceaneng.2017.06.023
• Languages: English
• ISSNs: 0029-8018

Abstract

Abstract: The construction cost of subsea oil pipelines takes rather high portion in the overall developing investment in offshore oilfield, thus an effective design of subsea oil pipelines is one of the main measurements to decrease the cost in offshore oilfield. In this paper, a new method for design and optimization of subsea pipelines is proposed, which conjunctly analyzes thermal-hydraulic performance and structural integrity, and uniformly solves main parameters for pipeline design, such as internal diameter, wall thickness, insulation layer thickness and pipeline inlet pressure and temperature. A complex non-linear mathematical model is established to minimize the total construction investment and operation costs while ensuring that the system meets minimum structural integrity standards and operation requirements over its anticipated service life; the model also analyzes the uncertainties in operation parameters, such as environmental temperature, overburden pressure and delivery flow fluctuations. Four multi-swarm cooperative improved particle swarm optimization algorithms (MC-GPSO, MC-LPSO, MC-FIPSO and MC-SLPSO) are employed for calculation. Monte Carlo method is introduced into the algorithms to determine the uncertain parameters. Through comparison, MC-SLPSO algorithm can optimally solve this type of model when 5 slave swarms are employed. Finally, a virtual oil pipeline and a practical multiphase subsea pipeline are set as two examples to demonstrate the performance of the optimization schemes. Highlights: The model can be applied to analyzing the thermal-hydraulic and structural force, and solving the main pipeline parameters. Sea state uncertainties such as environment temperature, overburden pressure, and delivery flow are considered. Four improved particle swarm optimization algorithms are employed for calculation. Monte Carlo method is introduced into the algorithms to determine the uncertainty parameters.