PREDICTION AND QUALIFICATION OF RADIAL BIRDCAGE AND LATERAL BUCKLING OF FLEXIBLE PIPES IN DEEPWATER APPLICATIONS

被引:0
|
作者
Zhu, Linfa [1 ]
Tan, Zhimin [1 ]
Nogueira, Victor Pinheiro Pupo [1 ]
Liu, Jian [2 ]
Clevelario, Judimar [3 ]
机构
[1] GE Oil & Gas, Houston, TX USA
[2] GE Oil & Gas, Newcastle Upon Tyne, Tyne & Wear, England
[3] GE Oil & Gas, Rio De Janeiro, Brazil
来源
PROCEEDINGS OF THE ASME 34TH INTERNATIONAL CONFERENCE ON OCEAN, OFFSHORE AND ARCTIC ENGINEERING, 2015, VOL 5A | 2015年
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中图分类号
P75 [海洋工程];
学科分类号
0814 ; 081505 ; 0824 ; 082401 ;
摘要
Increasing oil exploitation in deepwater regions is driving the R&D of flexible pipes which are subjected to high external pressure loads from the hydrostatic head during their installation and operation. One of the challenges of flexible pipe design for such applications is to overcome the local buckling failure modes of tensile armor layers due to the combination of high external pressure, compressive loads and pipe curvature. This paper presents the latest progress in local buckling behavior prediction theory and the qualification process of flexible pipes. First, the mechanisms of two types of buckling behaviors, radial birdcage buckling and lateral buckling, are described. For each failure mode, the analytical buckling prediction theory is presented and the driving parameters are discussed. As part of the qualification process, the ability to resist radial birdcage and lateral buckling must be demonstrated. Suitable test protocols are required to represent the installation and operation conditions for the intended applications by deep immersion performance (DIP) tests. Several flexible pipes were designed based on radial birdcage and lateral buckling prediction theory, and pipe samples were manufactured using industrial production facilities for DIP tests. The results clearly show that flexible pipes following current design guidelines are suitable for deepwater applications. An alternative in-air rig was developed to simulate the DIP tests in a controlled laboratory environment to further validate the model prediction as a continuous development.
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页数:7
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