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Research Papers: Piper and Riser Technology

Multi-Objective Shape Optimization Design for Liquefied Natural Gas Cryogenic Helical Corrugated Steel Pipe

[+] Author and Article Information
Zhixun Yang

State Key Laboratory of Structural Analysis for
Industrial Equipment,
Department of Engineering Mechanics,
Dalian University of Technology,
No. 2 Linggong Road,
Dalian 116023, China
e-mail: yangzhixun@mail.dlut.edu.cn

Jun Yan

State Key Laboratory of Structural Analysis for
Industrial Equipment,
Department of Engineering Mechanics,
Dalian University of Technology,
No. 2 Linggong Road,
Dalian 116023, China
e-mail: yanjun@dlut.edu.cn

Jinlong Chen

State Key Laboratory of Structural Analysis for
Industrial Equipment,
Department of Engineering Mechanics,
Dalian University of Technology,
No. 2 Linggong Road,
Dalian 116023, China
e-mail: cjldut@163.com

Qingzhen Lu

State Key Laboratory of Structural Analysis for
Industrial Equipment,
Department of Ocean Science and Technology,
Dalian University of Technology,
2 Dagong Road,
Panjin 124221, China
e-mail: luqingzhen@dlut.edu.cn

Qianjin Yue

State Key Laboratory of Structural Analysis for
Industrial Equipment,
Department of Ocean Science and Technology,
Dalian University of Technology,
2 Dagong Road,
Panjin 124221, China
e-mail: yueqj@dlut.edu.cn

1Corresponding author.

Contributed by the Ocean, Offshore, and Arctic Engineering Division of ASME for publication in the JOURNAL OF OFFSHORE MECHANICS AND ARCTIC ENGINEERING. Manuscript received October 18, 2016; final manuscript received March 3, 2017; published online May 25, 2017. Assoc. Editor: Theodoro Antoun Netto.

J. Offshore Mech. Arct. Eng 139(5), 051703 (May 25, 2017) (11 pages) Paper No: OMAE-16-1127; doi: 10.1115/1.4036372 History: Received October 18, 2016; Revised March 03, 2017

Recently, the flexible cryogenic hose has been preferred as an alternative to exploit offshore liquefied natural gas (LNG), in which helical corrugated steel pipe is the crucial component with C-shaped corrugation. Parametric finite element models of the LNG cryogenic helical corrugated pipe are established using a three-dimensional shell element in this paper. Considering the nonlinearity of cryogenic material and large geometric structural deformation, mechanical behaviors are simulated under axial tension, bending, and internal pressure loads. In addition, design parameters are determined to optimize the shape of flexible cryogenic hose structures through sectional dimension analysis, and sensitivity analysis is performed with changing geometric parameters. A multi-objective optimization to minimize stiffness and stress is formulated under operation conditions. Full factorial experiment and radial basis function (RBF) neural network are applied to establish the approximated model for structure analysis. The set of Pareto optimal solutions and value range of parameters are obtained through nondominated sorting genetic algorithm II (NSGA-II) under manufacturing and stiffness constraints, thereby providing a feasible optimal approach for the structural design of LNG cryogenic corrugated hose.

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References

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Figures

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Fig. 1

Structure of flexible cryogenic hose

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Fig. 2

Operation schematic diagram of flexible cryogenic hose for LNG transportation

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Fig. 3

Geometric model of helical cryogenic corrugated pipe

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Fig. 4

Local geometric dimension of axial section

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Fig. 5

Cryogenic stress–strain constitutive relationship

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Fig. 6

Layout method for sectional nodes

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Fig. 7

Local meshing sketch diagram

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Fig. 8

(a) The front view of numerical models and (b) schematic diagram of two reference points

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Fig. 9

Displacement change curve with tensional force

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Fig. 10

Maximum Mises stress changing curve

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Fig. 11

Displacement change curve with bending angle

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Fig. 12

Maximum equivalent stress changing curve

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Fig. 13

Stress change curve with internal pressure

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Fig. 14

Corrugation configuration changing under different internal pressures

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Fig. 15

(a) Height variation of corrugation section, (b) pitch variation of corrugation section, and (c) thickness variation of corrugation section

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Fig. 16

(a) Tension behaviors under different corrugation heights, (b) bending behaviors under different corrugation heights, and (c) the maximum stress under internal pressure with different corrugation heights

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Fig. 17

(a) Tension behaviors under different corrugation pitches, (b) bending behaviors under different corrugation pitches, and (c) the maximum stress under internal pressure with different corrugation pitches

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Fig. 18

(a) Tension behaviors under different thicknesses, (b)bending behaviors under different thicknesses, and (c) the maximum stress under internal pressure with different thicknesses

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Fig. 19

Changing trends of (a) tensional stiffness with design parameters, (b) bending stiffness with design parameters, and (c) the maximum stress under internal pressure stress with design parameters

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Fig. 20

Optimization design flowchart

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Fig. 21

Sample points under full factorial design

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Fig. 22

Schematic of radial basis function neural network structure

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Fig. 23

Optimal solution set frontiers by (a) AMGA, (b) NCGA, and (c) NSGA-II

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Fig. 24

Pareto front for multi-objective optimization

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Fig. 25

Optimal range of design parameter

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