Evaluation of Slug Flow-Induced Flexural Loading in Pipelines Using a Surrogate Model

Abstract

Slug flow induces vibration in pipelines, which may, in some cases, result in fatigue failure. This can result from dynamic stresses, induced by the deflection and bending moment in the pipe span, growing to levels above the endurance limits of the pipeline material. As such, it is of paramount importance to understand and quantify the size of the pipeline response to slug flow under given speed and damping conditions. This paper utilizes the results of an optimization procedure to devise a surrogate closed-form model, which can be employed to calculate the maximum values of the pipeline loadings at given values of speed and damping parameters. The surrogate model is intended to replace the computationally costly numerical procedure needed for the analysis. The maximum values of the lateral deflection and bending moment, along with their locations, have been calculated using the optimization method of stochastic perturbation and successive approximations (SPSA). The accuracy of the proposed surrogate model will be validated numerically, and the model will be subsequently used in a numerical example to demonstrate its applicability in industrial situations. An accompanying spreadsheet with this worked example is also given.

Guideline for the Decommissioning/Abandonment of Subsea Pipelines

“…A pipeline refers primarily to an enclosed pipe system that extends between two or more process facilities (e.g., offshore platforms, pumping/compressor stations, tank farm/storage facilities, refineries, etc.) to convey bulk volumes of fluid or fluids between those process facilities [1][2][3][4][5]. There is demand by different oil and gas operators to utilise existing ageing offshore structures, which has led to the need for the development of new regulations [6,7].…”

Modelling of a Flow-Induced Oscillation, Two-Cylinder, Hydrokinetic Energy Converter Based on Experimental Data

“…At high Reynolds number, the accuracy of numerical simulation is greatly reduced. In order to circumvent the problems inherent in experimental and numerical simulations, a modeling method named "surrogate model" has been widely used by researchers in recent years [30,31]. This surrogate model also can be considered as an effective substitute for experimental device and numerical software to predict the data for cases that have not be directly measured.…”

“…This surrogate model also can be considered as an effective substitute for experimental device and numerical software to predict the data for cases that have not be directly measured. Based on its modeling efficiency, predictive strength, and ability to explore unknown data, surrogate models have been utilized in many engineering fields [29,30,[32][33][34].…”