水平及微倾斜管道中高压气液两相流段塞长度预测

Eissa M. Al-Safran, A. Aql
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引用次数: 0

摘要

段塞流是管道中最常见的流态。段塞长度是管道和下游分离设施设计和运行的重要特征。此外,机械式两相流模型以段塞流长度作为封闭关系来求解段塞流中的压力梯度和平均含液率。然而,现有的用于低压的段塞长度封闭关系在高压条件下(即高气液密度比)表现不佳,导致段塞长度、压力梯度和液含率的预测具有很高的不确定性。本工作旨在建立一个机械段塞长度模型,并利用遗传算法的误差最小化技术确定高压条件下的最佳关闭关系。此外,所确定的闭包关系与所研究条件下段塞流的物理特性相匹配。因此,该模型的决定系数R2 = 0.85,绝对平均误差(AAE)约等于70%,优于文献中表现最好的现有模型。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Prediction of Slug Length for High Pressure Gas/Liquid Two-Phase Flow in Horizontal and Slightly Inclined Pipes
Slug flow in pipelines is the most common flow pattern. Slug length is crucial characteristic for pipeline and downstream separation facility design and operation. In addition, mechanistic two- phase flow models require slug length as closure relationship to solve for pressure gradient and average liquid holdup in slug flow. However, the existing slug length closure relationships developed for low pressure are found to poorly perform in high-pressure conditions, i.e. high gas- to-liquid density ratio high, resulting in high uncertainty predictions of slug length, pressure gradient and liquid holdup. This work aims to propose a mechanistic slug length model and to identify the optimal closure relationship for high-pressure condition through error minimization technique using Genetic Algorithm. In addition, the identified set of closure relationships are found to match the physics of slug flow under the investigated conditions. As a result, the proposed model result in a coefficient of determination R2 = 0.85 and an Absolute Average Error (AAE) approximately equals 70% outperforming the best-performing exiting model in the literature.
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