A conceptual framework to model interfacial contamination in multiproduct petroleum pipelines

Patrachari, Anirudh R.; Johannes, Arland H.

doi:10.1016/j.ijheatmasstransfer.2012.04.017

Cited by 22 publications

(12 citation statements)

References 23 publications

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“…Patrachari et al [16] and Botros et al [17] studied the additional contamination problem in a main pipe run due to dead-legs. Their work shows that in a pump station with four pumps, the bypass line of each pump will form a dead-leg, and the four dead-legs will result in an additional 400 m to 420 m of contamination due to diffusion.…”

Section: Introductionmentioning

confidence: 99%

Formation Mechanism of Trailing Oil in Product Oil Pipeline

Liu

Hong-jun

et al. 2018

Processes

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Trailing oil is the tail section of contamination in oil pipelines. It is generated in batch transportation, for which one fluid, such as diesel oil follows another fluid, such as gasoline, and it has an effect on the quality of oil. This paper describes our analysis of the formation mechanism of trailing oil in pipelines and our study of the influence of dead-legs on the formation of trailing oil. We found that the oil replacement rate in a dead-leg is exponentially related to the flow speed, and the length of the dead-leg is exponentially related to the replacement time of the oil. To reduce the amount of mixed oil, the main flow speed should be kept at about 1.6 m/s, and the length of the dead-leg should be less than five times the diameter of the main pipe. In our work, the Reynolds time-averaged method is used to simulate turbulence. To obtain contamination-related experimental data, computational fluid dynamics (CFD) software is used to simulate different flow rates and bypass lengths. MATLAB software was used to perform multi-nonlinear regression for the oil substitution time, the length of the bypass, and the flow speed. We determined an equation for calculating the length of the trailing oil contamination produced by the dead-leg. A modified equation for calculating the length of the contamination was obtained by combining the existing equation for calculating the length of the contamination with new factors based on our work. The amounts of contamination predicted by the new equation is closer to the actual contamination amounts than predicted values from other methods suggested by previous scholars.

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Section: Introductionmentioning

confidence: 99%

Formation Mechanism of Trailing Oil in Product Oil Pipeline

Liu

Hong-jun

et al. 2018

Processes

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“…(19), the debris field is more dispersed for lower temperatures and particle diameters. In this work the mixture flows in laminar regime, however, in larger pipelines turbulence is an important factor (Patrachari & Johannes (2012)). At higher Reynolds numbers, the competition between turbulence and settling could keep the particle in suspension and it is unclear if small enough debris remain suspended.…”

Section: Discussionmentioning

confidence: 91%

An inertial two-phase model of wax transport in a pipeline during pigging operations

Boghi

Brown²,

Sawko

et al. 2017

International Journal of Multiphase Flow

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Pig in pipelines performs operations for cleaning the pipe interior and internal inspection. In the past few years many 1D models have been developed to simulate the process because of their reduced computational cost; however, they rely on simplifications which are not always valid. In this paper, the results of a three-dimensional (3D) numerical investigation of the interaction between a waxy-oil and a dynamic sealing pig in a pipeline are presented. The results are obtained at a reduced computational cost by using a moving frame of reference, and an "injection" boundary condition for the wax deposited on the wall. The effect of the temperature and the wax particles' size has been investigated. The 3D results show the structure assumed by the debris field in front of the pig. In particular, a lubrication region at the bottom of the pipe, whose dimensions are temperature dependent, is shown. This information cannot be deduced from 1D modeling. The influence of the oil on the mixture viscosity and the internal bed dynamics are discussed. This work provides insights into the interaction between the debris field in front of the pig and pipeline hydraulics.

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“…总传热系数 [36,63,113,119] 、有效扩散系数 [45,100] 、雷诺数等特征数 [100] 、流体状态方程和管壁方程 [59,118] 以及边界层效应 [36,63,68,69,80,97,113,119] 的建模和计算, 不同学者建立不同的模型描述这些关键量之间及与待求变量之间的关系, 部分学者还考虑了纯油品的物性参数与温度和压力的关系 [45,100] 及计算混油物性的混合法则 [73,100] . 在处理模型的耦合性方面, 不同的学者在各自建立的假设基础上对方程组进行适当简化再求解 , 一是将非稳态问题近似为稳态问题 [36,63,113,119] , 二是将耦合性强的项进行适当简化再用数值 [45,59,68,69] 或半数值 [33,36,63,113,119] 的办法求解, 三是直接利用商业CFD软件进行数值模拟 [68,69,79] , 利用其内 [124] .…”

Section: 在建立定解条件使方程组封闭方面主要问题是对unclassified