A Novel Numerical Model for Simulating the Quantity of Tailing Oil in the Mixed Segment between Two Batches in Product Pipelines

Cutting mixed oil in product pipelines has a great influence on the economy of the pipeline operation processes. The reasonable prediction of CDMS (the concentration distribution in the mixed segment) is important for cutting mixed segments. The classical model cannot explain the tailing phenomenon well which should not be neglected during operation processes. Based on Fick’s diffusion law, a new model for calculating the diffusion coefficient is proposed in this article, which originates from the essence of the diffusion phenomenon and considers the effects of both physical properties of oil products and the turbulence. At the same time, the dynamic fluid equilibrium model of CDMS near the pipe wall is given which has considered the adsorption effect of wall roughness. Based on these two factors, a novel numerical model for simulating the quantity of tailing oil is proposed, which is solved via the characteristic method and the finite difference method. The effects of different physical properties, as well as the adsorption, on both LFMS (the length of the front of the mixed segment) and LTMS (the length of the tail of the mixed segment), are analyzed. The comparison between the simulation results and the experimental data is utilized to validate the proposed numerical model. The simulation results show that the novel model can well describe the mixed segment tailing phenomenon and also explain the mixing essence of two miscible but dissimilar fluids in the pipeline more clearly. To sum up, this model can provide theoretical guidance for the prediction of CDMS and cutting process in practical operation processes; therefore, more economic benefit can be obtained.

[1]  Geoffrey Ingram Taylor,et al.  The dispersion of matter in turbulent flow through a pipe , 1954, Proceedings of the Royal Society of London. Series A. Mathematical and Physical Sciences.

[2]  G. G. Stokes.  "J." , 1890, The New Yale Book of Quotations.

[3]  Gong Jing.  DEVELOPMENT OF MODEL FOR CONTAMINATED OIL PRODUCT CAUSED BY ELEVATION DIFFERENCE IN MULTIPRODUCT PIPELINES , 2003 .

[4]  Neil Genzlinger.  A. and Q , 2006 .

[5]  Z. Aunický.  The longitudinal mixing of liquids flowing successively in pipelines , 1970 .

[6]  Thomas Baron,et al.  Axial mixing in pipes , 1957 .

[7]  Diego C. Cafaro,et al.  A Rigorous Mathematical Formulation for the Scheduling of Tree-Structure Pipeline Networks , 2011 .

[8]  Renan Martins Baptista,et al.  Predicting Mixing Volumes in Serial Transport in Pipelines , 2002 .

[9]  Zukui Li,et al.  Modeling and Optimization of the Upgrading and Blending Operations of Oil Sands Bitumen , 2016 .

[10]  A. Patrachari,et al.  A conceptual framework to model interfacial contamination in multiproduct petroleum pipelines , 2012 .

[11]  장윤희,et al.  Y. , 2003, Industrial and Labor Relations Terms.

[12]  Yongtu Liang,et al.  Experimental and numerical research on the axial and radial concentration distribution feature of miscible fluid interfacial mixing process in products pipeline for industrial applications , 2018, International Journal of Heat and Mass Transfer.

[13]  Nélida B. Brignole,et al.  Simulated Annealing Optimization for Hydrocarbon Pipeline Networks , 2013 .

[14]  Feng Li,et al.  A method for simulating the entire leaking process and calculating the liquid leakage volume of a damaged pressurized pipeline. , 2017, Journal of hazardous materials.

[15]  Jing Gong,et al.  The Calculation Method of Mixing Volume in a Products Pipeline , 2010 .

[16]  Pedro M. Castro,et al.  A Novel Monolithic MILP Framework for Lot-Sizing and Scheduling of Multiproduct Treelike Pipeline Networks , 2015 .

[17]  Felipe Bastos de Freitas Rachid,et al.  Computing Transmix in Complex Batch Transfers via the Mixing-Volume-Equivalent-Pipe Concept , 2010 .

[18]  J. E. Austin,et al.  Mixing of Miscible but Dissimilar Liquids in Serial Flow in a Pipeline , 1963 .