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  • Open Access

    ARTICLE

    Prediction Model of Wax Deposition Rate in Waxy Crude Oil Pipelines by Elman Neural Network Based on Improved Reptile Search Algorithm

    Zhuo Chen1,*, Ningning Wang2, Wenbo Jin3, Dui Li1

    Energy Engineering, Vol.121, No.4, pp. 1007-1026, 2024, DOI:10.32604/ee.2023.045270

    Abstract A hard problem that hinders the movement of waxy crude oil is wax deposition in oil pipelines. To ensure the safe operation of crude oil pipelines, an accurate model must be developed to predict the rate of wax deposition in crude oil pipelines. Aiming at the shortcomings of the ENN prediction model, which easily falls into the local minimum value and weak generalization ability in the implementation process, an optimized ENN prediction model based on the IRSA is proposed. The validity of the new model was confirmed by the accurate prediction of two sets of experimental data on wax deposition… More > Graphic Abstract

    Prediction Model of Wax Deposition Rate in Waxy Crude Oil Pipelines by Elman Neural Network Based on Improved Reptile Search Algorithm

  • Open Access

    ARTICLE

    The Paraffin Crystallization in Emulsified Waxy Crude Oil by Dissipative Particle Dynamics

    Ruiqiong Wang1, Tiantian Du2, Jinchen Cao2,*, Guoqiang Wang3

    Frontiers in Heat and Mass Transfer, Vol.22, No.1, pp. 129-139, 2024, DOI:10.32604/fhmt.2024.047825

    Abstract With the advancement of oilfield extraction technology, since oil-water emulsions in waxy crude oil are prone to be deposited on the pipe wall, increasing the difficulty of crude oil extraction. In this paper, the mesoscopic dissipative particle dynamics method is used to study the mechanism of the crystallization and deposition adsorbed on the wall. The results show that in the absence of water molecules, the paraffin molecules near the substrate are deposited on the metallic surface with a horizontal morphology, while the paraffin molecules close to the fluid side are arranged in a vertical column morphology. In the emulsified system,… More >

  • Open Access

    ARTICLE

    THE STUDY OF TEMPERATURE PROFILE INSIDE WAX DEPOSITION LAYER OF WAXY CRUDE OIL IN PIPELINE

    Zhen Tiana,*, Wenbo Jina, Lei Wangb, Zhi Jinc

    Frontiers in Heat and Mass Transfer, Vol.5, pp. 1-8, 2014, DOI:10.5098/hmt.5.5

    Abstract Taking the axial heat conduction of wax deposition layer into account, a two-dimensional heat transfer model of calculating the temperature profile inside wax deposition layer was deduced and established based on the energy balance equation, the finite difference method was used to solve this model, and the influence of axial heat conduction on the distribution law of temperature profile inside the wax deposition layer under different boundary conditions and thickness were discussed. The results showed that: Temperature profile inside wax deposition layer in middle region of testing pipe section was mainly influenced by axial heat conduction under boundary conditions of… More >

  • Open Access

    ARTICLE

    PREDICTING THE WAX DEPOSITION RATE BASED ON EXTREME LEARNING MACHINE

    Qi Zhuanga,* , Zhuo Chenb, Dong Liuc, Yangyang Tiand

    Frontiers in Heat and Mass Transfer, Vol.19, pp. 1-8, 2022, DOI:10.5098/hmt.19.19

    Abstract In order to improve the accuracy and efficiency of wax deposition rate prediction of waxy crude oil in pipeline transportation, A GRA-IPSO-ELM model was established to predict wax deposition rate. Using Grey Relational Analysis (GRA) to calculate the correlation degree between various factors and wax deposition rate, determine the input variables of the prediction model, and establish the Extreme Learning Machine (ELM) prediction model, improved particle swarm optimization (IPSO) is used to optimize the parameters of ELM model. Taking the experimental data of wax deposition in Huachi operation area as an example, the prediction performance of the model is evaluated… More >

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