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Computational Thermal Sciences: An International Journal

年間 6 号発行

ISSN 印刷: 1940-2503

ISSN オンライン: 1940-2554

The Impact Factor measures the average number of citations received in a particular year by papers published in the journal during the two preceding years. 2017 Journal Citation Reports (Clarivate Analytics, 2018) IF: 1.5 To calculate the five year Impact Factor, citations are counted in 2017 to the previous five years and divided by the source items published in the previous five years. 2017 Journal Citation Reports (Clarivate Analytics, 2018) 5-Year IF: 1 The Immediacy Index is the average number of times an article is cited in the year it is published. The journal Immediacy Index indicates how quickly articles in a journal are cited. Immediacy Index: 0.3 The Eigenfactor score, developed by Jevin West and Carl Bergstrom at the University of Washington, is a rating of the total importance of a scientific journal. Journals are rated according to the number of incoming citations, with citations from highly ranked journals weighted to make a larger contribution to the eigenfactor than those from poorly ranked journals. Eigenfactor: 0.00017 The Journal Citation Indicator (JCI) is a single measurement of the field-normalized citation impact of journals in the Web of Science Core Collection across disciplines. The key words here are that the metric is normalized and cross-disciplinary. JCI: 0.28 SJR: 0.279 SNIP: 0.544 CiteScore™:: 2.5 H-Index: 22

Indexed in

NUMERICAL MODELING OF ASPHALTENE DEPOSITION

巻 5, 発行 2, 2013, pp. 153-163
DOI: 10.1615/ComputThermalScien.2013006316
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要約

Asphaltene deposition on the wall of wellbore or pipeline during oil production and processing will cause dire consequences if left untreated. A better understanding of this phenomenon is required. This study presents a general modeling framework based either on the level-set approach or the total-concentration approach for modeling asphaltene deposition processes. Both the level-set approach and the total-concentration approach belong to the family of front-capturing methods. Therefore, the dynamics of the depositing front can be captured implicitly on fixed spatial mesh. The presented frameworks are validated against each other for general deposition process. Preliminary parametric studies are then performed to study the influences of various factors on the deposition process.

によって引用された
  1. Tavakkoli Mohammad, Boggara Mohan, Garcia-Bermudes Miguel, Vargas Francisco M., Asphaltene Deposition: Impact on Oil Production, Experimental Methods, and Mitigation Strategies, in Exploration and Production of Petroleum and Natural Gas, 2016. Crossref

  2. Guan Q., Yap Y.F., Goharzadeh A., Chai J.C., Vargas F.M., Chapman W.G., Zhang M., Integrated one-dimensional modeling of asphaltene deposition in wellbores/pipelines, 2017 7th International Conference on Modeling, Simulation, and Applied Optimization (ICMSAO), 2017. Crossref

  3. Ramirez-Corredores Maria Magdalena, Asphaltenes, in The Science and Technology of Unconventional Oils, 2017. Crossref

  4. Gounder Ramasamy Marappa, Emani Sampath, CFD Simulations of Crude Oil Fouling on Heat Transfer Surfaces, in Computational Fluid Dynamics - Basic Instruments and Applications in Science, 2018. Crossref

  5. Han Zhimin, Xu Zhiming, Yu Xiaoyan, CFD modeling for prediction of particulate fouling of heat transfer surface in turbulent flow, International Journal of Heat and Mass Transfer, 144, 2019. Crossref

  6. Bagherzadeh Hadi, Mansourpour Zahra, Dabir Bahram, Numerical analysis of asphaltene particles evolution and flocs morphology using DEM-CFD approach, Journal of Petroleum Science and Engineering, 199, 2021. Crossref

  7. Naseri Saman, Jamshidi Saeid, Taghikhani Vahid, A new multiphase and dynamic asphaltene deposition tool (MAD-ADEPT) to predict the deposition of asphaltene particles on tubing wall, Journal of Petroleum Science and Engineering, 195, 2020. Crossref

  8. Seyyedbagheri Hadi, Mirzayi Behruz, Eulerian Model To Predict Asphaltene Deposition Process in Turbulent Oil Transport Pipelines, Energy & Fuels, 31, 8, 2017. Crossref

  9. Rajan Babu Narmadha, Lin Pei-Hsuan, Abutaqiya Mohammed I. L., Sisco Caleb J., Wang Jianxin, Vargas Francisco M., Systematic Investigation of Asphaltene Deposition in the Wellbore and Near-Wellbore Region of a Deepwater Oil Reservoir under Gas Injection. Part 2: Computational Fluid Dynamics Modeling of Asphaltene Deposition, Energy & Fuels, 33, 5, 2019. Crossref

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