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Study on the Economic Insulation Thickness of the Buried Hot Oil Pipelines Based on Environment Factors

Shihao Fan, Mingliang Chang*, Shouxi Wang, Qing Quan, Yong Wang, Dan Li
College of Petroleum Engineering, Xi’an Shiyou University, Xi’an, 710065, China
* Corresponding Author: Mingliang Chang. Email:
(This article belongs to this Special Issue: Advances in Modeling and Simulation of Complex Heat Transfer and Fluid Flow)

Computer Modeling in Engineering & Sciences 2020, 124(1), 45-59. https://doi.org/10.32604/cmes.2020.08973

Received 29 October 2019; Accepted 20 May 2020; Issue published 19 June 2020

Abstract

It is important to determine the insulation thickness in the design of the buried hot oil pipelines. The economic thickness of the insulation layer not only meets the needs of the project but also maximizes the investment and environmental benefits. However, as a significant evaluation, the environmental factors haven’t been considered in the previous study. Considering this factor, the mathematical model of economic insulation thickness of the buried hot oil pipelines is built in this paper, which is solved by the golden section method while considering the costs of investment, operation, environment, the time value of money. The environmental cost is determined according to the pollutant discharge calculated through relating heat loss of the pipelines to the air emission while building the model. The results primarily showed that the most saving fuel is natural gas, followed by LPG, fuel oil, and coal. The fuel consumption for identical insulation thickness is in the order: coal, fuel oil, LPG, and natural gas. When taking the environmental costs into account, the thicker the economic insulation layer is, the higher cost it will be. Meanwhile, the more pollutant discharge, the thicker the economic insulation layer will be.

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Cite This Article

Fan, S., Chang, M., Wang, S., Quan, Q., Wang, Y. et al. (2020). Study on the Economic Insulation Thickness of the Buried Hot Oil Pipelines Based on Environment Factors. CMES-Computer Modeling in Engineering & Sciences, 124(1), 45–59.



This work is licensed under a Creative Commons Attribution 4.0 International License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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