Evaluation of the performance of anti-icing natural gas regulator in terms of heat transfer and hydrodynamics

Document Type : Research Paper

Authors

1 Department of Mechanical Engineering, Kermanshah University of Technology

2 Imam Khomeini highway

10.22059/ees.2023.2008497.1438

Abstract

In this study, frost-resistant regulators in terms of temperature and hydrodynamics in COMSOL Multiphysics software were investigated. The heat exchanger considered in this research was investigated from various aspects including changes in dimensions, location of the exchanger, the effect of changes in the temperature of the exchanger wall, as well as the effect of square and triangular fins. The results showed that by increasing the dimensions, both longitudinally and transversely, the efficiency of the heat exchanger increases. However, increasing the dimensions of the heat exchanger is slightly allowed due to limited space as well as the limitations of solid mechanics. Also increase the temperature of the heat exchanger wall causes Intense temperature gradients occur in the orifice area, which can be effective in melting the ice created in that wall. The presence of square and triangular fins can help increase efficiency and create a more intense temperature gradient in the orifice area. Square fins are more effective than triangular fins, although the maximum temperature difference in that area is about 3 Kelvin. The largest temperature gradient is between the temperature of the inlet gas and the temperature of the orifice bottleneck and is equal to 24 Kelvin. The maximum temperature of the heat exchanger wall is 523 K, which results in a temperature of 360 K in the orifice wall, which can lead to the melting of possible frost.

Keywords

References

[1] Choi M-E, Kim S-W, Seo S-W. Energy Management Optimization in a Battery/Supercapacitor Hybrid Energy Storage System. IEEE Transactions on Smart Grid 2012;3:463–72. https://doi.org/10.1109/TSG.2011.2164816.
[2] Mellouk L, Ghazi M, Aaroud A, Boulmalf M, Benhaddou D, Zine-Dine K. Design and energy management optimization for hybrid renewable energy system- case study: Laayoune region. Renewable Energy 2019;139:621–34. https://doi.org/10.1016/j.renene.2019.02.066.
[3] Thermodynamic and economic assessment of an integrated thermoelectric generator and the liquefied natural gas production process - ScienceDirect n.d. https://www.sciencedirect.com/science/article/abs/pii/S0196890419302171 (accessed August 4, 2023).
[4] Woldeyohannes AD, Majid MAA. Simulation model for natural gas transmission pipeline network system. Simulation Modelling Practice and Theory 2011;19:196–212. https://doi.org/10.1016/j.simpat.2010.06.006.
[5] The Optimal Design of Natural Gas Transmission Pipelines: Energy Sources, Part B: Economics, Planning, and Policy: Vol 8, No 1 n.d. https://www.tandfonline.com/doi/abs/10.1080/15567240802534193 (accessed August 4, 2023).
[6] Zhou J, Adewumi MA. Simulation of transient flow in natural gas pipelines: Pipeline Simulation Interest Group Annual Meeting, PSIG 1995, 1995.
[7] Yu W, Song S, Li Y, Min Y, Huang W, Wen K, et al. Gas supply reliability assessment of natural gas transmission pipeline systems. Energy 2018;162:853–70. https://doi.org/10.1016/j.energy.2018.08.039.
[8] Osiadacz AJO. Simulation and Analysis of Gas Networks. UNKNO; 1987.
[9] Chapman KS, Krishniswami P, Wallentine V, Abbaspour M, Ranganathan R, Addanki R, et al. Virtual Pipeline System Testbed to Optimize the U.S. Natural Gas Transmission Pipeline System. UNT Digital Library 2005. https://doi.org/10.2172/861668.
[10] Ehrhardt K, Steinbach MC. Nonlinear Optimization in Gas Networks. In: Bock HG, Phu HX, Kostina E, Rannacher R, editors. Modeling, Simulation and Optimization of Complex Processes, Berlin/Heidelberg: Springer-Verlag; 2005, p. 139–48. https://doi.org/10.1007/3-540-27170-8_11.
[11] Simulation of transients in natural gas pipelines using hybrid TVD schemes - Zhou - 2000 - International Journal for Numerical Methods in Fluids - Wiley Online Library n.d. https://onlinelibrary.wiley.com/doi/abs/10.1002/%28SICI%291097-0363%2820000229%2932%3A4%3C407%3A%3AAID-FLD945%3E3.0.CO%3B2-9 (accessed August 3, 2023).
[12] Zhou D, Jia X, Ma S, Shao T, Huang D, Hao J, et al. Dynamic simulation of natural gas pipeline network based on interpretable machine learning model. Energy 2022;253:124068. https://doi.org/10.1016/j.energy.2022.124068.
[13] A. Bayat, K. Abbaspour Sani. Thermal analysis of gas heater gas pressure reduction station (CGS) in Zanjan city, Iran: 2016.
[14] Banda, Mapundi K., Michael Herty, and Axel Klar. Gas flow in pipeline networks. Networks and Heterogeneous media 2006;1:41.

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