2019
DOI: 10.1080/19942060.2019.1624197
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Numerical simulation of pressure pulsation effects of a snubber in a CNG station for increasing measurement accuracy

Abstract: Natural companies employ turbine flow meters to measure natural gas which delivered to Compressed Natural Gas stations. The stations utilize compressors to increase pressure. The compressor produces a flow pulsation, which affects the accuracy of the measurement. The main aim of this article is to decrease the compressor effects on measurement accuracy by utilizing a snubber between the turbine flow meter and the reciprocating compressors. For this aim, numerical modeling has been built to simulate natural gas… Show more

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Cited by 25 publications
(18 citation statements)
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“…State of the art surveys on the data-driven methods and machine learning algorithms, e.g., [9][10][11][12][13][14][15][16][17][18][19][20][21][22][23][24][25][26], indicates that deep learning, along with the ensemble and hybrid machine learning methods are the future of data science. Further comparative studies, e.g., [26][27][28][29][30][31][32][33][34][35][36][37][38][39][40][41][42], report that deep learning models and hybrid machine learning models often outperform conventional machine learning models.…”
Section: Introductionmentioning
confidence: 99%
“…State of the art surveys on the data-driven methods and machine learning algorithms, e.g., [9][10][11][12][13][14][15][16][17][18][19][20][21][22][23][24][25][26], indicates that deep learning, along with the ensemble and hybrid machine learning methods are the future of data science. Further comparative studies, e.g., [26][27][28][29][30][31][32][33][34][35][36][37][38][39][40][41][42], report that deep learning models and hybrid machine learning models often outperform conventional machine learning models.…”
Section: Introductionmentioning
confidence: 99%
“…For future research employing artificial intelligence methods, in particular, machine learning techniques (e.g. Farzaneh-Gord et al, 2019;Ghalandari, et al, 2019aGhalandari, et al, , 2019bMenad et al, 2019;Mosavi, Shamshirband, Salwana, Chau, & Tah, 2019;Mou, He, Zhao, & Chau, 2017) is encouraged considering higher accuracy and lower computational costs.…”
Section: Discussionmentioning
confidence: 99%
“…The process of testing the engine influence CONTACT Dong Li ldgh@nwpu.edu.cn in wind tunnel, especially using powered engine (normally Turbine Power Simulator method or Ejector Powered method), is complex and expensive (Ruiz-Calavera, Funes-Sebastian, & Perdones-Diaz, 2010; Zhaoguang, Yingchun, & Jiangtao, 2014). Compared to wind tunnel testing, numerical simulation (Abadi et al, 2020;Farzaneh-Gord et al, 2019) is not only more convenient but also low cost. There are usually two types of engine models used for numerical computation: Flow Through Nacelle (FTN) and With Powered Nacelle (WPN) (Kozakiewicz & Frant, 2013;Li, Gao, Huang, & Zhao, 2013).…”
Section: Introductionmentioning
confidence: 99%