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Modeling natural gas compressibility factor using a hybrid group method of data handling
Engineering Applications of Computational Fluid Mechanics ( IF 5.9 ) Pub Date : 2019-11-07 , DOI: 10.1080/19942060.2019.1679668
Abdolhossein Hemmati-Sarapardeh 1, 2 , Sassan Hajirezaie 3 , Mohamad Reza Soltanian 4 , Amir Mosavi 5, 6 , Narjes Nabipour 7 , Shahaboddin Shamshirband 8, 9 , Kwok-Wing Chau 10
Affiliation  

The natural gas compressibility factor indicates the compression and expansion characteristics of natural gas under different conditions. In this study, a simple second-order polynomial method based on the group method of data handling (GMDH) is presented to determine this critical parameter for different natural gases at different conditions, using corresponding state principles. The accuracy of the proposed method is evaluated through graphical and statistical analyses. The method shows promising results considering the accurate estimation of natural gas compressibility. The evaluation reports 2.88% of average absolute relative error, a regression coefficient of 0.92, and a root means square error of 0.03. Furthermore, the equations of state (EOSs) and correlations are used for comparative analysis of the performance. The precision of the results demonstrates the model’s superiority over all other correlations and EOSs. The proposed model can be used in simulators to estimate natural gas compressibility accurately with a simple mathematical equation. This model outperforms all previously published correlations and EOSs in terms of accuracy and simplicity.



中文翻译:

使用数据处理的混合组方法对天然气可压缩性因子进行建模

天然气可压缩系数表示天然气在不同条件下的压缩和膨胀特性。在这项研究中,提出了一种基于数据处理组方法(GMDH)的简单二阶多项式方法,使用相应的状态原理确定不同条件下不同天然气的关键参数。通过图形和统计分析来评估所提出方法的准确性。考虑到天然气可压缩性的准确估算,该方法显示出令人鼓舞的结果。该评估报告的平均绝对相对误差为2.88%,回归系数为0.92,均方根误差为0.03。此外,状态方程(EOS)和相关性用于性能的比较分析。结果的精度证明了该模型优于所有其他相关性和EOS的优势。所提出的模型可以在模拟器中用于通过简单的数学方程式准确估算天然气的可压缩性。在准确性和简便性方面,该模型优于所有先前发布的相关性和EOS。

更新日期:2020-04-20
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