Abstract
Two intelligent-based models which do not require complete gas compositions are presented to estimate natural gas density correction factor using comprehensive datasets (nearly 60 000 instances) originating from the AGA8-DCM (Detail Characterization Method) standard: (1) NGDC-ANN model (Natural Gas Density Calculator based on Artificial Neural Network) and (2) AGA8-GCMD model (Gross Characterization Method Developed by applying genetic algorithm technique). In the suggested models, only five input variables (specific gravity at base condition, operating temperature and pressure and molar composition of CO2 and N2) are employed. The experimental datasets obtained from this work (68 instances) and literature (505 instances) are applied to validate the developed model showing a very good agreement between experimental and estimated data. Simplicity, improving accuracy and satisfactory results of the suggested models over a wide range of operational conditions show that these models would be excellent alternatives for the traditional standard methods, so that, the NGDC-ANN model prediction besides of its simplicity to use show the highest accuracy over a wide of operational range in comparison to similar models.
Highlights
In recent years, significant attention has been paid to developing an easy and accurate measurement methods of natural gas mass flow rate in gas industries especially in European and Asian countries
To predict the density correction factor of natural gas, AGA8-DCM model was replaced by a proposed NGDCANN model, which requires less input variables like AGA8-GCM and NX-19 Equation of State (EOS)
The model was optimized by specific properties of Artificial Neural Network (ANN) including number of hidden layers (NL), number of neurons in the hidden layers (N Ln ), transfer function, and Back-Propagation Learning Algorithm (BPLA) as described
Summary
Significant attention has been paid to developing an easy and accurate measurement methods of natural gas mass flow rate in gas industries especially in European and Asian countries. Density metering along with volume flow metering which needs less cost is essential in natural gas marketing. Devices such as multiple ultrasonic transient-time meters and conventional orifice plates are employed to measure the volume flow rate of natural gas [2]. Direct measurement of natural gas density is difficult as it needs highly expert staffs and costly instruments such as Coriolis density meters, gas chromatographs, etc. These instruments have their own problems; the potential of erosion, sensitivity to pulsation and vibration close to operating frequency, and requirements of regular calibration [5,6,7,8]
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