Prediction of Joule-Thomson coefficient and inversion curve for natural gas and its components using CFD modeling

Abstract

In this study, three equations of state (EOS) in conjunction with computational fluid dynamics (CFD) modeling were used to predict the Joule – Thomson (JT) process behavior for natural gas and various pure gases. The JT effect is encountered in several industrial applications. The experimental determination of the JT coefficient (JTC) is complicated, and there is little gas pressure-volume-temperature (PVT) data available for estimating these JTC. Thus, the development of an efficient model to predict the JT effect in industrial processes is necessary. This study was carried out to attain a clear view of the single phase-flow of hydrocarbons and nitrogen in the JT process with CFD modeling. The JT valve was modeled in a pipe so as to predict the JTC, inversion curve (IC) and the isenthalpic curve of nitrogen, methane, ethane, propane and their mixtures in a wide range of temperature and pressure. Generally, the low-temperature branch of IC was predicted accurately by most of EOSs. Among the considered EOSs, Soave-Redlich-Kwong (SRK) EOS is able to predict more accurately the Joule – Thomson inversion curve (JTIC) in comparison with the other EOS. The validation of this CFD modeling was conducted using the experimental data from the literature and the industrial data of natural gas from an Iranian Gas Dehydration unit. The outlet temperature obtained from the CFD model agreed well with the industrial data of the JT process. The proposed CFD model accurately predicts the experimental and the industrial data of the JT process.