LAUSR

Diagnosis of detailed conditions of hydrate formation, as an important issue of gas fuels, can help related industries a lot, particularly in storing, transportation and processing equipment. Hydrate formation temperature or pressure can be predicted by application of mathematical models, due to thermodynamic behavior of hydrate phenomenon. A number of thermodynamical approaches along with some mathematical techniques (analytical and numerical methods) have been used to estimate hydrate formation temperature. However, there are also a variety of other techniques which have not been investigated. Application of genetic programming in developing predictive models seems novel. In the present study, three new data-based models were produced for estimation of hydrate formation temperature of natural gas, as functions of equilibrium pressure and gas molecular weight by implementation of genetic programming methodology. A total of 891 experimental data covering large range of temperatures (10.31–89.33 °F), pressures (8.1511–10,004.7 psi) and molecular weights (16.04–58.12 g/mol) were collected from the literature and used in correlation developing. The correlation coefficient (R2 = 0.9673), root-mean-square deviation (RMSD = 2.2083 °F) and average absolute relative deviation percent (AARD = 3.0830%) show that the genetic-based new models have acceptable accuracy and efficiency.