Abstract
Performance of the oxidative coupling of methane (OCM) at elevated pressures has been simulated by a set of supervised Artificial Neural Network (ANN) models using reaction data gathered in a microreactor device. Accuracy of the developed models were evaluated by comparing the predicted results with the test data set showing a good agreement. In order to enhance the performance of OCM process at 0.4 MPa as a desired operating pressure for commercial application of OCM, the Hybrid Genetic Algorithm (HGA) was used to obtain the optimal values of the operating conditions. Nondominated Pareto optimal solutions were obtained and additional experiments were carried out at two different optimum conditions in order to verify the optimums. The results show that combination of ANN models with HGA could be used in finding the suitable operating conditions for OCM process at elevated pressures. It was shown that the C 2+ yield of above 23% can be achieved at 0.4 MPa by using Na–W–Mn/SiO 2 as the OCM catalyst.
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