Hydroisomerisation and Hydrocracking of <em>n</em>-Heptane: Modelling and Optimisation Using a Hybrid Artificial Neural Network–Genetic Algorithm (ANN–GA)

Abstract

In this paper, the focus is on upgrading the value of naphtha compounds represented by n-heptane (n-C7H16) with zero octane number using a commercial zeolite catalyst consisting of a mixture of 75% HY and 25% HZSM-5 loaded with different amounts, 0.25 to 1 wt.%, of platinum metal. Hydrocracking and hydroisomerisation processes are experimentally and theoretically studied in the temperature range of 300–400 °C and under various contact times. A feedforward artificial neural network (FFANN) based on two hidden layers was used for the purpose of process modelling. A total of 80% of the experimental results was used to train the artificial neural network, with the remaining results being used for evaluation and testing of the network. Tan-sigmoid and log-sigmoid transfer functions were used in the first and second hidden layers, respectively. The optimum number of neurons in hidden layers was determined depending on minimising the mean absolute error (MAE). The best ANN model, represented by the multilayer FFANN, had a 4–24–24–12 topology. The ANN model accurately simulates the process in which the correlation coefficient (R2) was found to be 0.9918, 0.9492, and 0.9426 for training, validation, and testing, respectively, and an average of 0.9767 for all data. In addition, the operating conditions of the process were optimised using the genetic algorithm (GA) towards increasing the octane number of the products. MATLAB® Version 2020a was utilised to complete all required computations and predictions. Optimal operating conditions were found through the theoretical study: 0.85 wt.% Pt-metal loaded, 359.36 °C, 6.562 H2/n-heptane feed ratio, and 3.409 h−1 weight-hourly space velocity (WHSV), through which the maximum octane number (RON) of 106.84 was obtained. Finally, those operating conditions largely matched what was calculated from the results of the experimental study, where the highest percentage of the resulting isomers was found with about 78.7 mol% on the surface of the catalyst loaded with 0.75 wt.% Pt-metal at 350 °C using a feed ratio of 6.5 H2/n-C7 and WHSV of 2.98 h−1.

Keywords

• <i>n</i>-heptane
• Pt/HY-HZSM-5 zeolite catalyst
• hydroisomrisation
• hydrocracking
• octane number
• artificial neural network