اعتبار سنجي و آناليز حساسيت شبيه سازي راكتورهاي توليد استايرن

Validation and Sensitivity Analysis for Simulation of Styrene Production Reactors

Due to the wide application of styrene as an important product in petrochemical industry, optimizing production conditions of this monomer is of great importance. In this paper, styrene reactors of Tabriz Petrochemical Complex are modeled and the good agreement was found between the model results and industrial data. The sensitivity analysis are used to predict the amount of styrene output from reactors as a function of effective input parameters such as the molar ratio of steam to ethyl benzene at the input of reactors, oxygen flow rate and inlet temperature. Also, the optimal values of effective variables for the maximum production of styrene were obtained. It was found that the product amount decreased with an increase in steam/ethylbenzene molar ratio. On the other hand, the amount of styrene increased with increasing oxygen flow rate and inlet temperature. According to results, it was confirmed that the model was able to predict the styrene production rate under different conditions.

Due to the wide application of styrene as an important product in petrochemical industry, optimizing production conditions of this monomer is of great importance. In this paper, styrene reactors of Tabriz Petrochemical Complex are modeled and the good agreement was found between the model results and industrial data. The sensitivity analysis are used to predict the amount of styrene output from reactors as a function of effective input parameters such as the molar ratio of steam to ethyl benzene at the input of reactors, oxygen flow rate and inlet temperature. Also, the optimal values of effective variables for the maximum production of styrene were obtained. It was found that the product amount decreased with an increase in steam/ethylbenzene molar ratio. On the other hand, the amount of styrene increased with increasing oxygen flow rate and inlet temperature. According to results, it was confirmed that the model was able to predict the styrene production rate under different conditions.