| This paper used Aspen Plus software to simulate the dichloromethane-ethanol-water triple mixture, choosing the product purity in the overhead and the reboiler duty as the objective functions and using the method of the factor analysis to investigate the effects of theoretical plate number of distillate column,the feed position,the solvent feed position,the reflux ratio,the solvent rate on objective functions. Based on simulated calculation, a experimental verification has been done. It shows that simulation results are reliable.According to the factors of distillation process, the orthogonal experiment was designed. The optimum operating conditions were found out by range analysis and variance analysis on simulation results. For dichloromethane column, choosing the dichloromethane purity in the overhead as objective function, the optimum technology parameters are as follows: the theoretical plate number is 20, the feed location is 17, and the reflux ratio is 1.8.The purity of dichloromethane is 99.20%. While choosing the reboiler duty as objective function, the optimum technology parameters are the theoretical plate number is 20, the feed location is 15, and the reflux ratio is 1.2. The energy consumption is 20.07 kW. A forecasting modle is founded by Artificial Neural Network and got the optimized results. The purity of dichloromethane is 99.28%, and the energy consumption is 18.25 kW.For ethonal column, choosing the ethanol purity in the overhead as objective function, the optimum technology parameters are as follows: the theoretical plate number is 12, the feed location is 11, the reflux ratio is 1.4, the solvent location is 4, and the solvent ratio is 1.1. The purity of dichloromethane is 99.99%. While choosing the reboiler duty as objective function, the optimum technology parameters are as follows: the theoretical plate number is 15, the feed location is 8, the reflux ratio is 1.0, the solvent location is 3, and the solvent ratio is 0.7. The energy consumption is 0.97 kW. By using the neural network modeling, the optimized results was got. The purity of ethanol is 99.71%, and the energy consumption is 0.78 kW.This paper combined artificial neural network and orthogonal design in the parameters optimization of distillate separation process of dichloromethane-ethanol-water triple mixture. This method can short the time of parameter optimization process obviously and improve the efficiency of process design. It can obtain more optimized results than using orthogonal design method simply. This paper proposed a research and optimization methods about distillation separating dichloromethaneethanol-water triple system. The study has the extremely vital significance for the recycle of dichloromethane and ethanol. This will lay the foundation for the future pilot trial and industrial application. |
