Optimization of structure parameters in a coal pyrolysis filtration system based on CFD and quadratic regression orthogonal combination and a genetic algorithm

An optimization method of structure parameters based on the quadratic regression orthogonal combination (QROC) and Genetic Algorithm (GA) is proposed in this work. The following work has been conducted to improve the performance of the coal pyrolysis filtration system and prolong the service life of the filter tubes based on QROC-GA method. Firstly, a simulation model is established and two factors always are chosen as optimization objectives. Then one single factor regression prediction algorithm is used to optimize each factor separately while the result was not satisfactory. Secondly, QROC is introduced to achieve the optimization of two factors in the filtration system. The regression relationship is obtained proved to be effective by statistical test and back propagation neural network (BPNN). Finally, a QROC-GA method is established to find the optimization points. Then a verification calculation is done with CFD again. The optimal result has the parameters that phi=40 degrees and psi=25 degrees. From the simulation results, the mean square error is 0.401. The mean square error is 0.4992 by the QROC-GA results. The errors are within 0.1 between CFD and QROC-GA. The QROC-GA model has a good effect in the prediction of models under changing parameters, and the significance is also confirmed.