Multi-objective optimization of urea injection parameters of selective catalytic reduction system based SSABP-NSGA-II-TOPSIS

Selective catalyst reduction (SCR) system efficiency is significantly affected by issues like uneven ammonia distribution and incomplete urea decomposition, which are closely related to urea injection parameters. Initially, a 3D CFD model was developed to analyze how spray angle, offset angle, the distance between the nozzle and the front section of the catalyst, and injection velocity affect NOx conversion and NH3 uniformity. Then, a hybrid optimization framework combining SSABP neural network with NSGA-II and TOPSIS is used to optimize the impact of four parameters on the SCR system. The SSABP surrogate model showed good predictive accuracy compared with CFD simulations, with error metrics such as Mean…

• NN
  National Natural Science Foundation of China

  Award: 22572038
• NS
  Natural Science Foundation of Guangxi Province

  Award: 2022GXNSFFA035029