Based on the experimental data of Mn_(1)Co_(0.5)Cr_(0.5)O_(x)catalysts and the component transport model in computational fluid dynamics(CFD),a kinetic model for the standard NH_(3)-SCR(NH_(3)selective catalytic reduc...Based on the experimental data of Mn_(1)Co_(0.5)Cr_(0.5)O_(x)catalysts and the component transport model in computational fluid dynamics(CFD),a kinetic model for the standard NH_(3)-SCR(NH_(3)selective catalytic reduction)process was effectively established.The objective of the model development was to predict the denitrification reaction rate of the catalyst,which incorporates various factors such as the Arrhenius parameters(pre-exponential factor and activation energy),inertial resistance,viscous resistance,and surface-to-volume ratio.To verify the practicability of the model,simulation results were compared with actual experimental data.The effects of NH_(3),NO,O_(2)concentrations,and gas hourly space velocity(GHSV)on NO conversion were simulated and analyzed.Subsequently,the NO conversion prediction model was trained and established using a combination of numerical simulation results,backpropagation neural network,and genetic algorithm(BP-GA).Furthermore,the significance of the impact that various factors had on the denitrification activity of the catalyst was determined.展开更多
基金supported by Science and Technology Research Project of Henan Province(242102230078)Key Research Project of Higher Education Institutions of Henan Province(23A470002)Innovative Research Team of Henan Polytechnic University(T2020-3).
文摘Based on the experimental data of Mn_(1)Co_(0.5)Cr_(0.5)O_(x)catalysts and the component transport model in computational fluid dynamics(CFD),a kinetic model for the standard NH_(3)-SCR(NH_(3)selective catalytic reduction)process was effectively established.The objective of the model development was to predict the denitrification reaction rate of the catalyst,which incorporates various factors such as the Arrhenius parameters(pre-exponential factor and activation energy),inertial resistance,viscous resistance,and surface-to-volume ratio.To verify the practicability of the model,simulation results were compared with actual experimental data.The effects of NH_(3),NO,O_(2)concentrations,and gas hourly space velocity(GHSV)on NO conversion were simulated and analyzed.Subsequently,the NO conversion prediction model was trained and established using a combination of numerical simulation results,backpropagation neural network,and genetic algorithm(BP-GA).Furthermore,the significance of the impact that various factors had on the denitrification activity of the catalyst was determined.
