Catalytic cracking is the main method to lighten heavy crude oil,this process can produce high quality oil products such as gasoline and diesel,but also produces a large amount of fluid catalytic cracking slurry(FCCS)...Catalytic cracking is the main method to lighten heavy crude oil,this process can produce high quality oil products such as gasoline and diesel,but also produces a large amount of fluid catalytic cracking slurry(FCCS).The catalyst particles in FCCS seriously restrict the secondary processing of FCCS and need to be removed,and the properties of Fccs is an important factor that affects the removal efficiency of the catalyst particles.Based on the"effective contact point"model proposed by the research group,this study further proposed the"electrostatic separation efficiency calculation"model.In this model,since Fccs has a uniform distribution of catalyst particles,the ratio of the number of catalyst particles can be expressed as the ratio of area to achieve the calculation of separation efficiency.Then the catalyst removal efficiency under different viscosity was analyzed,thus verifying the feasibility of this model.The effects of temperature and mass ratio of four components on the viscosity of FccS were investigated respectively,then the effects of temperature and four components'mass ratio on the electrostatic sep-aration can be directly converted into the effect of viscosity on the electrostatic separation efficiency.All the results show the electrostatic separation efficiency decreases with increasing viscosity,and the best separationtemperatureis120℃.展开更多
The characteristics of the packing material under an alternating electric field are an important factor in the removal of FCCS particles.In this study,the electric field distribution of a separation unit consisting of...The characteristics of the packing material under an alternating electric field are an important factor in the removal of FCCS particles.In this study,the electric field distribution of a separation unit consisting of packed spheres under an alternating electric field is simulated,and the movement mechanism of catalyst particles is analysed.An"effective contact point"model is derived to predict the adsorption of filler contact points on catalyst particles under the alternating electric field,and the model is validated by simulations and experiments.The numerical calculation and experimental results indicate that the electrical properties of the filler spheres,the filler angleθ,and the frequency f of the alternating electric field affect the adsorption of catalyst particles.As the frequency of the electric field increases,the particle removal efficiency of the high-conductivity filler(silicon carbide)increases and then settles,and the separation efficiency of the low-conductivity filler(glass,zirconia)is not sensitive to the change in electric field frequency.展开更多
Metastable nanostructured electrocatalyst with a completely different surface environment compared to conventional phase-based electrocatalyst often shows distinctive catalytic property.Although Ru-based electrocataly...Metastable nanostructured electrocatalyst with a completely different surface environment compared to conventional phase-based electrocatalyst often shows distinctive catalytic property.Although Ru-based electrocatalysts have been widely investigated toward hydrogen oxidation reaction(HOR)under alkaline electrolytes,these studies are mostly limited to conventional hexagonal-close-packed(hcp)phase,mainly arising from the lack of sufficient synthesis strategies.In this study,we report the precise synthesis of metastable binary RuW alloy with face-centered-cubic(fcc)phase.We find that the introduction of W can serve as fcc phase seeds and reduce the formation energy of metastable fcc-RuW alloy.Impressively,fcc-RuW exhibits remarkable alkaline HOR performance and stability with the activity of 0.67 mA cm_(Ru)^(-2)which is almost five and three times higher than that of hcp-Ru and commercial Pt/C,respectively,which is attributed to the optimized binding strength of adsorbed hydroxide intermediate derived from tailored electronic structure through W doping and phase engineering.Moreover,this strategy can also be applied to synthesize other metastable fcc-RuCr and fcc-RuMo alloys with enhanced HOR performances.展开更多
Samples(25500)were collected from a selective catalytic reduction(SCR)denitrification system in a fluid catalytic cracking unit and preprocessed using the quartile method and the K-nearest neighbors interpolation meth...Samples(25500)were collected from a selective catalytic reduction(SCR)denitrification system in a fluid catalytic cracking unit and preprocessed using the quartile method and the K-nearest neighbors interpolation method to remove outliers.Using the Pearson correlation coefficient and LightGBM feature score method,13 key operational variables were identified and used to establish a model to predict outlet nitrogen oxide(NO_(x))concentration in an SCR system with backpropagation neural network,long short-term memory(LSTM)and LSTM-attention fully connected(FC)model,respectively.The LSTM-attention FC model showed better accuracy and generalization capability compared with other models.Its mean square error,mean absolute error,and coefficient of determination on the training and test datasets were 11.32 and 12.51,3.65%and 3.97%,and 0.96 and 0.94,respectively.Furthermore,a combination of the LSTM-attention FC model with a genetic algorithm used to optimize four feature variables including ammonia pressure compensation,inlet pressure,gas inlet upper temperature,and outlet ammonia concentration.The outlet NO_(x)concentration could be controlled below 80±3 mg/m^(3),and the ammonia slip concentration could be controlled below 0.1 mg/m^(3),demonstrating that the optimization model can provide effective guidance for reducing NO_(x)emissions and ammonia slip of SCR systems.展开更多
基金supported by the[Natural Science Foundation Project of Shandong Province#1]under Grant[ZR2019MEE033][Fundamental Research Funds for the central Universities#2]under Grant[19CX02035A].
文摘Catalytic cracking is the main method to lighten heavy crude oil,this process can produce high quality oil products such as gasoline and diesel,but also produces a large amount of fluid catalytic cracking slurry(FCCS).The catalyst particles in FCCS seriously restrict the secondary processing of FCCS and need to be removed,and the properties of Fccs is an important factor that affects the removal efficiency of the catalyst particles.Based on the"effective contact point"model proposed by the research group,this study further proposed the"electrostatic separation efficiency calculation"model.In this model,since Fccs has a uniform distribution of catalyst particles,the ratio of the number of catalyst particles can be expressed as the ratio of area to achieve the calculation of separation efficiency.Then the catalyst removal efficiency under different viscosity was analyzed,thus verifying the feasibility of this model.The effects of temperature and mass ratio of four components on the viscosity of FccS were investigated respectively,then the effects of temperature and four components'mass ratio on the electrostatic sep-aration can be directly converted into the effect of viscosity on the electrostatic separation efficiency.All the results show the electrostatic separation efficiency decreases with increasing viscosity,and the best separationtemperatureis120℃.
基金supported by the Natural Scienceof Shandong Province,China(ZR2019MEE033)。
文摘The characteristics of the packing material under an alternating electric field are an important factor in the removal of FCCS particles.In this study,the electric field distribution of a separation unit consisting of packed spheres under an alternating electric field is simulated,and the movement mechanism of catalyst particles is analysed.An"effective contact point"model is derived to predict the adsorption of filler contact points on catalyst particles under the alternating electric field,and the model is validated by simulations and experiments.The numerical calculation and experimental results indicate that the electrical properties of the filler spheres,the filler angleθ,and the frequency f of the alternating electric field affect the adsorption of catalyst particles.As the frequency of the electric field increases,the particle removal efficiency of the high-conductivity filler(silicon carbide)increases and then settles,and the separation efficiency of the low-conductivity filler(glass,zirconia)is not sensitive to the change in electric field frequency.
基金the support from the National Natural Science Foundation of China(22272121,21972107)the National Key Research and Development program of China(2021YFB4001200)。
文摘Metastable nanostructured electrocatalyst with a completely different surface environment compared to conventional phase-based electrocatalyst often shows distinctive catalytic property.Although Ru-based electrocatalysts have been widely investigated toward hydrogen oxidation reaction(HOR)under alkaline electrolytes,these studies are mostly limited to conventional hexagonal-close-packed(hcp)phase,mainly arising from the lack of sufficient synthesis strategies.In this study,we report the precise synthesis of metastable binary RuW alloy with face-centered-cubic(fcc)phase.We find that the introduction of W can serve as fcc phase seeds and reduce the formation energy of metastable fcc-RuW alloy.Impressively,fcc-RuW exhibits remarkable alkaline HOR performance and stability with the activity of 0.67 mA cm_(Ru)^(-2)which is almost five and three times higher than that of hcp-Ru and commercial Pt/C,respectively,which is attributed to the optimized binding strength of adsorbed hydroxide intermediate derived from tailored electronic structure through W doping and phase engineering.Moreover,this strategy can also be applied to synthesize other metastable fcc-RuCr and fcc-RuMo alloys with enhanced HOR performances.
基金This work was supported by the SINOPEC:Development of Remote Diagnosis Technology for FCC Flue Gas Desulfurization and Denitrification(320076).
文摘Samples(25500)were collected from a selective catalytic reduction(SCR)denitrification system in a fluid catalytic cracking unit and preprocessed using the quartile method and the K-nearest neighbors interpolation method to remove outliers.Using the Pearson correlation coefficient and LightGBM feature score method,13 key operational variables were identified and used to establish a model to predict outlet nitrogen oxide(NO_(x))concentration in an SCR system with backpropagation neural network,long short-term memory(LSTM)and LSTM-attention fully connected(FC)model,respectively.The LSTM-attention FC model showed better accuracy and generalization capability compared with other models.Its mean square error,mean absolute error,and coefficient of determination on the training and test datasets were 11.32 and 12.51,3.65%and 3.97%,and 0.96 and 0.94,respectively.Furthermore,a combination of the LSTM-attention FC model with a genetic algorithm used to optimize four feature variables including ammonia pressure compensation,inlet pressure,gas inlet upper temperature,and outlet ammonia concentration.The outlet NO_(x)concentration could be controlled below 80±3 mg/m^(3),and the ammonia slip concentration could be controlled below 0.1 mg/m^(3),demonstrating that the optimization model can provide effective guidance for reducing NO_(x)emissions and ammonia slip of SCR systems.
