In fluid catalytic cracking(FCC) unit, it is greatly important to control the coke yield, since the increase of coke yield not only leads to the reduction of total liquid yield, but also affects the heat balance and o...In fluid catalytic cracking(FCC) unit, it is greatly important to control the coke yield, since the increase of coke yield not only leads to the reduction of total liquid yield, but also affects the heat balance and operation of FCC unit. Consequently, it is significant to predict the coke yield accurately. The coke formation and burning reactions are affected by many parameters which influence each other, so it is difficult to establish a prediction model using traditional models. This paper combines the industrial production data and establishes a generalized regression neural network(GRNN) model and a back propagation(BP) neural network model to predict the coke yield respectively. The comparison and analysis results show that the accuracy and stability of the BP neural network prediction results are better than that of the GRNN. Then, the particle swarm optimization to optimize BP neural network(PSO-BP) and genetic algorithm to optimize the BP neural network(GA-BP) were further used to improve the prediction precision. The comparison of these models shows that they can improve the prediction precision. However, considering the accuracy and stability of the prediction results, the GA-BP model is better than PSO-BP model.展开更多
The stability of petroleum coke water slurry（PCWS） is currently a hot topic. The inherent relationship between yield stress and stability of bubble-PCWS was studied through orthogonal experiments and range analysis ...The stability of petroleum coke water slurry（PCWS） is currently a hot topic. The inherent relationship between yield stress and stability of bubble-PCWS was studied through orthogonal experiments and range analysis in this work. The results showed that the stability of bubble-PCWS was positively related to the yield stress and that the yield stress could be greatly impacted by the operation conditions during preparation of bubble-PCWS. The main factors affecting the yield stress of bubble-PCWS were solid concentration, aeration time and dosage of frother. However, the effects of aperture size of air distribution plates and type of frother on the yield stress were slight within the experimental range. The optimal conditions for the greatest yield stress were as follows： aeration time of 30 min, solid concentration of 65 wt%, frother dosage of0.030 wt% of the air-dried pulverized petroleum coke, aperture size of air distribution plate of 2-5 lm and AOS frother.The yield stress and the pour rate of bubble-PCWS under this optimum operation condition could reach maxima of more than 0.4 Pa and 96%, respectively.展开更多
Delayed coking is an important process consumption and light oil yield are important factors used to convert heavy oils to light products. Energy for evaluating the delayed coking process. This paper analyzes the ener...Delayed coking is an important process consumption and light oil yield are important factors used to convert heavy oils to light products. Energy for evaluating the delayed coking process. This paper analyzes the energy consumption and product yields of delayed coking units in China. The average energy consumption shows a decreasing trend in recent years. The energy consumption of different refineries varies greatly, with the average value of the highest energy consumption approximately twice that of the lowest energy consumption. The factors affecting both energy consumption and product yields were analyzed, and correlation models of energy consumption and product yields were established using a quadratic polynomial. The model coefficients were calculated through least square regression of collected industrial data of delayed coking units. Both models showed good calculation accuracy. The average absolute error of the energy consumption model was approximately 85 MJ/t, and that of the product yield model ranged from 1 wt% to 2.3 wt%. The model prediction showed that a large annual processing capacity and high load rate will result in a reduction in energy consumption.展开更多
文摘In fluid catalytic cracking(FCC) unit, it is greatly important to control the coke yield, since the increase of coke yield not only leads to the reduction of total liquid yield, but also affects the heat balance and operation of FCC unit. Consequently, it is significant to predict the coke yield accurately. The coke formation and burning reactions are affected by many parameters which influence each other, so it is difficult to establish a prediction model using traditional models. This paper combines the industrial production data and establishes a generalized regression neural network(GRNN) model and a back propagation(BP) neural network model to predict the coke yield respectively. The comparison and analysis results show that the accuracy and stability of the BP neural network prediction results are better than that of the GRNN. Then, the particle swarm optimization to optimize BP neural network(PSO-BP) and genetic algorithm to optimize the BP neural network(GA-BP) were further used to improve the prediction precision. The comparison of these models shows that they can improve the prediction precision. However, considering the accuracy and stability of the prediction results, the GA-BP model is better than PSO-BP model.
基金he financial supports from National Natural Science Foundation of China (Grant No. 51506185)Zhejiang Provincial Natural Science Foundation of China (Grant No. LQ15E060002)
文摘The stability of petroleum coke water slurry（PCWS） is currently a hot topic. The inherent relationship between yield stress and stability of bubble-PCWS was studied through orthogonal experiments and range analysis in this work. The results showed that the stability of bubble-PCWS was positively related to the yield stress and that the yield stress could be greatly impacted by the operation conditions during preparation of bubble-PCWS. The main factors affecting the yield stress of bubble-PCWS were solid concentration, aeration time and dosage of frother. However, the effects of aperture size of air distribution plates and type of frother on the yield stress were slight within the experimental range. The optimal conditions for the greatest yield stress were as follows： aeration time of 30 min, solid concentration of 65 wt%, frother dosage of0.030 wt% of the air-dried pulverized petroleum coke, aperture size of air distribution plate of 2-5 lm and AOS frother.The yield stress and the pour rate of bubble-PCWS under this optimum operation condition could reach maxima of more than 0.4 Pa and 96%, respectively.
文摘Delayed coking is an important process consumption and light oil yield are important factors used to convert heavy oils to light products. Energy for evaluating the delayed coking process. This paper analyzes the energy consumption and product yields of delayed coking units in China. The average energy consumption shows a decreasing trend in recent years. The energy consumption of different refineries varies greatly, with the average value of the highest energy consumption approximately twice that of the lowest energy consumption. The factors affecting both energy consumption and product yields were analyzed, and correlation models of energy consumption and product yields were established using a quadratic polynomial. The model coefficients were calculated through least square regression of collected industrial data of delayed coking units. Both models showed good calculation accuracy. The average absolute error of the energy consumption model was approximately 85 MJ/t, and that of the product yield model ranged from 1 wt% to 2.3 wt%. The model prediction showed that a large annual processing capacity and high load rate will result in a reduction in energy consumption.
