In the non-linear microwave drying process, the incremental improved back-propagation （BP） neural network and response surface methodology （RSM） were used to build a predictive model of the combined effects of ind...In the non-linear microwave drying process, the incremental improved back-propagation （BP） neural network and response surface methodology （RSM） were used to build a predictive model of the combined effects of independent variables （the microwave power, the acting time and the rotational frequency） for microwave drying of selenium-rich slag. The optimum operating conditions obtained from the quadratic form of the RSM are： the microwave power of 14.97 kW, the acting time of 89.58 min, the rotational frequency of 10.94 Hz, and the temperature of 136.407 ℃. The relative dehydration rate of 97.1895% is obtained. Under the optimum operating conditions, the incremental improved BP neural network prediction model can predict the drying process results and different effects on the results of the independent variables. The verification experiments demonstrate the prediction accuracy of the network, and the mean squared error is 0.16. The optimized results indicate that RSM can optimize the experimental conditions within much more broad range by considering the combination of factors and the neural network model can predict the results effectively and provide the theoretical guidance for the follow-up production process.展开更多
A thermodynamics analysis on the leaching process of selenium residue and discussion on the behaviors of aqueous ionic in the leaching process were carried out. Through thermodynamical calculation, the values of AG an...A thermodynamics analysis on the leaching process of selenium residue and discussion on the behaviors of aqueous ionic in the leaching process were carried out. Through thermodynamical calculation, the values of AG and relevant potential expressions were obtained. According to these thermodynamical data, the φ-pH diagrams of Se-H2O system at 298 and 373 K were obtained; Simultaneously, the φ-pH diagrams of SO2-H2O and SO2-Se-H2O systems were drawn at 298 K. With increasing the temperature, the stable regions of HSeO3, SeO2- and SeO2- in the φ-pH diagram of Se-H2O system become gradually large, but the limits of pH in the stable region become gradually small. The stability area of reduction precipitation in the SO2-Se-H2O system was finally determined. The results of oxidization leaching experiments of selenium residue indicate that when the mass ratio of selenium residue to sodium chlorate is 2, the concentration of sulfuric acid is 300 g/L and the residue is agitated for 3 h at leaching temperature of 80 ℃, the leaching rate of selenium could reach 97.76 %. The experimental results conform the calculated results by φ-pH diagram. The selenium reduction precipitation in oxidization-leaching solution was analyzed under the conditions of acidity of 150 g/L, the sodium sulphite concentration of 35 g/L at the reductive temperature of 23 ℃ for 120 min. And this demonstrates the thermodynamics analysis.展开更多
基金Project(50734007) supported by the National Natural Science Foundation of China
文摘In the non-linear microwave drying process, the incremental improved back-propagation （BP） neural network and response surface methodology （RSM） were used to build a predictive model of the combined effects of independent variables （the microwave power, the acting time and the rotational frequency） for microwave drying of selenium-rich slag. The optimum operating conditions obtained from the quadratic form of the RSM are： the microwave power of 14.97 kW, the acting time of 89.58 min, the rotational frequency of 10.94 Hz, and the temperature of 136.407 ℃. The relative dehydration rate of 97.1895% is obtained. Under the optimum operating conditions, the incremental improved BP neural network prediction model can predict the drying process results and different effects on the results of the independent variables. The verification experiments demonstrate the prediction accuracy of the network, and the mean squared error is 0.16. The optimized results indicate that RSM can optimize the experimental conditions within much more broad range by considering the combination of factors and the neural network model can predict the results effectively and provide the theoretical guidance for the follow-up production process.
基金Project(51072233) supported by the National Natural Science Foundation of China
文摘A thermodynamics analysis on the leaching process of selenium residue and discussion on the behaviors of aqueous ionic in the leaching process were carried out. Through thermodynamical calculation, the values of AG and relevant potential expressions were obtained. According to these thermodynamical data, the φ-pH diagrams of Se-H2O system at 298 and 373 K were obtained; Simultaneously, the φ-pH diagrams of SO2-H2O and SO2-Se-H2O systems were drawn at 298 K. With increasing the temperature, the stable regions of HSeO3, SeO2- and SeO2- in the φ-pH diagram of Se-H2O system become gradually large, but the limits of pH in the stable region become gradually small. The stability area of reduction precipitation in the SO2-Se-H2O system was finally determined. The results of oxidization leaching experiments of selenium residue indicate that when the mass ratio of selenium residue to sodium chlorate is 2, the concentration of sulfuric acid is 300 g/L and the residue is agitated for 3 h at leaching temperature of 80 ℃, the leaching rate of selenium could reach 97.76 %. The experimental results conform the calculated results by φ-pH diagram. The selenium reduction precipitation in oxidization-leaching solution was analyzed under the conditions of acidity of 150 g/L, the sodium sulphite concentration of 35 g/L at the reductive temperature of 23 ℃ for 120 min. And this demonstrates the thermodynamics analysis.
