To reduce the fuel consumption and emissions and also enhance the molten aluminum quality, a mathematical model with user-developed melting model and burning capacity model, were established according to the features ...To reduce the fuel consumption and emissions and also enhance the molten aluminum quality, a mathematical model with user-developed melting model and burning capacity model, were established according to the features of melting process of regenerative aluminum melting furnaces. Based on validating results by heat balance test for an aluminum melting furnace, CFD （computational fluid dynamics） technique, in association with statistical experimental design were used to optimize the melting process of the aluminum melting furnace. Four important factors influencing the melting time, such as horizontal angle between burners, height-to-radius ratio, natural gas mass flow and air preheated temperature, were identified by PLACKETT-BURMAN design. A steepest descent method was undertaken to determine the optimal regions of these factors. Response surface methodology with BOX-BEHNKEN design was adopted to further investigate the mutual interactions between these variables on RSD （relative standard deviation） of aluminum temperature, RSD of furnace temperature and melting time. Multiple-response optimization by desirability function approach was used to determine the optimum melting process parameters. The results indicate that the interaction between the height-to-radius ratio and horizontal angle between burners affects the response variables significantly. The predicted results show that the minimum RSD of aluminum temperature （12.13%）, RSD of furnace temperature （18.50%） and melting time （3.9 h） could be obtained under the optimum conditions of horizontal angle between burners as 64°, height-to-radius ratio as 0.3, natural gas mass flow as 599 m3/h, and air preheated temperature as 639 ℃. These predicted values were further verified by validation experiments. The excellent correlation between the predicted and experimental values confirms the validity and practicability of this statistical optimum strategy.展开更多
In this work,Fe3O4-Al2O3@CNFs nanocomposite was synthesised and used as a nanosorbent in the ultrasound-assisted dispersive magnetic solid phase extraction(UA-DMSPE)of 17-beta estradiol(E2)in wastewater samples.The qu...In this work,Fe3O4-Al2O3@CNFs nanocomposite was synthesised and used as a nanosorbent in the ultrasound-assisted dispersive magnetic solid phase extraction(UA-DMSPE)of 17-beta estradiol(E2)in wastewater samples.The quantification of E2 was achieved using high performance liquid chromatography coupled with diode array detector(HPLC-DAD).Various parameters affecting the efficiency of this sample preparation technique were optimised to achieve excellent sensitivity and high recoveries of E2.Response surface methodology was utilised for optimisation of these parameters.Using the optimised conditions,the linear dynamic range was achieved in the range of 0.1e1000 mgL^-1and the correlation coefficient was found to be 0.9981.The preconcentration factor,enrichment factor,limit of detection(LOD)and limit of quantification(LOQ)were 67,169,0.025 mgL^-1and 0.083 mg L1,respectively.The relative standard deviation(%RSD)for the intraday(n?10)and interday(n?5 working days)were 1.8%and 3.3%,respectively.The developed UA-DMSPE/HPLC-DAD method was applied for the preconcentration and determination of E2 in wastewater samples.The obtained results indicated that E2 was present in the wastewater samples.展开更多
基金Project(2009BSXT022) supported by the Dissertation Innovation Foundation of Central South University, ChinaProject(07JJ4016) supported by Natural Science Foundation of Hunan Province, ChinaProject(U0937604) supported by National Natural Science Foundation of China
文摘To reduce the fuel consumption and emissions and also enhance the molten aluminum quality, a mathematical model with user-developed melting model and burning capacity model, were established according to the features of melting process of regenerative aluminum melting furnaces. Based on validating results by heat balance test for an aluminum melting furnace, CFD （computational fluid dynamics） technique, in association with statistical experimental design were used to optimize the melting process of the aluminum melting furnace. Four important factors influencing the melting time, such as horizontal angle between burners, height-to-radius ratio, natural gas mass flow and air preheated temperature, were identified by PLACKETT-BURMAN design. A steepest descent method was undertaken to determine the optimal regions of these factors. Response surface methodology with BOX-BEHNKEN design was adopted to further investigate the mutual interactions between these variables on RSD （relative standard deviation） of aluminum temperature, RSD of furnace temperature and melting time. Multiple-response optimization by desirability function approach was used to determine the optimum melting process parameters. The results indicate that the interaction between the height-to-radius ratio and horizontal angle between burners affects the response variables significantly. The predicted results show that the minimum RSD of aluminum temperature （12.13%）, RSD of furnace temperature （18.50%） and melting time （3.9 h） could be obtained under the optimum conditions of horizontal angle between burners as 64°, height-to-radius ratio as 0.3, natural gas mass flow as 599 m3/h, and air preheated temperature as 639 ℃. These predicted values were further verified by validation experiments. The excellent correlation between the predicted and experimental values confirms the validity and practicability of this statistical optimum strategy.
基金the Department of Science and Technology(DST,South Africa)/National Nanoscience Postgraduate Teaching and Training Programme(NNPTTP)and National Research Foundation(NRF,South Africa,grant no.99270&91230).
文摘In this work,Fe3O4-Al2O3@CNFs nanocomposite was synthesised and used as a nanosorbent in the ultrasound-assisted dispersive magnetic solid phase extraction(UA-DMSPE)of 17-beta estradiol(E2)in wastewater samples.The quantification of E2 was achieved using high performance liquid chromatography coupled with diode array detector(HPLC-DAD).Various parameters affecting the efficiency of this sample preparation technique were optimised to achieve excellent sensitivity and high recoveries of E2.Response surface methodology was utilised for optimisation of these parameters.Using the optimised conditions,the linear dynamic range was achieved in the range of 0.1e1000 mgL^-1and the correlation coefficient was found to be 0.9981.The preconcentration factor,enrichment factor,limit of detection(LOD)and limit of quantification(LOQ)were 67,169,0.025 mgL^-1and 0.083 mg L1,respectively.The relative standard deviation(%RSD)for the intraday(n?10)and interday(n?5 working days)were 1.8%and 3.3%,respectively.The developed UA-DMSPE/HPLC-DAD method was applied for the preconcentration and determination of E2 in wastewater samples.The obtained results indicated that E2 was present in the wastewater samples.
