[TiO2],t and pH are named as the independent variables and the percentage of decolor(DC%)as the dependent variable.A Box-Behnken design and U12(6×4×3)design with three factors were established to form the tr...[TiO2],t and pH are named as the independent variables and the percentage of decolor(DC%)as the dependent variable.A Box-Behnken design and U12(6×4×3)design with three factors were established to form the training set and the validation set,respectively.And back propagation neural network(BPNN)model is adopted in order to establish the model of photo-catalytic degradation about weak acidic dyes mixture of the GRS big red and weak acid red R.The best result shows that the correlation coefficient(R)is 0.9345 and the mean relative error between the predictive value and experimental value(MRE(%))is 3.23,for training set;the value of R is 0.9257,MRE(%)is 2.75,for the validation set.Besides,we discussed the influences of the pH,[TiO2],and t vs.DC% by the BPNN model.The optimized experimental condition obtained is pH=5.0,[TiO2]=1.50g/L,and t=40min based on the BPNN model,and combination with optimization of nonlinear constraints programming.The experimental value of DC is 99.23%,the predictive value is 98.98%,and the relative error is-0.25% between the predictive value and the experimental value,in the optimized experimental condition.Above all these indicate that the model can not only simulate the system of photo-catalytic degradation commendably but also can obtain the optimal experimental conditions.展开更多
The class variable source GRS 1915+105 exhibits a wide range of time variabilities on timescales of a few seconds to a few days. Depending on the count rates in different energy bands and the nature of the conventiona...The class variable source GRS 1915+105 exhibits a wide range of time variabilities on timescales of a few seconds to a few days. Depending on the count rates in different energy bands and the nature of the conventional color-color diagram, the variabilities were classified into sixteen classes that were later sequenced in ascending order of Comptonization Efficiency(CE), which is the ratio of power-law and blackbody photons. However, CE estimation is based on an empirical model which does not provide us with a comprehensive picture regarding accretion flow dynamics around the central source. In reality, the accretion flow is comprised of two components: the high angular momentum Keplerian flow in the form of a radiatively efficient disk and a low angular momentum radiatively inefficient sub-Keplerian halo enveloping the disk. These two components contribute differently to the overall flux due to the differences in their radiative efficiencies. Therefore, it is necessary to analyze the spectral behaviors and time variabilities in terms of accretion rates. In χ class, X-ray flux is steady with no significant variation, however various χsubclasses are observed at different X-ray fluxes and variations of count rates across different χ subclasses must be linked to the variation of flow parameters such as the accretion rates, be it the Keplerian disk rate and/or the low angular momentum halo rate. This motivated us to analyze the spectra of the χ class data implementing the physical Two Component Advective Flow(TCAF) solution which directly extracts these two rates from spectral fits. We find that in the χ2,4 classes, which are reportedly devoid of significant outflows, the spectra could be fitted well applying the TCAF solution alone. In the χ1,3 classes, which are always linked with outflows, a cutoff power-law model is needed in addition to the TCAF solution.At the same time, the normalization required by this model along with the variation of photon index and exponential roll-off factor provides us with information on the relative dominance of the outflow in the latter two classes. TCAF fit also supplies us with the size and location of the Compton cloud along with its optical depth. Thus by fitting with TCAF, a physical understanding of the flow geometry in different χclasses of GRS 1915+105 has been obtained.展开更多
文摘[TiO2],t and pH are named as the independent variables and the percentage of decolor(DC%)as the dependent variable.A Box-Behnken design and U12(6×4×3)design with three factors were established to form the training set and the validation set,respectively.And back propagation neural network(BPNN)model is adopted in order to establish the model of photo-catalytic degradation about weak acidic dyes mixture of the GRS big red and weak acid red R.The best result shows that the correlation coefficient(R)is 0.9345 and the mean relative error between the predictive value and experimental value(MRE(%))is 3.23,for training set;the value of R is 0.9257,MRE(%)is 2.75,for the validation set.Besides,we discussed the influences of the pH,[TiO2],and t vs.DC% by the BPNN model.The optimized experimental condition obtained is pH=5.0,[TiO2]=1.50g/L,and t=40min based on the BPNN model,and combination with optimization of nonlinear constraints programming.The experimental value of DC is 99.23%,the predictive value is 98.98%,and the relative error is-0.25% between the predictive value and the experimental value,in the optimized experimental condition.Above all these indicate that the model can not only simulate the system of photo-catalytic degradation commendably but also can obtain the optimal experimental conditions.
基金support from a fellowship of the S.N.Bose National Centre for Basic Sciences,Kolkata,Indiapartial support from the DST/GITA sponsored India-Taiwan(China)collaborative project fund(GITA/DST/TWN/P76/2017)+1 种基金partial support from the ISRO sponsored RESPOND project(ISRO/RES/2/418/17-18)fundsupported in part by the Higher Education Dept.of the Govt.of West Bengal,India。
文摘The class variable source GRS 1915+105 exhibits a wide range of time variabilities on timescales of a few seconds to a few days. Depending on the count rates in different energy bands and the nature of the conventional color-color diagram, the variabilities were classified into sixteen classes that were later sequenced in ascending order of Comptonization Efficiency(CE), which is the ratio of power-law and blackbody photons. However, CE estimation is based on an empirical model which does not provide us with a comprehensive picture regarding accretion flow dynamics around the central source. In reality, the accretion flow is comprised of two components: the high angular momentum Keplerian flow in the form of a radiatively efficient disk and a low angular momentum radiatively inefficient sub-Keplerian halo enveloping the disk. These two components contribute differently to the overall flux due to the differences in their radiative efficiencies. Therefore, it is necessary to analyze the spectral behaviors and time variabilities in terms of accretion rates. In χ class, X-ray flux is steady with no significant variation, however various χsubclasses are observed at different X-ray fluxes and variations of count rates across different χ subclasses must be linked to the variation of flow parameters such as the accretion rates, be it the Keplerian disk rate and/or the low angular momentum halo rate. This motivated us to analyze the spectra of the χ class data implementing the physical Two Component Advective Flow(TCAF) solution which directly extracts these two rates from spectral fits. We find that in the χ2,4 classes, which are reportedly devoid of significant outflows, the spectra could be fitted well applying the TCAF solution alone. In the χ1,3 classes, which are always linked with outflows, a cutoff power-law model is needed in addition to the TCAF solution.At the same time, the normalization required by this model along with the variation of photon index and exponential roll-off factor provides us with information on the relative dominance of the outflow in the latter two classes. TCAF fit also supplies us with the size and location of the Compton cloud along with its optical depth. Thus by fitting with TCAF, a physical understanding of the flow geometry in different χclasses of GRS 1915+105 has been obtained.
