The effectiveness of an internal filtration system intended for separation of wax-catalyst from Fischer–Tropsch synthesis products is investigated in the present study. The generalization performances of in-house Regularization Network (RN) equipped with efficient training algorithm is recruited for prediction of filtrate flux. The network was trained by resorting several sets of experimental data obtained from a specific system of air/paraffin liquid phase/alumina oxide particle conducted in a slurry bubble column reactor. The RN is employed to explore the relationship between the slurry phase temperature (10–60 °C), pressure difference (0.3, 0.6 and 0.9 bar) and time (0–120 min) on the rate of outcome filtrate from various size of filter element (4, 8 and 12 microns). The superior recall and validation performances with different exemplars data points show that the optimally trained RN which has solid roots in multivariate regularization theory, is a reliable tool for prediction of filtrate flux. Faithful generalization performance of RN revels that around 66 % reduction in filtrate flux is observed by decreasing temperature from 60
{}_{}^ \circ C to10
{}_{}^ \circ C for filter pore size of 4 microns. Decreasing of slurry viscosity is the main reason of such behavior. Increasing pressure driving force has a significant effect on elevating filtrate flux. Due to cake formation, filtrate flux is decreased from 2 to 1.4 (ml/min.cm2) at constant temperature of 60
{}_{}^ \circ C for filter pore size of 8 microns. Furthermore, the backwashing process is more effective for smaller pore size filter and temperature variation does not have any considerable effect on filter recovery.
The SCS-CN developed by the USDA Soil Conservation Service is a widely used technique for estimation of direct runoff from rainfall events. The watershed CN represents the hydrological response of watershed as an indicator of watershed potential runoff generation. The aim of this research is determining the CN from recorded rainfall-runoff events in different seasons and analyzing its relationship with rainfall components in the Jafarabad Watershed, Golestan Province. The CN values of 43 simultaneous storm events were determined using SCS-CN model and the available storm events of each season have been separated and the significant differences of CN values were analyzed using ANOVA method. The Triple Diagram Models provided by Surfer software were used to analyze the relationships of CNs and rainfall components. Results showed that the mean values of CN were 60 for summer and winter seasons and the CN values in the spring and autumn seasons were 50 and 65, respectively. The interrelationships of CN amounts and rainfall characteristic showed that the high values of CNs were related to high rainfall intensities (>10 mm/hr) and rainstorms with total rainfall more than 40 mm. Also the CN values were about >70 for the storm events with 40-80% runoff coefficient values.
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