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- 저자 : Gholam Reza Ghezelbash (검색결과 2 건)
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Mohammad S. Pakbaz,Ali Kolahi,Gholam Reza Ghezelbash 대한토목학회 2022 KSCE JOURNAL OF CIVIL ENGINEERING Vol.26 No.3
Microbial induced calcite precipitation (MICP) technology in recent decade has been introduced to geotechnical engineering society as a mean for soil improvement. In this regard stimulation of indigenous aerobic and anaerobic bacteria is an alternative to bioaugmentation process in which bacteria are added to the soil. The aim of this study was to compare the effects of the bio cementation process on natural sand samples by stimulation of indigenous anaerobic and aerobic bacteria. About 109 natural intact samples of poorly graded sand samples were collected from the field in polyvinyl chloride (PVC) tubes 10 cm in diameter and 50 − 100 cm in height. They were then treated with different stimulating solutions by injection procedure. After 7, 15, and 21 days of treatment, direct shear (DS), unconfined compressive strength (UCS) test results, calcite content, and scanning electron microscopy (SEM) images obtained using an instrument equipped with an energy dispersive X-ray spectroscope (EDX) were used to analyze the samples. Results demonstrated that the values of UCS for the samples through stimulation of aerobic bacteria were 22 − 73% higher than those for the samples treated through stimulation of anaerobic bacteria. Samples treated for stimulation of both aerobic and anaerobic bacteria produced 8 − 15% calcite whereas samples treated for stimulation of either aerobic or anaerobic bacteria alone produced only1-6% calcite. The values of UCS for samples treated for stimulation of both aerobic and anaerobic bacteria were increased by 254 − 283% and those for samples treated for stimulation of either aerobic or anaerobic bacteria alone increased by 156 − 270% from that for the untreated samples.
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Ebrahim Alipanahpour Dil,Mehrorang Ghaedi,Gholam Reza Ghezelbash,Arash Asfaram,Mihir Kumar Purkait 한국공업화학회 2017 Journal of Industrial and Engineering Chemistry Vol.48 No.-
In this research, biosorption of Hg2+, Pb2+ and Cu2+ from aqueous solution via Yarrowia lipolytica 70562living mass was described. Correction and dependency of biosorption efficiency to effective variables likepH, initial Hg2+, Pb2+ and Cu2+ concentration, contact time and temperature was studied by centralcomposite design under response surface methodology. Three responses were simultaneously studied bynumerical optimization methodology. The optimum biosorption efficiency of Hg2+, Pb2+ and Cu2+ ions at18, 22 and 25 mg L 1 onto Y. lipolytica 70562 was found to be 99.26%, 101.15% and 99.74% at pH of 6.4 and25 C after around 8 h under well mixing. Finally, optimum condition for acceptable and repeatableagreement among experimental and real data was explored. The artificial neural network (ANN) modelwas used for predicting simultaneous biosorption of Hg2+, Pb2+ and Cu2+ ions based on experimental data. It was found that using ANN model with 12 neurons at hidden layer for all three ions, the R2 of 0.989 andMSE of 993 for Hg2+ ion were obtained. The R2 of 0.981 and MSE of 1.155 for Pb2+ ion were obtained andalso for Cu2+ ion the values of the R2 and MSE were found to be 0.971 and 1.589, respectively. Langmuirisotherm model was bestfitted with the equilibrium experimental. The experimental kinetic data wasrepresented well by using pseudo-second-order model and intraparticle diffusion model.
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