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permeability-coefficient
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Laboratory and Numerical Modeling of Hydraulic Behavior of Saturated Fine Grained Soils Dewatered by Electrokinetic Geosynthetic
, M.Sc. Thesis Sharif University of Technology ; Pak, Ali (Supervisor) ; Shariatmadari, Nader (Co-Advisor)
Abstract
Most available methods which are well able to improve or dewater coarse soils have little success dealing with fine soils and clays and using these methods to dewater clays needs great amount of time and money. Electrokinetic Geosynthetic is one of new methods that have had a promising future. Regarding the importance and tremendous usage of dewatering in fine soils, the efficiency of electrokinetic geosynthetic method in dewatering fine soils has been taken under the consideration in this research. Following laboratory experimentation, numerical modeling of this process has been done. In this research some laboratory test has been done on kaolinite clay and the effects of pH of specimen,...
Analyzing and predicting permeability coefficient of roller-compacted concrete (RCC)
, Article Journal of Testing and Evaluation ; Volume 49, Issue 3 , 2019 ; 00903973 (ISSN) ; Toufigh, V ; Ghaemian, M ; Sharif University of Technology
ASTM International
2019
Abstract
The permeability of roller-compacted concrete (RCC) substantially affects its functionality and safety. This study investigates the effect of mix design parameters on the performance of RCC. For this purpose, approximately 500 laboratory specimens were prepared and tested. A formula and an artificial neural network (ANN) were proposed to predict the permeability coefficient of RCC by considering the main parameters, which were then verified independently using new specimens. Furthermore, the experimental data were analyzed by the Taguchi method and analysis of variance (ANOVA) to evaluate the level of parameter contribution. Based on the results, the permeability coefficient was highly...
DeePore: A deep learning workflow for rapid and comprehensive characterization of porous materials
, Article Advances in Water Resources ; Volume 146 , 2020 ; Babaei, M ; Shams, R ; Wang, Y. D ; Chung, T ; Sharif University of Technology
Elsevier Ltd
2020
Abstract
DeePore2 is a deep learning workflow for rapid estimation of a wide range of porous material properties based on the binarized micro–tomography images. By combining naturally occurring porous textures we generated 17,700 semi–real 3–D micro–structures of porous geo–materials with size of 2563 voxels and 30 physical properties of each sample are calculated using physical simulations on the corresponding pore network models. Next, a designed feed–forward convolutional neural network (CNN) is trained based on the dataset to estimate several morphological, hydraulic, electrical, and mechanical characteristics of the porous material in a fraction of a second. In order to fine–tune the CNN design,...
Chitosan-g-PLGA copolymer as a thermosensitive membrane
, Article Carbohydrate Polymers ; Volume 80, Issue 3 , 2010 , Pages 740-746 ; 01448617 (ISSN) ; Abdekhodaie, M. J ; Sharif University of Technology
2010
Abstract
A thermosensitive copolymer was synthesized by graft copolymerization of poly(lactide-co-glycolide) (PLGA) copolymers onto the surface of chitosan membranes. Acryloyl chloride was used as a coupling reagent for the covalent attachment of PLGA to the chitosan membranes. FTIR spectroscopy and DSC analysis were used to characterize the resulting graft copolymer. Thermosensitive swelling behaviors of the copolymer were investigated as well. The membranes exhibited reversible swelling-shrinking behavior; higher swelling ratios were obtained observed at higher temperatures. Drug permeation studies were carried out using vancomycin hydrochloride and betamethasone sodium phosphate as the model...