Sharif Digital Repository

In this study, we have utilized 3-D micro-tomography images of real and synthetic rocks to introduce two mathematical correlations which estimate the distribution parameters of 3-D coordination number using a single 2-D cross-sectional image. By applying a watershed segmentation algorithm, it is found that the distribution of 3-D coordination number is acceptably predictable by statistical analysis of the network extracted from 2-D images. In this study, we have utilized 25 volumetric images of rocks in order to propose two mathematical formulas. These formulas aim to approximate the average and standard deviation of coordination number in 3-D pore networks. Then, the formulas are applied... 

In this work the effects of backwash pressure, duration of acid and sodium hydroxide backwashing, sodium hydroxide concentration, and the duration of forward washing on performance of permeate flux recovery (PFR) were investigated. A two-level fractional factorial design (FFD) was used to design the experiments. The ability of back propagation neural network (BPNN) and radial basis function neural network (RBFNN) in predicting the performance of cleaning-in-place (CIP) of hydrophilic polyethersulfone (PES) membrane were investigated. It is found that BPNN has better ability in predicting the PFR performance than RBFNN. The best architecture of BPNN was a network consisting of 1 hidden layer... 

This study implements an adaptive neuro-fuzzy inference system (ANFIS) approach to predict the precipitation amount of the asphaltene using temperature (T), dilution ratio (Rv), and molecular weight of different n-alkanes. Results are then evaluated using graphical and statistical error analysis methods, confirming the model’s great ability for appropriate prediction of the precipitation amount. Mean squared error and determination coefficient (R2) values of 0.036 and 0.995, respectively are obtained for the proposed ANFIS model. Results are then compared to those from previously reported correlations revealing the better performance of the proposed model. © 2018, © 2018 Taylor & Francis... 

The objective of this study was to model the extent of improvement in the degradability of phenol dyes by SnO2/Fe3O4 nanoparticles using a photocatalytic reactor. The effect of operative parameters including catalyst concentration, initial dye concentration, stirring intensity, and UV radiation intensity on the photocatalytic batch reactor during removal of phenol red was investigated. Fractional factorial design and response surface methodology were used to design the experiment layout. The SnO2/Fe3O4 nanoparticles were synthesized using the core-shell method. The results of x-ray diffraction and transmission electron microscopy showed the successful synthesis of these nanoparticles. The... 

One of the main issues of wastewater treatment is the silica deposition in steam turbines. Evaporation of silica with the steam in adequate concentration is one of the main sources of scale formation in steam turbines. In this study, the authors introduce the utilization of a genetic-based approach—gene expression programming (GEP)—for solubility prognostication of the silica in superheated steam of boilers with respect to water silica content and pressure. The result of GEP mathematical approach is a new algebraic formula to achieve our goals. Developed model predicts the silica solubility in the range of 0.8–22.1 MPa and 1–500 mg/kg for pressure and boiler water silica content,... 

In this study, effects of dried saffron purple petals (SPP) powder were examined on the rheological, fluid loss, and corrosion inhibition properties of bentonite-based drilling fluids. Drilling fluids containing different amounts of the SPP powder were prepared and their rheological behavior was investigated via the rotary viscometry and rheometric mechanical spectroscopy (RMS). Rotary viscometer results were fitted with Power-law, Bingham plastic, and Herschel-Bulkley models and the obtained data were compared with that of the base mud. All models fitted the rotary viscometer data with the determination coefficients higher than 0.93. The presence of 3 wt% of the SSP in the fluid... 

In salting-out liquid-liquid extraction (SALLE) technique, water-miscible organic solvents are used for extraction of polar analytes from saline solutions. In this study, for the first time, a coupled 1-mL syringes system was utilized to perform a miniaturized SALLE method. Sulfanilamide antibiotic was extracted and determined via the developed method followed by high performance liquid chromatography-ultraviolet detection (HPLC-UV). The extraction process was carried out by rapid shooting of acetonitrile as extraction solvent (syringe B) into saline aqueous sample solution (syringe A), and then the shooting was repeated several times at a rate of 1 cycle s-1. Thereby, an extremely large... 

This study proposes a novel socio-hydrological modeling framework for assessing the performance of complex water resources systems. It employs and integrates agent-based modeling (ABM) and the theory of planned behavior (TPB) into the socio-hydrological modeling framework to account for agents’ behaviors. Due to farmers’ major role in anthropogenic droughts, this paper mainly focuses on farmers’ behavior. The TPB framework and the agents’ behavioral rules in ABM are structured based on the data obtained from field questionnaires and interviews by the farmers in the Zarrineh River Basin as the main river feeding the Urmia Lake. The proposed modeling framework, including the TPB and ABM... 

One of the most prevalent problems in drilling industry is lost circulation which causes intense increase in drilling expenditure as well as operational obstacles such as well instability and blowout. The aim of this research is to develop smart systems for estimating amount of lost circulation making able to use appropriate prevention and remediation methods. To obtain this aim, a large data set were collected from 61 recently drilled wells in Marun oil field in Iran to be used for developing relevant models. After that, using the extracted data set consisting of 1900 data subset, intelligent prediction models including decision tree (DT), adaptive neuro-fuzzy inference systems (ANFIS),...