Sharif Digital Repository

In this study, silicon microchannel heat sink (MCHS) performance using nanofluids as coolants was analyzed. The nanofluid was a mixture of nanoscale Cu particles and pure water with various volume fractions. Based on theoretical models and experimental correlations, the heat transfer and friction coefficients required in the analysis were used. In the theoretical model, nanofluid was treated as a single-phase fluid. In the experimental correlation, thermal dispersion due to particle random motion was included. The microchannel heat sink performances for a specific geometries with Wch = W fin = 100 μm and Lch =300 μm is examined. In this study, flow in laminar and turbulent regimes using the... 

The connectivity between two points in porous media is important for evaluating hydrocarbon recovery in underground reservoirs or toxic migration in waste disposal. For example, the connectivity between a producer and an injector in a hydrocarbon reservoir impact the fluid dispersion throughout the system. The conventional approach, flow simulation, is computationally very expensive and time consuming. Alternative method employs percolation theory. Classical percolation approach investigates the connectivity between two lines (representing the wells) in 2D cross sectional models whereas we look for the connectivity between two points (representing the wells) in 2D aerial models. In this... 

Ionic liquids are a significant type of organic salts with attractive and superior physicochemical features for employing in a number of chemical processes. Ionic liquids include one large and asymmetric cationic or anionic functional group. The properties of cationic functional group are almost similar and it is main motivation of this study. In the present investigation, we extended various semi-empirical correlations to predict some temperature-based properties of ionic liquids mixture (IL-mixture). These properties are density, viscosity, surface tension and bubble point pressure. In the case of IL-mixture density, modified Rackett equation and Taylor equation with three scenarios,... 

Screening analysis is a useful guideline that helps us with proper field selection for different enhanced oil recovery processes. In this work, reservoir simulation is combined with experimental design to estimate the effect of reservoir rock and fluid properties on performance of immiscible nitrogen injection. Reservoir dip, thickness, and horizontal permeability are found to be the most influential parameters. Possible interactions of parameters are also discussed to increase reliability and robustness of screening results. Finally, significance of both main effects and interactions are evaluated by employing a statistical inference approach (hypothesis testing) and results are compared to... 

Asphaltene instability is one of the major problems in gas injection projects throughout the world. Numerous models have been developed to predict asphaltene precipitation; The scaling equation is an attractive tool because of its simplicity and not involving complex properties of asphaltene. In this work, a new scaling model is presented to account for asphaltene precipitation due to gas injection at reservoir conditions. Extensive published data from literature have been used in model preparation. To check predictive capability of the equation, miscible gas injection experiments are conducted for a southwest Iranian oil reservoir. Experimental results show that methane injection has... 

In fractured oil reservoirs, the gravity drainage mechanism has great potentials to higher oil recovery in comparison with other mechanisms. Recently, the forced gravity drainage assisted by gas injection has also been considered; however, there are few comprehensive studies in the literature. Dual porosity model, the most common approach for simulation of fractured reservoirs, uses transfer function concept to represent the fluid exchange between matrix and its neighborhood fractures. This study compares the results of different available transfer functions with those of fine grid simulations when forced gravity drainage contributes to oil production from a single matrix block. These... 

Hybrid nanofluids have several advantages compared with the conventional types due to their modified properties. Their enhanced thermophysical and rheological properties make them more appropriate for solar energy systems. In this review paper, an overview of solar energy systems is represented, and afterwards, applications of hybrid nanofluids in various solar technologies, especially solar thermal, are reviewed. Comparison between the nanofluidic systems, and the conventional ones is performed in order to gain a deeper insight into the advantages of using nanofluids. According to the results of the reviewed studies, the most important reason for performance enhancement of nanofluidic solar... 

In this investigation, neural networks were used to predict pressure drop of CuO-based nanofluid in a car radiator. For this purpose, the neural network with the multilayer perceptron structure was used to formulate a model for estimating the pressure drop In this way, different concentrations of copper oxide-based nanofluid were prepared. The base fluid was the mixture of ethylene glycol and pure water (60:40 wt%) which usually used as the cooling fluid in automotive industries. The prepared nanofluid samples were used in a car radiator and the pressure drop of nanofluid flows in the system at different Reynolds were measured. The main purpose of this study was developing the optimized... 

In the current study, CuO nanoparticles were dispersed in a mixture of Ethylene Glycol-Water (60/40 wt. %) to prepare stable nanofluid in different concentrations (0.05 − 0.8 vol. %). The samples were used as the coolant fluid in a specific car radiator to evaluate the thermal performance of nanofluid and base fluid in the system. Five different and novel Machine-learning methods were applied over experimental data to predict the Nusselt number and output temperature of the coolant in the system. These methods are M5 tree regression, Linear and Cubic Multi-Variate Adaptive Regression Splines (MARS), Radial Basis Function (RBF), and Artificial Neural Network-Levenberg Marquardt Algorithm... 

Enhanced Oil Recovery from carbonate reservoirs is a major challenge especially in naturally fractured formations where spontaneous imbibition is a main driving force. The Low Salinity Water Injection (LSWI) method has been suggested as one of the promising methods for enhanced oil recovery. However, the literature suggests that LSWI method, due to high dependence on rock mineralogy, injected and formation water salt concentration, and complexity of reactions is not a well-established technology in oil recovery from carbonate reservoirs. The underlying mechanism of LSWI is still not fully understood. Due to lack of LSWI study in free clay dolomite fractured reservoir, and to investigate of...