Sharif Digital Repository

In this investigation, application of the least square support vector machine (LSSVM) for modeling of the electrical resistivity of the magnetic Zn-Mn-S nanocrystalline semiconductor films has been described. The model has been trained based on the experimental data obtained from a published work by Sreekantha Reddy et al. The model inputs are temperature and variations in the concentrations of Zn, Mn. The results indicate that LSSVM is able to be used for accurate prediction of the electrical resistivity of the Zn-Mn-S nanocrystalline semiconductor films  

The permeability is one of the most important reservoir parameters and its accurate prediction is necessary for reservoir management and enhancement. Although many empirical formulas are derived regarding permeability and porosity in sandstone reservoirs [1], these correlations cannot be modified accurately in carbonate reservoir for the wells which are not cored and there is no welltest data. Therefore estimation of these parameters is a challenge in reservoirs with no coring sample and welltest data. One of the most powerful tools to estimate permeability from well logs is Artificial Neural Network (ANN) whose advantages and disadvantages have been discussed by several authors [2]. In this... 

Viscosity of mixed oil is an important parameter which is required in transportation and production processes of mixed crude oils. There is no universal and general model for prediction of viscosity of mixed oils at different conditions. Hence, developing simple, accurate and general models for prediction of mixed oil viscosity is of great importance. In this work three computer based models named MLP-NN, PSO-RBF and Hybrid-ANFIS were developed for prediction of viscosity of mixed oils. A number of 513 experimental data covering wide ranges of influencing parameters were utilized to develop the models. The accuracy of predictions of the developed models was examined by using different... 

Over the years, accurate prediction of dew-point pressure of gas condensate has been a vital importance in reservoir evaluation. Although various scientists and researchers have proposed correlations for this purpose since 1942, but most of these models fail to provide the desired accuracy in prediction of dew-point pressure. Therefore, further improvement is still needed. The objective of this study is to present an improved artificial neural network (ANN) method to predict dew-point pressures in gas condensate reservoirs. The model was developed and tested using a total set of 562 experimental data point from different gas condensate fluids covering a wide range of variables. After a... 

Process variation has an increasingly dramatic effect on delay and power as process geometries shrink. Even if the amount of variation remains the same as in previous generations, it accounts for a greater percentage of process geometries as they get smaller. So an accurate prediction of path delay and power variability for real digital circuits in the current technologies is very important; however, its main drawback is the high runtime cost. In this paper, we present a new fast EDA tool which accelerates Monte Carlo based statistical static timing analysis (SSTA) for complex digital circuit. Parallel platforms like Message Passing Interface and POSIX® Threads and also the GPU-based CUDA... 

In the design of a carbon dioxide capture and storage (CCS) process, the thermal conductivity of carbon dioxide is of special concern. Hence, it is quite important to search for a quick and accurate determination of thermal conductivity of CO2 for precise modeling and evaluation of such a process. To achieve this aim, a robust computing methodology, entitled least square support vector machine (LSSVM) modeling, which is coupled with an optimization approach, was used to model this transport property. The model was constructed and evaluated employing a comprehensive data bank (more than 550 data series) covering wide ranges of pressures and temperatures. Before constructing the model, outlier... 

This paper concerns extending applicability of Dehaghani association equation of state (in short DA-EOS) to model non-ideality in phase behavior caused by hydrogen bonding. Advantageously, this equation only needs two and one parameters to treat self- and cross association, respectively, which were determined for methanol/water and ethanol/water mixture in this study. In this respect, DA was coupled with PR and SRK EOS to account for physical interaction between molecules. Notably, DA-PR persistently provides more accurate prediction than DA-SRK for both aqueous methanol and ethanol solutions  

This paper presents an innovative hybrid approach for the estimation of the solar global radiation. New prediction equations were developed for the global radiation using an integrated search method of genetic programming (GP) and simulated annealing (SA), called GP/SA. The solar radiation was formulated in terms of several climatological and meteorological parameters. Comprehensive databases containing monthly data collected for 6 years in two cities of Iran were used to develop GP/SA-based models. Separate models were established for each city. The generalization of the models was verified using a separate testing database. A sensitivity analysis was conducted to investigate the... 

Accurate prediction of static and dynamic response of nano structures under external excitations has been one of the interests of scientists in the last decade. Several applications of nano machines make it necessary to analyze their components, such as nano bearing, precisely. In this paper, the static and vibrational behavior of a fullerene as a sensitive part of nano bearing under external forces is simulated by a newly designed spherical super element. This super element is designed in such a way that the user can select as many numbers of nodes as desired, so that it can be implemented in different desired precisions. In this study, a 228-node super element, which is similar to a hollow... 

Accurate prediction of static and dynamic response of nano structures is one of the important interests of scientists in the last decade. Nano bearing as an important part of nano machines has been extensively implemented in recognizing and disassembling cancerous cells and building molecular support structures for strengthening bones. For this reason, Molecular Dynamic Method and some experimental methods are implemented in this area. As nano ball bearing is one of the most important components of nano machines, a large number of studies are concentrated to analyze it statically and dynamically. In this paper, a Fullerene is simulated by a spherical super element whose stress, deformation... 

Accurate prediction of static and dynamic response of nano structures is one of the important interests of scientists in the last decade. Nano bearing as an important part of nano machines has been extensively implemented in recognizing and disassembling cancerous cells and building molecular support structures for strengthening bones. For this reason, Molecular Dynamic Method and some experimental methods are implemented in this area. As nano ball bearing is one of the most important components of nano machines, a large number of studies are concentrated to analyze it statically and dynamically. In this paper, a Fullerene is simulated by a spherical super element whose stress, deformation... 

In this study, the liquid-liquid phase behavior of aromatic compound. +. aliphatic compound. +. ionic liquid (IL) ternary systems was estimated by using two artificial neural networks (ANN) developed based on back propagation (BP) and hybrid group method of data handling (GMDH). Molar ratio of aliphatic compound, aromatic compound, and IL as well as temperature, molecular weight ratio of aliphatic compound to IL, and molecular weight ratio of aromatic compound to IL were chosen as the inputs to the networks. Additionally, the mole fraction of components in final alkane-rich phase and IL-rich phase was considered as desired outputs. The best topology of the BP-ANN model was found as (6-8-4).... 

Receptance coupling substructure analysis (RCSA) is extensively used to determine the dynamic response of milling tool at its tip for the purpose of prediction of machining stability. A major challenge in using this approach is the proper modelling of the joint between the substructures and determination of its parameters. In this paper, an inverse RCSA is developed for experimental extraction of tool-holder frequency response function (FRF) including joint parameters. The accuracy and efficiency of this method is evaluated through an analytical investigation. It is shown that the extracted holder FRF can provide a highly accurate prediction of the tool tip FRF. The developed method is used... 

Stay and guide vanes (distributor) are essential parts of a turbine. They are used to control the flow rate and to appropriately transfer the flow momentum to the runner. In this work, flow through the distributor is analyzed. For various Boundary Conditions (BC) and different configurations, threedimensional flows in the distributor of a Francis turbine are evaluated and compared with each other. The numerical simulations were carried out using Fluent software and the results were validated with a GAMM Francis turbine, where the geometry and detailed best efficiency measurements were publically available. In these simulations, the flow was assumed to be steady and the effect of turbulence... 

Boiling of water/triethyleneglycol (TEG) binary solution has a wide-ranging application in the gas processing engineering. Design, operation and optimization of the involved boilers require accurate prediction of boiling heat transfer coefficient between surface and solution. In this investigation, nucleate pool boiling heat transfer coefficient has been experimentally measured on a horizontal rod heater in water/TEG binary solutions in a wide range of concentrations and heat fluxes under ambient condition. The present experimental data are correlated using major existing correlations. In addition a correlation is presented for prediction of pool boiling heat transfer for the system in which... 

Today, many limitations are faced in sludge treatment and disposal. Therefore evaluation of different approaches to reduce sludge production in the activated sludge process has attracted great attention. Application of ultrasonic waves in sludge treatment caused to reduce sludge volume and accelerate sludge digestion. This research intended to study the efficiency of ultrasound in dewatering biological sludge in wastewater treatment plants under different conditions. In this study, response surface method was used to investigate results and optimum conditions were determined. Sludge was treated in different conditions as follows: 330–920 W ultrasound power, 1.5–3.9 L sample volume and... 

The present work developed a mixed-mode cohesive zone model (CZM) with a mode I failure criterion to predict the delamination bending loads of multilayer, composite printed circuit boards (PCBs) assembled with soldered ball grid array (BGA) components that were reinforced with an underfill epoxy adhesive. Two different delamination modes were observed in these microelectronic assemblies: delamination at the interface between the solder mask and the first conducting layer of the PCB, and PCB subsurface delamination at the interface between the epoxy and glass fibers of one of the prepreg layers. The cohesive parameters for each of the two crack paths were obtained from fracture tests of... 

The present work developed a mixed-mode cohesive zone model (CZM) with a mode I failure criterion to predict the delamination bending loads of multilayer, composite printed circuit boards (PCBs) assembled with soldered ball grid array (BGA) components that were reinforced with an underfill epoxy adhesive. Two different delamination modes were observed in these microelectronic assemblies: delamination at the interface between the solder mask and the first conducting layer of the PCB, and PCB subsurface delamination at the interface between the epoxy and glass fibers of one of the prepreg layers. The cohesive parameters for each of the two crack paths were obtained from fracture tests of... 

Viscosity of mixtures of biodiesels (admixtures) and mixtures of biodiesel/diesel (blends) is a important parameter for determining their combustion behavior. There is no universal and general model for prediction of viscosity of these systems at different conditions. Hence, developing simple, accurate, and general models for prediction of viscosity of these systems is of great importance. In this work, three computer-based models named multilayer perceptron neural network (MLP-NN), radial basis function optimized by particle swarm optimization (PSO-RBF), and adaptive neuro fuzzy inference system optimized by hybrid approach (Hybrid-ANFIS) were developed for prediction of viscosity of blends... 

Simulation of brittle regime machining of materials (such as ceramics) is often difficult because of the complex material removal mechanisms involved. In this study, the discrete element method is used to simulate the dynamic process for machining of slip-cast fused silica ceramics. Flat-joint contact model is exploited to model contacts between particles in synthetic discrete element method models. This contact model is suitable for modeling of brittle materials with high ratios (higher than 10) of unconfined compressive strength to tensile strength. The discrete element method has the ability to simulate initiation, propagation, and coalescence of cracks leading to chip formation in the...