Sharif Digital Repository

The burning of fossil fuels such as gasoline, coal, oil, natural gas in combustion reactions results in the production of carbon dioxide. The phase behavior of the carbon dioxide + water system is complex topic. Unlike methane, CO2 exhibits a minimum in the water content. These minima cannot be predicted by existing methods accurately. In this communication, two mathematical-based procedures have been proposed for accurate computation of CO2 water content for tempe-ratures between 273.15 and 348.15 K and the pressure range between 0.5 and 21 MPa. The first is based on least squares support vector machine (LSSVM) algorithm and the second applies multilayer perceptron (MLP) artificial neural... 

In this paper, a new fatigue lifetime prediction model is presented for the aluminium-silicon-magnesium alloy, A356.0. This model is based on the plastic strain energy density per cycle including two correction factors in order to consider the effect of the mean stress and the maximum temperature. The thermal term considers creep and oxidation damages in A356.0 alloy. To calibrate the model, isothermal fatigue and out-of-phase thermo-mechanical fatigue (TMF) tests were conducted on the A356.0 alloy. Results showed an improvement in predicting fatigue lifetimes by the present model in comparison with classical theories and also the plastic strain energy density (without any correction... 

Experimental permeability and diffusivity values for CO2 and CH4 through imidazolium-based ionic liquid 1-hexyl-3-methylimidazolium bis(trifluoromethanesulfonyl)imide ([hmim][Tf2N]) were determined in the temperature range of 300-320K using temperature correction factor defined in our previous study. According to literature, experimental values of permeability and diffusivity obtained in this study for CO2 in [hmim][Tf2N], showed good agreement with predictive models reported by other researchers. In addition, experimental values of permeability and diffusivity for CH4 in [hmim][Tf2N] as a function of pressure have been reported in this study. Considering the results of present study and... 

Nanofluids viscosity is one of the most important thermophysical properties in nanofluids usage especially in chemical and petroleum engineering applications. So it is highly desirable to predict the viscosity of nanofluids accurately. Experimental measurements are impossible in most situations and present models are not comprehensive and efficient especially for high temperature, high volume concentration and high viscosity values. In this study, a new correlation has been developed based on the comprehensive database of water based Al2O3, TiO2, SiO2 and CuO nanofluids viscosity data found in literature. The proposed correlation uses temperature, nanoparticle size, nanoparticle volumetric... 

This paper investigates the influence of intumescent paint on the performance of FRP bars subjected to low (25–450 °C) and severe (450–800 °C) elevated temperatures. In this research, glass and carbon FRP bars with epoxy resin and coated with nitrogen-based intumescent paint were used. In addition to the temperature effects, a variety of FRP bar diameters were employed to determine its effect on the tensile behavior of FRP bars in the presence of intumescent paint. Further, Bayesian regression methods and ANOVA (ANalysis Of VAriance) were applied on the results to develop a predictive model form and quantify the contribution of the variables in the tensile performance of FRP bars,... 

Asphaltene precipitation is known as one of the challenging problems in petroleum industries which have significant effects on production such as formation damage and wellbore plugging. To solve this problem, calculation of precipitated asphaltene becomes highlighted so in the present study a novel approach is proposed based on ANFIS algorithm to estimate precipitated asphaltene in terms of dilution ration, carbon number of precipitants and temperature. The particle swarm optimization (PSO) method is applied to optimize ANFIS algorithm parameters. The proposed model was evaluated based on statistical parameters and the calculated R2, AARD and RMSE for the total data are 0.90309, 9.4908 and... 

Community Question Answering platforms such as Stack Overflow help a wide range of users solve their challenges on-line. As the popularity of these communities has grown over the years, both the number of members and posts have escalated. Also, due to the diverse backgrounds, skills, expertise, and viewpoints of users, each question may obtain more than one answer. Therefore, the focus has changed toward producing posts that have a set of answers more valuable for the community as a whole, not just one accepted-answer aimed at satisfying only the question-asker. Same as every universal community, a large number of low-quality posts on Stack Overflow require improvement. We call these posts... 

One of the most essential and costly stages in Concrete Face Rockfill Dams (CFRD) construction is to implement the concrete at the upstream face of the dam without joints. As the face concrete is considered as the most integral part to prevent water penetration in CFRDs, it's quality control is of paramount importance. One of the conventional approaches for quality control of the concrete which is used in CFRD is the compressive strength of laboratory samples. The comparison of laboratory and in situ measurements provides information about the accuracy of the obtained results. This research investigates the correlation of concrete compressive strength determined by using different methods in... 

Ultrasonic motors (USM) possess heavy nonlinear, and load dependent characteristics such as dead-zone and saturation reverse effects, which vary with driving conditions. These properties have made the position/velocity control of USM a difficult and challenging task. In this paper, a generalized model predictive (GPC) controller for precise USM position control is suggested. Simulation results indicate improved performance of the motor for both set point tracking and disturbance rejection. Since the motor and the controller both are of type one, the applied saturation would cause in wind up phenomenon. This drawback is removed by implementing the Quadratic GPC controller. © 2004 IEEE  

Transmission Control Protocol (TCP) uses multiple timers to do its work. The most important of these is the retransmission timer. In this paper, the TCP retransmission timer adjustment mechanism is approached from a system point of view and a new mechanism is proposed. A simple recursive system identification algorithm is used to capture both time variant and time invariant Internet behavior. Also a dynamic model-based Round-Trip Time (RTT) predictor was provided. Based on network simulation and real Internet data collection, it was observed that when the retransmission timer is adjusted by the proposed predictor instead of the traditional RTT estimator, performance increased significantly  

In this study; a Sugeno type ANFI model which describes the relationship between the bio surfactant concentration as a model output and the critical medium components as its inputs has been constructed. The critical medium components are glucose, urea,SrCl2 and MgSo4 .The experimental data for training and testing capability of the model obtained by a statistical experimental design which have been captured from literatures. Six generalized bell shaped membership function have been selected for each of input variables and based on the training data ANFI model has been trained using the hybrid learning algorithm. The yielded biosurfactant concentration values from the model prediction shows... 

Present research represents the application of artificial neural networks to predict the chemical composition of electrodeposited Ni-Mo thin films. Artificial neural networks commonly are utilized as a prediction tools so that these networks could approximately find kind of logic relationships between inputs and target; they fitted appropriate coefficient and weighting factors to the inputs which are proportional to their importance. In order to evaluate the model developed, experimental results were compared with the predicted ones. However, more data are required to train more reliable prediction models, presents study revealed an acceptable error less than 1% between predicted values and... 

In this study, the quantitative structure-property relationship method is applied to predict the enthalpy of fusion of pure chemical compounds at their normal melting point. A genetic algorithm-based multivariate linear regression is used to select the most statistically effective molecular descriptors for evaluating this property. To propose a comprehensive and predictive model, 3,846 pure chemical compounds are investigated. The root mean square of error and the average absolute deviation of the model are equal to 2.57 kJ/mol and 9.7%  

The artificial neural network-group contribution (ANN-GC) method is applied to estimate the standard enthalpy of combustion of pure chemical compounds. A total of 4590 pure compounds from various chemical families are investigated to propose a comprehensive and predictive model. The obtained results show the squared correlation coefficient (R 2) of 0.999 99, root mean square error of 12.57 kJ/mol, and average absolute deviation lower than 0.16% for the estimated properties from existing experimental values  

Rail noise prediction models enable consideration of different scenarios for the optimal management of noise prevention and mitigation. This project is aimed at developing an equation that enables computation of LA,max for the Tehran-Karaj commuter train, a type of Diesel-Electric Locomotive. The form of the proposed model is derived from equations for predicting LA,max for a single locomotive pass-by, proposed in the manual prepared by Harris Miller Miller & Hanson Inc. for the US Federal Transit Administration, and in the French rail noise prediction model. The algorithm for predicting LA,max for the Tehran-Karaj commuter train has been developed on the basis of the 50 measurements from 5... 

In the present paper, thermo-mechanical fatigue (TMF) and low cycle fatigue (LCF) or isothermal fatigue (IF) lifetimes of a cast magnesium alloy (the AZ91 alloy) were studied. In addition to a heat treatment process (T6), several rare elements were added to the alloy to improve the material strength in the first step. Then, the cyclic behavior of the AZ91 was investigated. For this objective, strain-controlled tension-compression fatigue tests were carried out. The temperature varied between 50 and 200. °C in the out-of-phase (OP) TMF tests. The constraint factor which was defined as the ratio of the mechanical strain to the thermal strain, was set to 75%, 100% and 125%. For LCF tests,... 

The purpose of the paper presented here is to control the fluid temperature that flows in the inner tube of a tubular heat exchanger system by means of the fluid flow pressure. This system in its present form has a specified range of the coefficients' variation, while the temperature of the outlet fluid could generally be controlled by either the temperature or the flow of the inlet fluid flowing in the shell tube. The control realization for the system presented is often complicated, because the variation of the system coefficients and the reference signal must be thoroughly covered by the control action. In such a case, the system behaviour must first be represented by the multiple... 

Asphaltene precipitation in petroleum industries is known as major problems. To solve problems there are approaches for inhibition of asphaltene precipitation, Asphaltene inhibitors are known effective and economical approach for inhibition and prevention of asphaltene precipitation. In the present study Adaptive neuro-fuzzy inference system (ANFIS) was coupled with Particle swarm optimization (PSO) to create a novel approach to predict effect of inhibitors on asphaltene precipitation as function of crude oil properties and concentration and structure of asphaltene inhibitors.in order to training and testing the algorithm, a total number of 75 experimental data was gathered from the...