Sharif Digital Repository

The brushless doubly-fed induction generator (BDFIG) has substantial benefits, which make it an attractive alternative as a wind turbine generator. The aim of this work is to present a nodal-based magnetic equivalent circuit (MEC) model of the BDFIG which provides performance characteristics and flux density distributions. The model takes into account stator winding distributions, special configuration of rotor bars, slotting effects, teeth saturation, flux fringing and current displacement effects. The real flux tubes are considered for creating an MEC network and calculating its non-linear elements. A method for simplifying the rotor magnetic network has been applied and Gauss elimination... 

The time headway of vehicles is an importan microscopic traffic flow parameter which affects the safety and capacity of highway facilities such as freeways and multi-lane highways. The present paper intends to provide a report on the results of a study aimed at investigating the effect of the lane position on time headway distributions within the high levels of traffic flow. The main issue of this study is to assess the driver's behavior at different highway lanes based on a headway distribution analysis. The study was conducted in the city of Isfahan, Iran. Shahid Kharrazi six-lane highway was selected for collecting the field headway data. The under-study lanes consisted of passing and... 

Utilizing improved production methods have been always challenging in upstream industries. Nowadays, hydraulic fracturing is one of the most prestigious mechanical methods. Application of this method is in wells with low productivity index. Hydraulic fracturing efficiency depends on various factors, such as fracture geometry, fluid composition, and stress distribution. But some of them would be ignored, such as fracture geometry, which is neglected due to nongravity and lack of investigation of DFN statistical population assumption. The authors develop a more comprehensive methodology based on fracture geometry and aim to model one of the gas reservoirs in Iran that is naturally fractured by... 

The stochastic behavior of a point reactor is modeled with a system of Ito stochastic differential equations. This new approach does not require computing the square root of a matrix which is a great computational advantage. Moreover, the derivation procedure clearly demonstrates the mathematical approximations involved in the final formulation. Three numerical benchmarks show the accuracy of this model in predicting the mean and variance of the neutron and precursor population in a point reactor  

With the rise in oil price and population growth, renewable energies are assumed to be the main source of energies for the next generation. Wind as a natural, eco-friendly and renewable source of energy has been at the center of concentration for decades. Recently there has been some ideas regarding the self-regulating urban wind turbines. Researchers have shown that a proper enclosure increases the wind velocity and therefore more torques can be exerted on the rotors, therefore more power can be generated. These enclosures are light and cheap, therefore they are applicable and effective. In the present study, an enclosure was modified to increase the exerted torque with implementing a step... 

This paper describes an attempt to shed some light on road safety in Asia Pacific region by characterizing and assessing its road accidents. The relevant national road accident data were extracted from centralized data sources of international agencies. Due to data incompleteness and missing values, 21 Asia Pacific countries, presenting more than half of the world's population, were selected for detailed analysis. The study database consisted of 7 variables, covering years 1980 and 1995. The univariate and multivariate statistical analyses for the selected countries showed interesting results and relations for the selected variables. Accident rates, reflecting road accident risk and... 

Recently, a new data collection was initiated within the RedDots project in order to evaluate text-dependent and text-prompted speaker recognition technology on data from a wider speaker population and with more realistic noise, channel and phonetic variability. This paper analyses our systems built for RedDots challenge-the effort to collect and compare the initial results on this new evaluation data set obtained at different sites. We use our recently introduced HMM based i-vector approach, where, instead of the traditional GMM, a set of phone specific HMMs is used to collect the sufficient statistics for i-vector extraction. Our systems are trained in a completely phraseindependent way on... 

The climate change and human development in lake catchments have put these habitats in drying conditions, e.g. Aral Sea in Asia, Lake Chad in Africa, Lake Mead in USA, Lake Urmia in Iran, etc. These ecosystems play an important role in social, ecological, and economic activities. Lake Urmia, recognized as an international wetland in 1973 and located in Iran, which is the second largest hypersaline lake in the world, is in the same state. Lake Urmia biologically and ecologically is one of the most interesting places in the world. This lake is a habitat for various species. The lake's surface has shrunken from 6000 km2 to 900 km2 in 2013. The statistics indicate that the population has... 

Tehran is the capital of Iran and is one of the largest cities in the world. With its history of earthquakes, high population density, and a population of over 8.5 million, it must be prepared to cope with disaster. This article introduces a new method for estimating the reliability of a roadway network that considers the physical characteristics of the road and link capacity degradation. The proposed method was applied to a real road network and the connectivity reliability of the city was calculated. The proposed technique for computing connectivity reliability is sensitive to the characteristics of the road and adjacent buildings. The results indicate that northern Tehran, with a low... 

In spite of the development of different experimental methods and theoretical models devoted to understand and predict the asphaltene behavior in dead/model oils, the asphaltene aggregation phenomena in live oil systems at high pressure-high temperature conditions has been grossly missing in the available literature. In this study, a population balance model with geometric scaling approach is proposed to simulate the asphaltene aggregates growth in time for live oil systems. Appropriate collision kernels are incorporated to describe the aggregation mechanisms taking into account the effect of pressure, temperature and oil characteristics. In modeling of the asphaltene aggregation phenomena... 

Association mapping of genetic diseases has attracted extensive research interest during the recent years. However, most of the methodologies introduced so far suffer from spurious inference of the associated sites due to population inhomogeneities. In this paper, we introduce a statistical framework to compensate for this shortcoming by equipping the current methodologies with a state-of-the-art clustering algorithm being widely used in population genetics applications. The proposed framework jointly infers the disease-associated factors and the hidden population structures. In this regard, a Markov Chain-Monte Carlo (MCMC) procedure has been employed to assess the posterior probability... 

Economic development and population growth in Tehran has increased demand for goods movement and road transportation. This trend has increased mobile source emissions and citizens’ exposure, imposing severe health risks. We used the framework of Land-Use Regression models to quantify the effect of real-time traffic, within buffer distance, on hourly exposure of CO, NO2, and PM2.5. Effect of residential, industrial, and governmental land-use in addition to the effect of pollution sources, such as construction sites and airport were assessed on air pollution. Meteorological variables were also employed to adjust between day variations. R-squared of the models were 38, 27, and 38% for CO, NO2,... 

A statistical algorithm is introduced to improve the false inference of active loci, in the population in which members are admixture. The algorithm uses an advanced clustering algorithm based on a Bayesian approach. The proposed algorithm simultaneously infers the hidden structure of the population. In this regard, the Monte Carlo Markov Chain (MCMC) algorithm has been used to evaluate the posterior probability distribution of the model parameters. The proposed algorithm is implemented in a bundle, and then its performance is widely evaluated in a number of artificial databases. The accuracy of the clustering algorithm is compared with the STRUCTURE method based on certain criterion. © 2019... 

Driving simulators can provide safe real-world driving conditions that may help researchers study driving behavior; however, driving simulator sickness (DSS) has been recognized as one of the most frequent challenges associated with using driving simulators. The DSS issue may affect the validity and reliability of results obtained during the driving simulator experience. Therefore, it is necessary to understand the potential consequences of DSS in the virtual environment of a driving simulator. The goal of this study is to analyze DSS symptoms among participants of a driving simulator by their demographics. The samples of four simulator studies were combined, including a total of 259... 

Multi-modal data comprising imaging (MRI, fMRI, PET, etc.) and non-imaging (clinical test, demographics, etc.) data can be collected together and used for disease prediction. Such diverse data gives complementary information about the patient's condition to make an informed diagnosis. A model capable of leveraging the individuality of each multi-modal data is required for better disease prediction. We propose a graph convolution based deep model which takes into account the distinctiveness of each element of the multi-modal data. We incorporate a novel self-attention layer, which weights every element of the demographic data by exploring its relation to the underlying disease. We demonstrate... 

In this study, a hybrid stochastic model (BScA model) using Bayesian approach and scenario analysis to forecast long term energy demand is developed. The main objective of this study is to design and develop a model for energy analysis in demand side and describe the energy saving and GHG reduction potential on the other. For this, total energy demand is selected as the response variable and primary energy production, population, GDP and natural gas and gasoline prices are chosen as covariates. Also, Political drivers, economic drivers, social-environmental and technological drivers are the key driving forces for scenario development. After interview and ranking the drivers, we have built... 

This paper addresses a real-world problem faced by the public healthcare sector. The problem consists of both the patients’ and service provider's requirements (i.e., accessibility vs. costs) for locating healthcare facilities, allocating service units to those facilities, and determining the facilities’ capacities. The main contribution of this study is capturing both short-term and long-term uncertainties at the modelling stage. The queuing theory is incorporated to consider stochastic demand and service time as a short-term uncertainty, as well as a service level measurement. The developed nonlinear model is then converted into a linear model after introducing a new set of decision... 

In this paper, a simpler approach compared to the existing approaches is developed to analyze nuclear reactor dynamics based on the explicit Monte Carlo method. A new population control method is also introduced to prevent neutron population growth and consequent computer memory shortages, which also increases simulation speed. The scheme is applied for time-dependent particle tracking in three-dimensional arbitrary geometries in the presence of feedbacks through a code named MCSP-Explicit. Changes in material density, as well as geometry dimensions, are also considered during simulation. MCSP-Explicit can be run with either continuous or multigroup data libraries, and it is further boosted... 

Extensive studies have examined the effect of variables such as demographic characteristics, insomnia, and working conditions of drivers individually on inattention-related error as well as expression of anger in driving. Nevertheless, so far no study has tested the concurrent effect of these factors on crashes. This study has dealt with indirect investigation of the effect of variables including demographic characteristics, insomnia, and working conditions of drivers on inattention-related error and expression of anger in driving (as mediation model). Next, the effect of these two variables on the probability of incidence of road crashes has been assessed among truck drivers. For this... 

The combined effects of climate change and growing water demand due to population growth, industrial and agricultural developments cause an increase in water scarcity and the subsequent environmental crisis in river basins, which results in conflicts over the property rights and allocation agreements. Thus, an integrated, sustainable and efficient water allocation considering changes in water resources due to climate change and change of users’ demands is necessary. In this study, the drainage basin of Zarinehrood was chosen to evaluate the function of selective methods. Assessing climate change impact scenarios of the Fifth IPCC reports, e.g., RCP2.6, RCP4.5, RCP6.0 and RCP8.5, have been...