Sharif Digital Repository

Determination of different facies in an underground reservoir with the aid of various applicable neural network methods can improve the reservoir modeling. Accordingly facies identification from well logs and cores data information is considered as the most prominent recent tasks of geological engineering. The aim of this study is to analyze and compare the five artificial neural networks (ANN) approaches with identification of various structures in a rock facies and evaluate their capability in contrast to the labor intensive conventional method. The selected networks considered are Backpropagation Neural Networks (BPNN), Radial Basis Function (RBF), Probabilistic Neural Networks (PNN),... 

Complicated sedimentary processes control the spatial distribution of geological heterogeneities. This serves to make the nature of the fluid flow in the hydrocarbon reservoirs immensely complex. Proper modeling of these heterogeneities and evaluation of their connectivity are crucial and affects all aspects of fluid flow. Since the natural variability of heterogeneity occurs in a myriad of length scales, accurate modeling of the rock type connectivity requires a very fine scheme, which is computationally very expensive. Hence, this makes other alternative methods such as the percolation approach attractive and necessary. The percolation approach considers the hypothesis that a reservoir can... 

Reservoir characterization, especially during early stages of reservoir life, is very uncertain, due to the scarcity of data. Reservoir connectivity and permeability evaluation is of great importance in reservoir characterization. The conventional approach to addressing this is computationally very expensive and time consuming. Therefore, there is a great incentive to produce much simpler alternative methods. In this paper, we use a statistical approach called the percolation theory, which considers a hypothesis wherein the reservoir can be split into either permeable (i.e. sand/fracture) or impermeable flow units (i.e. shale/matrix), and assumes that the connectivity of permeability... 

Understanding the fresh groundwater lens (FGL) behavior and potential threat of climatic-induced seawater intrusion (SWI) are significant for the future water resources management of many small islands. In this paper, the FGL of Kish Island, an arid-region case in the Persian Gulf, Iran, is modeled using two-dimensional (2D) and three-dimensional (3D) simulations. These simulations are based on the application of SUTRA, a density-dependent groundwater numerical model. Also, the numerical model parameters are calibrated using PEST, an automated parameter estimation code. Firstly a detailed conceptualization of the FGL model is completed to understand the sensitivity of the FGL to some... 

The main objective of this paper is to provide comparative quantitative examinations on the capabilities of two-dimensional horizontal and pseudo-three-dimensional (3D) modelling approaches for simulating spatial and temporal variability of the flow and salinity in Lake Urmia, Iran. The water quality in the lake has been an environmentally important subject partly because this shallow hypersaline aquatic ecosystem is considered to be one of the largest natural habitats of a unique multicellular organism, Artemia urmiana. This brine shrimp is the major food source for many of the protected and rare shorebirds that visit the lake. A.urmiana can grow and survive in certain ranges of salinity,... 

Metropolitan areas consist of complicated systems of interconnected infrastructures that are highly interdependent. Disruption of one infrastructure may induce disruption in other interconnected ones. The results from analysis of one infrastructure as an independent system are not realistic without considering the behavior of other interconnected infrastructures. Consequently, the study of the interdependencies among critical infrastructures is important for addressing the cascading effects of a failed infrastructure on the entire network to properly model its performance and help the disaster management team in decision making. In this study, the extended Petri net and Markov chain have... 

Pricing for an insurance policy can be described as the process of calculation of expected compensation to be paid to property losers as well as associated costs of potential risks. Loss forecast is accurate if the risks will be identified appropriately in order to calculate the frequency and expected severity of losses.This is particularly important about environmental risks since most of them appear in the long run. Environmental risk assessment model is both able to estimate the environmental liability premium for environmental pollution and degradation, and it can play a valuable role in promoting this industry. ELIS (Environmental Liability Insurance) software calculates the... 

In this paper we examine how exchange flow in Urmia Lake plays a crucial role in dynamics of the lake. Urmia Lake, a very large hyper-saline lake of high ecological significance, is located in northwest of Iran with a 15-km causeway dividing it into north and south lakes. A 1250-m opening in the causeway near the east coast links the two lakes. The differences in mean water levels and densities of the two lakes increase in spring due to large freshwater inflows into the south lake. High evaporation dominates the lake in summer. By incorporating the results of a two-layer hydraulics theory into a mixing model of the lake, we show that the exchange flow through the opening diminishes the water... 

Determination of different facies in an underground reservoir with the aid of various applicable neural network methods can improve the reservoir modeling. Accordingly facies identification from well logs and cores data information is considered as the most prominent recent tasks of geological engineering. The aim of this study is to analyze and compare the five artificial neural networks (ANN) approaches with identification of various structures in a rock facies and evaluate their capability in contrast to the labor intensive conventional method. The selected networks considered are Backpropagation Neural Networks (BPNN), Radial Basis Function (RBF), Probabilistic Neural Networks (PNN),... 

Increasing concerns about unbridled fossil fuel consumption and a growing generation of municipal solid waste (MSW) in Iran and related environmental challenges require adoption of more sustainable approaches in energy and waste management. Energy recovery from waste can play an important role to achieve environmentally sustainable development that has been defined for the country as a main policy. Iran’s growing urban population generates massive amounts of MSW that mostly end up in landfills. A population of 75 million is generating 50,000 tonnes of MSW every day that mostly are buried in landfills. Detrimental emissions from landfills and many other long-lasting environmental issues have... 

The present study was aimed at performance and energy analysis of a hybrid wind-hydrogen power system. Such system consists of wind turbines, batteries for the short time energy storage, electrolyzer, fuel cell and hydrogen tank for long time energy storage. The proposed configuration is used to supply energy demand of a region with discrete seasonal wind speed regime. Temporary wind energy profiles restrict using batteries for electricity storage as they lose much electrical stored energy for the long time. Based on direct wind turbine usage, batteries and hydrogen storage, different energy supply strategies are introduced and analyzed to power the household electricity demand. The energy... 

The present study is a nationwide survey of language identity among English language learners in Iran. The participants who completed the survey in this research included 1851 English language learners from different parts of the country who belonged to different genders, age groups and English language proficiency levels. The main instrument was a validated questionnaire which included 19 items and was administered online and by hand. The results of this survey revealed that Iranian English language learners had a moderate level of language identity and there was no significant difference between the language identity of male and female participants. In addition, the results indicated that... 

Objectives: Although dental practitioners are confronted with a number of musculoskeletal disorders, relatively few studies have focused on this profession. The aim of this study was to investigate the prevalence of some musculoskeletal complaints of dentists in Iran. Methods: Four hundred and forty-six dentists in Tehran city, Iran were surveyed to determine the prevalence of musculoskeletal problems. We administrated a Persian-language version of the Nordic Questionnaire for this purpose. Results: Data gathered from Iranian dentists showed that most dentists [81%] reported pain in at least one joint. The most prevalent musculoskeletal disorders during the previous 12 months were reported... 

Recent advancements in photovoltaic (PV) system technologies have decreased their investment cost and enabled the construction of large PV farms for bulk power generations. The output power of PV farms is affected by both failure of composed components and solar radiation variability. These two factors cause the output power of PV farms be random and different from that of conventional units. Therefore, suitable models and methods should be developed to assess different aspects of PV farms integration into power systems, particularly from the system reliability viewpoint. In this context a reliability model has been developed for PV farms with considering both the uncertainties associated... 

This article introduces the concept of latecomer systems integration capability (LSIC) as a construct for theory development in the area of emergence and competitiveness of producers of complex capital goods from developing economies. The study draws on three bodies of the literature to conceptualize LSIC and then presents an in-depth case study of the development of LSIC in a major Iranian firm engaged in producing electricity generation systems. Although an exploratory study, the findings suggest that, in this case, LSIC evolved in a fairly short period of time from simple low-cost project management skills to innovative capabilities, supported by some sophisticated engineering and design... 

In this study the bioleaching of a low-grade uranium ore containing 480 ppm uranium has been reported. The studies involved extraction of uranium using Acidithiobacillus ferrooxidans derived from the uranium mine samples. The maximum specific growth rate (μ max) and doubling time (t d) were obtained 0.08 h-1 and 8.66 h, respectively. Parameters such as Fe2+ concentration, particle size, temperature and pH were optimized. The effect of pulp density (PD) was also studied. Maximum uranium bio-dissolution of 100 ± 5 % was achieved under the conditions of pH 2.0, 5 % PD and 35 °C in 48 h with the particles of d 80 = 100 μm. The optimum concentration of supplementary Fe2+ was dependent to the PD.... 

Numerous studies yet have been carried out on downscaling of the large-scale climate data using both dynamical and statistical methods to investigate the hydrological and meteorological impacts of climate change on different parts of the world. This study was also conducted to investigate the capability of feedforward neural network with error back-propagation algorithm to downscale the provincial segmentation of Iran (30 provinces) on a daily scale. This model was proposed for the downscaling daily temperature, precipitation and wind speed data, and it was calibrated and verified by using the daily outputs derived from the National Center for Environmental Prediction (NCEP) database... 

Prediction of accident frequency based on traffic and roadway characteristics has been a very significant tool in the field of traffic management. The accident frequencies on 185 roadway segments of the city of Mashhad, Iran, for the year 2007, were used to develop accident prediction models. Negative Binomial Regression, Zero Inated Negative Binomial Regression, Support Vector Machine and Back-Propagation Neural Network models were used to fit the accident data. Both fitting and predicting abilities of the models were evaluated through computing error values. Results show that the NBR model is the most effective model for predicting the number of accidents because of its low prediction and... 

Dental professionals are in a unique position to promote smoking cessation among their patients. We evaluated the effects of a brief counselling intervention by a dentist on patients' attitude towards the role of dentists in tobacco cessation programmes. In a semi-experimental study in Tehran, Islamic Republic of Iran, 70 eligible smokers were selected and randomly assigned to intervention and control groups. The initial attitudes of the patients regarding tobacco cessation counselling services provided by the dentist were determined using a validated questionnaire. The intervention group received a brief chair-side counselling by a dentist based on the 5 A's approach, while no intervention... 

Stock return is usually considered to be affected by firm's financial ratios as well as economic variables. Fundamental method assume that stock returns is not solely related to the stock market. Most result come from the company condition, industry situation and whole economy. In this paper, this relationship between stock return and fundamentals is studied using the data for 22 pharmaceutical companies in Tehran Stock Exchange over a 7 year period, and effective factors on stock return are investigated. Because of our data natural we used panel data model from econometric methods. The results show that 80 pecent of change in stock return can be explained with 9 fundamental variables...