Moein Molavi; Mohammad Taleai; Gasem Javadi
Abstract
Finding the optimum location of wind turbines for the proper use of wind energy, as one of the sources of renewable energy, is very important. Determining the location of wind turbines has a great influence on the efficiency of their equipment. So far, research in the Khorasan Razavi area has limited ...
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Finding the optimum location of wind turbines for the proper use of wind energy, as one of the sources of renewable energy, is very important. Determining the location of wind turbines has a great influence on the efficiency of their equipment. So far, research in the Khorasan Razavi area has limited to the statistical analysis of wind speed and directional data while the spatial criteria affecting finding the optimum location of wind turbines was rarely considered. This research seeks to find optimum location for the wind power plant using environmental (including slope, altitude, distance from the fault, distance from the river, distance from protected areas), technical (including average wind speed, wind congestion and wind density), and economic (including distance from the city, the village, the airport, the natural resources and from the road) criteria and using ANP, ANP-DEMATEL and ANP-OWA multi-criteria decision-making methods. The aim is to evaluate the results of each method and produce a land suitability map for the construction of wind power plants in different decision scenarios. Based on this, using the analysis tools of the geospatial information system, the land suitability map is produced based on the aggregation of the mentioned criteria and the results of utilizing the mentioned decision-making methods are compared. By considering land suitability maps, it has been determined that in different scenarios of decision making, the southeastern province has the most potential for wind power plant construction. The results of this research indicate that the proposed method provides a good tool for choosing the right place to build a wind power plant.
Sogol Moradian; Mohammad Taleai; Ghasem Javadi
Abstract
Nowadays, water supply is one of the main causes of tension for scientists in arid countries. Therefore, the assessment of water resources can be considered as a main challenge for the authorities around the world. Successful dicision making in water resources management tries to resolve competing and ...
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Nowadays, water supply is one of the main causes of tension for scientists in arid countries. Therefore, the assessment of water resources can be considered as a main challenge for the authorities around the world. Successful dicision making in water resources management tries to resolve competing and conflicting needs of water users from different sectors including: domestic, agriculture and industry. In this research, a systematic framework for assessing different scenarios in the system, has been defined based on WEAP. The proposed model was used in the Urmia Lake basin as a case study; A scenario, proposed by the Urmia Lake Reconstruction Team, presists on transmission of water to the lake. In this study, this scenario and some others, proposed by the Urmia Lake Reconstruction Team, were used in this model and the best scenario was identified using a decision support tool based on the principles of TOPSIS, which has been written in FORTRAN. In the following section, water allocation in the catchment was investigated based on the principles of game theory and the outcome of this research shows that applying game theory and using full cooperation games (based on the Shapley Values method), provides better outcomes for all competing users of water. In other words, using the notion of coalition between different sectors including domestic, agriculture and industry, can save about 332 MCM of water which can be used in the dying lake.
M Zakipour; M Taleai; Gh Javadi
Volume 10, Issue 1 , June 2018, , Pages 41-56
Abstract
Flood is one of the most common and destructive natural events in the world. Conventional methods which aim to prevent floods, mostly are based on resistance approaches. Considering uncertainties about time and location of flood occurrence and design variables such as discharge, structure resistance ...
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Flood is one of the most common and destructive natural events in the world. Conventional methods which aim to prevent floods, mostly are based on resistance approaches. Considering uncertainties about time and location of flood occurrence and design variables such as discharge, structure resistance and physical characteristics of a basin, resistance methods are not suitable solutions. However, resistance methods for preventing from the flood are effective on lower discharges, they may become less effective or ineffective in extreme-case emergencies. As an example, levees are only effective when flood waters remain below their design capacity. Therefore, in order to manage and reduce human casualties and financial losses, more suitable solutions based on resilience are introduced. Flood resilience is interpreted as the capacity to tolerate flooding to avoid disaster when undergoing- not preventing- flooding, or when physical damage and socioeconomic disruption still occur, the capacity to reorganize and recover quickly. Recovery is defined as assisting of communities affected by flood waters to achieve a proper and effective level of functioning. Resilience approach in water resources management plays an important role in flood risk management. In this study, several strategies of flood risk management with an emphasis on the concept of resilience have been evaluated. A case study was carried out on the Ghezel Ozan river, located in the Mahneshan basin. In order to model the flood, the data related to the topographic conditions of the river are adapted using the HEC GeoRAS extension in the ArcGIS. Then, the flood characteristics in the 25, 50, and 100-year return periods are estimated by the HEC RAS model. Flood flow modeling has been carried out based on eight different management strategies including resistance and resilience strategies based on structural and non-structural approaches. The comparison of these strategies is based on the values of resilient indicators including the amplitude, graduality and recovery rate. Indicators for the amplitude are the expected annual damage (EAD) and the expected annual number of casualties (EANC). The graduality is measured by comparing the relative increase of discharge in a river by the corresponding relative increase of damage. Recovery rate is a function of social, economic and physical condition. In this research, in order to quantify the recovery rate, it is presented as a function of evaporation, transpiration and water penetration into the soil. Finally, after calculating the resilience indicators for each scenario, in order to prioritize the scenarios, the entropy method is used for weighting and TOPSIS is utilized to prioritize the scenarios. According to the results, it has been observed that resilience based methods are preferred to resistance methods and dry farming with flood warning and flood insurance has been determined as the best strategy.
Z Ghaemi; M Taleai; M Farnaghi; G Javadi
Volume 9, Issue 3 , February 2018, , Pages 45-70
Abstract
Urban growth and increased use of vehicles have led to an increase in air pollution, especially in large and industrialized cities in recent years. Because of the adverse effect of air pollution on human and other creatures, prediction and modeling of this complex phenomenon have the main concern of ...
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Urban growth and increased use of vehicles have led to an increase in air pollution, especially in large and industrialized cities in recent years. Because of the adverse effect of air pollution on human and other creatures, prediction and modeling of this complex phenomenon have the main concern of researchers during the last years. The purpose of this research is to design an air pollution prediction system to identify the contaminated areas in order to help the urban managers and planners to control and reduce the amount of contaminants. In the proposed system in order to predict the air pollution in different seasons, PCA-ANFIS model has been used. In this system, meteorological data and concentrations of pollutants are used to predict air pollution in Tehran over the next 24 hours. In addition, spatial parameters including height, topography and distance from the road are used to model the spatial distribution of air pollution. Comparing the results of PCA-ANFIS and ANFIS methods prove that the proposed model obtained higher accuracy in less processing time.
H Habibi; M Taleai; Gh Javadi
Volume 9, Issue 4 , May 2017, , Pages 22-36
Abstract
Distribution warehouses have great importance in the economy of the country, and a significant percentage of assets are accumulated in warehouses. Choosing the best place of the warehouses has a significant impact on the economic efficiency and performance of the warehouses and reduction of supply chain ...
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Distribution warehouses have great importance in the economy of the country, and a significant percentage of assets are accumulated in warehouses. Choosing the best place of the warehouses has a significant impact on the economic efficiency and performance of the warehouses and reduction of supply chain costs. In this research, a multi-criteria decision-making model based on a geospatial information system is presented to evaluate the potential areas for distribution depots in the province of Tehran. The proposed process consists of four main steps. In the first step, different criteria were extracted and the required data were collected in the context of GIS. In the second step, the evaluation factors were identified by experts and then weighted and integrated utilizing ANP method. At the third step, defining different scenarios based on the Ordinary Weighted Average (OWA) method taking into account the risk compensation in the decision-making process. Finally, using the data of Tehran province, the effectiveness of the proposed model was evaluated and results were analyzed. At the end, by combining the outputs of different scenarios, the places which recognized as good alternatives in most scenarios, were identified as appropriate options for doing additionalstudies to construct distribution warehouses.
