فهرست مطالب بهروز احمدی

This study aims to assess reinforced concrete moment frames designed at varying ductility levels within a typical reinforced concrete structure, from a reliability perspective. The article explores the probabilistic methods for designing different ductility levels in the current Iranian Concrete Code, focusing on reliability. Specifically, a three-story concrete moment frame structure, designed to low, medium, and special ductility levels as per the Iranian code, is studied. The reliability analysis encompasses uncertainties in loading, dimensional parameters, and evaluating structural performance functions such as floor drift and acceleration. The study utilizes horizontal earthquake components specified by the FEMA P-695 standard to analyze earthquake record uncertainties. Furthermore, a comparison of the reliability index and probability of failure for each performance function is used to assess failure uniformity. The findings reveal a maximum probability of failure in collapse damage state of approximately 9%, 5%, and 2% for low, medium, and special ductility frames, respectively.

This study aimed to evaluate land surface temperature in relation to vegetation and urban land use using remote sensing data within the city of Ardabil and urban margin of up to 15km radius, using 2010 Landsat TM image, after preprocessing, such as data preparation, radiometric and geometric correction, which was performed using ENVI®4.7 software. Then for measuring the surface temperature, the thermal band of an image using relevant equations for converting digital numbers to radiance and radiance to brightness temperature was used. In the next step for calculating emissivity the Normalized Difference Vegetation Index (NDVI) index was used and finally land use map in six classes using supervised classification method were extracted from the image. For extracting the vegetation fraction the Dimidiate model was used. To assess the accuracy of surface temperature extracted from the image, hourly data from 4 weather stations was used and to reconcile these data with each other, a simple regression equation was used. Results show that the coefficient of relationship between land surface temperature (derived from the image) and air temperature recorded at the stations was 0.79 and the correlation between recorded air temperature of stations and derived air temperature from the image was obtained 0.99.