Showing 6 results for borna
Zeinab Mokhayeri, Ebrahim Fatahi, Reza Borna,
Volume 0, Issue 0 (3-1921)
Abstract
To conduct this research, first, the data of monthly observations of synoptic and hydrometric precipitation from the National Meteorological Organization and the Ministry of Energy during the 30-year period (2006-2005) were obtained. To examine the prospect of future rainfall changes, the historical data of the period (1976-2005) and the simulated climate data of the period (2050-2021) using two models of CM3), (CSIRO-Mk3.6 from the series) Models (CMIP5) and according to 4 scenarios RCP2.6, RCP4.5, RCP6 and RCP8.5) that are available with a spatial resolution of 0.5 x 0.5 with the BCSD method have been used.Mean-based (MB) strategy has been used to correct the bias in the output of these models. The results of the AOGCM models showed that the CSIRO-Mk3.6 error coefficient was less than the GFDL-CM3 model for simulating precipitation in the case of Large Karun.The average future rainfall (2021-2050) in the whole basin compared to the average observed rainfall during the statistical period of 1976-2005 shows, in both models and scenarios in both basins in terms of amount and area of precipitation is decreasing significantly.Heavy rains in the Greater Karun Basin have been concentrated in all scenarios and models east of the basin. The highest rainfall was in the central foothills. The lowest rainfall is in the southwest and southeast. The final results of the present study are expected to be 83-116 mm. Both models are expected to have the highest rainfall in the Greater Karun Basin, with two scenarios: rcp4.5 and rcp2.6.
Ali Ahmadi, Majid Vali Shariat Panahi, Reza Borna, Rahmatollah Farhoodi,
Volume 0, Issue 0 (3-1921)
Abstract
Due to the many complexities, housing planning, especially for vulnerable groups, in a city as large as Tehran, requires a model to simplify the process and speed up calculations, which does not currently exist. With the aim of solving this problem, the present study proposes a model with the following steps: 1) Explaining the objectives 2) Estimating the housing needs of the target community 3) Identifying expandable areas 4) Proposing construction patterns 5) Proposing dispersion patterns 6) Calculations and patterns Financial and 7) suggest operating patterns. The information required to implement the model was collected from two questionnaires and data from the Statistics Center. In this model, three housing models with minimum, optimal and average areas and three types of existing housing construction, 100% infrastructure and freeing up the yard space were used as public urban space. The proposed zoning was adapted to the 22 districts of Tehran Municipality due to compliance with the available data. Sales price and financial calculations were calculated based on the internal rate of return of 20% and contract subsidies, and finally 4 free transfer models, lifelong lease, lease on condition of ownership in the program areas were proposed. The results show that one of the problems in this sector is the lack of appropriate decision-making structure and planning tools that can provide a comprehensive and complete review of the current situation, comprehensive and comprehensive solutions. Therefore, according to the model and using the indicators used, regions 2, 6 and 13 have the lowest and regions 19 and 22 have the highest potential for housing development of low-income and vulnerable groups, and finally, the model has suggested the most housing in regions 22, 4, 19 and 11.
Mr Danesh Nasiri, Dr Reza Borna, Dr Manigheh Zohorian Pordel,
Volume 0, Issue 0 (3-1921)
Abstract
Widespread and frequent droughts in recent decades in Khuzestan province have become one of the most important challenges of this province. The use of remote sensing products in temporal and spatial monitoring of drought can play a key role in managing this risk and reducing and adjusting its destructive effects. The main goal of this research is to provide a remote sensing index for temporal and spatial monitoring of drought in Khuzestan province and its validation using station meteorological drought indices. In this research, by using the products of vegetation (MOD13C2) and land surface temperature (MOD11C3) of MODIS sensor, a drought index based on vegetation called VHI plant health index was produced. SPI Meteorological Drought Index, which was based on station rainfall data during the statistical period of 2000-2012, was used to evaluate and quantify this index. The comparison of VHI drought index with three-month SPI meteorological drought index values showed a significant correlation between 0.68 and 0.75. By identifying 4 years with widespread and relatively severe drought in Khuzestan province (based on both VHI and SPI indices), which included the years 2000, 2005, 2012, 2015, the spatial distribution pattern of meteorological drought and VHI plant drought to In general, it indicated that the northern parts of the province were generally involved in mild to moderate droughts and the southern parts were generally involved in moderate to severe droughts. The spatial correlation matrix based on the number of 2500 pixels with dimensions of 5x5 km, which included VHI and SPI values of selected drought years, indicated the existence of a significant spatial correlation between the two mentioned indicators. In the widespread drought of 2000, at the level of Khuzestan province, two drought indices VHI and SPI, the correlation was equal to 0.47, and in 2005, equal to 0.35, and
Reza Reza Borna, Nasrin Nasrin Jafari, Farideh Farideh Asadian,
Volume 20, Issue 57 (6-2020)
Abstract
In order to understand the total consumption of buildings and accurately calculate how much energy each building uses, taking in consideration all the building's lifecycle phases is essential. In order to select the correct methodology for the main study, the researcher began with the determination and the parameters that would have been researched, as well as the analysis and comparison of the different methods used by other researchers to achieve similar goals. The following parameters define the final results and are stabilized or examined to determine their actual effect: A- Constant parameters: 1- Climate data 2- and data on the use of the building: B- variables: 3- Design data: 1- orientation 2- window to wall ratio 3- aspect ratio. This research uses a survey followed by a computer modeling methodology to achieve the goal of providing architects with techniques that reduce energy consumption in building units. To obtain reliable results that are useful to the construction industry in the country, the researcher has ensured that the virtual environment created in the modeling process mimics a typical building environment of Tehran units. Research has shown that passive design techniques have a major impact on the energy consumption of buildings. A significant reduction in consumption (67 percent) was noted when the orientation and percentages of the opening on the wall were changed. In summary, this study has shown that the application of passive, economical and simple design techniques has a major impact on the energy consumption of the unit rooms. If the architects take these ideas into account during the design process, the buildings will take on more responsibility for the environment and consequently reduce carbon dioxide emissions.
Shahla Qasemi, Reza Borna, Faredeh Asadian,
Volume 23, Issue 69 (7-2023)
Abstract
Abstract
In the history of humanity, human always has suffered all difficulties with effort to reach to comfort and well-being until the human provides a way to achieve the comfort. In the viewpoint of climate four elements have significant role in formation of human comfort and discomfort conditions that according to the climatic conditions in different areas, the type and effect of these elements on individuals are also different. The aim of this research is to determine the areas of climatic comfort. For this purpose, temperature, precipitation and humidity data were derived from database of Esfazari for Khuzestan province during statistical period 1965 to 2014. In this process, at first discomfort climate has been defined using temperature, precipitation and humidity based on distribution probability conditional. This research is to determine the areas of climatic comfort in Khuzestan province using multivariate analysis (Cluster analysis and Discriminant analysis) and spatial autocorrelation pattern (Hot Spot index and Moran index) with emphasis on architecture. The results showed that the areas with climatic comfort are included in north and east parts of Khuzestan province. However, the areas of climatic comfort by spatial method have been limited somewhat. Results further indicated that the areas of climatic comfort have decreased significantly towards recent periods especially in cluster analysis and discriminant analysis that a trend of reduction has been remarkable in cluster analysis (from 23.60% in the first period to 17.60% in the fifth period) and discriminant analysis (from 26.97% in the first period to 14.98% in the fifth period).
Mr Danesh Nasiri, Dr Reza Borna, Dr Manijeh Zohourian Pordel,
Volume 24, Issue 72 (6-2024)
Abstract
Knowledge of supernatural microphysical properties and revealing its relationship with the spatial temporal distribution of precipitation can significantly increase the accuracy of precipitation predictions. The main purpose of this study is to reveal the relationship between the Cloud microphysical structure and the distribution of precipitation in Khuzestan province. In this regard, first 3 inclusive rainfall events in Khuzestan province were selected and their 24-hour cumulative rainfall values were obtained. The rainfall event of 17December2006, was selected as a sample of heavy rainfall, 25 March 2019, as a medium rainfall case, and finally 27 October 2018, as a light rainfall case. Microphysical factors of clouds producing these precipitations were obtained from MODIS (MOD06) cloud product. These factors included temperature, pressure, and cloud top height, optical thickness, and cloud fraction. Finally, by generating a matrix with 64000 information codes, and performing spatial correlation analysis at a confidence level of 0.95, the relationship between the Cloud microphysical structure and the spatial values and distribution of selected precipitates was revealed. The results showed that in the case study of heavy and medium rainfall, the spatial average of 24-hour cumulative rainfall in the province was 36 and 12 mm, respectively. A fully developed cloud structure with a cloud ratio of more than 75% and a vertical expansion of 6 to 9 thousand meters, with an optical thickness of 40 to 50, has led to the occurrence of these widespread and significant rainfall in the province. While in the case of light rain, a significant discontinuation was seen in the horizontal expansion of the cloud cover in the province and the cloud cover percentage was less than 10%. In addition, the factors related to the vertical expansion of the cloud were much lower, so that the height of the cloud peak in this rainfall was between 3 to 5 thousand meters. The results of this study showed that in heavy and medium rainfall cases, a significant spatial correlation was observed at a confidence level of 0.95 between MOD06 Cloud microphysical factors and recorded precipitation values, while no significant spatial correlation was observed in light rainfall case.
