r.farhadi

 Solar collectors and photovoltaic panels are usually exposed to the sun at a fixed angle relative to the horizon. The optimal angle has a significant effect on receiving maximum energy. Since there is not a comprehensive study to determine the optimal angle in Khuzestan province, in this research, the centers of counties in Khuzestan province, including twenty-six cities, were considered. The energy received on an inclined surface was calculated based on the average of 16 years of solar radiation data and the isotropic and non-isotropic models (HDKR model). Different angles from -20 to 90 degrees with a step of 0.1 were examined using Fortran codes, and the angle corresponding to the maximum received energy was determined as an optimal angle. Comparing the obtained results with previous studies showed that the HDKR model has better performance, and the average optimal angle of the cities of Khuzestan province was approximately 26 degrees with a standard deviation of 0.8 degrees.

Greenhouse cultivation is the popular intensive kind of crop production with a yield per cultivated unit area more than 10 times higher compared to field crops. Greenhouse production requires the use of large amounts of energy, water, and pesticides and it usually generates huge quantities of wastes to be disposed of it. Investment, labor, and energy costs per unit area are much higher in the greenhouse industry than in any other agricultural sectors. Sustainable greenhouse systems, socially supportive, commercially competitive, and environmentally sound, depend on cultivation techniques, equipment management, and constructive materials that aim to reduce agrochemicals, energy and water consumption as well as waste generation. The management of the greenhouse environment is depending on temperature manipulation. Temperature manipulation is critical to influencing plant growth, quality, and morphology and so is a major strategy in the environmental modification of crops. Heterogeneous indoor microclimate of a greenhouse has long become a matter of concern in many studies. It is believed to be unfavorable for crop growth, which damages crop activity, particularly transpiration and photosynthesis, one of the major causes of non-uniform production and quality. Since early and conventional methods are not sufficient to evaluate microclimate variables inside a greenhouse, Computational Fluid Dynamics (CFD) approach was applied for better and more accurate results. CFD is an effective numerical analysis technique to predict the distribution of the climatic variables inside cultivation facilities. Numerous studies have focused on the internal temperature, humidity, solar radiation, and airflow inside multiple cultivation facilities. For example, the CFD method was used to simulate natural ventilation for agricultural buildings and improve crop production systems. The CFD simulation and evaluation models could be applied for evaluation of the inside situation and temperature in greenhouses. Thermal and water vapor transfer is influenced by the openings of greenhouses in the CFD simulation. The CFD model was developed to predict the distribution of temperature, water vapor, and CO2 occurring in a Venlo-type semi-closed glass greenhouse equipped with air conditioners. Based on the above literature, this research aims to evaluate the energy flow and modeling of an un-even semi-buried greenhouse using external and internal variables and numerical solutions by the CFD method.

In this study, Computational Fluid Dynamic (CFD) solution was applied to evaluate the inside environment of a semi-double glass greenhouse with an east-west location. This greenhouse has a special structure that is used in very hot or very cold areas due to its depth of more than one meter below the ground. The greenhouse has an area of 38m2 and an air volume of 78.8m3. The temperature and humidity data were collected from inside and outside the greenhouse by temperature sensors (SHT 11 model made by CMOS USA). Irradiation data were collected inside the greenhouse, on level ground, by the TES132 radiometer.

In this study, the CFD method was used for a model solution with ANSYS Fluent version 2020R2 software. To evaluate the predictive capability of the model and its optimization, the comparison between actual (ya) and predicted values (yp) was used. Three criteria of RMSE, MAPE, and R2 were also used to evaluate the accuracy of the final model. The results showed that the dynamic model can accurately estimate the temperature of the air inside the greenhouse at a height of 1 m (R2 = 0.987, MAPE = 2.17%) and 2 m (R2 = 0.987, MAPE = 2.28%) from the floor. The results of energy flow showed that this greenhouse transfers 6779.4.4 kJ of accumulated thermal energy to the ground during the experiment.

In the present study, the computational fluid dynamics method was used to simulate the internal conditions of an un-even semi-buried greenhouse with external and internal variables including temperature and solar radiation. The results showed that this greenhouse structure is able to transfer part of the increase in temperature caused by sunlight to the soil depth (104.214 kJm-2 heat through the floor, 178.443 kJm-2 through the north wall and 113.757 kJm-2 through the south wall). By increasing the thermal conductivity of the inner surface of the greenhouse, the heat flux to the depth of the soil can be increased.

Today, air pollution in urban areas is a major issue that have been affecting human health and the environment. Over the years artificial neural network methods has been used for prediction of pollutants concentration in many metropolitans. In the present study data were obtained from department of environment and air quality controlling stations in city of Tehran from March 2012 to October 2013. Prediction of CO and PM10 contaminations during cold and warm seasons under the influence of instability indices and meteorological parameters was done using the artificial neural network. Results of the modeling process showed that the highest correlation coefficient was obtained 0.84 for PM10 in warm season. On the contrary, the highest correlation coefficient of CO in cold season was 0.78. Also, the effect of instability indices on air pollution was investigated. The highest CO concentration occurred during cold seasons (R2= 0.81), while the lowest concentration was in warm season (R2= 0.72). In case of  PM, the highest concentration occurred during warm seasons (R2= 0.84), while the lowest concentration was in cold season (R2=0.75).

To determine the mechanical behavior (creep) of potato under constant load, two potato cultivars were stored in two different conditions and the effects of storage time and temperature were investigated on creep behavior of the samples. Creep parameters included instantaneous elastic coefficient, delay elastic coefficient, initial viscoelastic coefficient, delayed viscoelastic coefficient and delay time. Two samples showed different mechanical properties, However, in both samples, there was a significant decrease (P <0.05) in all creep parameters except retardation time with increasing storage time. The effect of storage temperature on these parameters was also checked that results showed the reduction of these parameters in the non-technical storage especially in the Clone variety compared to the technical storage. A mathematical model showed as well the creep behavior of stored potatoes. Regression equations showed good results (R2 = 0.73-0.85) for the effect of storage time and temperature on creep parameters. The results of these equations showed that the Instantaneous modulus of elasticity parameter had the most effect on the creep parameters. According to these results, it can be said that in technical storage due to low temperature and controlled moisture than non-technical storage, there are better conditions for tuber durability than non-technical warehouse. The length of storage period of ‘Agria’ genotype is higher due to lower loss of moisture content and starch content and no sprouting compared to ‘Clone’ genotype. However, the tissue of the ‘Clone’ genotype is softened in comparison to the fresh sample less than two months in non-technical storage and less than three months in the technical storage due to the loss of moisture and the reduction of starch content that directly affected on tissue.

Storage of potato is essential for the continuous supply of raw materials for domestic and industrial use.Dueto structural changes (tissue) and followed by changes in the mechanical properties of the tubers during storage and its impact on product quality, the information of the mechanical properties of potato tubers reduces losses and economic lossespartly along with other factors.In this research two potato genotype (Agria and Clone397009-8) were stored in two technical and non-technical storage for three monthsin Ardebil.The uniaxial compression test was used to measure the effect of variety,storage temperature and storage duration on elastic modulus, failure force and failure energy, and penetration test to measure hardness and penetration energy.Measurement was done weekly and the final results were reported after the storage period. The results showed thatcultivar, storage temperature and storage duration have a significant effect on all mechanical properties in both cultivars.With increase storage time, the elastic modulus, failure force, failure energy, hardness and penetration energy in technicalstorage were lower than non-technical storage,which this difference was statistically significant (P <0.05). The results showed that cultivar Agria has a higher elastic coefficient and rigidity than Clone genotype because of rigid texture and asa result, the storage period is longer.