میثم سالاری

The aim of this research is to optimize the design parameters of underground drainage systems with an economic approach. The study of the relationship between the depth and distance of drain installation has been the subject of many researchers, each of whom has tried to reduce the costs of drain implementation. In this research, genetic and multi-world algorithm optimization model was used to optimize the main design parameters of the underground drainage system of regional agricultural lands around Gorgan city. The area of the construction area of the drainage system was around 200 hectares. In this research, by using genetic and multi-world algorithm, the design parameters were selected in such a way that they lead to the lowest implementation cost of the underground drainage system. In this regard, the design parameters have been selected by combining Hohhot's permanent equation and optimization algorithms.

The area under study is Aliabad district, one of the functions of Gorgan city. The lands of Ali Abad region are also located in the upper part of the plains. These lands are located in eastern longitude and northern latitude. The study area covers about 200 hectares.
Genetic Algorithm:Genetic algorithm is an optimization method inspired by living nature, which can be referred to as a numerical method, direct and random search in classifications. This algorithm is based on repetition and its basic principles are adapted from genetic science.
Multi verse Algorithm:The big bang theory considers the occurrence of a big explosion as the beginning of the origin of our universe. According to this theory, the big bang is the origin of everything in this universe and nothing existed before it. A population-based algorithm performs the search process in two stages: exploration and exploitation. In this algorithm, the concepts of white hole and black hole are used to explore the search space. In contrast, wormholes help exploit search spaces.

Genetic Algorithm:By applying the genetic algorithm optimization model to the data of the studied lands, the optimal parameters were calculated. Table (4) shows the design parameters obtained from the genetic algorithm optimization model in different drainage coefficients for the allowed depth of drain installation. Considering the entire search area (permissible depth of drainage installation from 1.5 to 3.5 meters from the ground surface), the results obtained from the land input data of the studied area showed that taking into account the drainage coefficient of 2.5 mm per day, the minimum cost the equivalent of 51.3 million Tomans has happened in 8 hectares at a depth of 2.62 meters from the ground surface with an installation distance of 79.9 meters and a diameter of 125 mm.
Multiverse algorithm
The optimal parameters were calculated by applying the multi-world algorithm optimization model. Table (7) shows the design parameters obtained from the optimization model in different drainage coefficients for the allowed depth of drain installation. Considering the entire search area (permissible depth of drain installation from 1.5 to 3.5 meters from the ground surface), the results obtained from the input data of Aliabad lands showed that taking into account the drainage coefficient (discharge intensity) 2.5 mm per the minimum cost equivalent to 51.5 million Tomans has happened in an 8-hectare unit at a depth of 2.61 meters from the ground with an installation distance of 79.5 meters and a diameter of 125 mm.
Comparing the results of genetic and multiverse algorithms
Comparing the performance of genetic and multi-world algorithms shows the high efficiency of both algorithms in solving the problem of optimizing the diameter of drainage pipes and their installation depth. Both algorithms have almost the same performance in solving this optimization problem; So that both algorithms in the distance of the impervious layer to the depth of the drain installation (D) is equal to 2.25 meters, the stabilization depth of the water table (in the middle of the two drains) from the ground level (H) is equal to 1.5 meters and intensity Drainage or drainage from the surface unit (q) is equal to 4 mm per day, and they have calculated the optimal depth of drainage installation to be 13.3 meters

The design of drainage systems consists of choosing three parameters: depth, diameter and distance of drains. Various approaches can be used to choose the best combination of three parameters. One of the approaches can be to reduce the costs of implementing the drainage system. In this research, using the genetic algorithm, these parameters were selected in such a way that they lead to the lowest implementation cost of the drainage system. In this regard, the design parameters have been selected by combining Hohhot's permanent equation and genetic algorithm.

Ecosystems management of river and water flow necessary for continuity of life and ecological sustainability of river based systems, requires recognition of environmental flows in the politics and intentions of water resource development projects and inclusion it in watershed management programs. In order to, in this research were analysis application of hydrological methods (Tennant, Tessman, Flow Duration Curve, Smakhtin, Arkansas, FDC-Shifting and DRM) and ecohydraulic habitat suitability simulation model (SEFA) in the environmental flows assessment of Qarasoo River in Golestan Province in interval of hydrometry stations Ghazmahalleh and Siahab, respectively with mean annual flow of 0.26 and 1.92 m3/s for restoration habitat, natural resurrection and conservation of biodiversity. The investigating provision of optimal flow ecosystem with field studies and measurements hydraulic and qualitative characteristics of the river in order to identify the favorable conditions of Capoeta capoeta gracilis hierarchical habitat showed would have the maximum and minimum flow regime required to preservation the Qarasoo river ecosystem according to ecological needs in months of april and september is estimated to order equivalent 3.11 and 0.48 m3/s, with average annual 1.6 m3/s (equivalent 83 percent of natural stream of the river). The results of study show environmental menaces will follow using the values obtained from simple hydrological methods Tennant, Smakhtin and Flow Duration Curve in water resource planning of this river , by contrast ecohydraulic model of SEFA can provide a general croquis of habitat suitability in intervals different of river relative to regime changes natural flow and attainment to optimal

Groundwater resources are the most important sources of agriculture, industry and drinking water supply in many areas. Water quality management for groundwater resources are very important due to the wide use of these resources and there is a need for an adequate understanding of the groundwater quality in the present and future. Coastal aquifers are in contact with the sea which are exposed to saltwater intrusion into fresh groundwater. Therefore, they have a high risk of groundwater water quality degradation. On the other hand, the presence of residential areas in coastal aquifers is accompanied by the entry of drinking water’s wastewater by absorbing wells and leakage from the sewage collection network, which can increase the risk of quality pollution in these areas. Furthermore, the climate change can be very effective in changing water quality in this area due to the direct impact on recharge, and discharge. The Bandar-e-Gaz coastal aquifer is located in the northern part of Iran which is the most important source of fresh water for the inhabitants of this area. The present study aims to assess the impact of climate change on the content and spatial distribution of total dissolved solids, as a water quality measure, in the coastal aquifer level using numerical simulation.

Bandar-e-Gaz coastal aquifer is located to the west of Golestan province in the north of Iran with an area of 173 square kilometers. This aquifer is limited to the Gorgan Gulf from the north, and to the highlands of the Alborz Mountains from the south, and also to the adjacent aquifers from the east and west. In the northern part of the aquifer, groundwater levels have low depth and, on the other hand, significant areas of the Bandar-e-Gaz coastal aquifer area are in the residential area. The drinking water’s wastewater in residential areas is mainly evacuated by absorbing wells, which can significantly reduce the quality of groundwater resources in this aquifer.
The MODFLOW and MT3DMS groundwater models in the form of an integrated model were used to simulate the groundwater level and content and spatial distribution of total dissolved solids. These models solve the driving partial differential equations numerically using a finite difference method. To implement this model, determination of boundary conditions, quantitative and qualitative observation wells, hydrodynamic coefficients of the aquifer, recharge, and discharge from the aquifer, porosity, and longitudinal dispersion coefficient are necessary. The models used for a 12-month calibration period were verified in next 12 months. Besides, the mean of absolute error or MAPE was used to determine the precision of the model.
In this study, the 5th report of International Panel on Climate Change (IPCC) and new emission scenarios were used to investigate the climate change impacts on future changes in content and spatial distribution of total dissolved solids in the Bandar-e-Gaz coastal aquifer. The impacts of climate change on groundwater quality were studied under two optimistic and pessimistic scenarios. These are as follows:Optimistic climate scenario (RCP2.6) + extraction of groundwater at a constant rate until 2100+ no change in Caspian Sea level up to 2100.
Pessimistic climate scenario (RCP8.5) + extraction of groundwater with an increase equal to 2% per year by the year 2100 + 5 meters decrease of Caspian Sea level at the end of the period 2100.

Considering the model's precision criterion (mean absolute percentage error) indicates that this criterion in the calibration and verification period is in the range of (0.0008-0.029) and (0.032-0.055) which indicates the precision and also the perfect reliability of the model to estimate the content and spatial distribution of the total dissolved solids in Bandar-e-Gaz coastal aquifer. The results of the emission scenarios show that both scenarios indicate an increase in future precipitation and temperatures, but the intensity of the changes in these two scenarios are different. The simulation of total dissolved solids based on the optimistic scenario shows that the average content of this pollutant will have a seasonal periodic behavior in the long term and will experience a very limited increase in the aquifer level. The use of a pessimistic scenario represents a periodic and increasing behavior in the average content of total dissolved solids at the aquifer. Moreover, there will be a different intensity of increases in different periods, with the greatest increase in near future. Furthermore, the prediction of spatial distribution of total dissolved solids indicates that pollution in the north of the aquifer will be significantly increased, and the increase in pollution at the aquifer level will not be uniform in the spatial pattern, which can be due to the spatial distribution of residential areas, as well as water extraction wells.

The prediction of the response of coastal aquifers to pollutants from the sea and by humans is very important. In this study, numerical models were used to predict the quality response of Bandar-e-Gaz coastal aquifer to climate change as well as human activities. The results of this study indicate that an increase in the total dissolved solids content in the aquifer will occur in future. The numerical simulation also leads to the estimation of spatial distribution and changes of total dissolved solids c in Bandar-e-Gaz coastal aquifer. The predicted values for increasing the total dissolved solids content, as well as the expansion of spatial distribution maps of this pollutant, can be used as a suitable tool for managing groundwater quality in the area.

Introduction. Citrus is one of the most commercially important horticultural crops grown in tropical and sub-tropical regions of the world. They are classified as non-climacteric fruits. Harvesting date and storage can influence citrus fruit quality and shelf life. In Iran, some members of citrus family including sweet orange and mandarin are produced as an export crop, so research on fruit quality and storage life is needed. There is no available scientific literature regarding the effect of harvesting date and storage duration on retaining the postharvest physicochemical properties of Kinnow mandarin under cold storage. The main objective of the present study was to evaluate the effect of harvesting date and storing time on shelf life and quality of Kinnow mandarin fruits under Jiroft weather conditions.
Materials and Methods. Investigations were carried out on mandarin (Citrus reticulata) cv. Kinnow grafted on sour orange rootstock in an orchard located in Jiroft and Kahnooj Agricultural Research Center, Jiroft, Iran. Fruits were harvested on 6th December, 21th December, 5th January, 20th January and 4th February. After cold storage for 30-90 days at 4-6 °C, the fruit was analyzed for quantitative and qualitative characteristics including weight of fruit, peel, meat, pulp and juice, fruit weight loss, pH, total soluble solids (TSS), titratable acidity (TA) and TSS/TA. Experiment was arranged in a split plot based on randomized complete block design (RCBD). Data analysis and similarity coefficient (Pearson's method) were performed using SPSS.16 software, and means comparison was performed by using Duncan's multiple range test at 1 and 5% probability levels.
Results and Discussion. The results showed that the interaction effect of harvesting date and storage period on the weight of the fruit, meat, pulp and juice and TSS, TA and TSS/TA was significant at 1% probability level. Weight of harvested fruits from 6th December to 5th January was constant, but fruits harvested on 20th January and 4th February were heavier as much as 12.5 and 14.3 percent, respectively, compared to 6th December. Fruit weight loss increased along with the increase in storage time duration, so that mean fruits weight loss percentages were 3.5 and 16.5 at 30 and 90 days of storage, respectively, due to continued transpiration of the fruits after harvesting. As a result of transpiration, water enters into the atmosphere through the pores existing on fruit surface. The greatest fruit weight (121.8 g) was recorded for combination of harvesting on 20th January and 30-day storage. Fruits harvested on 20th January and 30-day storage had higher meat and pulp weight (89.6 and 52.3 g, respectively) and a significant correlation coefficient was detected between them. Changes of fruit juice pH at different stages of fruit ripening and storage times did not follow a fixed pattern, though pH slightly increased in some cases during storage, which can be due to oxidation of citric acid during storage. The maximum TSS was recorded for harvesting on 5th January and 90-day storage (11.7 °Brix) as well as 4th February and 60- and 90-day storages (11.8 °Brix), while the minimum TSS was observed on 6th December and 30-day storage (8.7 °Brix). The results exhibited that TSS content of fruit juice increased when storage period increased, which was possibly attributed to the hydrolysis of starch and increase in sucrose content. However, increase in TSS during storage is not always directly related to changes in the simple sugar content of fruit. During storage and maturation of the fruits on the tree, TA reduced due to the use of citric acid in respiration. Taste index (TSS/TA) in fruits harvested at full maturity was greater than that in fruits harvested in the fall. Besides, TSS/TA increased during storage, so that the highest and lowest average TSS/TA ratios were related to harvesting on 4th February and 30-day storage as well as 6th December and 30-day storage, respectively. According to the results, fruits did not reach full maturity until 5th January under Jiroft weather conditions.
Conclusion. Postharvest quality and shelf life of Kinnow mandarin fruits were affected by harvesting date and storage duration. Delay in harvest resulted in an increase in fruit weight, TSS and TSS/TA. TSS and TSS/TA were higher when fruits harvested on 4th February. Fruit weight loss increased when the storage period increased.. Overall, 4th February is the best date to harvest Kinnow mandarin fruit in Jiroft.

Nowadays filtration process is increasingly used in various areas such as water purification, food industries, filtering the air dust and other separation applications. In this work, the HDPE microporous filters have been fabricated at different pressure and time conditions via sintering process and then were characterized by different techniques. It can be expected that microstructure and mechanical properties of the samples could be controlled by changing the fabrication parameters like temperature, pressure, time of the process and also by changing the properties of the resin such as powder shape, particle size and rheological properties. In the first step, by using DSC, MFI, rheology test and optical microscope, the most suitable polymeric powder for sintering process was chosen. The sintering temperature was fixed in the vicinity of melting temperature of the used HDPE powder, based on DSC result. In order to evaluate mechanical properties and porosity of the samples, the results obtained from the shear punch test, acetone drop permeability, gas permeability, transition optical microscopy and SEM, have been used; then the effect of pressure and time parameters on the characteristics of the product has been studied. Finally, it was concluded that it is possible to make microporous filters with suitable mechanical properties, using sintering process at controlled pressure and temperature conditions.It can be seen that by increasing time and pressure, on the one hand the mechanical properties of the products increase, and on the other hand, their porosity and the gas permeability of the vents decrease.

In the conventional methods of flood frequency analysis, the flood peak variable is just considered and assumed that this variable follows some specific parametric distribution function. This assumption would restrict us and lead us to the limited available information to evaluate the flood risk. It is well known that a flood event has three variables of flood peak, volume and duration which are random in nature and are mutually dependent. In this research, the concept of the Copula function is briefly introduced and then used to modeling the dependency structure of the flood variables of the Karun River at the Ahvaz hydrometric stationand then estimate their joint probability distribution. We use three well-known and appropriate copulas, including Ali–Mikhail–Haq, Cook–Johnson and Gumbel–Hougaard which belong to the Archimedean class of copulas, to modeling the joint probability distribution of the flood variables, where the marginal distributions of the flood’s variables are selected from the parametric and non-parametric distributions. The Gumbel–Hougaard family led to better modeling of different combination of flood’s variables based on goodness of fit criteria. The selected copula is used to estimate conditional cumulative distribution function and joint return periods which lead to better estimation of flood risk.

Banks as financial institutions must estimate the credit risk of their debtors. This is the basis of pricing a loan, determining appropriate interest rates and determining the mortgage required to each borrower. Since the continuity of bank activities largely depends on the amount of credit losses in a particular period, banks should consider the credit quality of their loan portfolio as a collection of debts.In this paper, the calculation of credit risk of corporates applying for loans has been investigated. Using fuzzy analytic hierarchy process, effective criteria for credit risk have been analyzed.The neural network is used to extract an open box model that describes the relationship between effective criteria and the credit risk of the companies who apply for a loan. Neural network model has been run with historical data. Observations have been based on 174 corporate who had taken out a loan from a major Iranian bank named Mellat (All loans had been made during 2005 to 2008).The output of the model can predict credit risk of a corporate by at least 84% accuracy.