Design and Construction
S. Naderi Parizi; R. Alimardani; M. Soleimani; H. Mousazadeh
Abstract
IntroductionActivated carbon has a wide range of applications as a porous material in the liquid or gas phase adsorption process. The physical process of activated carbon production is divided into two stages thermal decomposition and activation. In this study, only the activation stage has been studied ...
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IntroductionActivated carbon has a wide range of applications as a porous material in the liquid or gas phase adsorption process. The physical process of activated carbon production is divided into two stages thermal decomposition and activation. In this study, only the activation stage has been studied because it is very important in the properties of activated carbon being produced.The production of activated carbon from horticultural waste not only leads to cheap production and supply of many industrial and environmental necessities but also reduces the amount of the produced solid waste. Iran produces about 94,000 tons of pistachio husk annually, which is a good raw material for the production of activated carbon. The profitability index of activated carbon production in Iran is equal to 3.63, which in the case of export, the profitability index will be tripled.Studies have shown that temperature, period, and activation gas flow are the key factors affecting burn-off and iodine number during activated carbon production. Among the various activators tested, steam was found to be the most efficient, with the fastest activation time. For pistachio crops, the minimum iodine number required for economic efficiency is 600 mg g-1, while the highest specific surface area according to the BET test is 1062.2 m2 g-1.Materials and MethodsA Mannesmann tube made of 10 mm thick steel was used to construct the rotating reactor. To minimize heat loss during operation, the kiln body was insulated with a ceramic blanket capable of withstanding temperatures up to 1400°C. The kiln had a length and diameter of 190 cm and 48 cm, respectively, and operated at a temperature of 600°C, requiring approximately 25 kWh of energy for heating. CATIA V5 R21 software was employed to design the device, while ANSYS R20 software was used for thermal and mechanical analysis. The rotary reactor was identified as a critical component due to the high levels of thermal and mechanical stress it experiences. To address these issues, a thermal and fluid analysis was conducted, followed by a mechanical analysis using the results from the prior step. Subsequently, experimental tests were performed on the actual model, and the results were analyzed using statistical methods, including the T-student test in IBM SPSS software.The central heating unit and its surroundings were modeled using ANSYS CFX to obtain valuable information on fluid velocity, radiant properties, and heat transfer within the kiln and surrounding area at an operating temperature of 650°C. The analysis revealed uniform steam flow velocity between the kiln and the heating unit. To accommodate longitudinal expansion resulting from heat stress, taller rollers were employed to allow freedom of movement in that direction, while the lateral movement was unrestricted. This arrangement allows the reactor length to increase under varying temperatures. The reactor's end was designed with grooves and pressure plates, incorporating abrasion and compression plates made from refractory fibers to effectively seal the device. Furthermore, telescopic movement of the parts compensates for expansion effects.Results and DiscussionThe operating temperature of the system was gradually increased to reduce thermal stresses in the reactor shell. This led to a maximum increment in a longitudinal increase of 11.75 mm. Results from five sets of experimental tests and five software analyses demonstrated no significant differences between the experimental and analytical results at a significance level of 5%. Based on the thermal contour analysis, the thickness of the insulation layer was determined to be 5 cm. To control the operating temperature of the device, two methods were employed: adjusting the flame length of the burner and using different types of exhaust outlets. These measures effectively reduced thermal stress on the device.ConclusionThermal and mechanical analysis were useful methods for predicting heat distribution, thermal stresses, and potential dimensional changes in the activated carbon reactor. To compensate for possible alterations in the reactor's length and diameter, abrasive plates and friction washers were implemented. Careful control of fuel input to the burner and regulation of exhaust gas flow helped effectively reduce thermal stresses on the device.
A. Omidi; R. Alimardani; M. Khanali
Abstract
Introduction Geographical location and climatic conditions are the important factors affecting the wind energy potential of each region. Iran is a vast country with different climates and the exploitation of its wind energy needs to study and research on the meteorological data. In the study area during ...
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Introduction Geographical location and climatic conditions are the important factors affecting the wind energy potential of each region. Iran is a vast country with different climates and the exploitation of its wind energy needs to study and research on the meteorological data. In the study area during the warm season and the hottest hours of the day, coinciding with peak electricity consumption in the region and the country, wind blowing continuously carried out. The surpassed consumption over production of electricity in summer and vice versa in winter is considered as one of the country's problems. The aim of this study was to investigate the parameters of the wind energy and the feasibility of wind potential (in study area) in the warm season in particular and other seasons to supply the needed electrical power of area, avoid of unwanted blackouts, development of wind energy as an important renewable energy, attraction of investors, and policymakers to build wind farms in the study area. Materials and Methods This study was conducted in the Dehloran city, located in the southern part of Ilam province. The region has a temperate winter and very hot and dry summer. The important criteria for construction of wind power plants and using of its energy are wind power density and the annual wind speed average. For this reason and analysis, and statistical analyzes, wind data includes three-hour direction and speed were obtained from the meteorological organization and during 2004 to 2013. The average of annual, monthly and daily wind speed and their standard deviation were calculated. Based on the commercial turbines in the country, and the rotor blades are at altitudes up to about 80 meters, the wind speed at altitudes of 40, 60 and 80 meters was calculated. To evaluate the potential of wind speed the Rayleigh and Weibull distribution functions were used and their parameters were calculated. The wind energy potential using the available data and the Weibull and Rayleigh functions were calculated. Results and Discussion Based on the results of the ten-year data, average of wind speed had relatively slight variation, with the highest and the lowest value of 3.6 and 3.25 m s-1 in 2007 and 2010, respectively. The annual average was about 6 m s-1 in height of 50 meters that seems appropriate. The highest and the lowest monthly average values were 4.62 m s-1 and 2.24 m s-1 in June 2005 and November 2006, respectively. Generally, the warm months had significantly higher wind speed than that of cold months. The Weibull distribution function parameters, k and c were calculated. Minimum and maximum amount of k were 1 and 1.828, in December 2006 and May 2011, respectively. The minimum and maximum amount of c was 2.37 and 5.69 in November 2004 and June 2013, respectively. The highest value of wind power density was 312 w m-2 in June. The lowest power density was observed in November. Therefore, we can say that the wind energy potential of the region has coincident with peak electricity consumption in the warm months. The most frequent and the least frequent wind direction were the southeast and northeast, respectively. Conclusion Daily evaluation of wind speed during different months, seasons and years showed a significant change during the day that represented the high value of the wind speed in noon and afternoon. The highest value of monthly wind energy density was for the warm season. The lowest and highest power density was in November and June, respectively. Therefore, we can say that the peak of wind energy potential of the region has a coincident with the country's peak power consumption in warm months. With considering that the study area has a warm climate and high consumption of energy in the hot days of a year and the probability of unwanted blackout of electricity in warm months, and the long hours of the wind blowing in the mentioned times, construction of wind farm in these areas can be reasonable.
Design and Construction
S. I. Saedi; R. Alimardani; H. Mousazadeh; R. Salehi
Abstract
Introduction Global increase in the food demand and challenges regarding the water, energy and fertile soil has made it clear that current strategies are no longer efficient for maintaining food safety. Therefore, attention to novel, science-based, seasonal and climate-independent farming methods which ...
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Introduction Global increase in the food demand and challenges regarding the water, energy and fertile soil has made it clear that current strategies are no longer efficient for maintaining food safety. Therefore, attention to novel, science-based, seasonal and climate-independent farming methods which could result in the higher crop quality and quantity is an inescapable decision. Among all agricultural practices and technologies, intensive culture and hydroponic methods in controlled environments play an important role. Materials and Methods To address these challenges, an indoor solar-powered auto-irrigate rotary cropping system (SARCS) was designed and implemented. Arrangement of plants in the surface area of an open-ended drum makes it possible to use space rather than area to maximize the acreage. An embedded fuzzy control system managed the irrigation process based on the plant water requirement predictions, and photovoltaic panels (PVs) was responsible for system electrical energy provision. The drum rotates around its horizontal axis where LED lamps are positioned to provide light to plants. This structure causes the plants gain the light illumination efficiently while getting access to water accumulated in the secondary tank positioned beneath the drum. Fertigation fuzzy control was based on plant evapotranspiration (ET) estimations with temperature, humidity, and light as its inputs. The instantaneous estimated ETs which were measures for root substrate moisture were summed until reaching its critical value which is equivalent to plant readily available water (RAW). This tends to trigger a pump submerged in a primary tank to fill the secondary one up to a predefined height ruled by a level sensor. The solar energy system consisted of PVs, MPPT, inverter, and battery bank. The SARCS evaluation procedure included two valid lettuce cultivation in grow bags filled with the same proportions of perlite and coco peat as a root substrate. The first cultivation used water level sensors to rule the irrigation process (non-fuzzy) while the second one (fuzzy) were governed by fertigation cycle fuzzy control. Results and Discussion The results showed that employing these two modes increased lettuce planting density to about 12 times in the field culture and 4 times in the greenhouse. The energy consumption evaluation revealed that in fuzzy and non-fuzzy approaches the same amounts of energy were needed. But in fuzzy mode the amount of energy consumed per kilogram of marketable lettuce was 74.33% less than in non-fuzzy mode. Fuzzy and non-fuzzy modes utilized 58.81% and 48.41% of the total energy requirements from PVs, respectively. It was calculated that the solar system is able to supply 51.16 % of SARCS total annual energy requirements in Karaj Province. The results of water consumption evaluations revealed that the fuzzy approach could cut the needed water to 24%, and improved the marketable product to 74.47%. For producing one kilogram dry and fresh biomass, fuzzy mode used 50.41% and 55.53% less water than non-fuzzy, respectively. Furthermore, one kilogram marketable product in fuzzy approach needed 56.46% less water than in non-fuzzy. The averaged water needed for growing one lettuce plant in non-fuzzy and fuzzy modes were 15 times less than in field lettuce. The comparison of growth parameters of harvested lettuce in the two studied approaches revealed that fuzzy mode would have significantly higher results in all parameters. Conclusion The results suggested that the development of intensive culture strategies would play an important role in the sustainable agricultural production and food safety. Also, the solar energy utilization in farming practices could save fossil resources and decrease air pollutions. Finally, purposeful irrigation approaches which are based on plant water requirement predictions can significantly reduce the total water consumption and improve products quality. This strategy, therefore can be introduced to other farming practices such as field and greenhouse methods.
S. I. Saedi; R. Alimardani; H. Mousazadeh
Abstract
Introduction Global solar radiation is the sum of direct, diffuse, and reflected solar radiation. Weather forecasts, agricultural practices, and solar equipment development are three major fields that need proper information about solar radiation. Furthermore, sun in regarded as a huge source of renewable ...
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Introduction Global solar radiation is the sum of direct, diffuse, and reflected solar radiation. Weather forecasts, agricultural practices, and solar equipment development are three major fields that need proper information about solar radiation. Furthermore, sun in regarded as a huge source of renewable and clean energy which can be used in numerous applications to get rid of environmental impacts of non-renewable fossil fuels. Therefore, easy and fast estimation of daily global solar radiation would play an effective role is these affairs. Materials and Methods This study aimed at predicting the daily global solar radiation by means of artificial neural network (ANN) method, based on easy-to-gain weather data i.e. daily mean, minimum and maximum temperatures. Having a variety of climates with long-term valid weather data, Washington State, located at the northwestern part of USA was chosen for this purpose. It has a total number of 19 weather stations to cover all the State climates. First, a station with the largest number of valid historical weather data (Lind) was chosen to develop, validate, and test different ANN models. Three training algorithms i.e. Levenberg – Marquardt (LM), Scaled Conjugate Gradient (SCG), and Bayesian regularization (BR) were tested in one and two hidden layer networks each with up to 20 neurons to derive six best architectures. R, RMSE, MAPE, and scatter plots were considered to evaluate each network in all steps. In order to investigate the generalizability of the best six models, they were tested in other Washington State weather stations. The most accurate and general models was evaluated in an Iran sample weather station which was chosen to be Mashhad. Results and Discussion The variation of MSE for the three training functions in one hidden layer models for Lind station indicated that SCG converged weights and biases in shorter time than LM, and LM did that faster than BR. It means that SCG provided the fastest performance. However, the story for accuracies was different i.e. the BR, LM, and SCG algorithms provided the most accurate performances, respectively, both among one or two hidden layers. According to the evaluation criteria, six most accurate derived models out of 1260 tested ones for Lind station was 3-14-1 and 3-11-19-1 with LM, 3-20-1 and 3-20-19-1 with BR, and 3-9-1 and 3-20-17-1 with SCG training algorithm, and 3-20-19-1 topology with BR showed the best performance out of all architectures. Results of the evaluation of the six accurate models in the remaining 18 stations of Washington State proved that regardless of the climate, in each weather station, BR with its inherent automatic regularization, provided the most accurate models (0.87 67.41 %), and then SCG (0.90>R>0.83, 3.91>RMSEMAPE > 77.28 %). Therefore, the Bayesian neural networks, which showed the best performance among all Washington State weather stations, were evaluated for Mashhad station, as an Iran sample climate. The results proved the ability of the said networks for this climate (R=0.82, RMSE=3.92 MJm-2, MAPE=79.92%). Conclusion The results indicated that the Bayesian neural networks are capable of predicting global solar radiation with minimum inputs in different climates. This was concluded both in Washington State weather stations, which has a variety of climates, and also in Mashhad as an Iran sample weather station. These models would eliminate the need for complex climate-dependent mathematical relations or other models which are mostly dependent on many inputs. So, this algorithm would be a good means first in weather forecast practices, also in the design and development of solar assisted equipment, as well as in managerial practices in agriculture when monitoring crop solar-dependent processes like photosynthesis and evapotranspiration.
K. Afsahi; A. Akram; R. Alimardani; M. Azizi
Abstract
For improvement or change in a plowing system, it is crucial that all important parameters to be taken in account. Recommendation of a tillage system should receive supports from research data as well as from skilled farmers in order to find a resolution to problems of that system. In this study, strengths, ...
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For improvement or change in a plowing system, it is crucial that all important parameters to be taken in account. Recommendation of a tillage system should receive supports from research data as well as from skilled farmers in order to find a resolution to problems of that system. In this study, strengths, weaknesses, opportunities and threats (SWOT) of different tillage systems for wheat cultivation in the Khodabandeh region (Zanjan province, Iran) were identified and ranked using Analytic Hierarchy Process (AHP). Based on the viewpoints of skilled farmers, the main threats in tillage systems, which include small farm lands in the region, lack of qualitative research on new tillage systems and lack of government support, affected the system selection (32 percent), relative strengths(26 percent), opportunities (22 percent), and weakness(20 percent). Because of these threats, farmers keep using conventional tillage method (with the value of 47 percent) in spite of their awareness about the benefits of conservation tillage and no-tillage methods. In this situation, the recommended measures are; making new policies for the land integration, performing qualitative research specially on new machinery, clarifying the government's policies on exporting and importing agricultural products and on the amount of guaranteed prices of products before starting the growing season. By these activities the threats can be replaced by opportunities and strengths.
H. Mohamadi-Monavar; R. Alimardani; M. Omid
Abstract
Agricultural sector experiences the application of automated systems since two decades ago. These systems are applied to harvest fruits in agriculture. Computer vision is one of the technologies that are most widely used in food industries and agriculture. In this paper, an automated system based on ...
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Agricultural sector experiences the application of automated systems since two decades ago. These systems are applied to harvest fruits in agriculture. Computer vision is one of the technologies that are most widely used in food industries and agriculture. In this paper, an automated system based on computer vision for harvesting greenhouse tomatoes is presented. A CCD camera takes images from workspace and tomatoes with over 50 percent ripeness are detected through an image processing algorithm. In this research three color spaces including RGB, HSI and YCbCr and three algorithms including threshold recognition, curvature of the image and red/green ratio were used in order to identify the ripe tomatoes from background under natural illumination. The average error of threshold recognition, red/green ratio and curvature of the image algorithms were 11.82%, 10.03% and 7.95% in HSI, RGB and YCbCr color spaces, respectively. Therefore, the YCbCr color space and curvature of the image algorithm were identified as the most suitable for recognizing fruits under natural illumination condition.
D. Mohammad Zamani; S. Minaei; R. Alimardani; M. Almassi; R. Yusefi
Abstract
In this study evaluation and comparison of various interpolation approaches for estimation un-sampled values of soil Organic Matter Content (OMC) and soil texture is presented. The main objective is to develop a precision method for generation of management maps for variable rate application of herbicide ...
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In this study evaluation and comparison of various interpolation approaches for estimation un-sampled values of soil Organic Matter Content (OMC) and soil texture is presented. The main objective is to develop a precision method for generation of management maps for variable rate application of herbicide that eventuate to save herbicide application and to reduce adverse impact on the environment. For this purpose after sampling of 42 points on the test field and generation of local and global grid of sample points on a PC, various interpolation methods were applied to estimate soil OMC and texture on un-sampled points by Surfer software. Inverse distance to a power, Kriging, minimum curvature, weighed moving average and radial basis function were used as interpolators. To evaluate the mentioned methods, cross-validation approach and two statistical parameters MAE and MBE were used. The results showed that minimum curvature method with MAE equal to 1.31 has the minimum error than other methods. In this method MAE value for sand, silt and clay was equal to 1.6, 1.18 and 0.59, respectively. In comparison with other methods, this approach had the minimum error. It was demonstrated that minimum curvature method was the best approach to estimate grid point values at un-sampled points. Finally after selection of appropriate method and using considered manufacturer recommendations of herbicide application based on OMC and soil texture, a digital management map of Cyanazine variable rate application in a corn field was generated. Based on this map and considering the herbicide uniform application in the farm as 1.7, 2.9 and 4 Lha-1, herbicide application rate compared with 1.8 Lha-1, decreases 39% and increases 4 and 50% respectively. This means that if the entire field is sprayed with the uniform rate of 1.7 Lha-1, Compared with1.8 Lha-1 which is obtained using management map, herbicide application will be saved 39 %. Similarly, if herbicide is applied 2.9 and 4 Lha-1 uniformly, compared to the amount 1.8 Lha-1, 4 and 50% of herbicide application will increase respectively.
