Modeling
S. Karimi Avargani; A. Maleki; Sh. Besharati; R. Ebrahimi
Abstract
The main objective of this paper is to develop a seven-link dynamic model of the operator’s body while working with a motorized backpack sprayer. This model includes the coordinates of the sprayer relative to the body, the rotational inertia of the sprayer, the muscle moments acting on the joints, ...
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The main objective of this paper is to develop a seven-link dynamic model of the operator’s body while working with a motorized backpack sprayer. This model includes the coordinates of the sprayer relative to the body, the rotational inertia of the sprayer, the muscle moments acting on the joints, and a kinematic coupling that keeps the body balanced between the two legs. The constraint functions were determined and the non-linear differential equations of motion were derived using Lagrangian equations. The results show that undesirable fluctuations in the ankle force are noticeable at the beginning and end of a swing phase. Therefore, injuries to the ankle joint are more likely due to vibrations. The effects of engine speed and sprayer mass on the hip and ankle joint forces were then investigated. It is found that the engine speed and sprayer mass have significant effects on the hip and ankle forces and can be used as effective control parameters. The results of the analysis also show that increasing the engine speed increases the frequency of the hip joint force. However, no significant effects on the frequency of the ankle joint force are observed. The results of this study may provide researchers with insight into estimating the allowable working hours with the motorized backpack sprayers, prosthesis design, and load calculations of hip implants in the future.
Modeling
H. Soltanali; M. Khojastehpour
Abstract
Introduction: With the emergence of new automation and mechanized technologies in the production and processing of agricultural products in Iran, which aim to accelerate the food supply process, adopting appropriate management models in the field of maintenance becomes inevitable. This is crucial to ...
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Introduction: With the emergence of new automation and mechanized technologies in the production and processing of agricultural products in Iran, which aim to accelerate the food supply process, adopting appropriate management models in the field of maintenance becomes inevitable. This is crucial to maintain and enhance the operational reliability of agricultural machinery, tools, and equipment. Furthermore, proper management of various physical assets in the agricultural industry, including operation and maintenance, is one of the most important requirements. This is due to their crucial role in ensuring readiness and high availability during the seasons of planting, cultivating, and harvesting agricultural products. These needs differ from that of other continuous production processes. Materials and Methods: To achieve an efficient model in the field of maintenance, the following steps have been investigated:a) Reviewing and identifying the most important criteria and sub-criteria driving the maintenance management. This is based on the previous literature and the experts’ opinion.b) Evaluating and prioritizing the main criteria and the interactions between their sub-criteria using the Best-Worst Method (BWM).c) Providing improved solutions for maintenance management of Iranian agro-industries.We decided to employ BWM because, compared to similar methods, it (i) provides more reliable pairwise comparisons, (ii) reduces the possible anchoring bias that may occur during the weighting process by respondents, (iii) is the most data-efficient method, and (iv) provides multiple optimal solutions which increase flexibility when accessing the best weight point. The process of weighting by BWM is summarized in five steps:1) Determine a set of evaluation criteria identified by the experts or decision-makers.2) Identify the most important (Best) and the least important (Worst) criteria according to the experts or decision-makers, each of which may have their own Best and Worst.3) Determine the preference of the Best criterion over all the other criteria using a number from 1 to 9 (where 1 represents equal importance and 9 represents extremely more important).4) Determine the preference of all the decision criteria over the Worst criterion.5) Compute optimal weights. Results and Discussion: According to the preliminary surveys, the most important criteria in the excellence maintenance model were identified as “organizational management”, “human-related factors”, and “organizational aspects”, respectively. The results of the BWM revealed that sub-criteria such as "top management support," "fund allocation and inventory resource management," and "appropriate maintenance strategies" had the greatest impact on maintenance management in agro-industries, with global weights of 0.108, 0.075, and 0.067, respectively. Additionally, these findings were compared to previous research conducted in the field of agricultural and production system maintenance models. Conclusion: The findings of this study could assist managers in revising and developing maintenance management models in the agro-industries. Future studies could consider calculating the interactions among the criteria that were omitted in this study to simplify the evaluation process which might improve the accuracy of weighing criteria. This can be achieved through the combination of the Decision Making Trial and Evaluation Laboratory (DEMATEL) and structural equation modeling.
Modeling
M. A. Hormozi; H. Zaki Dizaji; H. Bahrami; N. Monjezi
Abstract
IntroductionThe development of mechanization and machine technology can have positive and negative effects on the economic, social, and environmental conditions of a region. Conflicts in these areas complicate the selection and optimization of sustainable mechanization systems. One of the basic questions ...
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IntroductionThe development of mechanization and machine technology can have positive and negative effects on the economic, social, and environmental conditions of a region. Conflicts in these areas complicate the selection and optimization of sustainable mechanization systems. One of the basic questions in the selection of a sustainable agricultural mechanization system is how and with what methodology would it be possible to propose the closest mechanization model that will overcome the simultaneous contradictions between the three pillars of sustainability; taking into account the natural and technical limitations in agricultural production. What is the appropriate approach considering the economic, environmental, and social aspects? The current research aims to provide a framework for an optimal mechanization model to achieve the goals of agricultural sustainability so that it can be implemented and applied practically. It is possible to provide a model that addresses the conflicting economic, social, and environmental aspects by quantitatively optimizing the level of mechanization.Materials and Methods In this study, a framework is applied whereby contradictory goals of agricultural sustainability can be achieved simultaneously. After selecting the indices and data collection, by combining Shannon entropy and TOPSIS, the similarity index was obtained for each objective. The similarity indices and values of the Benefit-Cost Ratio calculated for each system were considered as coefficients of three objective (economic, social, and environmental) functions in multi-objective optimization. The multi-objective optimization model was applied to achieve sustainable mechanization patterns and was solved using the NSGA-II algorithm. For framework validation, paddy production mechanization systems in the Ramhormoz region located in southwestern Iran were analyzed with constraints: land, water, and machinery. The five mechanization systems of paddy production included puddled transplanted, un-puddled transplanted, water seeded, dry seeded, and, no-till.Results and DiscussionPareto-optimal solutions of different scenarios with water and machine constraints showed that this framework cannot only meet the sustainable goals, but also the optimal allocation of mechanization systems is identified and the effect of different scenarios under different constraints can be examined. The sustainability goals between the no-tillage and planting with puddling systems are highly contradictory. The no-tillage system has the highest score in the environmental aspect and the lowest score in the social and economic aspects. This modern system was developed in Ramhormoz three years ago and has faced technical, economic, and social challenges ever since. The cultivated area using this system was 43 hectares in 2019. Despite the speed and ease of planting with this system, and its direct environmental benefits, the possibility of fungal outbreaks is raised due to the presence of wheat residues from previous cultivation and the warm and humid environment of cultivation. Additionally, weed outbreaks caused by periodic irrigation have greatly affected the satisfaction and profitability of this system, leading to the highest amount of pesticides consumed among the studied systems. The results of multi-objective optimization of sustainable rice mechanization systems in Ramhormoz city showed that the total surface area of optimal point systems is in the range of 2700 to 3200 hectares, which is close to the area under rice cultivation in Ramhormoz (3310 hectares) and it indicates that the output of the model is according to the applied restrictions and close to reality. The limitation of machinery and water has made the two planting systems of un-puddled transplanting and dry-seeding better than other systems. Removing only the machinery restriction can lead to an increase in the area under rice cultivation by about 700 hectares. This means that the requirement for the development of sustainable rice cultivation in Ramhormoz is to strengthen and support modern mechanized systems of no-tillage, dry-seeding, and planting with puddling, with a focus on systems with less water consumption which are the systems with higher levels of mechanization. Without water limitation, if the model is subject to the current machinery limitations, the optimal mechanization systems are the more traditional ones such as transplanting without puddling and wet-seeding.ConclusionOne of the most fundamental challenges in the development of mechanization is identifying systems that can best balance the economic, social, and environmental aspects of sustainability and minimize environmental damage whilst maximizing economic and social benefits. Using the framework for sustainable mechanization will not only accomplish sustainable goals in identifying the optimum agricultural mechanization level, but it will also allow researchers and implementers in the agricultural sector to examine the outcome of various scenarios under different constraints. This framework can be used to find the optimal model for mechanization of all stages of tillage, planting, harvesting, and post-harvest in diverse geographical areas.
Modeling
R. Khodabakhshian; R. Baghbani
Abstract
The present study aimed to examine the application of accurate and principle-based evaluation of a measuring instrument called the Form Tester in determining and detecting the wear phenomenon in the cylinder liner of agricultural tractors. For this purpose, a cylinder liner of the Perkins 4-248 engine ...
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The present study aimed to examine the application of accurate and principle-based evaluation of a measuring instrument called the Form Tester in determining and detecting the wear phenomenon in the cylinder liner of agricultural tractors. For this purpose, a cylinder liner of the Perkins 4-248 engine (related to the Massey Ferguson 285 tractor) was manufactured by Keyhan Sanat Ghaem Company was used. The geometric parameters that were measured in this research included roundness, straightness, and concentricity of the cylinder liner. The evaluations on roundness and concentricity of cylinder liner were conducted in 12 circular positions with the same longitudinal distances. The straightness was measured in five lines with the same longitudinal distances in 90° around the cylinder liner environment. The results of the measurements were discussed and analyzed to evaluate the engine status along the functional path of the piston within the cylinder liner. The degree of deviation rate of the parameters indicated significant wear within the cylindrical liner. The wear rate in cross-sections at high and low dead points was significantly greater than that of the same cross-section in the vicinity of the midpoint of the piston movement path inside the cylinder, as well as the cross-sections near the high dead point. The results of this research provide feedbacks for engine designers to apply various changes to the engine and for maintenance and repair engineers to ensure the correct implementation as well as preventive and predictive repair and maintenance strategies.
Modeling
A. Niazi; H. Golpira; H. Samimi Akhijahani
Abstract
IntroductionOne of the biggest problems in growing legumes like peas is harvesting these types of crops. During the machine harvesting process the harvest loss is very high. Therefore, in most parts of Iran chickpea harvested by hand and this is very tedious. Based on the literature review there are ...
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IntroductionOne of the biggest problems in growing legumes like peas is harvesting these types of crops. During the machine harvesting process the harvest loss is very high. Therefore, in most parts of Iran chickpea harvested by hand and this is very tedious. Based on the literature review there are different types of harvesting machines which designed, constructed and optimized by Miller et al., 1990; Golpira, 2015; Shahbazi, 2011; Jalali and Abdi, 2014; Mahamodi, 2016. But using different varieties of chickpea in mountainous areas has limited the use of harvesting mechanisms. The purpose of this study is mechanization of the harvesting process of chickpea with low losses and suitable performance. Moreover the optimization process of lowering the weight of the header was carried out by modeling of software.Materials and MethodsTo reduce the amount of chickpea losses from the reel, a perforated plate with defined holes was installed in the header, where the separated chickpea pods fell behind the plate without returning to the farm. By using the plate in the header of the chickpea harvesting machine and by changing the harvesting height at the three levels of 10, 15 and 20 cm and the distance of the cutter at three levels of 3, 5 and 7 mm, the performance of the machine was evaluated. The experiments were carried out with Caboli variety cultivated in Kurdistan province, which is proper for mountainous areas without regular watering condition in three replications. The plants were placed in a fiber, wooden plate considering farm conditions. In addition, the header was modeled statically and dynamically under the influence of the external forces applied to the header using Ansys and Abaqus software. Based on the actual data, the validity of the applied model was determined and according to the verification results the optimization of the header was performed considering minimal weight (to reduce energy consumption).Results and DiscussionThe evaluation results of the performance of header showed that the effects of using perforated plate and the height of the header for harvesting on the chickpea harvesting and losses are significant at the level of 1% and 5%, respectively, and the interaction between perforated plate and the header height on the chickpea loss is significant at 5%. Using a perforated plate in the harvesting machine increases the amounts of chickpea collected from the farm increases. In this condition the chickpea pods separated from the plant and passed through the plate. With the separation of the stems, due to the proper wear that exists between the plate and the reel, the pods are properly separated and pass through the perforated plate. Moreover, the chickpea loss is higher for the system without perforated plate. The effect of the distance between the reel and header plate is affects the remaining chickpea on the plate. By increasing the distance from 5 mm to 7 mm the amount of harvested had a considerable effect. The best method of harvesting chickpeas is at the kinematic index of 1.5 with perforated plate, the harvesting height of 15 cm and the distance of 5 mm. According to modeling processes of the reel and the results of the static analysis, the minimum and maximum stress values were recorded about 3.31 MPa and 6.50 MPa (based on the von misses criteria), respectively, which is very small compared to the yield stress of the reel constructed with St-37. Also, the results of the dynamic analysis of the reel showed that the maximum von misses stress occurred with increasing the kinematic index. The maximum stress for kinematic index of 1, 1.5 and 2 was observed about 32.2, 40.1 and 52.72 MPa, respectively. The results of 3D model validation showed that the applied model with Abaqus software (R2>0.9264) was able to predict the amount of stress in different parts of the reel.ConclusionIn this study, the changes were made on the chickpea harvesting machine to get the proper performance and increasing machine efficiency. A perforated plate was used to prevent pea’s losses. The best condition for the harvesting process is obtained with the harvesting height of 15 cm and the distance of 5 mm. By using 3D modeling of the reel weight was reduced about 10%.
Modeling
F. Motazedian; M. Taki; R. Farhadi; M. Rahmati-Joneidabad
Abstract
IntroductionGreenhouse 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 ...
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IntroductionGreenhouse 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.Materials and MethodsIn 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.Results and DiscussionIn 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.ConclusionIn 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.
Modeling
M. Dana; P. Ahmadi Moghaddam
Abstract
IntroductionToday, the development of the livestock industry and feed supply is a vital issue due to the growing world population, the importance of animal protein supply, and the growing requirement for livestock products.A porous medium refers to a solid-void (pore) space that is occupied by a fluid ...
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IntroductionToday, the development of the livestock industry and feed supply is a vital issue due to the growing world population, the importance of animal protein supply, and the growing requirement for livestock products.A porous medium refers to a solid-void (pore) space that is occupied by a fluid (gas or liquid). Generally, many of these pores are interconnected which makes the transportation of mass and heat possible through the pores and this contributes to a faster transportation process through the solid matrix. Porosity is the fraction of void space to total volume.While the pores are large enough, water vapor and air in the porous media can be transported by molecular diffusion. Molecular diffusion of a gas species (e.g., vapor) in a gas mixture (e.g., vapor and air) is described by Fick’s law.Materials and MethodsIn this study, the samples were classified into four categories, including control, 3-impacts (low conditioning), 8-impacts (average conditioning), and 13-impacts (high conditioning). Each category included six samples (50-grams) that were used to measure different characteristics at different stages. All samples were weighed every two hours using a digital scale (0.001 gr precision). The leaf-stem separation force then was extracted using a texture analyzer. All experiments were repeated three times, and finally, the mean of these three repetitions was reported as the final value for the intended parameter.The geometry of the alfalfa stem was drawn in Gambit software and after meshing and applying boundary conditions; it was transferred to ANSYS Fluent software. Then, while the solver was selected, adjusted under relaxation factors were applied. In the following, mesh independency was checked and the results were reported.Results and DiscussionTo ensure numerical accuracy, the experimental data should be validated with the simulation results. For this purpose, experimental moisture losses were compared to the software results and showed a good agreement. Then, the moisture ratio curves (kinetics of drying) and force-time chart were presented.The impact of the moisture content of the tissue was evaluated on the value of force per time. Therefore, three samples of alfalfa with different relative humidity in terms of leaf-stem separation force were reported.The results of the numerical simulations were presented as two main contours: the velocity magnitude and moisture (water vapor) mass fraction. The simulation results were provided for all different modes and compared to the experimental data. Finally, errors between both results were presented in a table.ConclusionRegarding the quality and losses of the final product and comparisons between four different modes (control, 3 impacts, 8 impacts, and 13 impacts), the mode with 8 impacts was selected as the best mode.The Force-time chart illustrated two peaks due to the special multi-layer texture of the alfalfa. Regarding reducing the moisture ratio of the alfalfa as compared to the optimal, the force required to separate the leaves from the alfalfa stem was significantly decreased. Also, a significant increase in the losses was observed for impacts modes higher than 8.
Modeling
E. Aghaei Badelbou; V. Rostampour; A. Rezvanivand fanaei; A. M. Nikbakht
Abstract
IntroductionCyclone separators use the centrifugal force generated by the gas flow stream to separate the particles from their carrier gas. Simple design, low capital, and easy maintenance make them ideal for use as a valuable pre-refining or sedimentation device. The cause of the particles moving towards ...
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IntroductionCyclone separators use the centrifugal force generated by the gas flow stream to separate the particles from their carrier gas. Simple design, low capital, and easy maintenance make them ideal for use as a valuable pre-refining or sedimentation device. The cause of the particles moving towards the wall and separating from the fluid phase is the centrifugal force created by the rotational flow in a cyclone.Computational fluid dynamics (CFD) is one of the most well-known and widely used advanced modeling methods used for a variety of applications, including separation processes, thermal processes such as dryers, as well as a wide range of engineering and agricultural applications. The numerical solution of Navier-Stokes equations is the basis of all CFD techniques, which is the result of the rapid progress of computers and a deep understanding of the numerical solution of turbulence phenomena.Materials and MethodsThe measurement system of experimental data includes a cyclone separator, feeder, piping, and fan. Measurements of velocity and pressure were carried out using a hot wire air flow rate, (Model 8465-TSI with a resolution of 0.07 m.s-1 and a working range of 0.125 to 150 m.s-1), as well as a differential pressure gauge (CPE310s- KIMO, with an accuracy of 0.1 Pa), respectively. To investigate the effect of the output flow regulator plate on the cyclone performance, five different positions in addition to the base position (zero degree angle or fully open) including angles of 15, 30, 45, 60, and 75 degrees were evaluated.The conservation laws governing the various flows and geometries in the CFD include the conservation law of mass, conservation law of momentum, and conservation law of energy.According to the Mach number value, the pressure base solver was selected. Also, the Reynolds stress model (RSM) was applied to model the flow turbulence. In the discrete phase model (DPM), the fluid phase is solved continuously by solving averaged time equations, while the dispersed phase is calculated by tracing a large number of particles through the flow field.The boundary conditions used in this study include the inlet velocity boundary condition at the inlet of the cyclone, the outlet pressure boundary condition in the upper and lower outlet sections, and the non-slip wall boundary condition for other surfaces. The particle collision to the wall was also defined as reflective. In the mesh section of the cyclone simulation, five mesh levels were used to check the mesh independence test. The numbers of mesh cells in the five levels were 196810, 283120, 427890, 634940, and 1045290. The selected mesh was 427890 level regarding time consideration.Results and DiscussionIn the first section, the validation of simulation results with experimental results is discussed. The value of the velocity magnitude decreased with increasing the angle of the plate, which is probably due to the reduction of the inlet level as well as the reduction of the exhaust airflow in the cyclone air outlet.The maximum value of velocity magnitude occurred according to the direction of the air inlet in the cyclone inlet, which is gradually reduced due to the rotational motion inside the cyclone.The collection efficiency in the cyclone at different levels of regulating plate has values of 85.1% to 95.3%, with maximum collection efficiency at 30° which was 95.3%. The turbulent intensity contours show that turbulence intensity decreases to an angle of 30°, and then reaches an almost constant value for the 30, 45, and 60° angles.ConclusionAs the angle of the output current regulator plate increased, the magnitude of velocity decreased significantly.The separation efficiency showed an increasing-decreasing trend for different values of the regulator plate such that up to a 30° angle of the plate had a positive effect on the separation efficiency.In general, considering the compromise between separation efficiency and pressure drop as two key parameters affecting the performance of the cyclone, an angle of 30 degrees was selected as the best angle among the studied angles for application.
Modeling
A. Rezvanivand fanaei; A. Hasanpour; A. M. Nikbakht
Abstract
IntroductionThermo-compressors or ejectors are used to enhance the vapor enthalpy in the process industry. The low costs of construction and maintenance, and simple structure, have increased by using this equipment in relevant fields of industry and agriculture. The thermo-compressor's inlet parameters, ...
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IntroductionThermo-compressors or ejectors are used to enhance the vapor enthalpy in the process industry. The low costs of construction and maintenance, and simple structure, have increased by using this equipment in relevant fields of industry and agriculture. The thermo-compressor's inlet parameters, including the thermodynamic properties of the motive steam and suction vapor, are the foremost affecting factor of a thermo-compressor.The steam used in processing factories loses its capability after passing through evaporators due to the reduction of pressure and temperature, gets cooled again, and returns to the boiler despite having a moderate energy level. Therefore, the use of vapor-recovery equipment can increase the efficiency of energy systems. That will lead to a significant reduction in greenhouse gas emissions and harmful environmental effects, which increase the lifetime of energy resources.Materials and MethodsThe realizable k-ε turbulence model is used to simulate turbulence within the flow. The thermo-compressor geometry has meshed in 2D and 3D modes to apply the conservation laws. For this purpose, quadratic (quad) and hexahedral (hex) types are used for two and three-dimensional meshing, respectively. Structured meshes have a high ability to obtain numerical results due to creation of structural meshes in the flow direction.The axisymmetric structure of the thermo-compressor leads to a half simulation of geometry. The thermodynamic properties of the input flows and their variations in the output, such as pressure, velocity, Mach number, and mass ratios for different motive steam pressure are extracted and discussed.Results and DiscussionDifferent levels of meshes are examined to investigate the mesh-independence test. In axisymmetric two-dimensional analysis, these levels include 33460, 51340, 78620, and 103590 cells, respectively. The relatively insignificant difference in motive flow for the third and fourth mesh levels (which proves less than 5%) clearly shows the independence of the results from the mesh size. Regarding the time considerations, the grid with 78,620 meshes was used in the simulations.The experimental data from the article by Sriveerakul et al. (2007) are used to validate the numerical results of the present work. Validation shows that the results obtained from the simulations are in good agreement with the experimental data. Since the final results of the two-dimensional analysis are very close to the three-dimensional one, the first one is selected due to the time considerations and higher computational costs of the three-dimensional mesh analysis.Considering the problem conditions, pressures of 10 and 15 bars are appropriate for practical application. Since the 15 bar motive stem creates a longer development length in the diffuser section, it is a better choice. At this level (15 bar), the temperature field within the thermo-compressor is well distributed in the presence of ideal temperature conditions. The ideal velocity distribution within the thermo-compressor and the uniformity of the motive and suction flows indicate the high performance of the thermo-compressor in these operating conditions. Applying the motive steam of 15 bars, the values of 0.59 and 0.41 for the motive and suction mass ratios of the diffuser output were achieved, respectively.ConclusionGeometrically, the study was examined in asymmetrical two-dimension and three-dimension. It was observed that there is a slight difference between the two analysis modes by comparing the velocities along the longitudinal line of the thermo-compressor. Therefore, to save computational and time costs, results are presented for the axisymmetric two-dimensional mode.The effect of 4 levels of motive steam pressure on the thermodynamic properties within the computational domain, including pressure, temperature, velocity, Mach number, mass ratios of both motive steam, and suction vapor are evaluated. Finally, the values of the performance curve for steam with motive pressures of 3.7, 5, 10, and 15 bars are presented.
Modeling
H. Golpira; M. Loghavi
Abstract
The main aim of this study was to optimize the design parameters of the fruit shakers for efficient harvesting of Shengy olive. A single-degree-of-freedom spring-mass model was established to determine the natural frequency and damping coefficient of the limb. A tractor-mounted shaker that transmits ...
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The main aim of this study was to optimize the design parameters of the fruit shakers for efficient harvesting of Shengy olive. A single-degree-of-freedom spring-mass model was established to determine the natural frequency and damping coefficient of the limb. A tractor-mounted shaker that transmits vibration to limbs and fruits via a reciprocating mechanism was fabricated for field evaluation of the forced vibration modes. A 3×4 factorial experiment with a completely randomized design was conducted to investigate the effects of shaking amplitudes and frequencies on fruit removal. The shaking mode with a frequency of 10 Hz and amplitude of 80 mm transmitted the average power of 92 W to remove 95% of fruits in the field trial. This oscillation characteristic should be used to redesign the fruit shakers to pass human safety standards and efficient harvesting.
Modeling
Gh. Amini; F. Salehi; M. Rasouli
Abstract
In this study, the effects of infrared (IR) dryer system parameters such as IR power, the distance of mucilage from lamp surface, mucilage thickness on drying kinetics and, color indexes (L*, a*, b* and ΔE) of wild sage seed mucilage (WSSM) were investigated in an IR dryer system. Experimental ...
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In this study, the effects of infrared (IR) dryer system parameters such as IR power, the distance of mucilage from lamp surface, mucilage thickness on drying kinetics and, color indexes (L*, a*, b* and ΔE) of wild sage seed mucilage (WSSM) were investigated in an IR dryer system. Experimental moisture ratio (MR) data were fitted to 7 various empirical thin-layer models. It was found that the Page model has the best fit to show the kinetic behavior and acceptably described the IR drying behavior of WSSM with the lowest mean square error (MSE), root mean square error (RMSE), mean absolute error (MAE), and standard error (SE) values and the highest correlation coefficient (r) value. The values of MSE, RMSE, and MAE for all experiments were in the range of 0.1×10-3-1.1×10-3, 1.04×10-2-3.25×10-2 and 8.7×10-3-27.1×10-3, respectively. The average effective moisture diffusivity (Deff) increased from 4.61×10-9 m2s-1 to 15.8×10-9 m2s-1 with increasing lamp power from 150 W to 375 W, while it was decreased from 14.4×10-9 m2s-1 to 5.16×10-9 m2s-1 and 13.2×10-9 m2s-1 to 4.31×10-9 m2s-1 with increasing the distance of mucilage from 4 to 12 cm and the reduction of mucilage thickness from 1.5 to 0.5 cm, respectively. Increasing in IR radiation power has a positive influence on the yellowness (increasing 19.78% in b* index) of dried WSSM. Also, it increased the color changes index (ΔE) from 16.05 to 17.59.
Modeling
J. Javadi Moghaddam; S. Ozlati; Gh. Zarei; D. Momeni; F. Azadshahraki
Abstract
IntroductionGreenhouse technology is a flexible solution for sustainable year-round cultivation of many horticulture products, particularly in regions with adverse climate conditions or limited water and resources. Greenhouses are the structures that provide the desired conditions for plant growth throughout ...
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IntroductionGreenhouse technology is a flexible solution for sustainable year-round cultivation of many horticulture products, particularly in regions with adverse climate conditions or limited water and resources. Greenhouses are the structures that provide the desired conditions for plant growth throughout the all seasons. Plant growing and crop production in the greenhouses require proper ventilation conditions to provide optimal temperature, relative humidity and CO2 and to minimize the toxic gases. Ventilation method of greenhouse is depending on the design of greenhouse ventilation and cooling is usually done by evaporative pad and fan systems or fan and vent systems. Recently different designs, different structures and different layouts of fans, pads and vents are used in greenhouses. Layout of fans, pads and vents affects the performance of ventilation systems. The aim of this study was to layout the fans, pads and vents to provide best air flow in an octagonal greenhouse. Materials and MethodsIn this study, three layouts of evaporative pad and fan systems and vents were modeled by computational fluid dynamics (CFD) method. For computational fluid dynamic of inside greenhouse airflow, the air flow was considered to be compressible. In order to estimate density, velocity and temperature, the Navier- Stokes equation included momentum, state, energy, continuity was used. For modeling the fluid flow, all necessary and dependent parameters of climate were considered based on the concentration and air pressure at the level of the open sea. Fluid flow equations were solved by finite volume technique. Three mentioned layouts of this study were 1- fans on the roof of the pyramids and vents on the wall of the pyramids, 2- pads and fans on the greenhouse side walls and 3- pads on the greenhouse side walls and fans on the roof of the pyramids (parallel pads). The performances of each arrangement can be improved by the speed of the fans, the size of the vents. The main equation in fluid flow simulation using CFD can be done by the following set of equations in which the continuity equation in the form of indicial notation can be presented as: Moreover, the momentum equation can be written by the following form: The equation 4 shows the state equation in a fluid flow interaction. All technical calculations and CFD simulations were done by Solidworks 2018 software.Results and DiscussionThe results showed that octagonal greenhouse by a specific form of the vents on the walls and fans on the roof could provide a circular air flow around the plants in the greenhouse. However, due to different powers of the fans, different velocity and different shape of air circulation could be achieved. When pads and fans are located on the greenhouse side walls, uniform air flow from the pads move uniformly throughout the greenhouse and then exit from opposite fans which causes desired air flow in the greenhouse. When the fans are located on the roof of the pyramids and pads are located on the side walls parallel, pad surface increases in the greenhouse and thus relative humidity increases and temperature decreases.ConclusionBecause of the specific shape of the vents in octagonal greenhouse, different air velocity and different shape of air circulation will be achieved when different power of the fan is used. This causes that the octagonal greenhouse can be used in different climate conditions. When the fans are located on the roof of the pyramids and pads are located on the side walls, temperature decreases and relative humidity increases and this layout is desirable for hot and dry climate. An octagonal greenhouse can be used in different climate by using a suitable layout of fan, pad and vents.
Modeling
S. Rezaei; N. Behroozi-Khazaei; H. Darvishi
Abstract
IntroductionMicrowave drying compared to conventional hot air drying has many benefits to apply in food drying processes such as volumetric heating, high thermal efficiency, shorter drying time and improved product quality. In conventional microwave drying method, a fixed microwave power was used during ...
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IntroductionMicrowave drying compared to conventional hot air drying has many benefits to apply in food drying processes such as volumetric heating, high thermal efficiency, shorter drying time and improved product quality. In conventional microwave drying method, a fixed microwave power was used during the drying process. However, the water of the product evaporated and mass of product decreased over the time that resulted in microwave power density (MPD) increasing during the drying process. Increasing the power density, especially at the end of the process, sharply increased the product temperature. High temperature of products led to the deterioration of the product quality. Most research used variable microwave power program for preventing the risk of overheating and charring of product. The evaporation of the water causes the shrinkage of product. Therefore, many studies have used machine vision for measuring the shrinkage and this technology has been used in modeling and predicting the MC.Materials and MethodsThe fresh potato samples (Solanum tuberosum cv. Santana) with 83% (w.b.) of initial MC were sliced into the chips of 5mm thickness. The developed drying systems consisted of microwave oven, lighting unit and imaging unit, temperature sensor, microwave power adjusting unit and a data acquisition unit (DAQ). A LabVIEW (V17.6, 2017) program was developed to integrate all measurements and adjusting the microwave power during the drying process. In this study, two sets of experiment with different aims have done. The first set of experiments was used for calculating the shrinkage by developed image processing algorithm and MC by offline mass measurement and then data sets were used to investigate the artificial neural networks (ANNs). The second set was used for evaluating the reliability of investigating models. The experiments, in the first set, were done with 8, 4 and 2.67 W g-1. In the variable mode, the power varied in two/three steps with respect to the MC of samples during the drying process. Second set of experiments was done in two variable and constant power modes with 5 and 3 W g-1. An image processing algorithm was developed to measure the shrinkage of potato slice during the drying process. In this study the feed forward ANN with back propagation algorithm was used. Two structures of ANN were used for modeling of MC. In the first model time and power density and the second model shrinkage and power density were used as input. Also moisture ratio was used as an output parameter in two models.Results and DiscussionThe obtained results indicated that for the first model the ANN with 2-3-1 structure had better results than others structures. This structure had 0.0713, 0.0337 and 0.0640 of RMSE and 0.9764, 0.9973 and 0.9800 of R for train, validation and test, respectively. For the second model, the 2-2-2-1 structure of ANN with 0.0780, 0.0816 and 0.0908 of RMSE and 0.9598, 0.9799 and 0.9746 of R for train, validation and test, respectively had better results than other structures. The evaluation of these models with a second data set showed that the second model with shrinkage and power density as input with 0.067 of RMSE and 0.994 of R had better results than the first model with 0.173 of RMSE and 0.961 of R. These consequences expressed that the second model had higher reliability for prediction of MC based on shrinkage and power density during drying process.ConclusionIn this study, a microwave dryer was developed with a real-time image recording system and a microwave power level program during the drying process. Two ANN models were used for modeling of drying kinetics of the potato slices. Also image processing algorithm was investigated by measuring the shrinkage of potato slice during the drying process. The outcomes revealed that shrinkage as input in the ANN had great effect on MC prediction during the drying process.
Modeling
S. Mirzamohammadi; A. Jabarzadeh; M. Salehi Shahrabi
Abstract
IntroductionThe increasing global population on the one hand and limited water and soil resources on the other hand, contribute to the need for the supply of agricultural products by adopting modern methods. One of the modern methods of farming is the cultivation of products in commercial greenhouses. ...
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IntroductionThe increasing global population on the one hand and limited water and soil resources on the other hand, contribute to the need for the supply of agricultural products by adopting modern methods. One of the modern methods of farming is the cultivation of products in commercial greenhouses. Despite favorable performance of greenhouses in the agricultural sector, high demand for direct and indirect energy is among the main considerations of developing them because the energy supply of greenhouses has the highest influence on the performance of greenhouses, quality of products, and market price of products. In this study, the energy supply of greenhouses in the case of using renewable resources is done in a grid connection state. Trading energy with main grid is enabled. Decision-makers’ objective is determining the optimal number of renewable resources and energy storage units for the purpose of income maximization.Materials and MethodsBasically, the supply of energy for greenhouses or in other terms supply of electric, cooling, and heating loads required by greenhouses is intended to cover lighting, internal temperature, emission of CO2, and relative humidity. Since many greenhouses have proper access to the main grid for the supply of their demanded load, the problem seeks maximum use of renewable energy rather than buying power from the grid for supplying the loads which greenhouses need to its secure revenues. To this, mathematical modeling has used to determine the optimal number of energy sources and storage units that revenues of using renewable energy resources be optimized based on existing limitations. These limitations include balancing generation and consumption of thermal and electrical power in each hour, logical relationship between charging and discharging of batteries, limit of power generation of renewable sources in each hour of the day and the level of capital available for investment.Results and DiscussionBased on the collected data, 9 different issues have been defined in terms of the proportion of costs of solar energy and wind energy and the proportion of purchasing and selling price of power. The obtained results suggest that in the case of equality of investment and maintenance costs of solar and wind energies, the use of wind energy rather than solar energy will be justified. The most significant reasons for this is considering proper conditions of wind speed which causes its inclusion in optimal solution of the problem since using solar energy during nightly hours is impossible. In addition, in the case of the equality of above costs, when purchasing and selling price of power cost is the same, the generated energy is completely used in the greenhouse. In the case of increasing the selling price, energy supply to the main grid will be economically justified. Since investment and maintenance costs of wind power are two times and 1.5 times higher than those of solar energy, using wind energy is cost-effective.ConclusionThe results suggest that in the case of an equal price of selling power to the grid and buying power from it, all of the energy will be consumed in the greenhouse. In the case of an increase in selling price, the supply of energy to the main grid will be economically justified. In addition, the results imply the significant effect of geographic conditions of the region, since sometimes concurrent use of renewable energies is unjustified. Since the lack of supply of energy to greenhouses significantly influences the cultivation of products, considering the cost of lack of energy supply in modeling is one of the contributions of the present study. Another significant aspect of the study is the generalization of modeling from the greenhouse to greenhouse complexes. To do so, using the notion of micro-hub for greenhouses and their management will be useful.
Modeling
M. Sami; A. Akram; M. Sharifi
Abstract
IntroductionThe need to develop alternative energy sources especially renewable energy has become increasingly apparent with the incident of fuel shortages and escalating energy prices in recent years. With the advent of renewable energy, various studies have been conducted to investigate the potential ...
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IntroductionThe need to develop alternative energy sources especially renewable energy has become increasingly apparent with the incident of fuel shortages and escalating energy prices in recent years. With the advent of renewable energy, various studies have been conducted to investigate the potential of biogas production from agricultural waste. Considering the importance of retention time and methane production potential for designing industrial digesters, many studies on potential analysis and modeling of the digestion process of different products have been carried out by various researchers. These studies are valuable for the design and implementation of anaerobic digesters. Apple is one of the most popular fruits in many parts of the world and is widely cultivated in many temperate regions of the world. Considering the large volume of apple waste in Iran, this study was designed based on potential evaluation and modeling of biogas production from apple pulp.Materials and MethodsIn order to measure the potential of biogas production from apple pomace, a number of lab-scale digesters with a capacity of 600 ml and a working capacity of 400-500 ml were made. pH and C/N ratio were modified by adding NaOH and urea solution, respectively. Three different temperature treatments including psychrophilic (ambient temperature), mesophilic (37ºC), and thermophilic (47ºC) were applied to the substrate. Used pomace samples were collected from the output of an apple juice factory in southern Isfahan province, Iran. Anaerobic Biodegradability (ABD) was obtained by dividing the experimental methane production potential (BMP) obtained from the experimental results on the theoretical methane production potential. Three most common kinetic models of Gompertz, Logistic, and Richards were used to predict and stimulate the cumulative methane production of treatments.Results and DiscussionUnder ambient temperature, the digestive process took a longer time, and the time of maximum dilly biogas production was considerably more than the other two treatments. Statistically, production time and peak time of this treatment was higher than the other two treatments at 1% significance level. Maximum daily biogas production in the ambient treatment was observed on day 37th with a volume of 6.99 g-VS-1 ml, while maximum daily biogas production in the treatments of 37 °C and 47 °C were observed on days 22th (20.16 ml g-VS-1) and 20th (25.57 ml g-VS-1), respectively. In all three treatments, daily biogas production increased sharply in the first incubation days and after that reduced and then production increased again. In mesophilic and thermophilic treatments, the production of biogas modestly stopped after 35 days, but under the ambient temperature, the process of production continued after 55 days. The methane concentration of biogas in the psychrophilic treatment was significantly lower than the other two treatments at 1% level. Two treatments of 37°C and 45°C have a significant difference in methane yield at 1% level. Nevertheless, the production of biogas in two treatments was not statistically different. In all three treatments, the lowest pH was recorded after 7 days of production and the highest pH was recorded on days 34-40. All three kinetic equations were able to simulate the methane production process with high precision, although the results of the Logistic model provided higher accuracy. In the treatment 47 °C, the efficiency of the studied equations was higher than other treatments and models were able to predict the production process with higher accuracy. Results of the experiment show the high biochemical methane production potential of apple pomace (473.17 ml g-VS-1), which under laboratory condition of this study up to 63.9% of this potential (302.70 ml g-VS-1) was obtained. ConclusionThis study results are valuable for the design and implementation of industrial digesters. The results indicate the apple pomace has a high potential for the production of methane and its biodegradability is high. Apart from pH that is acidic, other apple pulp factors are appropriate for the activity of methanogenic bacteria. In terms of nutrients, apple pomace is also a good environment for the growth of anaerobic bacteria.
Modeling
P. Ghiasi; M. Safari
Abstract
Introduction Sunflower planting is mostly carried out for two particular purposes; oil production and as nut. Harvesting is one of the biggest problems in both types of sunflower. The difficulty of harvesting and less scientific research have led us to study the mechanized harvesting of this kind of ...
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Introduction Sunflower planting is mostly carried out for two particular purposes; oil production and as nut. Harvesting is one of the biggest problems in both types of sunflower. The difficulty of harvesting and less scientific research have led us to study the mechanized harvesting of this kind of crops. In this research, head losses and grain losses for the inner section of combine were investigated during mechanized harvesting of oily sunflower and a regression model was used based on the experimental tests for head losses and grain losses in the inner section of the combine.Materials and Methods After preparing an especial head for harvesting sunflower, the head was set up on the combine for measuring the harvest losses. The cutting, threshing and clearing process for sunflower seeds were done during the tests. The design of the head is the same as the sunflower bushes are firstly bent by the bar and then sequentially the cutting, and transferring processes are done. The tests were implemented in an oily sunflower farm by a combine harvester (1055 john deer) in 3 replications. The farm performance was 2170 kg ha-1 and was located in Kermanshah province in Iran. A pre-test was done to define the best combine forward speed and finally 2.5 km h-1 was adjusted for combine forward speed. The bar height (BH) in two levels (20 and 70 cm) and head height (HH) in two levels (60 and 120 cm) were independent parameters to evaluate the head. The dependent parameters were the combine losses and head losses. For the analysis of variance of the variable parameters, a 2×2 factorial plot with 3 replications was used. A regression model was defined based on experimental tests.Results and DiscussionHaving done the experimental tests, data were analyzed and the effect of independent parameters on the head and combine grain losses were investigated. The effect of the bar height on the head grain losses was significant at 1% level and the effect of the head height and interaction between bar height and head height on the head grain losses was also significant at 5% level. Results showed that with increasing in bar height, the head grain losses increased. With a change in the bar height, the location of the cutting point is changed and this led to a change in the head grain losses. The effect of the bar height on the combine grain losses was significant at 5% level but the effect of the head height and interaction between bar height and head height was not significant on the combine grain losses. Increasing in the bar height led to increase in material other grain (MOG) which enters to the combine, and also resulted in increasing in combine grain losses. The coefficient of determination of head grain losses in the regression model was 0.97. The model was able to explain the relationship between the bar and head height with head grain losses due to the relationship between independent and dependent parameters. The amount of R-squared for the combine grain losses in the regression model was 0.53. Because of the effect of other parameters in the inner section of the combine, the output of the model predicted that increasing in the bar height and head height, resulted in increasing in head grain losses, and also increasing in the bar height and decreasing in head height let to increasing in combine grain losses. The output of model showed that regulating the bar height and cutting height could reduce the harvest losses by less than 3%. This R-squared is obviously less than R-squared of head grain losses model. The output of the regression model predicted that the increase in the bar height and head height was associated with increase in the head grain losses, and increasing in the bar height and decreasing in head height, resulted in increasing in combine grain losses. The output of the regression model showed that the harvest losses can be reduced less than 5% by regulating the bar height and cutting height.ConclusionOne of the most important parameters for mechanized harvesting is the head mechanism which cuts the crops and transfers them to the threshing unit. The cutting height in the sunflower head was defined by the bar height and head height. According to the linear relationship between the head and combine losses with the bar height and head height, and the interaction between them, the regression model was able to predict the result successfully. This model of grain losses in the head and combine model can be used in the intelligent combine to minimize the harvest losses. The optimization of the bar height and head height for minimizing the harvest losses can be the subject of next researches.
Modeling
M. Rahmatian; R. Yeganeh; M. A. Nematollahi
Abstract
IntroductionTillage is a very important operation that influences the growth and productivity of agricultural products. It is necessary to introduce some conditions to improve soil physical properties, aeration, permeability and root development in tillage operations. However, in primary tillage, especially ...
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IntroductionTillage is a very important operation that influences the growth and productivity of agricultural products. It is necessary to introduce some conditions to improve soil physical properties, aeration, permeability and root development in tillage operations. However, in primary tillage, especially when moldboard ploughs are used, this may be time consuming and costly for researchers to use it in their research. Some researchers use physical experiments to perform the work, which the accuracy of the results is dependent on the measuring instruments precision. However, some other researchers use simulation and mathematical modeling to reduce the time and costs and increase the relative accuracy of the research results. Many studies have also shown that modeling the forces involved in tillage is a good way to estimate the performance of different tillage tools and improve their geometry. However, the key to success in numerical simulation of tillage operations is to simulate the exact instrumentation, based on the correct assumptions as well as the proper methods. The prediction of the forces involved in tillage tools has an important role in their design. Collecting data on the forces involved in tillage tool under different farm conditions is a time consuming and costly task. Therefore, the prediction of a tillage tool forces is very important for the designer and the user in order to achieve better performance of the tool. Materials and MethodsIn this study, a cylindrical moldboard made by Alpler Company in Turkey was used to simulate the moldboard. A measuring device was designed and constructed to measure the various points of the desired moldboard. Then, the spatial points obtained by the measuring device were presented to the SolidWorks 2016 software and the desired moldboard was modeled. The finite element method by Abacus 2016 was then used to simulate the interaction between soil and moldboard. Treatments used in simulated tillage operations included tillage depths (5, 10, 15, 20 and 25 cm) and forward speed (1, 1.5, 2, 2.5 and 3 millimeters per second). The independent variables were considered as tensile, vertical and lateral forces (Kilo newton). After simulating the tillage operations, tensile, vertical and lateral forces were obtained. These forces were modeled using response surface and artificial neural networks techniques. Then, the obtained models were compared using R2, RMSE and MRDM statistical indices and the best model was selected. Results and DiscussionWhen using the response surface method, the quadratic model was selected by using the maximum value of the statistical indices R2, R2a and R2p, among the linear, two-factor and quadratic models. Then, the significance of model variables was evaluated by using variance analysis. The forces were also modeled by using the neural network method. According to the fitting curves and statistical indices of R2, RMSE and MRDM for the tensile, vertical and lateral forces, it is revealed that both methods could well predict the forces but artificial neural network was more suitable than the response surface method. Moreover, by investigating the interactions of tillage treatments and forward speed on the forces in this research, it was observed that by increasing the depth of tillage and velocity, tensile, vertical and lateral forces were increased nonlinearly by 66.55%, 68.47%, and 64.76%, respectively. ConclusionRegarding all the results obtained from this study, it can be concluded that the developed models using the artificial neural network in this research was a good and powerful tool for predicting the forces involved in moldboard ploughs both in the field operations and in related studies. It is also recommended that the developed models in this study can be used to manage the tillage operations, such as selecting the proper tractor. However, it is also suggested that other affecting factors, such as moldboard angles, should be included in future models to increase the ability of the model to predict the forces involved in moldboard plows.
Modeling
Z. Zibahoosh; J. Khodaei; S. Zareei
Abstract
IntroductionThe most costly part of poultry breeding is feeding. Due to the noticeable developments in animal husbandry and agricultural sectors, it is necessary to use the mechanized methods to reduce the casualties, increase the productivity as well as reduce the time and cost in each of these sectors. ...
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IntroductionThe most costly part of poultry breeding is feeding. Due to the noticeable developments in animal husbandry and agricultural sectors, it is necessary to use the mechanized methods to reduce the casualties, increase the productivity as well as reduce the time and cost in each of these sectors. Reducing the particle size is one of the ways to process cereals which improves the mixing and also the nutritional value of the feed and the quality of the pellet feed. Optimizing the performance of hammer mill with the aim of reducing the size of different materials for poultry feed, would be very beneficial for obtaining the minimum cost of food, maximum quality and capacity. The main objective of this research was to optimize the operational variables, including sieve size, grain moisture content, feed rate and the number of hammers, each of them at three levels, on a hammer mill during the process of poultry food production from wheat, corn, barley and soybean grains. Materials and MethodsThe seeds used in experiments were wheat (Azar2 variety), corn (Brazilian variety), soybean (Danpars variety) and barley (Aras variety). A laboratory hammer mill was used to perform experiments. The treatments including sieve diameter (2, 2.3and 4.4 mm), grain moisture content (10, 14 and 18%), seed input rate to milling compartments (one-third, two-thirds and fully openness of tank gate) and the number of hammer (12, 18 and 24) were investigated. In order to measure the working capacity of the hammer mill, the required time for milling was recorded. The amount of final milled crop in each experiment was weighed and divided into the needed time for milling. Sieve analysis was used to determine the distribution and dispersion of the milled material which works according to the standard of ASTM E-11-70 Part 41 (Anonymous, 2004). In this study, the effects of input variables were investigated using the response surface method focusing on the central composite design approach to optimize the fineness degree and working capacity of the mill. The Design Expert 8.0.6 software was applied for statistical analysis, modeling and optimization. Results and DiscussionThe results indicated that sieve size and the number of hammers have been affected by the fineness degree of wheat grains, significantly. In addition, all four factors and interaction effects between sieve size and moisture content and also moisture content and number of hammers influential working capacity at the significant level of 1%. In the case of corn, the influence of moisture content and its interaction with sieve size on grain fineness, and the effect of sieve size, moisture content, feed rate and interactions between sieve size and moisture content and moisture content and feed rate of working capacity were significant at the level of 1%. For barley, moisture content at the level of 1% and interaction between sieve size and moisture content at the probability level of 5% were effective on barley fineness degree. Meanwhile, the moisture content at the level of 1% and sieve size and its interaction with moisture content at the level of 5% influenced working capacity, significantly. Soybeans were not able to respond the required moisture level for the experiments due to their soft and brittle texture, whereas unreliable results were obtained by changing its moisture levels. The best size of sieve holes, grain moisture content, feed rate and the number of hammers were determined to minimize the fineness degree and maximize the working capacity of the hammer mill. ConclusionIn this research, the response surface method considering a central composite design was used to optimize the operational variables of a hammer mill, including sieve hole size, grain moisture, feed rate and the number of hammer to produce poultry feed with the aim of achieving a minimum fineness degree (more grain crushing) and maximum milling capacity. The results of variance analysis were presented for wheat, corn, barley and soybean. Regression models could represent the relationship between the independent variables and the outputs with high confidence coefficient, and the best values of input variables were determined to optimize grinding operation.
Modeling
H. Zaki Dizaji; H. Bahrami; N. Monjezi; M. J. Sheikhdavoodi
Abstract
Introduction The sugar industry usually gathers huge amounts of information during normal production operations, which is rarely used to study the relative importance of both management and environment on sugarcane yield performance. Yield prediction is a very significant problem of agricultural organizations. ...
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Introduction The sugar industry usually gathers huge amounts of information during normal production operations, which is rarely used to study the relative importance of both management and environment on sugarcane yield performance. Yield prediction is a very significant problem of agricultural organizations. Each agronomist wants to know how much yield to expect as soon as possible. The aim of this study was to determine the performance of C5.0 and QUEST algorithms to predict the yield of sugarcane production in Amir-Kabir agro-industry Company of Khuzestan province, Iran. However, the working method described in this paper is applicable to other geographical areas and other kinds of crops. Materials and Methods The data for the study were collected from Amir-Kabir agro-industry Company. The data is obtained from 2012 to 2016 years. The study area is located in Khuzestan Province which is a major agricultural region in Iran. The geographical location of the study area is between latitudes 31° 15′ to 31° 40′ north and longitudes 48° 12′ to 48° 30′ east. It covers an area of about 12000 ha. The average elevation of the study area is 8m above sea level. Mean annual rainfall within the study area is 147.1mm, the mean annual temperature is approximately 25°C and the mean soil temperature at 50cm depth is 21.2°C. The used data were obtained from a survey with 15 variables carried out on 1201 sugarcane farms. Variables used in the study of data mining can be divided into two categories: target variable and predictor variables. The variable of yield was used as the target variable (dependent) and other variables as predictor variables (independent). In two models, the input data included crop cultivar, month of harvest, chemical fertilizer (Nitrogen), chemical fertilizer (Phosphate), age (plant or ratoon), times irrigation, ratio of surface spraying, soil texture, soil electrical conductivity (EC), water consumption per hectare, drain, farm management, crop duration, area, and yield-category. The study was included in 1201 farms. The necessary data were collected and pre-processing was performed. We propose to analyze different decision tree methods (C5.0 and QUEST). Results and Discussion First, decision tree methods were analyzed for variables. Then, according to C5.0 method (error rate 0.2319 for the training set and 0.3306 for test set) performed slightly better than another method in predicting yield. Crop cultivar is found that an important variable for the yield prediction. 24 rules were found in this study, C4.5 showed a better degree of separation. The measured prediction rate of C5.0 was correct: 76.81% and wrong: 23.19% in the training data, and correct: 66.94% and wrong: 33.06% in the test data. The prediction rate of QUEST was correct: 68.25% and wrong: 31.75% in the training data, and correct: 70.83% and wrong: 29.17% in the test data. Using the training data comparison between the model types showed that the C5.0 model produces a more accurate prediction model and was, therefore, the model to use. Using the testing data in comparison with the model types showed that the QUEST model produced a more accurate prediction model. The results of our assessment showed that C5.0 and QUEST algorithms were capable to produce rules for sugarcane yield. Therefore, our proposed methods as an expert and intelligent system had an impressive impact on sugarcane yield prediction. Conclusion In today's conditions, agricultural enterprises are capable of generating and collect large amounts of data. Growth of data size requires an automated method to extract necessary data. By applying data mining technique it is possible to extract useful knowledge and trends. Knowledge gained in this manner may be applied to increase work efficiency and improve decision making quality. Data mining techniques are directed towards finding those schemes of work in data which are valuable and interesting for crop management. In this research, decision tree algorithms (C5.0 and QUEST) were used. This classification algorithm was selected because it has the potential to yield good results in prediction and classification applications. This study was performed to present a model-based data mining to predict sugarcane yield in 2012-2016. The 24 classification rules generated from the C5.0 decision tree algorithm have great practical value in agricultural applications. The results showed the QUEST and C5.0 decision tree algorithms produced the best prediction accuracy. Sensitivity analysis results indicated that crop cultivar was the most important variables. It was observed that efficient technique can be developed and analyzed using the appropriate data, which was collected from Khuzestan province to solve complex agricultural problems using data mining techniques (decision tree). The decision tree has been found useful in classification and prediction modeling due to the fact that it can capability to accurately discover hidden relationships between variables, it is capable of removing insignificant attributes within a dataset.
Modeling
J. Baradaran Motie; M. H. Aghkhani; A. Rohani; A. Lakziyan
Abstract
Introduction Presently, the loss of ground water levels and the increase in dissolved salts have given importance to the determination of salinity and the management of their variations in irrigated farms. Soil electrical conductivity is an indirect method to measure soil salts. The direct electrode ...
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Introduction Presently, the loss of ground water levels and the increase in dissolved salts have given importance to the determination of salinity and the management of their variations in irrigated farms. Soil electrical conductivity is an indirect method to measure soil salts. The direct electrode contact method (Wenner method) is one of the widely used methods to rapidly measure soil ECa in farms. However, soil scientists prefer soil actual electrical conductivity (saturated extract electrical conductivity) (ECe) as an indicator of soil salinity, though its measurement is only possible in the laboratory. The aim of this study was to find a relationship between the prediction of soil actual electrical conductivity (ECe) in terms of temperature, moisture, bulk density and apparent electrical conductivity of soil (ECa). Thereby, the estimation of ECe would allow the partial calculation of ECa that is dependent upon soil salinity and dissolved salts. Materials and Methods This study used RBF neural network in Box-Behnken statistical design to explore the impacts of effective parameters on direct contact method in the measurement of soil ECa and provided a model to estimate ECe from ECa, temperature, moisture content and bulk density. In this study soil apparent electrical conductivity (ECa) was measured by direct contact (Wenner) method. The present study considered four most effective factors: ECa (saturated paste extract EC), moisture, bulk density, and temperature (Baradaran Motie et al., 2010). Given the characteristics of farming soils in Khorasan Razavi Province (Iran), the maximum and minimum of each independent variable were assumed as 0.5-6 mS.cm-1 for ECe, 5-25% for moisture content, 1-1.8 g.cm-3 for bulk density, and 2-37°C for soil temperature. Considering the experimental design, three moisture levels (5, 15 and 25%), three salinity levels (0.5, 3.25 and 6 mS.cm-1), three temperature levels (2, 19 and 37°C) and three compaction levels with bulk densities of 1, 1.4 and 1.8 g.cm-3 were assumed in 27 trials with predetermined arrangement on the basis of Box-Behnken technique. 13 common algorithms were explored in MATLAB software package for the training of the artificial neural network in order to find the optimum algorithm (Table 4). The input layer of the network designed by integrating a Randomized Complete Block Design (RCBD) with k-fold cross-validation. Using k-fold cross-validation, 20 different datasets were generated for training and validation of RBF neural network. Results and Discussion A combination of an RCBD and k-fold cross-validation was used. The results of both training and validation phases should be considered in the selection of training algorithm. In addition, R2 of T1 training algorithm had a much lower standard deviation than other training algorithms. The lower standard deviation is, the more capable the algorithm would be in learning from different datasets. Considering all aspects, trainbr (T2) training algorithm was found to have the best performance among all 13 training algorithms of the neural network. Table 7 tabulates the results of means comparison for R2 of RBF model for both training and validation phases resulted from the application of some combinations of S and L2 factors as interaction. As can be observed, R2 = 0.99 for all of them with no significant difference. However, the magnitude of order differed between training and validation phases. Given the importance of the training phase, L2=9 and S=0.1 were regarded as the optimum values. The sensitivity analysis of the network revealed that soil ECa, moisture, bulk density, and temperature had the highest to lowest impact on the estimation of soil ECe, respectively. This model can improve the precision of soil ECa measurement systems in the estimation and preparation of soil salinity maps. Furthermore, this model can save in time of data analysing and soil EC mapping because it does not need data recollection for the calibration of systems. A validation prose was done with a 60 field collected data set. The results of validation show R2=0.986 between predicted and measured ECa. Conclusion The present research focused on improving the precision of soil ECe measurement on the basis of easily accessible parameters (ECa, temperature, moisture, and bulk density). In conventional methods of soil EC mapping, the systems only measure soil ECa and then calibrate it to ECe by collecting some samples and using statistical methods. In this study, Soil ECe was estimated with R2 = 0.99 by a multivariate artificial neural network model with the inputs, including ECa, temperature, moisture, and bulk density of soil without any need to collect further soil samples and calibration process. The Bayesian training algorithm was introduced as the best training algorithm for this neural network. Thereby, soil EC variation maps can be prepared with higher precision to estimate the spatial spread of salinity in farms. Also, the results imply that soil ECa, moisture, bulk density and temperature have the highest to lowest effectiveness on the estimation of soil ECe, respectively.
Modeling
M. Mehrijani; J. Khodaei; S. Zareei
Abstract
Introduction Tillage as a preliminary step for agricultural production consumes large amounts of energy. Regarding the energy crisis and the greenhouse gas emissions caused by the indiscriminate use of fossil fuels, many efforts have been done to reduce energy consumption as much as possible. About half ...
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Introduction Tillage as a preliminary step for agricultural production consumes large amounts of energy. Regarding the energy crisis and the greenhouse gas emissions caused by the indiscriminate use of fossil fuels, many efforts have been done to reduce energy consumption as much as possible. About half of the energy used in the crop production has been dedicated to tillage operations; hence the optimization of tillage tools performance can lead to decrease the energy loss. Tillage operation in most regions of Iran is carried out by moldboard plow. The ability of this plow in turning the soil has made it impressively different from the other plows. The energy used in tillage operations depends on various factors such as soil type and its conditions (soil moisture and texture), plow depth and forward speed. The aim of this study is to investigate the effect of forward speed, plow depth and soil moisture on fuel consumption and required tensile force during tillage operation with a moldboard plow which uses three plows in clay soil. Materials and Methods The current study was carried out to optimize the tillage operation with a moldboard plow in the clay soil. Tillage experiments were performed to evaluate the effect of forward speed, plow depth and soil moisture content on the required tensile force and tractor fuel consumption. A moldboard plow with three single-sided plows was used to conduct experiments. Two tractors (MF285 and U650) and a dynamometer were used to measure the required tensile force. To measure the fuel consumption of the tractor during operation, the fuel level was measured in a separate tank system installed on the tractor's fuel system. Experiments were carried out using response surface method and central composite design (CCD) by taking three levels of forward speed (4, 5 and 6 kmh-1), three plow depth (20, 25 and 30 cm) and three levels of soil moisture content (12, 16 and 20%). Design Expert 8.0.6 software was used to analyze the experimental data. Results and Discussion The result of the analysis of variance showed that the effects of plow depth, forward speed and soil moisture, as well as the interaction between forward speed and moisture content on the fuel consumption during tillage operations with moldboard plow are significant. The results also indicated that the increase in forward speed decreased the fuel consumption. Also, fuel consumption decreased with increasing in moisture content at first, but then increased. The reason for this was probably because of the increased strength of soil particles due to the reduced moisture content (the stronger coherence force between the particles), which required more energy to shear the soil. According to the results of analysis of variance, it can be concluded that all three factors of forward speed, plow depth and soil moisture had a significant effect on the required tensile force of moldboard plow at %1 probability level. With increasing the plow depth and forward speed, required tensile force increased significantly. The dependent variables were modeled as second order regression equations and optimal values of independent variables were determined. Optimum performance with maximum desirability was determined at forward speed of 5.08 kmh-1, plow depth of 20 cm and soil moisture content of 16.41%. Conclusion With increasing plow depth, tensile force and fuel consumption increased. Also, tensile force increased with increasing forward speed, but this increase was not severely affected by the plow depth and reduced the fuel consumption. The quadratic regression models can well predict the required tensile force and fuel consumption. Using response surface method, optimum performance was determined at forward speed of 5.08 kmh-1, plow depth of 20 cm and soil moisture content of 16.41%.
Modeling
Gh. Shahgholi; H. Ghafouri Chiyaneh; T. Mesri Gundoshmian
Abstract
Introduction Soil compaction is one of the most destructive effects of machine traffic. Compaction increases soil mechanical strength and reduces its porosity, plant rooting and ultimately the yield. Nowadays, agricultural machinery has the maximum share on soil compaction in modern agriculture. The ...
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Introduction Soil compaction is one of the most destructive effects of machine traffic. Compaction increases soil mechanical strength and reduces its porosity, plant rooting and ultimately the yield. Nowadays, agricultural machinery has the maximum share on soil compaction in modern agriculture. The soil destruction may be as surface deformation or as subsurface compaction. Any way machine traffic destructs soil structure and as result has unfavorable effect on the yield. Hence, soil compaction recognition and its management are very important. In general, soil compaction is the most destructive effect of machine traffic. Modeling of ecological systems by conventional modeling methods due to the multitude effective parameters has always been challenging. Artificial intelligence and soft computing methods due to their simplicity, high precision in simulation of complex and nonlinear processes are highly regarded. The purpose of this research was the modeling of soil compaction system affected by soil moisture content, the tractor forward velocity and soil depth by multilayer perceptron neural network. Materials and Methods In order to carry out the field experiments, a tractor MF285 which was equipped with a three-tilt moldboard plough was used. Experiments were conducted at the Agricultural research field of University of Mohaghegh Ardabili in five levels of moisture content of 11, 14, 16, 19 and 22%, forward velocity of 1, 2, 3, 4 and 5 km.h-1, and soil depths of 20, 25, 30, 35 and 40 cm as a randomized complete block design with three replications. In this study, perceptron neural network with five neurons in the hidden layer with sigmoid transfer function and linear transfer function for the output neuron was designed and trained. Results and Discussion Field experiments showed three main factors were significant on the bulk density (P<0.01). The mutual effect of moisture on depth and mutual binary effect of moisture on velocity and depth on velocity were significant (P<0.01). Mutual triplet effect of moisture on velocity on depth was significant (P<0.05). Maximum bulk density of 1362 kg/m3 was obtained at the highest moisture of 22% and the lowest forward velocity of 1 km/h at the depth of 20 cm. Whilst the minimum value of 1234.5 kg/m3 was related to the moisture, forward velocity and depth of 11%, 5 km/h and depth of 40 cm, respectively. Compaction increased as soil moisture content increased up to 22% which was critical moisture. In contrast, soil compaction decreased as the tractor velocity and soil depth increased. A comparison of neural network output and experimental results indicated a high determination coefficient of R2 = 0.99 between them. Also, the mean square error of the model was 0.174, in addition, mean absolute percentage error of the system (MAPE) was equal to %0.29 which showed high accuracy of neural network to model soil compaction.ConclusionIt was concluded that soil compaction increased as soil moisture content increased up to a critical value. Increasing soil moisture act as lubricant and soil layers compacted together. Hence knowledge of soil moisture can help us to manage soil compaction during agricultural operations. Increasing the tractor forward velocity reduced soil compaction. However, agricultural operations should be conducted at certain speeds to carry out the duty properly and increasing speed more that value decreases the efficiency of work.Neural network of MLP with 5 neurons in hidden layer and sigmoid function in middle layer and one neuron with linear transfer function was found the most accurate and precise in prediction of the soil bulk density. A high determination coefficient of R2 = 0.99 was found between measured and predicted values.
Modeling
J. Taghinazhad; R. Abdi; M. Adl
Abstract
Introduction Anaerobic digestion (AD) is a process of breaking down organic matter, such as manure, in the absence of oxygen by concerted action of various groups of anaerobic bacteria. The AD process generates biogas, an important renewable energy source that is composed mostly of methane (CH4), and ...
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Introduction Anaerobic digestion (AD) is a process of breaking down organic matter, such as manure, in the absence of oxygen by concerted action of various groups of anaerobic bacteria. The AD process generates biogas, an important renewable energy source that is composed mostly of methane (CH4), and carbon dioxide (CO2) which can be used as an energy source. Biogas originates from biogenic material and is therefore a type of biofuel. Enhancement of biogas production from cattle dung or animal wastes by co-digesting with crop residues like sugarcane stalk, maize stalks, rice straw, cotton stalks, wheat straw, water hyacinth, onion waste and oil palm fronds as well as with liquid waste effluent such as palm oil mill effluent. Nevertheless, the search for cost effective and environmentally friendly methods of enhancing biogas generation (i.e. biogas yield) still needs to be further investigated. Many workers have studied the reaction kinetics of biogas production and developed kinetic models for the anaerobic digestion process. Objective of this study is to investigate the effect of biological additive using of organic loading rate (OLR) in biogas production from cow dung. In addition, cumulative biogas production was simulated using logistic growth model, and modified Gompertz models, respectively. Materials and Methods The study was performed in 2015-2016 at the agricultural research center of Ardabil Province, Moghan (39.39 °N, 48.88° E). Fresh cow manure used for this research was collected from the research farm of the Institute for Animal Breeding and Animal Husbandry, Moghan. It was kept in 30 l containers at ambient temperature until fed to the reactors. In this study, experiments were conducted to investigate the biogas production from anaerobic digestion of cow manure (CM) with effect of organic loading rate (OLR) at mesophilic temperature (35°C±2) in a long time experiment with completely stirred tank reactor (CSTR) under semi continuously feeding. The complete-mix, pilot-scale digester with working volume of 180 l operated at different organic feeding rates of 2 and 3 kg VS. (m-3.d-1). the biogas produced was measured daily by water displacement method and its composition was measured by gas chromatograph. Total solids (TS), volatile solids (VS), pH and etc. were determined according to the APHA Standard Methods. The biogas production kinetics for the description and evaluation of methanogens was carried out by fitting the experimental data of biogas production to various kinetic equations. In addition, Specific cumulative biogas production was simulated using logistic kinetic model exponential Rise to Maximum and modified Gompertz kinetic model. Results and Discussion The experimental protocol was defined to examine the effect of the change in the organic loading rate on the efficiency of biogas production and to report on its steady-state performance. The biogas produced had methane composition of 58- 62% and biogas production efficiency 0.204 and 0.242 m3 biogas (kg VS input) for 2 and 3 kg VS.(m-3.d-1), respectively. The reactor showed stable performance with VS reduction of around 64 and 53% during loading rate of 2 and 3 kg VS.(m-3.d-1), respectively. Other studies showed similar results. Modified Gompertz and logistic plot equation was employed to model the biogas production at different organic feeding rates. The equation gave a good approximation of the biogas yield potential (P) and correlation coefficient (R2) over 0.99. Conclusion The performance of anaerobic digestion of cow dung for biogas production using a completely stirred tank reactor was successfully examined with two different organic loading rate (OLR) under semi continuously feeding regime in mesophilic temperature range at (35°C±2). The methane content of 58- 62% and actual biogas yield of 0.204 and 0.242 m3 biogas.(kg VS input-1) were observed for 2 and 3 kg VS. (m-3.d-1), respectively. The modeling results suggested Modified Gompertz plot and Logistic growth plot both had higher correlation for simulating cumulative biogas production. Therefore, arising from the increasing environmental concern and prevailing wastes management crises, optimizing biogas production by 2 kg VS. (m-3.d-1) represents a viable and sustainable energy option.
Modeling
M. R. Salar; S. H. Karparvarfard
Abstract
Introduction The dynamic response of soil on tillage tools, is an important factor in determining their performance. For a tractor with a certain size, a reduction in draft force, the working width and speed of tools can rise and result in increasing performance and reduce costs. Researches carried out ...
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Introduction The dynamic response of soil on tillage tools, is an important factor in determining their performance. For a tractor with a certain size, a reduction in draft force, the working width and speed of tools can rise and result in increasing performance and reduce costs. Researches carried out in order to reduce the draft force led to design and build new tillage tools called Bent Leg and Parra plows. The dual bent blade sub-surface tillage tool was built and examined inspired by the shape of a bent leg. The researches indicated that the combination of a dual bent blade sub-surface tillage tool and chisel plow could be used in order to reduce draft force, loosen the seed bed by the chisel plow and wings, increase in soil disturbance area by the wings, and create a suitable space for root growth by chisel plow. Since the fuel consumption and traction power of tractor are the limiting factors for pulling tools in the soil. The rake angle of tillage tools is the penetration factor of the tools to the soil. It is necessary to determine the optimized rake and bend angles according to their effect on draft force and better penetration in soil. In this research, the Response Surface Methodology (RSM) was utilized to determine the optimized points of wing geometry of winged chisel plow in order to minimize the draft and vertical forces of tillage tool. Materials and Methods Using the properties of dual bent blade subsurface tillage implement and chisel plow, the winged chisel plow was designed by Catia V5R20 software and was built in the workshop of mechanics of biosystems engineering department at Shiraz University. The effect of three factors of working depth of wing (5, 10, and 15 cm), bend angle (10, 20, and 30 degree), and rake angle (7.5, 15, and 22.5 degree) were analyzed on draft and vertical forces of wined chisel plow in soil bin of Karaj Agricultural Engineering Research Institute. The length, width, and depth of the soil bin were 24 m, 1.7 m, and 1 m, respectively. The most important issue was to study the main effects and interactions of factors. So, the Response Surface Methodology was selected. With the help of this statistical design, the numbers of experiments were reduced and all coefficients of quadratic regression and interaction factors were estimated. The experiments were conducted based on the central composite design considering three main surface including central and axial points for each factors. For each response the quadratic polynomial models were obtained using the multiple linear regression. Results and Discussion The results indicated that fitted quadratic model for draft force corresponded with the experimental data by determination coefficient of up to 94% (R2 ˃ 0.94). Increasing the depth of wing, the contact with loosened soil decreased that led to failure in unloosened soil around the chisel blade and increase in pressure to the blade. The results showed that the effect of bend angle was significant on draft force and increasing the bend angle, the tip of wing located in deeper place so, the draft force was increased that was in line with previous researches. The effect of rake angle was not significant on the draft force and its effect on the model was positive and negligible which was reported positive and significant in previous works. The fitted quadratic model for vertical force corresponded with the test data by determination coefficient of up to 93% (R2 ˃ 0.93). The effects of wing depth and bend angle were positively significant on the vertical force of the tool but the effect of rake angle was negligible. The increase in vertical force with increasing bend angle was further in deeper wing position. However, the impact of rake angle was seen in vertical force and the effect of bend angle was not significant in vertical force in rake angles of 7.5° and 15°, but it was significant in rake angle of 22.5°. Conclusion The draft and vertical forces were determined 3.43 and 1.31 kN, respectively, at optimum condition (wing depth of 5cm, bend angle of 11.1°, and rake angle of 19.46°). The proposed model to predict the dependent variables were very close to the results of obtained experimental findings. The wing depth and bend angle had positive and significant effects on draft and vertical forces but the effect of rake angle was positive and insignificant on both measured traits.
Modeling
A. Zareei; R. Farrokhi Teimourlou; L. Naderloo; M. H. Komarizade
Abstract
Introduction Spiral conveyors effectively carry solid masses as free or partly free flow of materials. They create good throughput and they are the perfect solution to solve the problems of transport, due to their simple structure, high efficiency and low maintenance costs. This study aims to investigate ...
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Introduction Spiral conveyors effectively carry solid masses as free or partly free flow of materials. They create good throughput and they are the perfect solution to solve the problems of transport, due to their simple structure, high efficiency and low maintenance costs. This study aims to investigate the performance characteristics of conveyors as function of auger diameter, rotational speed and handling inclination angle. The performance characteristic was investigated according to volumetric efficiency. In another words, the purpose of this study was obtaining a suitable model for volumetric efficiency changes of steep auger to transfer agricultural products. Three different diameters of auger, five levels of rotational speed and three slope angles were used to investigate the effects of changes in these parameters on volumetric efficiency of auger. The used method is novel in this area and the results show that performance by ANFIS models is much better than common statistical models. Materials and Methods The experiments were conducted in Department of Mechanical Engineering of Agricultural Machinery in Urmia University. In this study, SAYOS cultivar of wheat was used. This cultivar of wheat had hard seeds and the humidity was 12% (based on wet). Before testing, all foreign material was separated from the wheat such as stone, dust, plant residues and green seeds. Bulk density of wheat was 790 kg m-3. The auger shaft of the spiral conveyor was received its rotational force through belt and electric motor and its rotation leading to transfer the product to the output. In this study, three conveyors at diameters of 13, 17.5, and 22.5 cm, five levels of rotational speed at 100, 200, 300, 400, and 500 rpm and three handling angles of 10, 20, and 30º were tested. Adaptive Nero-fuzzy inference system (ANFIS) is the combination of fuzzy systems and artificial neural network, so it has both benefits. This system is useful to solve the complex non-linear problems in agricultural engineering applications. ANFIS by linguistic concepts can establish and inference non-linear relationship between inputs and outputs. In this research, generally modeling was performed by using toolbox of ANFIS and coding in MATLAB software. Five important and effective factors in modeling were optimized until the best ANFIS model was obtained. The five factors were: type of fuzzy sets for inputs, number of fuzzy sets for inputs, type of fuzzy set for output, method of optimization and number of epochs. The statistical model was done by using SPSS and in the multivariate regression method. In multivariate linear regression in statistical model, the independent variables were auger blade diameter, rotational speed and the angle of slope of the auger and dependent variable was volumetric efficiency. The factorial test in randomized complete block design was conducted for variance analysis of volumetric efficiency. Mean Comparison of volumetric efficiency in different levels of factors was performed using Duncan' test in 5% level. Conclusion In this study, volumetric efficiency of spiral conveyors was investigated as a function of auger blade diameter, auger rotational speed and slope of transfer. The performance was measured in terms of volumetric efficiency using ANFIS and statistical models with SPSS. The results showed that: Volumetric efficiency almost decreased by increasing of rotational speed, for all three conveyors. Maximum volumetric efficiency in all three spiral conveyors was in the speed range of 100 to 200 rpm. Volumetric efficiency significantly reduced in all three spiral conveyors by increasing in rotational speed and slope of transferring in spiral conveyors. Effect of spiral conveyor diameter on the volumetric efficiency in product transferring was irregular and no specific process is appeared. The correlation coefficient between the actual and predicted values was obtained as 0.98 in ANFIS model and 0.94 in multivariate linear regression with SPSS which showed the ANFIS model was more accurate than statistical model. Comparison between performances of spiral conveyor to transfer the seeds of wheat, with results by other researchers that has been reported for spiral conveyors with the same slope to transfer of corn kernels, was found that the angle effect on volumetric efficiency is quite significant. Therefore, it proves that performances of spiral conveyor are impressed by characteristics of transition material considerably. The maximum volumetric efficiency was corresponded in rotational speed of 100 rpm, inclination angle of 10º, and blade diameter of 17.5 cm that it was approximately 29.11%.
