G. Safar alizadeh herisi; A. M. Borghaee; A. Sharifi Malvajerdi
Abstract
Introduction One of the main factors affecting plant growth is soil compaction. More attention should be paid to soil compaction than the past. Soil compaction not only destroys the soil structure, but also leads to a heavier soil structure with natural cavities. The rolling resistance reduces energy ...
Read More
Introduction One of the main factors affecting plant growth is soil compaction. More attention should be paid to soil compaction than the past. Soil compaction not only destroys the soil structure, but also leads to a heavier soil structure with natural cavities. The rolling resistance reduces energy and occurs when the tire moves on a soft soil and rolling resistance of the tire is brought about by two processes of soil deformation and wheel change. This force is influenced by the design of the tire, the parameters of the tire, and the characteristics of the soil. The apparent electrical conductivity (ECa) indicates the direct conductivity of direct current in the soil. The electrical conductivity is effective on chemical and physical properties, including the amount of soluble salts in the soil, salinity, cation exchange capacity, soil texture, organic matter content, moisture content and water holding capacity, and compression. The purpose of this study was to investigate the effect of soil compaction and soil moisture on the soil electrical conductivity and rolling resistance of the Messy Ferguson 285 tractor rear tire. This study showed the density and soil moisture were associated with soil electrical conductivity and rolling resistance. Materials and Methods This test had independent and dependent variables. The dependent variables including rolling resistance and electrical conductivity, whose values were measured by a torque meter and a portable EC meter. Independent variable comprised of soil compaction and soil moisture measured by Penetrologger and soil moisture measurement tools including soil harvesting cylinder, scale and oven device. Experiments were carried out in the soil bin Laboratory with a 1.7 m wide, 24 m long and 1 m deep with soil texture of clay loamy in Agricultural Engineering Research Institute (Karaj). The soil was prepared layer by layer and up to a depth of 20 cm by the soil preparation unit. In all experiments, the vertical load was fixed at 4000 N and the tire pressure of 6899 N.m-2. On each layer, the water was evenly sprayed to reach the desired moisture. To do this research, factorial experiment with soil compaction levels at 3 levels of 2, 4 and 6 roller passes, respectively, with the bulk density of 1.47, 1.54 and 1.69 g.cm-3 and soil moisture at 3 levels of 10%, 12% and 14% were used in 3 replications. Data were analyzed using SPSS software. The tools used included the tire test rig, the rear tire of a Massy Ferguson 285 tractor, the soil preparation unit, and the measuring instrument, including the torque meter, the penetrologger and the portable EC meter. Results and Discussion In this experiment, it was found that as the amount of moisture increased, the compaction was also increased. The test indicated that the soil rolling resistance was increased by decreasing the soil moisture content. Moreover, increasing in the soil compaction ration led to decreasing the soil rolling resistance. The CI was used at a depth of 20 cm to 0 cm. In these experiments, we concluded that the higher density of compaction resulted in increasing the soil cone index (CI). This index was directly related to the compaction, but it had an adverse relation with the moisture. It means the lower amount of moisture led to the higher amount of CI. The amount of electrical conductivity of soil was measured at a depth of 0-25 cm. In this experiment, we concluded that the higher compaction ratio resulted in the higher electrical conductivity. It means that electrical conductivity had a direct relation with the compaction and the moisture content. The lower moisture content led to the lower electrical conductivity of the soil. Conclusion In general, considering all the tests and comparison between rolling resistance, soil cone index and apparent electrical conductivity before and after roller passing, it can be concluded that as the amount of moisture content increased, the soil cone index (CI) decreased. The soil cone index (CI) had a relationship with the moisture. The lower moisture content led to the lower soil moisture resistance, as well as the higher moisture content resulted in the higher soil resistance. The lower amount of soil compaction showed the greater soil rolling resistance, and the greater amount of soil compaction caused to the less soil moisture resistance. The electrical conductivity before and after the roller pass was different in the case of roller pass, and the higher amount of moisture led to the greater electrical conductivity, because the electrical conductivity was directly related to the moisture and the compaction affects all parameters.
P. Ahmadi Moghaddam; L. Eftekhari; A. Mardani; H. Khodaverdilo
Abstract
Introduction: Monitoring and management of soil quality is crucial for sustaining soil function in ecosystem. Tillage is one of the management operations that drastically affect soil physical quality. Conservation tillage methods are one of the efficient solutions in agriculture to reduce the soil erosion, ...
Read More
Introduction: Monitoring and management of soil quality is crucial for sustaining soil function in ecosystem. Tillage is one of the management operations that drastically affect soil physical quality. Conservation tillage methods are one of the efficient solutions in agriculture to reduce the soil erosion, air pollution, energy consumption, and the costs, if there is a proper management on the crop residues. One of the serious problems in agriculture is soil erosion which is rapidly increased in the recent decades as the intensity of tillage increases. This phenomenon occurs more in sloping lands or in the fields which are lacking from crop residues and organic materials. The conservation tillage has an important role in minimizing soil erosion and developing the quality of soil. Hence, it has attracted the attention of more researchers and farmers in the recent years.
Materials and Methods: In this study, the effect of different tillage methods has been investigated on the crop residues, mechanical resistance of soil, and the stability of aggregates. This research was performed on the agricultural fields of Urmia University, located in Nazloo zone in 2012. Wheat and barley were planted in these fields, consecutively. The soil texture of these fields was loamy clay and the factorial experiments were done in a completely randomized block design. In this study, effect of three tillage systems including tillage with moldboard (conventional tillage), tillage with disk plow (reduced tillage), chisel plow (minimum tillage) and control treatment on some soil physical properties was investigated. Depth is second factor that was investigated in three levels including 0-60, 60-140, and 140-200 mm. Moreover, the effect of different percentages of crop residues on the rolling resistance of non-driving wheels was studied in a soil bin.
The contents of crop residues have been measured by using the linear transects and image processing methods. In the linear transects method, the experiments were replicated three times in each block due to increasing the accuracy and mean of datawas calculated. The tests were randomly performed in each block. Then, the number of nodes, which are located on crop residues of size 25 mm, longitudinally, was counted. So the percentage of crop residue in each block was calculated through the percentage of nodes. The experiments of rolling resistance were also performed in three levels, 10, 50, and 90% of crop residues, inside the soil bin.
Results and Discussion: Result showed that, in comparison with control treatment, tillage operation significantly decreased bulk density (p<0.01), penetration resistance (p<0.01), and aggregates stability (p<0.01), in the soil surface (0-10 cm). Also, the results showed that penetration resistance of soil was increased by depth.
The results of variance analysis in crop residue dataset showed that there were significant differences among the treatments in the terms of crop residues (P<0.05). Because of increasing the intensity of tillage and also the different performance of various tillage tools would mix crop residues with the soil and lead to reduce the crop residues. The consequences revealed that the treatments had significant differences in the terms of mechanical resistance of soil at the confidence level of 5%. The mechanical resistance of soil in three levels of depth had the most and the least contents in chisel and disk plows treatments, respectively. Because of disk plows can powder soil more than other treatments and chisel plows can only make narrow in the soil. The results of investigating the effect of crop residues on rolling resistance of wheels showed that there were not any significant differences between the treatments.
Conclusions: It can be concluded that increasing the tillage intensity would reduce the stability of aggregates. Thus, the least stability of aggregates was obtained when using moldboard plows. However, the most stability was achieved using chisel and disk plows. Finally, disk plough is recommended as an appropriate tool in this research due to the high percentage of crop residues, lower mechanical resistance, lower bulk density, and higher stability of aggregates in the soil. Generally, in short-term period, conservation tillage (reduced tillage and minimum tillage) results the improvement of soil physical quality in comparison with tillage operation. Further studies on long-term effects of various tillage systems are suggested in order to select and implement of optimum tillage method in the region.
F. Gheshlaghi; A. Mardani
Abstract
Introduction: Rolling resistance is one of the most substantial energy losses when the wheel moves on soft soil. Rolling resistance value optimization will help to improve energy efficiency. Accurate modeling of the interaction soil-tire is an important key to this optimization and has eliminated the ...
Read More
Introduction: Rolling resistance is one of the most substantial energy losses when the wheel moves on soft soil. Rolling resistance value optimization will help to improve energy efficiency. Accurate modeling of the interaction soil-tire is an important key to this optimization and has eliminated the need for costly field tests and has reduced the time required to test.
Rolling resistance will change because of the tire and wheel motion parameters and characteristics of the ground surface. Some tire design parameters are more important such as the tire diameter, width, tire aspect ratio, lugs form, inflation pressure and mechanical properties of tire structure. On the other hand, the soil or ground surface characteristics include soil type; moisture content and bulk density have an important role in this phenomenon. In addition, the vertical load and the wheel motion parameters such as velocity and tire slip are the other factors which impact on tire rolling resistance. According to same studies about the rolling resistance of the wheel, the wheel is significantly affected by the dynamic load.
Tire inflation pressure impacted on rolling resistance of tires that were moving on hard surfaces. Studies showed that the rolling resistance of tires with low inflation pressure (less than 100 kPa) was too high.
According to Zoz and Griss researches, increasing the tire pressure increases rolling resistance on soft soil but reduces the rolling resistance of on-road tires and tire-hard surface interaction. Based on these reports, the effect of velocity on tire rolling resistance for tractors and vehicles with low velocity (less than 5 meters per second) is usually insignificant.
According to Self and Summers studies, rolling resistance of the wheel is dramatically affected by dynamic load on the wheel.
Artificial Neural Network is one of the best computational methods capable of complex regression estimation which is an advantage of this method compared with the analytical and statistical methods.
It is expected that the neural network can more accurately predict the rolling resistance. In this study, the neural network for experimental data was trained and the relationship among some parameters of velocity, dynamic load and tire pressure and rolling resistance were evaluated.
Materials and Methods: The soil bin and single wheel tester of Biosystem Engineering Mechanics Department of Urmia University was used in this study. This soil bin has 24 m length, 2 m width and 1 m depth including a
single-wheel tester and the carrier.
Tester consists of four horizontal arms and a vertical arm to vertical load. The S-shaped load cells were employed in horizontal arms with a load capacity of 200 kg and another 500 kg in the vertical arm was embedded. The tire used in this study was a general pneumatic tire (Good year 9.5L-14, 6 ply)
In this study, artificial neural networks were used for optimizing the rolling resistance by 35 neurons, 6 inputs and 1 output choices. Comparison of neural network models according to the mean square error and correlation coefficient was used. In addition, 60% of the data on training, 20% on test and finally 20% of the credits was allocated to the validation and Output parameter of the neural network model has determined the tire rolling resistance. Finally, this study predicts the effects of changing parameters of tire pressure, vertical load and velocity on rolling resistance using a trained neural network.
Results and Discussion: Based on obtained error of Levenberg- Marquardt algorithm, neural network with 35 neurons in the hidden layer with sigmoid tangent function and one neuron in the output layer with linear actuator function were selected. The regression coefficient of tested network is 0.92 which seems acceptable, considering the complexity of the studied process. Some of the input parameters to the network are speed, pressure and vertical load which their relationship with the rolling resistance is discussed.
The results indicated that in general trend of changes, the velocity is not affected by rolling resistance. Rolling resistance increases when tire pressure decreases. This is due to energy consumption for creating deflection on the body of the tire at the lower levels of tire inflation pressure. Another variable parameter is the vertical load on the wheel and its logical relation with rolling resistance using neural network. The results showed that increasing the vertical load increases the rolling resistance.
Conclusions: The major purpose of this study was the feasibility of using learning algorithms for interaction between wheel and soil. The parameters of the wheel when clashes with soil are not stochastic and in spite of their complexity follow a specific model, certainly. Artificial neural network trained with a correlation coefficient of 0.92 relatively had a good performance in education, testing and validation parts. To validate the network results, the impact of some factors on the extraction process such as velocity, load and inflation pressure was simulated. The main objective of this article is comparing the network performance with basic principles and other scientific reports.
In this regard, the predictions by trained neural network indicated that rolling resistance is independent of the velocity of the wheel. On the other hand, rolling resistance decreases by increasing tire inflation pressure which is a general trend similar to other studies and reports in the same mechanical condition of the soil tested. Rolling resistance changes are directly proportional to load vertical variations on the wheel in terms of quantity and quality, similar to experimental models such as Wismer and Luth.
N. Dibagar; A. Mardani; A. Modarres Motlagh; H. Jafari
Abstract
Introduction: Encountering soil from the viewpoint of management and product manufacturing has always been considered important, and an attempt is always made hat the tools and contrasting methods of soil be designed in such a way that itself prevents, as much as possible, the destructive consequences ...
Read More
Introduction: Encountering soil from the viewpoint of management and product manufacturing has always been considered important, and an attempt is always made hat the tools and contrasting methods of soil be designed in such a way that itself prevents, as much as possible, the destructive consequences or energy waste that include economical or environmental limitations. Enhancing the soil encountering methods, quality reformation, and its related equipment, requires performing reliable tests in actual soil conditions. Considering the complexity and variety of variables in soil and machine contrast, this is a hard task. Hence, the numeral simulations are the key of all optimizations that illustrate efficient models by removing the costly farm tests and reducing research time. Tire is one of the main factors engaged with soil, and it is one of those tools that are discussable in both farms, and software environments. Despite the complexities in soil behavior, and tire geometry, modeling, tire movement on the soil has been the researchers’ objective from the past.
Materials and methods: A non-linear finite element (FE) model of the interaction of a non-driving tire with soil surface was developed to investigate the influence of the forward speed, tire inflation pressure and vertical load on rolling resistance using ABAQUS/Explicit code. In this research numerical and experimental tests were done under different conditions in order to estimate tire rolling resistance. In numerical tests, the soil part was simulated as a one-layer viscous-elastic material with a Drucker-Prager model by considering realistic soil properties. These properties included elastic and plastic properties which were obtained in the soil laboratory using relevant tests. The soil samples were prepared from the soil which was inside the soil bin. The same soil was utilized in experimental tests. Finite strain hyper elasticity model is developed to model nearly incompressible rubber materials for the tire. Tire model consisted of three components: tread, rubber and ring. Using a soil bin and one wheel tester with their related equipment, experimental tests were carried out in the workstation of mechanics of bio system engineering department of the Urmia University. This system includes various sections such as soil storage in dimensions of 22×2×1 meter, tools carrier or tracker, soil processing equipment, dynamic system, evaluation tools and controlling systems. In order to launch the collection and supply required power for wheel carrier, an industrial three phase electromotor with 22 kW (30 hp) was used. Both numerical and experimental tests were done at three levels of wheel dynamic load (1, 2, 3, 4 and 5) kN, tire inflation pressure (100, 200 and 300) kPa and four levels of speed (0.25, 0.45, 0.65, 0.9 and 1.15) m s-1 to obtain the rolling resistance of the tire.
Results and discussion: In order to evaluate the performance of final non driving tire-soil model to estimate the rolling resistance, numerical results were compared with preliminary experimental data obtained from the soil-bin tests. The comparison showed reasonably good agreement between the computed and measured general pattern of the rolling resistance at the tire-soil interface under different speeds, vertical loads and inflation pressures. In both tests, a specified relation was not seen between tire velocity and its rolling resistance, as it was not seen in empirical models such as Wismar and Luce. Correlation coefficient between experimental and numerical data, in the minimum and maximum value of tire inflation pressure was computed to be 0.06 and 0.016 percent, respectively. The amount of tire rolling resistance significantly increased with increase of tire vertical load. Correlation coefficient between experimental and numerical data, in the minimum and maximum vertical loads was computed to be 80 and 87 percent, respectively. Gent and Walter obtained the same results. The tire inflation pressure and rolling resistance variables had inverse relation to each other in both numerical and experimental tests. Correlation coefficient between experimental and numerical data was computed to be 97 and 73 percent in the minimum and maximum tire inflation pressure, respectively. The gradient of changes in tire inflation pressure - rolling resistance diagram was less in numerical tests. This was because of differences between real properties and the properties entered into the software.
Conclusions: To conclude, in this investigation a new 3D tire-soil model was simulated which has specific features. The experimental results showed that the numerical data of estimation of non-driven tire rolling resistance were reliable. In both tests, the effect of changes in tire forward speed on rolling resistance was not significant.The amount of the tire rolling resistance significantly increased with increasing tire vertical load. Changes in tire inflation pressure and rolling resistance had an inverse relation with each other in both numerical and experimental tests. The slope of rolling resistance - inflation pressure diagram in numerical tests was less than the same diagram in the experimental tests.
