gholamhossein shahgholi

The use of fuel additives is an engineering solution to achieve a clean combustion with a high thermodynamic efficiency. Fuel quality in all types of internal combustion engines is mainly related to the thermophysical properties of the fuel. Based on this, there is a special desire to develop new gasoline fuel formulas to increase braking power and reduce spark-ignition engine fuel consumption and greenhouse gas emissions. Life cycle assessment is a reliable method to evaluate the environmental impact of a process. This study is dedicated to investigating the performance of gasoline engine and emission of greenhouse gases using Methyl tert-butyl ether gasoline mixture. Part of this research is an attempt to investigate the impact of the life cycle of fuel samples with the aim of obtaining a fuel mixture that can increase engine performance in addition to reducing pollutants. All tests are performed at constant engine speed and full engine load. Based on the results, it can be said that the addition of MTBE to gasoline was able to increase approximately 10-20% braking power. On the other hand, carbon dioxide emission increased by adding MTBE (about 20-35%). Also, with the increase of MTBE, the emission of carbon monoxide has decreased to some extent. The addition of MTBE also relatively reduced the environmental impact variables. With the advancement of technology, and the emergence of intelligent emission control systems, the movement towards the management and optimization of oxygenated additives and the achievement of more environmentally sustainable fuel formulations is prevalent. prevalent

Structural heterogeneity of fruits and vegetables makes it difficult to understand the associated physicochemical changes that occur during drying. Due to its heterogeneous structure, food is one of the most complex types of metamorphic materials. The porosity and hygroscopic nature of fruits and vegetables increase their shrinkage during the drying process, which is a physical process commonly observed during drying. Shrinkage has a significant effect on the mechanical and textural properties of fruits and vegetables. Most importantly, shrinkage is an important factor that has a great impact on drought rate and drought kinetics. Because of these factors, food researchers emphasize that shrinkage should not be ignored when predicting volume and heat transfer during drying. The shrinkage model is better suited to the experimental data during drying than the non-shrinkage model. Food shrinkage depends on several factors such as material properties, mechanical properties, and process status.Knowledge of porosity during drying can also help to accurately predict the transfer phenomenon and quality characteristics. Some researchers have used mathematical equations to predict the porosity of food as a function of moisture content, which can be classified into two categories: (1) theoretical models based on understanding of fundamental physics and the mechanisms involved in pore formation have been established, and (2) experimental models have been developed using parameters in experimental data. Many previous studies on experimental or laboratory shrinkage have predicted porosity as linear, quadratic, and exponential equations. On the other hand, theoretical modeling can provide a better understanding of the shrinkage that occurs simultaneously with heat and volume transfer during drying. However, limited efforts have been made in the theoretical modeling of the contraction of fruits and vegetables, due to the complexity of creating physics-based models. The first porosity model was introduced in the 1950s. Kilpatrick and colleagues proposed a simple model considering the volumetric contraction of fruits and vegetables during drying. Many models in previous research have considered shrinkage to be ideal, during which the reduction of the geometric volume of the product is exactly equal to that of water lost. But in fact, this linear relationship between the decrease in physical volume and the volume of water lost during the drying period is not observed. Cell loss and shrinkage of food tissues occur during the drying process of food. There is a fine distinction between shrinkage and loss, in that shrinkage refers to a reduction in food sample size, but loss indicates irreversible breakdown of cellular and tissue structure. Structural changes at the cellular level occur due to the transfer phenomenon during the dry period. As mentioned earlier, porosity and shrinkage during drying affect the transfer process as well as other quality characteristics. Accurate prediction of porosity and shrinkage helps design an advanced drying system to ensure quality products.Careful examination of theoretical and experimental models of porosity indicates the need for a simple model that can compensate for some of the limitations of theoretical models and use them for drying products and processes. Therefore, the aim of this study is to create a real contraction model with minimal use of experimental coefficients. A simple model considering heat gradient and humidity, glass transfer temperature, and drying time can be a potential way to predict structural changes during drying. Therefore, in this study, a new approach to contraction velocity is introduced. Therefore, paying attention to these parameters in shrinkage rate, process parameters, and material properties are considered in predicting metamorphism during drying. The physical meaning of shrinkage velocity is as follows: The velocity of the outer surface of the specimen during drying.

Apples were selected as the study sample in this study. Apples have high initial porosity and change of porosity during the drying period is very important. Therefore, it is expected that the experimental measurement of porosity changes and confirmation of the proposed model for this sample will be better. Kohn rose apples were prepared from a local supermarket and stored in a refrigerator at 2 ° C. The apples were selected from a box to have the same degree of ripeness. The treatment step was calculated using a liquid refractometer (BPTR-100 V3.0). The average ripeness of apples was 14.20 ± 0.20. The initial moisture content of fresh apples was calculated to be 77 ± 0.50% wb. 10 samples were used to measure the moisture content. Apples were removed from the refrigerator and washed at room temperature for one and a half hours. The skin of the samples was taken and cut into round pieces 10 mm thick and 40 mm in diameter. A hot air dryer with a fan was used. The drying temperature varied from 50 to 65 ° C and airspeed was set at 1 m / s. Particle density was measured using a gas (helium) pycnometer. The density of the mass was measured from the volume of the sample and the weight of the sample so that the sample was first coated with organic solvents to cover the open pores because there were numerous open pores that were large enough to be glass beads. They could have entered them. The density of the same sample was calculated before and after coating. The density of the glass beads was calculated from the weight of the required glass beads. The simulation was performed using COMSOL Multiphysics 5.6.0.280 Win / Linux. This software facilitates all stages of the modeling process including geometric structure definition, lattice, physical dimensioning, solving, and displaying results. COMSOL Multiphysics can manage variable properties that are a function of independent variables. A two-dimensional symmetry mode is also provided to facilitate the simulation process. There will be a small amount of 3D effects that can be ignored, and 3D consideration can complicate matters.

The physical quality of dried food depends on the degree of metamorphosis during drying. Shrinkage also has a significant effect on mechanical and textural properties as well as drying speed and kinetics. Accurate prediction of shrinkage can lead to better food quality and optimal drying process design. Food shrinkage depends on several factors including material properties, microstructure, mechanical properties, and process conditions. Experimental models can be created quickly that have a high impact. However, they do not show physical changes in the process. Physics-based models, on the other hand, are used as predictive models not only in food drying but also in other food industries. However, the theoretical model for predicting porosity is a complex one, due to the need for a number of properties that change under drying conditions. In this study, in order to counter the limitations of experimental and theoretical models, a simple shrinkage model based on the shrinkage rate was developed, which considers the main factors affecting porosity. The results show that the proposed model accurately predicts shrinkage and porosity, and this shows that the simulated shrinkage of the apple is related to the experimental results. For example, the porosity of the apple sample simulation is 0.6, which is consistent with laboratory data. The influence of desiccant air temperature and air velocity was also investigated. Studies show that process parameters (including air velocity and temperature) have a significant effect on the final porosity of the dried food. The porosity model proposed in this study requires the least experimental parameters. Future research could use this model to examine other foods because the structure of different foods is different, and this affects the porosity detection mechanism. Different types of process conditions can be used in future research to develop a general model for pore formation.

This research aimed to investigate co-digestion and the effects of alkaline pretreatment conditions on substrate degradability and methane production from municipal solid waste (MSW) and sewage sludge (SS) in a pilot and experimental approach in non-continuous reactors with a retention time of 30 days. For this purpose, co-digestion of the organic fraction of MSW and SS with 5 mixing ratios of raw materials was evaluated to evaluate the biogas and methane production from it in with mesophilic temperature conditions (37 °C). Therefore, the results showed that the increase of SS (up to 40% by weight of raw materials) in feed led to increased methane yield, while longer retention times were obtained by increasing the percentage of MSW. So, the ratio of MSW (60%) and SS (40%) (60:40) was determined as the preferred ratio for optimal biogas production. Based on the preferred ratio, the effect of different concentrations of alkaline pretreatment (2, 6 and 10% NaOH) for different time periods (1.5, 3 and 6 hours) on the biodegradability of MSW, biogas and methane production was evaluated. The results showed that the best improvement was with the treatment at a concentration of 6%NaOH for 3 hours, which led to a 30% improvement in methane production. Other treatments were also effective, in which 6%NaOH treatment for 1.5 hours resulted in a 17% improvement in methane yield compared to the control sample. Therefore, alkaline pretreatment significantly improves the decomposition of solid organic waste and thus increases methane production.

Potato is an important vegetable that grows all over the world and is considered an important product in developing and developed countries for the human diet as a source of carbohydrates, proteins, and vitamins. This product is native to South America and its origin is from Peru, and after wheat, rice and corn, it is the fourth product in the food basket of human societies. According to the statistics of the Food and Agriculture Organization of the United Nations, the area under cultivation of this crop in Iran in 2017 was 161 thousand hectares and the crop harvested from this area is about 5.1 million tons. As expectations for food products with high quality and safety standards increase, it is necessary to determine their characteristics accurately, quickly, and purposefully. In the potato crop, quality evaluation, after harvest and isolation, is very important to provide a reliable and uniform product to the market, because the potato, like many other crops, has the non-uniform quality and care during the harvest stage. While the quality of raw potatoes is primarily determined by the size, shape, color, and attractiveness of the tuber, the quality of potatoes is generally determined by examining the quality of the final product. The quality of processed products is examined in terms of color, flavor, and texture. The quality of most processed products stems from the quality of raw potatoes. Uniformity in size, shape, and composition is essential for optimal quality. During storage, processing, or cooking, potatoes are exposed to a variety of phenomena that affect the final quality of the product. For consumers, the main quality characteristics of potatoes are color, size, and texture. However, quality assessment for industrial potato processing includes various parameters such as dry matter content, starch content and characteristics, shelf life after storage (storage), and after processing. The type of cultivar, physical and chemical composition, and post-harvest storage are important factors that can affect the cooking characteristics of potatoes and potato crops. Quality assessment of agricultural products includes two main methods, quality rating systems based on the apparent properties of agricultural products and quality rating systems based on internal quality assessment, which has gained prominence in recent years. In the meantime, several methods have been developed so far for non-destructive quality classification of agricultural products based on the evaluation of their internal properties, only some of which have been able to meet the above conditions and are technically and industrially justified. To be. In the meantime, spectroscopy can have high efficiency in determining the quality of figures. Spectroscopy is a system that has a different structure and approach from other methods (image processing, neural network, etc.) and can classify and determine the quality of the digit.

First, 3 different potato cultivars were prepared from Ardabil Agricultural Research Center. After preparing the data, data were collected to determine the amount of sugar (SSC) and at the same time, the samples were tested with a spectrometer to determine the wavelengths of the samples. The glucose level of each sample was measured in 18 replications using an SBR-62T ocular refractometer. To do this, the water of the samples was placed on a refractometer at ambient temperature and its sugar level was read in terms of Brix. A PS-100 spectroradiometer (Apogee Instruments, INC., Logan, UT, USA) made in the USA was used to obtain the spectrum of the samples. This ultra-small, lightweight, portable spectrophotometer has a 1nm sprayer-type single-diffuser and a linear silicon CCD array detector with 2048 pixels, which has a range of 250-150 nm (Vis / NIR) cover. There is also the ability to connect fiber optics to the PS-100 spectroradiometer and transfer data to a computer for the purpose of displaying and storing the acquired spectra in the Spectra Wiz software via the USB port. The data obtained from spectral imaging may be affected by the scattering of light by the detector by changing the sample, changing the sample size, surface roughness in the sample, noise caused by the temperature of the device and many other factors, and unwanted information Affect the accuracy of calibration models. Therefore, data processing is required to achieve stable, accurate, and reliable calibration models. The application of non-destructive methods based on spectroscopy in the full range of wavelengths requires a lot of time and money, which makes the practical application of this method almost impossible; therefore, one should look for a way to find the optimal wavelengths and limit the wavelengths to the minimum possible. The partial least squares (PLS) regression method seems ideal in this regard. In this study, in order to build the models, the data were randomly divided into two parts: 80% of the samples were used for cross-training and cross-validation and the rest of the data were used for independent validation.

Mean absorption spectra Vis / NIR absorption spectra for different treatments in the range of 1000-500 nm are shown in Figure 1. Environmental factors (light and heat) as well as the quality of spectrometer expression cause perturbations in the initial and final wavelengths of the spectra, so part of these wavelengths are removed from the data set and as shown in Figure 1, the samples had a roughly similar pattern; This may be due to the color of the samples. According to Figure 1, there are two well-defined peaks for the spectra, and it appears that for the Colombo and Sante cultivars the peaks appeared at around 480 and 1000 nm and for the Milwa cultivar at around 540 and 950 nm. Figure 1 also shows that the absorption rate of the Milwa cultivar is higher than the other two cultivars, which can be due to differences in the number of different substances such as sugar or SSC. Based on the analysis (PCA) results presented in Figure 2, the first principal component (PC-1) describes 67% and the second principal component (PC-3) describes 27% of the variance of the samples tested. As a result, the first two principal components together represent 94% of the data. Due to the fact that the relationship between the properties of different samples during the tests, for various reasons such as technical problems of equipment, data collection, incorrect sampling, etc. in some samples is inappropriate or to correct. To be out. The values of R2 and RMSE for the calibration and validation sets of different regression models (PLS) with raw and processed data are presented in Figure 3, which is equal to 1.

Fuel additives are a promising engineering solution to achieve clean combustion with high thermodynamic efficiency. Combustion quality in a variety of internal combustion engines is significantly correlated with the thermophysical properties of the fuel. Accordingly, there is a significant tendency to develop a new formulation of gasoline fuel to increase braking power and reduce fuel consumption of spark ignition engines and reduce their emissions. For this purpose, the present study was dedicated to investigating a gasoline engine's performance changes and emissions by gasoline mixtures and ethanol and thinner additives. Part of this research is an attempt to investigate the effect of fuel samples on engine vibration to achieve a fuel mixture that reduces pollution, increases engine performance, and increases engine life. All tests were performed at constant engine speed and full engine load. After obtaining experimental data, the effects of single additives and their interaction were analyzed using statistical software such as. Based on the results, it can be said that integrated additives can be a good way for future studies in terms of the performance and pollution of gasoline engines. These additives can also be studied in terms of the engine's durability. It is suggested in future studies to use samples of fuels with high percentages of mixing with thinner and ethanol additives for a more detailed study.

In this study, gasoline was used as a control fuel, and thinner and ethanol were used as diesel additives (at three levels of 2, 4, and 6%). A homogenizer (Polytron® Switzerland) was used to stabilize the fuel sample at room temperature for 15 minutes.The prepared fuel samples were poured into half-liter bottles and then experimentally tested in a four-stroke single-cylinder ignition engine, model rme1000, with a displacement volume of 98 ccs and a maximum power of W800. In this study, in order to use fuel samples in the rme1000 generator engine and measure the amount of fuel consumed by installing a separate duct behind the carburetor and installing a valve in the fuel transfer path, an attempt was made to control the fuel consumed. In this way, the fuel could be measured from a separate tank by passing through a calibrated glass tube by the method of movement and the primary tank and the built-in valve; we could access the control fuel at any time. A variable resistor of TDGC2-5kVA type and a 1 kW heater were used to load the motor. The number of amps and voltage was measured by measuring the motor power (the product of amperes and direct voltage (DC) shows the amount of power consumed). The pollutant model QRO-401 made by QROTECH company was used to measure the number of pollutants emitted from the engine exhaust.A VIBRO RACK 1000 analyzer system was used to measure the engine's vibration due to combustion, which produces outputs in the form of broken waves. This device works with the help of a computer that is connected by network cables. Sensors were placed to measure the sensors on the motor block to reduce vibration errors and be ready for evaluation in the X, Y, and Z directions when the motor is started. The end parts of the sensors were threaded and connected to the engine block in rotation.One of the most important parts for measuring vibration is the sensors used in which directions to measure, and also the end of the sensor, which is located in the direction of each of the axes, should be placed somewhere closed or in a firm position to transmit the blows and vibrations to the complete state.

This study was conducted to study the effects of ethanol and thinner additives on performance, greenhouse gas emissions, and fuel consumption of single-cylinder, four-stroke gasoline in which gasoline additives were combined with a research octane number of 88. The research was performed on a single-cylinder gasoline engine. The results were evaluated from the perspective of engine performance, pollution and vibration, and based on the observations, suggestions were made. According to this:Adding thinner and ethanol to the samples of gasoline-containing fuels reduces the calorific value of the fuel and increases the density and viscosity, which can have a significant effect on the quality of combustion. It can be said that the addition of thinner and ethanol alone has caused a relative increase in fuel consumption. This trend is due to the decrease in calorific value of fuel samples containing thinner and ethanol compared to natural gasoline fuel. It can be seen that the addition of thinner ethanol has relatively reduced carbon monoxide emissions compared to the control fuel. This trend can be due to oxygen in the sample contents of fuels containing thinner and ethanol. On average, carbon dioxide emissions in samples with additives other than GT1E6, GT3E4, and GT3E6 are higher than in control fuel (gasoline). The trend of increasing carbon dioxide emissions from the GT5E2 fuel sample onwards is highest. On average, oxygen emissions are lower than in the control sample, except in GT0E2, GT0E4, GT0E6, and GT1E6 fuel samples. Low oxygen in the output can be a reason for reducing oxygen content in the output. It can promise high oxygen consumption in the combustion formulation due to complete combustion.The highest emissions of nitrogen oxides are related to GT5E2, GT5E4, and GT5E6 fuel samples. Also, the lowest emissions of nitrogen oxides are related to GT1E0 and GT1E6 fuel samples. In cases where the emission of nitrogen oxides is high, it is recommended to strengthen the engine cooling system. Alternatively, use ORC cycles to absorb as much energy as possible released into the combustion chamber to increase energy production stability. Based on the results, it can be seen that increasing the percentage of thinner and ethanol additives in the fuel sample has reduced the vibration of the gasoline engine compared to the control fuel sample.Based on what has been obtained from previous sections and this section, it can be said that integrated additives can be a good way forward for future studies both in terms of performance and pollution and in terms of examining engine durability because these types of additives benefit from several types of additives and reduce the disadvantages of existing fuels. It is suggested in future studies to use samples of fuels with high percentages of mixing with thinner and ethanol additives for a more detailed study.

The four-wheel drive and rear-wheel drive tractors are commonly used in agricultural operations. In order to investigate the effect of a type of driving system a series of tests were performed usin the three driving systems of foour wheel drive, rear wheel drive and front wheel drive in different axle loads of 0, 150 and 300 kg, tire inflation pressures of 170, 200 and 230 kPa and travel speeds of 1.26, 3.96 and 6.78 km/h. Bulk density was measured as an indicator of soil compaction at different depths of 10, 20, 30 and 40 cm. Also, under the different conditions, the drive wheel slip was measured. To carry out the tests, the four-wheel tractor of Goldoni 240 was used which has the ability to work with mentioned driving systems. The experiments were carried out under controlled conditions in a soil channel  with the length of 3 m and a width and depth of 1 and 0.6 m, respectively. Test were conducted in completely randomised block design with three repetations and results were analysied using SPSS 22 software. The results showed that by changing the driving system from 4WD to RWD and FWD, there was a significant increase in soil density, with the lowest density associated with 4WD system and the highest density related to FWD. The reason for increasing the density by changing the driving system can be attributed to different slip levels in each of these systems due to the lower slip percentage of the 4WD system than the other two systems.  Increasing axial load increased soil boulk density. Of note that with increasing the axial load, the stress was transferred from the surface soil to the subsoil layers. As the axial load on tire increases, the subsoil density was closer to the surface layer. Increased axial load on tire and decreasing tire pressure reduced wheel slip. Stepwise regression model with determination coefficient of 0.92 and according to calculated standard coefficients showed that axial load, soil depth, type of driving system, tractor speed, and finally tire pressure, have the greatest effect on soil bulk density, respectively.

One way to reduce soil compaction is to add organic matter and to manage the field traffic. In this research, farmyard manure was incorporated into clay soil with rates of 0, 45, 60, 90 ton ha-1. After 6 months (September to March), at different numbers of tyre passes of 1, 6, 11 and 16, and three soil moisture contents of 8%, 11% and 14% soil compaction was evaluated measuring soil bulk density and soil sinkage. Experiments were conducted in the soil bin at the Urmia University under a single trector’s tire 220/65 R 21l under a constant load of 4 kN, inflation pressure of 110 kPa and at a forward velocity of 2.88 km hr-1. It was found that at manure rate of of 90 ton ha-1, comparing to no-manure treatment, soil bulk density and soil sinkage decreased by 14.7 and 6.94 percent, respectively. Also, increasing the number of tyre passes from 1 to 16 and increasing soil moisture content from 8 to 14 percent, increased soil bulk density 7.21% and 7.92%, respectively. For neural network modeling multilayer perceptron network with six neurons in the hidden layer with sigmoid transfer function and linear transfer function for the output neuron was used. Comparison of neural network output and experimental results showed high correletion with correlation coefficient of R= 0.99 between them. The mean square error (MSE) of the model and mean absolute percentage error of the system (MAPE) were 0.0119071 and 0.0009641,respectivly, which showed high accuracy of neural network to model soil compaction.

In this study, a single tire tester was used to study the effects of vertical load, inflation pressure and moisture content on tire rolling resistance in a soil bin. A Goodyear 12.4-28, 6 ply tractor drive tire was employed and the soil texture was a clay loam. The experimental design was a completely randomized with factorial layout at three replications. A multivariate regression model was obtained with the correlation coefficient of R2=0.85 to predict the tire rolling resistance based on vertical load, inflation pressure, and moisture content. A multilayer feed-forward ANN (artificial neural network) with standard BP (back propagation) algorithm and LM (Levenberg-Marquardt) training function by using of two hidden layer in the network architecture was employed. RMSE (root mean squared error) and R2 was used as modeling performance criteria. Tire inflation pressure was identified as the controller parameter of tire rolling resistance at low moisture content and also moisture content was the most effective parameter on changing of rolling resistance in regression model. Also the obtained R2=0.977 from ANN model showed that ANN data were more close to actual data than the regression model.

One of the most important issues in agricultural machinery section is tyre - soil interactions. In this study, a single wheel tester was used to follow experiments in controlled conditions in a soil bin. A Goodyear 12.4-28, 6 ply tractor drive tyre was operated at three vertical loads of 6, 9 and 12 kN, three inflation pressures of 80, 120 and 160 kPa and three moisture content of soil: 11.20, 14.86 and 18.68 % d.b to investigate the effect of the variables on these parameters: contact area, contact pressure, compaction, and soil apparent electrical conductivity. It was found that medium contact pressure had a direct relation with vertical load, inflation pressure and moisture content. A regression model with R-square of 0.946 was achieved to predict contact pressure. Soil electrical conductivity changes was predicted with acceptable determination coefficient of 0.850 by using of vertical load, inflation pressure and moisture content. Determination coefficient magnitude for models to predict resistance to soil penetration (cone index) using soil apparent electrical conductivity decreased when moisture content was increased. The vertical load and inflation pressure were found two factors controlling the soil apparent electrical conductivity changes in low and high moisture content, respectively. Error percentage in using soil apparent electrical conductivity parameter to estimate the penetration resistance increased with increasing moisture content.

In this research, the effect of forward speed at four levels (1.8, 2.3, 2.9 and 3.5 km/h), tillage depth at three levels (30, 40 and 50 cm) and wing at two levels (winged and no-winged tines) were investigated on the draft requirement, soil disturbance area and specific draft of Paraplow. The results revealed that the effect of depth and wing was more than forward speed on the studied parameters, significantly. Increasing forward speed increased draft requirement and specific draft but decreased disturbance area. Increasing depth and adding wing led to increase draft requirement, disturbance area and specific draft. Transfering winged paraplow to under the hardpan decreased specific draft, significantly. The results recommended that using lower speed, minimum depth for hardpan breakage and wing will be better. A regression model included the speed, depth and wing width was developed to predict the draft requirement.

Interaction between soil and machine is essential challenge for researchers, developers, designers and manufacturers of agricultural machineries. Modeling of tillage equipment is an important Engineering work. However, interaction modeling is a complex process due to three-dimensional changes in soil, nonlinear soil behavior phenomenon and soil flow quality in connection area between the soil and tool and the dynamic effects of equipment. Correct simulation of the interaction of soil is the key point for the optimization of tillage tools and can eliminate required field tests with high costs. The purpose of this study is to develop a three-dimensional model of a vibrating subsoiler using discrete element method, simulation frequency and oscillation angle on the performance of vibration subsoiler and determining different parameters affecting the simulation results. The information from model simulation will be useful for the design and optimization of vibrating subsoiler. For modeling soil mass as a granular material, the computer program PFC3D. Blade was moved with angular and transition speed in the positive x-axis direction. For non-vibrating blade only included transition speed and for vibration blade in addition to transition speed, angular velocity was also defined. Working depth was 38 cm and blade speed of 0.89 meters per second was defined. To evaluate the effect of vibration angle on vibrating subsoiler different vibration of 27, 16, 8, zero,-14.5,-22.5 degrees in frequency of 4.9 Hz and amplitude of ± 69 amplitude was tested by simulation. In all vibration tests in comparison with non-vibrating,with Increasing vibration angle (positive and negative), the amount of vertical displacement of blade increased which caused more soil rupture. Simulation results showed that the rate of boundary work, kinetic energy and friction work at positive angles were more than negative vibration angles. With increasing negative angle boundary work and friction work significantly decreased. Changing the angle from -22.5 to 27 degrees decreased average bond energy of particles.