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 ...
Read More
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.
Bioenergy
A. Waismoradi; M. E. Khorasani; H. Bahrami; S. M. Safieddin Ardebili; H. Zaki Dizaji
Abstract
IntroductionToday, the number of diesel engines is increasing due to their high efficiency and low greenhouse gases. In the present study, the effect of adding nano cellulose as nanoparticles to diesel fuel on the performance parameters and emissions of diesel engine was investigated. Nano cellulose ...
Read More
IntroductionToday, the number of diesel engines is increasing due to their high efficiency and low greenhouse gases. In the present study, the effect of adding nano cellulose as nanoparticles to diesel fuel on the performance parameters and emissions of diesel engine was investigated. Nano cellulose was provided by the Nano Novin Company in Sari. Nano cellulose values were considered at 3 levels of zero, 25 ppm and 75 ppm. Also, the tests were performed at 3 engine speed of 1600, 2000 and 2400 rpm in full load mode.Materials and MethodsIn this study, nanocellulose was used as nanoparticles to add to diesel and to evaluate the performance and emission parameters of the engine. To prevent the deposition of nano cellulose in diesel fuel, jelly type nano cellulose was used. The samples were named after adding different amounts of nano cellulose, abbreviated D100N0, D100N25 and D100N75. D100 means 100% pure diesel and N means different amounts of nano cellulose with different amounts. Ultrasound was used to obtain homogeneous samples. About 3 liters were prepared from each sample so that it could be used for at least 3 repetitions. The required tests were performed at three different speeds of 1600, 2000 and 2400 rpm in full load mode. The necessary equipment was used to measure the performance parameters and air emissions, including diesel engine connected to the dynamometer, emissions measuring device, fuel system and control room (to apply the load and provide conditions for each treatment and data collection). The air-cooled, four-stroke, compression-ignition single-cylinder engine made by the Italian company Lombardini was used. The D400 eddy current dynamometer made in Germany was used. The ability to measure power by this dynamometer is a maximum of 21 hp, a maximum speed of 10,000 rpm and a maximum torque of 80 N.m. To measure of emissions, the MAHA MGT5 emissions meter was used. This device is able to measure the values of CO, CO2, NOX, O2 and UHC.Results and DiscussionThe results showed that increasing engine speed in all fuel combinations increased engine power, specific fuel consumption, carbon monoxide and unburned hydrocarbons and decreased torque. Also, increasing the amount of nano cellulose per engine speed increased the amount of power and torque, but reduced the specific fuel consumption, carbon monoxide and unburned hydrocarbons. The amount of NOX increased with increasing engine speed, but at each engine speed the addition of 25 ppm nanocellulose to pure diesel significantly increased the amount of NOX. But at low speed, increasing 75 ppm nanocellulose to pure diesel reduced the amount of NOX.ConclusionThe results of this study showed that the addition of nano cellulose as nanoparticles can improve the performance of diesel engines and also reduce the amount of emissions gases emitted from the engine. The results also showed that increasing 25ppm nanocellulose had a greater effect on engine performance. But to reduce the amount of emissions, 75 ppm nanocellulose was better.
B. Sabahi; H. Bahrami; M. J. Sheikhdavoodi; S. M. Safieddin Ardebili; E. Houshyar
Abstract
IntroductionToday, diesel engines provide the main power source for the world equipment e.g., common propulsion generators in industry and agriculture. These engines are widely used due to their high combustion efficiency, reliability, compatibility, and cost-effectiveness. However, diesel engines are ...
Read More
IntroductionToday, diesel engines provide the main power source for the world equipment e.g., common propulsion generators in industry and agriculture. These engines are widely used due to their high combustion efficiency, reliability, compatibility, and cost-effectiveness. However, diesel engines are one of the most critical consumers of fuel which in turn causes some environmental pollution. One of the convenient and low-cost ways to reduce the pollution of these engines is dual-fuel mode and the use of gaseous fuels as an alternative fuel. This study investigated the effect of blending CNG and LPG with neat diesel in dual-fuel mode. Besides, the variation in engine coolant temperature on engine performance characteristics was experimentally studied.Materials and MethodsThe experimental apparatus consisted of a stationary, four-stroke, naturally aspirated, water-cooled, single-cylinder compression ignition engine. To control the engine load, an electrical dynamometer was made using a 7.5 kW three-phase generator and coupled to the engine as a cradle. A load cell was used to determine the force applied to the generator. The engine speed was monitored continuously by a tachometer. Fuel consumption was measured by using a weight method. A thermostat with variable temperature was used to control the temperature of the engine coolant. To measure the mass flow of air entering the cylinder, an airbox with a sharp edge orifice was used. For this study, factorial experiments in the form of a randomized complete block design with three replications were utilized to analyze the data statistically. The studied parameters were three levels of fuel ratio (100% diesel, 20% diesel and 80%± 2% CNG, 20% diesel and 80%±2% LPG), 11 engine speeds (1500 to 1600 rpm with 10 rpm intervals), and three engine coolant temperatures (50, 60, and 70 °C). All experiments were conducted in the governor control mode.Results and DiscussionThe results showed that the torque, brake power and brake mean effective pressure (BMEP) in the diesel-CNG mode at all engine speeds and in the diesel-LPG mode at low engine speeds significantly increased compared to pure diesel. The increases in these parameters in the diesel-CNG mode were 18.67%, 19.56% and 19.85%, and in the diesel-LPG mode were 14.02%, 13.86% and 14.2%, compared to those related to the pure diesel, respectively. This increase could be due to the high calorific value of gas fuels and improvement of combustion inside the cylinder due to the formation of homogeneous charge. At low engine speeds, the reductions in the brake specific fuel consumption (BSFC) and brake specific energy consumption (BSEC) for coolant temperature 60 °C were 11.21% and 10.77%, compared to coolant temperature 50 °C, respectively. Also, the BSFC and BSEC for diesel-CNG dual-fuel mode decreased by 8.12% and 10.81%, respectively. These values for the diesel-LPG dual-fuel mode were 5.4% and 2.4%, respectively. The brake thermal efficiency (BTE) also showed a significant increase at high speeds and when using the dual-fuel operational mode. However, raising the coolant temperature due to reducing the heat losses of the engine increased the BTE. The increases in BTE for coolant temperatures 60 and 70 °C were 7.19% and 4.37%, compared to the coolant temperature of 50 °C, respectively. When using the engine in dual-fuel mode, the volumetric efficiency due to reducing the air ratio showed a significant reduction. These diesel-CNG and diesel-LPG dual-fuel mode values were 20.31% and 24%, respectively. Furthermore, raising the coolant temperature diminished the volumetric efficiency. The reduction in volumetric efficiency for the coolant temperatures of 60 °C and 70 °C were 6.84% and 19.91% compared to the coolant temperature of 50 °C, respectively.ConclusionThe following conclusions can be deduced based on this study:The use of gaseous fuels as the main fuel and with a small amount of diesel in compression ignition engines is possible and improves the engine's performance characteristics.In the diesel-CNG mode, torque, brake power and BMEP at all engine speeds and in the diesel-LPG mode at low engine speeds significantly increased compared to pure diesel because of improved combustion inside the cylinder.At low engine speeds, increasing the coolant temperature reduced the BSFC and BSEC. Also, in the dual-fuel mode compared to the engine with baseline diesel fuel, the BSFC and BSEC were significantly lower due to the higher calorific value of gaseous fuels and higher power generation.The BTE at high engine speeds and when the engine was in dual-fuel mode showed a significant increase. Also, increasing the coolant temperature due to reducing the heat losses of the engine increased the BTE.When using the engine in the dual-fuel mode, due to the volume of air replaced by the gas, the volumetric efficiency showed a significant reduction. Also, raising the coolant temperature diminished the volumetric efficiency.Overall, it can be stated that the use of a diesel-CNG dual-fuel mode with a coolant temperature of 60 °C at entire engine speeds has the best outputs on the performance and combustion characteristics of the engine.
A. Mirzaee; M. Soleymani; H. Bahrami; M. Norouzi Masir
Abstract
Introduction: Almost 18 percent of emitted greenhouse gasses in Iran come from livestock industries, especially from manure decomposition. With the anaerobic digestion of animal wastes, in addition to eliminating its disadvantages, biogas as a clean and renewable energy carrier is produced. In addition, ...
Read More
Introduction: Almost 18 percent of emitted greenhouse gasses in Iran come from livestock industries, especially from manure decomposition. With the anaerobic digestion of animal wastes, in addition to eliminating its disadvantages, biogas as a clean and renewable energy carrier is produced. In addition, the resulting sludge is a more healthy and nutritious fertilizer for use in agriculture. One of the challenges of the bio-gas industry is to increase gas production efficiency. Various approaches are proposed to enhance manure digestion efficiency and increase biogas production, which can be mentioned below: Changing operating parameters such as temperature, hydraulic retention time (HRT), and particle size of the substrate; adding some effective additives; returning the resulting sludge into the digestion process and using bio-filters. Therefore in this study, in order to increase biogas production from poultry manure, two methods (co-digestion with rumen contents, and chicken intestine and its contents, and returning the slurry into the reactor) were tested. The alkaline composition of chicken manure and its high content of ammonia makes it difficult to digest alone, and co-digestion with high-carbon organic matter improves its digestibility.Materials and Methods: Polyethylene bottles were used as batch reactor units. In order to the possibility of gas exit, as well as taking samples of the digester, two valves were placed on the bottle cap. All digesters were placed in a hot water bath and a 700 watts electric heater and a thermostat were used respectively to supply heat and to keep the temperature constant. A U-shaped tube, connected to the reactor output pipe was used to measure the amount of produced gas. The volume of water removed from the tube was an indicator of produced gas. The experiment was carried out in two stages. In the first stage 21 reactors were used according to the design of the experiment which was a completely randomized design with 7 treatments (adding rumen fluid in three levels (10, 20, and 30 percent of chicken manure (weight basis), respectively), adding chicken intestines and its content in three levels (10, 20, and 30 percent of chicken manure (weight basis), respectively), and control treatment), and three replicates of each treatment. During the whole experiment period, the pH and temperature were kept constant, respectively between 7.2-8.2 and 40-35 °C (mesophilic range). In the second stage of the experiment, after all the treatments reached the end of their hydraulic retention time, the resulting sludge was filtered and the liquid part was returned to the cycle. Three treatments were also provided here (supplying 50% of the water required by sludge liquid, supplying 100% of the water required by sludge liquid, and control treatment (no liquefied sludge).Results and Discussion: Based on the results, although the type of organic supplementation had a significant effect on the amount of biogas production, the quantity of them had not. Treatments of chicken manure + 20%, 30%, and 10% of chicken intestines resulted in the highest amount of biogas production, respectively. But these three treatments were not significantly different. Also, the co-digestion of chicken manure with chicken intestines was more effective than the co-digestion of chicken manure with rumen fluid. The return of sludge, resulted from anaerobic digestion of chicken manure, again into the cycle, in addition to enhancing the amount of produced gas, can reduce the waiting time to start gas production by at least six days (in the treatment of providing 100% of required water from returned sludge). This can lead to continuous gas production and availability of sufficient gas in commercial gas-producing units. The effect of treatments on the time of reaching the cumulative gas production index to 100 mm was significant (α= 5%) and treatment of S100 reduced this duration by approximately 17 days (65%) and S50, for approximately 16 days (74%). Conclusion: According to the results of this study, co-digestion of chicken manure with cow rumen fluid did not have a significant effect on the increase of biogas production, but co-digestion of chicken manure with chicken intestine and its contents (at least by 20% of chicken manure (weight basis)) can have a significant effect on the increase in the production of biogas and can increase the amount of gas at least twice. The highest amount of gas volume was about 305 Ml.gr-1 VSadded and came from the treatment of co-digestion of chicken manure with 20% (weight base) chicken intestine and its contents. The return of the resulting sludge of anaerobic digestion of chicken manure, back into the cycle, in addition to increasing the amount of gas, can minimize the time it takes to start to produce gas and help to produce gas continuously. Moreover, the water used for digestion will also be significantly reduced (at least 50%).
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. ...
Read More
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.
S. Abbasi; H. Bahrami; B. Ghobadian; M. Kiani Deh Kiani
Abstract
Introduction The extensive use of diesel engines in agricultural activities and transportation, led to the emergence of serious challenges in providing and evaluating alternative fuels from different sources in addition to the chemical properties close to diesel fuel, including properties such as renewable, ...
Read More
Introduction The extensive use of diesel engines in agricultural activities and transportation, led to the emergence of serious challenges in providing and evaluating alternative fuels from different sources in addition to the chemical properties close to diesel fuel, including properties such as renewable, inexpensive and have fewer emissions. Biodiesel is one of the alternative fuels. Many studies have been carried out on the use of biodiesel in pure form or blended with diesel fuel about combustion, performance and emission parameters of engines. One of the parameters that have been less discussed is energy balance. In providing alternative fuels, biodiesel from waste cooking oil due to its low cost compared with biodiesel from plant oils, is the promising option. The properties of biodiesel and diesel fuels, in general, show many similarities, and therefore, biodiesel is rated as a realistic fuel as an alternative to diesel. The conversion of waste cooking oil into methyl esters through the transesterification process approximately reduces the molecular weight to one-third, reduces the viscosity by about one-seventh, reduces the flash point slightly and increases the volatility marginally, and reduces pour point considerably (Demirbas, 2009). In this study, effect of different percentages of biodiesel from waste cooking oil were investigated. Energy distribution study identify the energy losses ways in order to find the reduction solutions of them. Materials and Methods Renewable fuel used in this study consists of biodiesel produced from waste cooking oil by transesterification process (Table 1). Five diesel-biodiesel fuel blends with values of 0, 12, 22, 32 and 42 percent of biodiesel that are signs for B0, B12, B22, B32 and B42, respectively. The test engine was a diesel engine, single-cylinder, four-stroke, compression ignition and aircooled, series 3LD510 in the laboratory of renewable energies of agricultural faculty, Tarbiat Modarres University. The engine is connected to a dynamometer and after reaching steady state conditions data were obtained (Fig. 1). In thermal balance study, combustion process merely as a process intended to free up energy fuel and the first law of thermodynamics is used (Koochak et al., 2000). The energy contained in fuel converted to useful and losses energies by combustion. Useful energy measured by dynamometer as brake power and losses energy including exhaust emission, cooling system losses and uncontrollable energy losses. Variance analysis of all engine energy balance done by split plot design based on a completely randomized design and the means were compared with each other using Duncan test at 5% probability. Results and Discussion Results showed that, in general, biodiesel use has a significant impact on all components of energy balance. Of total energy from fuel combustion, the share of energy losses to form of exhaust emissions the maximum value in all percentages allocated to biodiesel (Average 51.715 percent) with the maximum and minimum amount of B42 (55.982 percent) and B0 (46.481 percent), respectively (Fig. 2). Also, fuel blend with 12% biodiesel was diagnosed the best blend because of having the most useful power, having the lowest energy losses through the exhaust and cooling system. Conclusion Using biodiesel produced from waste cooking oil by transesterification process, lead to increase the useful power. The addition of biodiesel to pure diesel cause to significant reduction in the waste energy due to friction. In higher amounts of biodiesel increase energy losses especially through the exhaust and cooling system due to higher viscosity.
B. Sabahi; M. J. Sheikhdavoodi; H. Bahrami; D. Baveli Bahmaei
Abstract
Introduction: Today, all kinds of vehicle engines work with fossil fuels. The limited fossil fuel resources and the negative effects of their consumption on the environment have led researchers to focus on clean, renewable and sustainable energy systems. In all of the fuels being considered as an alternativefor ...
Read More
Introduction: Today, all kinds of vehicle engines work with fossil fuels. The limited fossil fuel resources and the negative effects of their consumption on the environment have led researchers to focus on clean, renewable and sustainable energy systems. In all of the fuels being considered as an alternativefor gasoline, methanol is one of the more promising ones and it has experienced major research and development. Methanol can be obtained from many sources, both fossil and renewable; these include coal, natural gas, food industry and municipal waste, wood and agricultural waste. In this study, the effect of using methanol–unleaded gasoline blends on engine performance characteristics has been experimentally investigated. The main objective of the study was to determine engine performance parameters using unleaded gasoline and methanol-unleaded gasoline blends at various engine speeds and loads, and finally achieving an optimal blend of unleaded gasoline and methanol.
Materials and Methods: The experimental apparatus consists of an engine test bed with a hydraulic dynamometer which is coupled with a four cylinder, four-stroke, spark ignition engine that is equipped with the carbureted fuel system. The engine has a cylinder bore of 81.5 mm, a stroke of 82.5 mm, and a compression ratio of 7.5:1 with maximum power output of 41.8 kW. The engine speed was monitored continuously by a tachometer, and the engine torque was measured with a hydraulic dynamometer. Fuel consumption was measured by using a calibrated burette (50cc) and a stopwatch with an accuracy of 0.01s. In all tests, the cooling water temperature was kept at 82±3˚C. The test room temperature was kept at 29±3˚C during performing the tests. The experiments were performed with three replications. The factors in the experiments were four methanol- unleaded gasoline blends (M0, M10, M20 and M30) and six engine speeds (2000, 2500. 3000, 3500, 4000 and 4500 rpm). Methanol with a purity of 99.9% was used in the blends. All experiments were performed at 50% open throttle. Engine performance characteristics for fuel blends were compared with unleaded gasoline.
Results and Discussion: The experimental results showed that adding methanol to unleaded gasoline increased brake torque and brake power in the M10 and decreased in the M30 compared to merely usingpure gasoline. Engine behavior when using M20 blend was similar to that of using pure gasoline (M0). The brake power and torque at engine speeds 2500, 3000, 3500 and 4000 rpm for M10 were increased by 5.42%, 7.76%, 14.89% and 16.78% compared to when these parameter relate to pure gasoline (M0), respectively, whereas the brake power and brake torque for M30 blend at engine speeds 2000, 2500, 3000, 3500, 4000 and 4500 rpm compared to when using pure gasoline was decreased by 6.91%, 8.1%, 6.23%, 5.29%, 4.59% and 14.27%, respectively.
The experimental results showed that brake specific fuel consumption for M30 blend was increased at all engine speeds. The increase in specific fuel consumption values for this blend from 2000 - 4500 rpm were 17.78%, 16.38%, 13.06%, 10.99%, 14% and 19.11%, respectively. Also, the specific fuel consumption for the M20 was similar to the specific fuel consumption of pure gasoline. Comparing the brake specific fuel consumption of M10 to M0 fuel at 2500, 3000, 3500, 4000 and 4500 rpm this parameter was decreased by 1.9%, 6.03%, 8.91%, 13.85% and 5.55%, respectively.
As the methanol content in the fuel blends increases, brake thermal efficiency also increases at all engine speeds and in all used fuels blends. The thermal efficiency at 2000, 2500, 3000, 3500, 4000 and 4500 rpm using M10 was increased by 3.73%, 8.12%, 12.43%, 15.57%, 22.34% and 12.01%, respectively in comparison to pure gasoline. These values for M20 were 4.14%, 7.82%, 10.12%, 13.37%, 18.94% and 13%, and for M30 were 2.69%, 3.89%, 6.35%, 8.01%, 5.12% and 0.78%.
Conclusions: From the results of the study, the following conclusions can be deduced:
1- Using methanol as a fuel additive to unleaded gasoline causes an improvement in engine performance.
2- The largest increment in engine torque and brake power compared with M0 showed about 16.78% with M10 at 4000 rpm.
3- Minimum brake specific fuel consumption was obtained at 4000rpm with M10 fuel.
4- Thermal efficiency increased compared to the pure gasoline usage at all engine speeds and in all used fuel blends. The largest increment in brake thermal efficiency compared with M0 showed 22.34% with M20 at 4000 rpm.
5- The 10 vol. % methanol in fuel blend gave the best results for all measured parameters at all engine speeds.
N. Kazemi; M. Almassi; H. Bahrami; M. J. Sheikhdavoodi; M. Mesgarbashi
Abstract
Overall energy efficiency (OEE) is an important indicator of energy consumption in tillage operations. Tillage energy was studied objectivity to accurately measure the OEE of MF399-4WD tractor. The tractor was equipped with different types of sensors to measure and calibrate the required data including: ...
Read More
Overall energy efficiency (OEE) is an important indicator of energy consumption in tillage operations. Tillage energy was studied objectivity to accurately measure the OEE of MF399-4WD tractor. The tractor was equipped with different types of sensors to measure and calibrate the required data including: fuel consumption, actual forward speed, wheel speed and slippage, engine speed, draft and drawbar power. The data were recorded with frequency of 1000 Hz and transmitted by employing a suitable wireless technology in the range of up to1.5 km to the user's personal computer and is stored in Excel format. The hardware and the software program, which was written in C# language, simultaneously monitor the changes in functional parameters and the monitoring can be done even from far away and via the Internet. The split factorial experiment with three factors including ballast, selected gear ratio and two wheel drive configurations (two and four wheel drive) was employed to perform analysis of variance (ANOVA), POST ANOVA AND PATH ANALYSIS. The results show that the performance of remote monitoring devices installation was very accurate and high-quality. Furthermore, statistical analysis showed that three parameters including slippage, fuel consumption and tractor Power Equivalent (PEQ) were the most effective parameters on overall energy efficiency of tractors – tillage. The variance analysis showed that the effect of gear ratio and drive configuration on the OEE were also significant at the one percent level. However, ballasting had no significant effect on the OEE.
Gh. R. Rabet; H. Bahrami; M. J. Sheikhdavoodi
Abstract
Delay in irrigated wheat primary tillage operations causes yield reduction and hidden timeliness cost in Fars province. Mechanization of primary tillage operations for irrigated wheat in Fars province was simulated using System Dynamics approach. A part of the model structure was related to the agricultural ...
Read More
Delay in irrigated wheat primary tillage operations causes yield reduction and hidden timeliness cost in Fars province. Mechanization of primary tillage operations for irrigated wheat in Fars province was simulated using System Dynamics approach. A part of the model structure was related to the agricultural operations timeliness costs. For the mentioned simulation, causal relations between system components were known and the model was run based on time step of 0.125 of one year. The simulation results showed that the operations timeliness cost remained constant (approximately one million rials per hectare) from 2001 to 2004 in the province. The timeliness cost increased from 2004 to 2007 due to the non-uniform distribution of atmospheric precipitation and reached to 1211724 rials per hectare in 2007. The upward trend of this cost continued for the period of 2007 to 2010 because of using depreciated moldboard plows. The model predicted the amount of 2090511 rials per hectare for the timeliness cost in 2018. Furthermore, it was found that reduction in the timeliness cost could be reached either by increasing the plowing speed by %30 in the permissible domain or increading the daily working hours by 4 hours.
