عباس زارع نژاد اشکذری

In this paper, a numerical study is performed in order to investigate the effect of the numerical diffusion on simulation of separated two-phase flow of gas-liquid. The governing equations solved by shock capturing method which can provide predicting the interface without the flow field solving. In this work, in order to calculate the numerical flux term, first-order centred scheme (Force scheme) was applied cause of its accuracy and appropriate validation. Analysis approves that the obtained stability range of this research is consistent with the classic kelvin-Helmholtz instability equation only for the long wavelength with small amplitude. Results reveal that when the wavelengths are reduced, the specified range is not consistent and wavelength affects on instability range and it is overpredicted. An algorithm for water faucet problem was developed in Fortran language. Short wavelength perturbations induce unbounded growth rates and make it impossible to achieve converging solutions. The approach taken in this article has been to adding numerical diffusion as a CFD technique is used to remedy this deficiency.

One of the novel strategies to improve the performance and emissions of diesel engines is the use of alternative fuels as well as suitable additives such as nanoparticles to diesel fuel. Nanofuels play an important role in the optimization of combustion processes, fuel consumption, and emissions. In this paper, the effect of adding different nanoparticles (cerium, aluminum, and copper oxide nanoparticles) at a concentration of 100 particles per million (ppm) to diesel fuel on the combustion process and emissions of diesel engines has been investigated by using FIRE computational fluid dynamics code. For validation, the in-cylinder pressure variations, the experimental peak pressure, and the angle of occurrence are compared with the numerical results. In addition, the experimental data of NOx, soot, power as well as brake specific fuel consumption were evaluated with numerical values. The results show that nanoparticles increase the amount of heat transfer to the fuel and decrease the ignition delay. Also, better mixing of fuel and air in cerium oxide nanoparticles compared to other nanoparticles improved the fuel ignition mechanism, which leads to more complete combustion and a 14.5% increase in power and also a 6% and 34% reduction in fuel consumption and soot compared to diesel fuel respectively. The only downside is the 31% increase in NOx, which can be reduced by catalytic converters.

In this study, the combination of biodiesel-diesel, ethanol-diesel, and ethanol-biodiesel-diesel emulsion blends on performance and emissions of a direct injection diesel engine was investigated. High purity ethanol in three levels of 2, 4 and, 6 by volume percent and biodiesel prepared from waste cooking oil in four levels of 5, 10, 15 and 20 by volume percent were mixed with pure diesel. Thus, 11 fuel samples were prepared which were shown with BxEy, that x and y represent the volume percent of biodiesel and ethanol in the prepared mixtures, respectively. The experiments were performed at full load with the change in engine speed from 800 to 1800 rpm, with the interval 200 rpm. The results showed that pure diesel has the lowest specific fuel consumption at all of the speeds compared to other prepared mixtures. Using of B15E6 blend, reduced the emission of carbon monoxide by 40% compared to pure diesel. This mixture also, reduced the emissions of carbon dioxide and hydrocarbon by 27 and 55% compared to pure diesel, respectively.

The location of Chabahar coastal areas on the development circuit requires knowledge of the environmental characteristics of this area for comprehensive planning. The genealogy of flood risk is very important for executives in planning and preparing the coast. One of the main drivers of floods on rainforest shores is that by identifying its behavior, floods can be managed Precipitation is one of the most variability climatic elements that it has complex behavior, spatially in arid and semi- arid arias. Therefore investigation of precipitation characteristics in a region has significant effects on the environmental planning. The recognition of precipitation characteristics of a region, its monthly and seasonal distributions, intensity, duration and amounts can result to determine the different types of precipitations patterns in a region. In this paper by using the daily precipitation data of Chabehar synoptic station (during 1985-2013) 280 rainy days from total days (4817 days) was obtainedFinally by applying a cluster analysis on the 183 rainy clusters in a 183*4 matrix, five patterns of precipitation types was recognized and the characteristics of these types were analyzed.

In this study, the simultaneous effect of ethanol-biodiesel-diesel emulsion with TiO2 nanoparticles in different EGRs on emission characteristics and performance of a direct injection diesel engine was investigated. TiO2 nanoparticles at three levels of 0, 40 and 60 ppm were added to biodiesel produced from waste cooking oil at levels of 0, 10 and 20% and ethanol at levels of 0, 4 and 6% and an EGR system was used at rates of 0, 20 and 30 %. A total of 31 mixtures from biodiesel/diesel, ethanol/diesel and ethanol/biodiesel/diesel emulsions with TiO2 nanoparticles and different percentages of EGR were tested at full load at speeds of 1000, 1400 and 1800 rpm. Briefly named with BxEy + EGRw + TiO2z, that x, y, w, and z represent the biodiesel volume percentage, ethanol, EGR, and TiO2 percentage used in the mixture, respectively. The results showed that the use of B10E4 + EGR20 + TiO260 reduced NOx, CO and HC compared to pure diesel by 5.8, 20.3 and 40 percent, respectively. Also, the output power of B10E0 + TiO260 was improved by 11.2 percent compared to pure diesel. In addition, by using B10E4 + EGR30, fuel consumption increased by 26.7 percent compared to pure diesel. .

In the present study, using artificial neural network, modeling and prediction of NOx, soot and fuel consumption in a direct injection diesel engine is done by applying control variables of engine speed, inlet air temperature and fuel mass injected into the combustion chamber. For this purpose, the empirical experiments were carried out to prepare the necessary modeling and correlation between input and output parameters by neural network. The neural network with the Levenberg-Marquardt training algorithm is designed to train the existing relationship between the above parameters, in which the output variables are modeled completely independently. In other words, for any output such as NOx, the number of hidden layer neurons as well as the lattice control parameters would be quite different from the same parameters for soot or fuel consumption. The results show that the designed neural network reaches accuracy 0.97 for 36 neurons in the hidden layer at 3733th epoch to test the data in NOx modeling. Also, modeling of soot with more neurons and accuracy 0.96 is performed in the 2081th epoch. On the other hand, the test accuracy for modeling fuel consumption for 19 neurons in the hidden layer at 3698th epoch was 0.94 which is due to the uneven distribution of the experimental data over a wide range of modeling ranges. The neural network can also be used as an effective method in direct injection diesel engines intelligent control systems to reduce pollutants and fuel consumption due to its fast convergence and hence short response time.

In this paper, optimization of fuel consumption and NOx and soot emissions in a direct diesel engine is done using neural network and ant algorithm by applying the parameters of inlet air temperature, rate of fuel injection mass and engine speed. Complexity of the behavior of internal combustion engines was first determined by using experimental experiments to establish the relationship between the input and output parameters by the neural network. The artificial neural network with the Levenberg-Marguerite training algorithm is used to model and train the existing relationship between the above parameters and is used as a subroutine for predicting optimal values in the ant colony algorithm. Results show the engine optimized parameters are drawn to lower temperatures due to lower NOx and soot emissions by lowering the inlet air temperature. Also the results of modeling and prediction performed by neural network show 98% and 94% concordance with the experimental data in emissions and fuel consumption, respectively. On the other hand, improving the quality of NOx values, because of its high weight in the objective function, affects the overall optimization result and the behavior of the objective function in convergence is very similar to NOx behavior. Also, combination of neural network-Ant algorithm approach due to its fast convergence and consequently short response time can be used as an effective method of diesel engine intelligent control systems to reduce emissions and fuel consumption.

The energy management of ships to improve the efficiency of ships and reduce greenhouse gas emissions is among the most important issues that have been considered as a milestone in designing and constructing of vessels in recent years. The study of energy trends and attention to technological changes and the importance of more stringent environmental standards in recent years have led to a major challenge in relation to air pollution, energy management, and exposure to end-of-life sources of fossil fuels. In recent years, focus on current fuels and technologies in vehicles has led to a major challenge regarding air pollution, greenhouse gas emissions, energy security, and also exposure to exhausting sources of fossil fuels. Now days, Hybrid propulsion systems are one of the solutions that are being followed in many countries to solve this problem. In this paper, after introducing the hybrid system; conceptual design and determination of a suitable hybrid system for vessels have been investigated. Then the calculations and relations dominating the hybrid parallel system of vessel are presented. The modeling is also done using the ADVISOR software run in the Simulink platform of the MATLAB for both conventional and hybrid systems. The results show that parallel hybrid vessel has improved by 7% in total efficiency and 7.1% for consumption. In addition, HC and CO emissions have been decreased by 0.44% and 0.39%, respectively.

The beaches anywhere in the world are important sources of development and capability. The beaches of the Oman Sea are one of the most diverse coastal areas in Iran. Access to the Free Sea and the features of the coastal geographic environment are the easiest potentials that are prepared for planning and development. His research has been conducted with a view to assessing the potential of the natural environment of the coastal coast of Oman for coastal tourism planning. The method of fieldwork and analysis is based on meteorological and geomorphological data. For this purpose, using the 10 biologic indexes, we first evaluated the desirable times and appropriate chapters of tourism. Then, every season, it was planned to plan various types of tourism, such as geo-tourism and sports tourism. The results showed that for at least four months from the year, the ideal climatic conditions for the use of potentials on the banks of the Oman, including swimming, diving, kite riding, sailing at sea, and 5 months of using the beach, such as geo-tourism visits such as miniaturized mountains, are suitable. Coastal tourism can be the most important tourist activity in the region

The aim of this paper is studying performance parameters and pollutant emissions on D-87 diesel engine and simulation of multiple injections process and choosing the optimum pattern of its for simultaneous reduction of soot and NOx. The simulations are divided into two parts. In first part the effect of different ratio of fuel mass in each of the injection pulse is studied and in the second part the effect of pause period length between injection pulses on engine performance and emissions will be studied. The results show that, if the majority of fuel injected in the second pulse with the large dwell time between them, increased in-cylinder pressure and thus the engine brake power losses and eventually brake specific fuel consumption increases. Therefore, it is optimal that the majority of fuel injected at the first pulse. In the multiple fuel injection process, despite decreasing maximum combustion temperature because of increasing the fuel injection period, the soot pollutant is in safe range; therefore the basis for selecting optimal point is based on trade off between NOx and soot pollutants diagram, in addition will be considered based on the behavior curves compromise between performance and NOx.

The electrical transmission of variable speed which makes it possible to change the output speed range ( minimum- maximum ) certain fixed period or be modified to be able to achieve their . This type of Electro who is also known by the names of variator due to the adjustable output is used to change round . In this paper , functional and design issues that will be assessed a review electrical transmission of variable speed. Relations also designed to improve the performance and efficiency from the perspective offered. Power generation system in most variators engine designed , via steel shot , whereas in the new system was designed , has oil pressure is used to generate power that the power production in constant speeds, provide the required torque.In other words at this system, according to its hydraulic and use of oil instead of gas flows through the issue of excessive wear and tear gas in the cyclic changes , which resulted in the failure to provide the torque to was gone . The results show that speed control in both directions of rotation output, high starting torque and high efficiency is 90%

In this paper, by using of the experimental results and numerical simulation with AVL FIRE software and using of artificial neural network, NOx and soot emissions and fuel consumption of a diesel engine was modeled, that input variables of modeling are, air intake temperature, mass fuel injected, fuel injection timing, injection duration, engine speed and IVC timing. Then by using of ant colony optimization algorithm and based on the obtained models for outputs, values of NOx and soot emissions and fuel consumption has been optimized. For this purpose, by using of experimental data and numerical simulation, the arranging for modeling of performance and output was provided by the ANN.
Artificial neural network with Levenberg-Marquardt training algorithm and using of the experimental and numerical data was applied for modeling and training of relationship between these parameters and this method was applied as a predictive method of ant colony algorithm to find the optimal values and used as a subroutine. Then the design variables that optimized the objective functions were obtained. The results show a fast convergence and good response times and optimizing the control parameters of the ant colony algorithm compared with other metaheuristic algorithms. Due to the rapid and significant convergence of output parameters, combination of artificial neural network (ANN) and ant colony optimization (ACO) can be used as an effective method in intelligent control systems for diesel engines to reduce emissions and fuel consumption.

Parameters of fuel injection system, play an important role in the combustion process and, consequently, fuel consumption and emissions output. Therefore, in this study, the effects of various parameters such as Injection timing, injection during, the geometry of the injector, (the injector orifice diameter), Spray cone angle and fuel injection pressure on the performance and emissions of a DI marine diesel engine have been investigated. To evaluate the results of simulation, the maximum In-cylinder pressure has been compared with experimental data. In addition to this parameter, the experimental values of NOx, soot and brake specific fuel consumption (BSFC) have been compared with simulated results. The results of simulation show that the good agreement with experimental data.

In present work، the spray characterization and mixture formation in MAN B&W L16/24 DI diesel engines are studied by using FIRE CFD Code. In addition، the effect of WAVE، KH-RT and TAB different spray breakup models in prediction of performance and pollutants of diesel engines has been investigated. Finally، the accuracy of each model in comparison with experimental data was reported. Results showed that the WAVE model are the better ability to predict the decomposition of the fuel spray’s droplets and predicts the droplet size produced by penetration and decomposition، correctly. Therefore، it can be used for simulation of spray’s wall impingement at engine’s operating conditions.