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•The orthogonal principal component-optimization method for performance enhancement of the diesel engine is proposed.•An improved chemical kinetics mechanism of 134 species and 475 ...reactions is developed.•Numerical model of diesel engine is simulated and are compared with the experimental results.•Improvement suggestions for performance enhancement of the diesel engine are proposed.
In this work, the biodiesel-diesel blending fuels (B20, B30 and B40) and pure diesel fuel (B0) were employed to investigate the effects of intake pressure and EGR ratio on the performance and emission characteristics of diesel engine. The 3D model is developed by the AVL-Fire coupled Chemkin code. In addition, an improved chemical kinetics mechanism of 134 species and 475 reactions is employed to simulate the fuel combustion process. The results show that the improved model improves the calculation accuracy and the high intake pressure and oxygen content in biodiesel are beneficial for the improvements of performance and emission characteristics. However, the NO emission increases. On the contrary, the EGR effectively reduces NOx emission. Finally, the performance and emission characteristics of diesel engine are optimized by the orthogonal principal component-optimization method. Moreover, the NOx mass fraction is reduced by 78.6 % and the engine power is decreased by 5.60%. Therefore, the reasonable parameter is beneficial for alleviating the conflict between performance and emission characteristics of diesel engine.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UL, UM, UPCLJ, UPUK, ZRSKP
ABSTRACT
The kinetic modeling of the pyrolysis and combustion of liquid transportation fuels is a very complex task for two different reasons: the challenging characterization of the complex mixture ...of several hydrocarbon isomers and the complexity of the oxidation mechanisms of large hydrocarbon and oxygenated molecules. While surrogate mixtures of reference components allow to tackle the first difficulty, the complex behavior of the oxidation mechanisms is mostly overcome by reducing the total number of involved species by adopting a lumping approach. After a first investigation of the different liquid fuels (gasoline, kerosene, and diesel fuels), a short discussion on the lumping techniques allows to highlight the advantages of this approach. The lumped POLIMI pyrolysis and oxidation mechanism of hydrocarbon and oxygenated fuels is then used for generating several skeletal mechanisms for typical surrogate mixtures, moving from pure n‐heptane up to heavy diesel fuels. These skeletal models are simply reduced with a reaction flux analysis, and they involve between 100 and 200 species. While these sizes already allow detailed computational fluid dynamics (CFD) calculations in internal combustion engines, further reduction phases are necessary when the interest is toward more complex CFD computations. To maintain the standard structure of the skeletal mechanisms, successive reduction phases are not considered. Moreover, new regulations pushed toward a greater use of renewable fuels. For these reasons, the skeletal models are also extended to biogasolines including methanol, ethanol, and n‐butanol. Similarly, skeletal models of diesel and biodiesel fuels, including methyl esters, are also provided. Several comparisons with experimental data and complete validations in the operating range of internal combustion engines are also reported. The whole set of comparisons with experimental data obtained in a wide range of conditions not only validate the reduced models of specific transportation fuels but also the complete kinetic scheme POLIMI_1404.
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FZAB, GIS, IJS, IZUM, KILJ, NLZOH, NUK, OILJ, PILJ, PNG, SAZU, SBCE, SBMB, UL, UM, UPUK
•Density-biodiesel content variation is well correlated by linear model.•Exponential equation is the best model for density-temperature variation.•Rational model is the most proper one to predict ...viscosities of fuel blends.•Power model is the best one to characterize viscosity vs. temperature variation.•Two-term power model better correlates density-viscosity variation.
One of the attempts to limit the use of fossil fuels in automobiles is to replace them partially or totally with clean and renewable fuels. Among renewable fuels, biodiesel has emerged as an important alternative to petroleum diesel fuel. Therefore, in this study, first, biodiesel was produced from hazelnut oil, which is agricultural product at Black Sea region of Turkey, by means of transesterification reaction. The produced biodiesel was blended with Ultra Force Euro diesel fuel at the volume ratios of 5, 10, 15, 20, 50 and 75% which are called as B5, B10, B15, B20, B50 and B75 as usual, respectively. Second, the densities and kinematic viscosities of each blends were measured at average climate conditions as 10, 20, 30 and 40°C by following international ISO 4787 and DIN 53015 standards. Finally, new models were derived through the least squares regression method for density-temperature, kinematic viscosity-biodiesel fraction, kinematic viscosity-temperature and kinematic viscosity-density relationships, and compared with well-known models previously published in literature to determine the well-matched models.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UL, UM, UPCLJ, UPUK, ZRSKP
•Sunflower and soybean oil mixture was utilized for the production of biodiesel.•Reaction parameters have optimized through the experimental investigation.•Biodiesel yield affected by the percentage ...of catalyst, methanol: oil ratio and reaction temperature.•Higher BSFC and lower BTE obtained for biodiesel and its blends.•Biodiesel and its blends show minimum CO, HC, Smoke, and CO2 emissions.
The influence of diesel/biodiesel blends on engine combustion, performance, and exhaust gas emissions have carried out experimentally at different engine loads and constant speed of 1400 rpm. Volumetric percentage of diesel/biodiesel blends: D70B30 (70% diesel−30% biodiesel), D50B50 (50% diesel−50% biodiesel) and D30B70 (30% diesel−70% biodiesel) were prepared to power a single cylinder diesel engine. The engine results as compared to diesel fuel, show a reduction in the rate of change of CO by 33.8% for D50B50. The slight decrease in maximum cylinder pressure for higher percentage of biodiesel blends due to low calorific value of biodiesel and lower ignition delay. The reduction in HRR for biodiesel blends as compared to diesel fuel. HRR was about 31.7, 52.4 and 63.5 (J/deg) for 10%, 30% and 60% of maximum engine power. The highest reduction in HC emissions concerning diesel fuel was about 4.18% for D30B70. NOx emissions of biodiesel blends were higher than diesel. Exhaust oxygen (EO) emissions for D30B70 was about 0.98% higher than diesel. Exhaust gas temperature (EGT) has observed for all biodiesel blends. Brake specific fuel consumption (BSFC) is increased until it reaches 11.43% for D30B70. A consequent reduction in brake thermal efficiency (BTE) and brake specific energy consumption (BSEC) is observed for all biodiesel blends.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UL, UM, UPCLJ, UPUK, ZRSKP
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•DEE was examined as an oxygenated fuel additive in various ratios in a CI engine.•Comparing performance, emissions and combustion attributes among all blends.•DEE in the ...biodiesel-diesel blend adversely affected the engine performance.•DEE in the ternary blends led to improve the exhaust emission characteristics.•Ternary blends exhibited almost similar combustion behaviors compared to the diesel.
The objective of the present study refers to the examination of a diesel engine characteristics for various fractions of diethyl ether (DEE) as an oxygenated fuel additive in cottonseed oil biodiesel-diesel fuel blends. Firstly, several tests performed for diesel and B20 blend. Then, 2.5%, 5%, 7.5%, and 10% of DEE by volume was mixed with biodiesel-diesel fuel to prepare the ternary blends. All the fuel samples were run on in a single-cylinder, four-stroke, and direct-injection diesel engine at five different engine loads and fixed engine speed conditions. The experimental results showed that BTE was decreased by 17.39% while increasing in BSFC by 29.15% for 10% addition of DEE in the blend as compared to diesel fuel. Besides, the engine fueled with ternary blends revealed mitigation up to 12.89%, 4.12%, and 8.84% in the HC, smoke, and NOX emissions, on an average, respectively than those of diesel fuel. CO emission exhibited increasing trends with the diesel fuel at higher proportions of DEE despite up to 40.09% dropdown remarked for lower concentration at the maximum load. By the way, the CO2 also dropped under high loads. However, the combustion behaviors vaguely deteriorated when the CI engine run on all ternary blends. As a consequence, DEE can be evaluated as an auspicious aspect to remove the main issues with the usage of cottonseed oil biodiesel. It can be further highlighted that the addition of DEE up to 10% (by vol.) could be considered as a promising techniquefor the utilization of biodiesel/diesel blend efficiently in the CI engines without any major modifications.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UILJ, UL, UM, UPUK, ZAGLJ, ZRSKP
The most recent developments in the modelling of heating and evaporation of fuel droplets, the results of which were published in 2014–2017, are reviewed, and the most important unsolved problems are ...identified. Basic principles of power law and polynomial approximations and the heat balance method for modelling the heating of non-evaporating droplets are discussed. Several approaches to modelling the heating of evaporating droplets, predicting different heating and evaporation characteristics, are compared. New results in modelling heating and evaporation of spheroidal droplets are identified. Basic principles of the Discrete Component Model and its application to biodiesel fuel droplets are summarised. Main ideas of the Multi-dimensional Quasi-discrete Model and its applications to Diesel and gasoline fuel droplets are discussed. New developments in gas phase evaporation models for multi-component fuel droplets are presented. A self-consistent kinetic model for droplet heating and evaporation is described. New approaches to the estimation of the evaporation coefficient, including those taking into account quantum-chemical effects, are summarised. Among unsolved problems, the effects of non-spherical droplets, limitations of the ETC/ED model, effects of the interaction between droplets, effects of the moving interface due to evaporation, modelling of complex multi-component droplets, modelling of droplet heating and evaporation in near- and super-critical conditions, development of advanced kinetic and molecular dynamics models and effective approximation of the kinetic effects are discussed.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UL, UM, UPCLJ, UPUK, ZRSKP
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•Supercritical methyl acetate (SCMA), glycerin-free process for converting total algal lipids into fatty acid methyl esters (FAMEs) and triacetin (TA).•Triacetin (additive) is ...miscible with FAME and can be readily used as biodiesel fuel (BDF).•Micro-elemental analysis (CHNOS) of total algal lipid and algal biodiesel fuel samples.•Comparison of fuel properties of algal biodiesel fuel with regular diesel and ASTM biodiesel standards.•Thermogravimetric analysis (TGA-DTA) of algal biodiesel fuel under nitrogen and oxygen environments.
Supercritical methyl acetate (SCMA) technology was demonstrated for converting total lipids from Nannochloropsis salina into fatty acid methyl esters (FAMEs) and triacetin (TA). In this non-catalytic process, triacetin is produced instead of glycerin as a side-product during transesterification which is miscible with FAME and can be readily used as biodiesel fuel (BDF). Supercritical carbon-dioxide (SC-CO2), clean and green technology was employed to extract total lipids from algal biomass. The process parameters such as lipid to methyl acetate molar ratio, reaction temperature and reaction time were studied to evaluate their effects on the FAME yield and algal biodiesel fuel yield. Algal lipid characterization and algal biodiesel fuel analysis were carried out using analytical instruments such as FTIR and GC–MS. Thermogravimetric analysis under nitrogen and oxygen environments was performed to examine the thermal and oxidative stability of the algal biodiesel fuel. A micro-elemental analysis (CHNOS) of total algal lipid and biodiesel fuel was performed according to ASTM methods. The fuel properties of algal biodiesel fuel produced were compared with those of the regular diesel and biodiesel American Society for Testing and Materials (ASTM) standards.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UL, UM, UPCLJ, UPUK, ZRSKP
In the present study, the performance and emission parameters of a single cylinder diesel engine powered by biodiesel-diesel fuel blends were predicted by Artificial Neural Network (ANN) and ...optimized by Response Surface Methodology (RSM). The data to be used for ANN and RSM applications were obtained by using biodiesel/diesel fuel blends at different engine loads and various injection pressures. ANN model has been developed to predict the outputs such as brake thermal efficiency (BTE), brake specific fuel consumption (BSFC), exhaust gas temperature (EGT), nitrogen oxides (NOx), hydrocarbons (HC), carbon monoxide (CO) and smoke regarding engine load, biodiesel ratio and injection pressure. A feed-forward multi-layer perceptron network is used to show the correlation among the input factors and the output factors. The RSM is applied to find the optimum engine operating parameters with the purpose of simultaneous reduction of emissions, EGT, BSFC and increase BTE. The obtained results reveal that the ANN can correctly model the exhaust emission and performance parameters with the regression coefficients (R2) between 0.8663 and 0.9858. It is seen that the maximum mean relative error (MRE) is less than 10%, compared with the experimental results. The RSM study demonstrated that, biodiesel ratio of 32% with 816-W engine load and 470 bar injection pressure are the optimum engine operating parameters. It is found that the ANN with RSM support is a good tool for predict and optimize of diesel engine parameters powered with diesel/biodiesel mixtures.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UL, UM, UPCLJ, UPUK, ZRSKP
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•Optimization of biodiesel production through Design of Experiment (DoE) and Grey Wolf Optimizer (GWO) showcased for the first attempt.•The superiority of GWO over DoE ...established.•The properties of waste sunflower oil methyl ester (WSOME) compiled with biodiesel standards.•Correlations on the measurement of densities of WSOME-kerosene blends established for aviation industry.
The failure of classical techniques and algorithms have triggered researchers to search for stochastic tools capably of exploring the search space with constant convergence speed. Grey wolf optimizer (GWO) is a moderately novel stochastic algorithm with only a few parameters to regulate that can be easily employed for global optimization. For the first time, this study explored GWO to model biodiesel yield. It is worthy to note that, kerosene (KS) popularly known as paraffin oil has gained global attention in the aviation and biodiesel industries to improve cold flow properties and can be mixed with diesel in different proportions. Therefore, in this study, (1) Response Surface Methodology (RSM) and GWO were explored to model the waste sunflower oil methyl ester (WSOME)/biodiesel (BD) production from waste sunflower oil (WSO) and (2) Least square regression method was accosted to correlate the density of (0%KS + 100%BD), (5PKS + 95%BD), (20%KS + 80% BD), (50%KS + 50%BD) and (100%KS + BD) blends. The yield of WSOME (96.70%) was optimum at the methanol/oil molar ratio of 5.99/1, catalyst amount of 1.1 wt.% and reaction time of 77.6 min. The GWO model displayed a higher coefficient of determination, and a lower value of root mean squared errors compared to the RSM model. GWO predicted values, as compared to RSM, predicted yield indicates its reliability and usefulness for prediction without trial and error of conventional experimentation. The fuel properties concurred with the ranges of the ASTMD6751 and EN 14214 specifications. The quadratic relation with high regression coefficient (R2) was detected for the densities of (0%KS+100%BD) and (20%KS +80% BD) while the linear was found suitable for the densities of (5KS + 95%BD), (50%KS +50BD) and (100%KS+0%BD). The model and correlations can find application in biodiesel and aviation industries.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UL, UM, UPCLJ, UPUK, ZRSKP
•RSM based optimization of was applied using desirability approach.•Engine load, biodiesel ratio and injection pressure were the input parameters.•The optimum fuel blends were determined based on ...optimum diesel engine operating parameters.•The optimum operating parameters showed great promise in the maximizing of BTE and reducing of emissions and EGT.•Proposed RSM model are capable for mapping engine performance-emission paradigms with high accuracy.
The primary objective of this study is to determine the optimum engine running parameters regarding the performance and emissions of diesel engine using response surface methodology (RSM). The optimization is utilized to maximize the brake thermal efficiency (BTE) and minimize the exhaust gas temperature (EGT), smoke emission, nitrogen oxide (NOx) emission and carbon dioxides (CO2) emission. The effects of different rates of biodiesel/diesel fuel blends were experimentally investigated on engine performance and exhaust emissions in a four-stroke, single cylinder, air cooled, direct injection diesel engine. A biodiesel combination involving of canola, safflower and waste vegetable oil mixtures made by transesterification was used. RSM was used to evaluate the usability of biodiesel in diesel engine. RSM model was formed by using experimental study data. Corresponding to the results taken from the optimization, best operating parameters of the engine were found to be 1484.85-watt engine load, 215.56 bar injection pressure with 25.79% biodiesel ratio. The optimum responses obtained under these operating conditions were found as 20.54%, 199.88 °C, 0.26%, 558.44 ppm and 4.52% for BTE, EGT, smoke, NOx and CO2, respectively. At the same time, R2 (correlation coefficient) values were found as 99.81%, 99.36%, 98.84%, 98.31% and 99.00% for BTE, EGT, smoke, NOx and CO2, respectively. The results of this study showed that the RSM is a useful technique for estimating and optimizing the performance and emission values of a diesel engine powered with biodiesel.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UL, UM, UPCLJ, UPUK, ZRSKP
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