Search

The present work aims to find a viable substitute fuel for diesel and control pollutants from compression ignition engines. Therefore, in the present investigation, an attempt has been made to study the effect of 20% proportion of five different biodiesel diesel blends in diesel engine. The 20% proportion of biodiesel such as Jatropha, Pongamia, Mahua, Annona and Nerium and 80% of diesel is denoted as J20, P20, M20, A20 and N20 are used in the present investigation. The experimental results showed that the different biodiesel blends' brake thermal efficiency is slightly lower compared to neat diesel fuel. However, the N20 blend has shown improvement in performance and reduction in exhaust emissions compared to other biodiesel diesel blends. From, the experimental work, it is found that biodiesel can be used up to 20% and 80% of a diesel engine without any major modification. [ABSTRACT FROM AUTHOR]

In automotive applications, artificial neural network (ANN) is now considered as a favorable prediction tool. Since it does not need an understanding of the system or its underlying physics, an ANN model can be beneficial especially when the system is too complicated, and it is too costly to model it using a simulation program. Therefore, using ANN to model an internal combustion engine has been a growing research area in the last decade. Despite its promising capabilities, the use of ANN for engine applications needs deeper examination and further improvement. Research in ANN may reach its maturity and be saturated if the same approach is applied repeatedly with the same network type, training algorithm and input–output parameters. This review article critically discusses recent application of ANN in ICE. The discussion does not only include its use in the conventional engine (gasoline and diesel engine), but it also covers the ANN application in advanced combustion technology i.e., homogeneous charge compression ignition (HCCI) engine. Overall, ANN has been successfully applied and it now becomes an indispensable tool to rapidly predict engine performance, combustion and emission characteristics. Practical implications and recommendations for future studies are presented at the end of this review. [ABSTRACT FROM AUTHOR]

[Display omitted] • The first study that used grasshopper optimization algorithm for biodiesel in ICE. • The GOA was utilized to predict the engine's performance and emission responses. • The GOA successfully found the optimal engine operating conditions. • The three confirmation tests also revealed satisfying results. • The optimized operating conditions was given by B50 run at 7 Nm engine load. A recently invented algorithm called the grasshopper optimization algorithm (GOA) was used to predict and optimize palm oil biodiesel operated in a diesel engine. The work was conducted in three stages: (i) designing an experiment and performing the experiments, (ii) mathematical modeling, and (iii) optimization using GOA. By using regression modeling over these experimental results, the mathematical equations between the factors (biodiesel ratio (%) and load (Nm)) and the responses (BTE, BSFC, BSCO, BSNO x , BSCO 2 , BSHC, and Smoke) were calculated. The results showed that the factors used in the model were sufficient to explain the change in the response, and no additional factors in the mathematical models were required. The ANOVA results showed that the p-value for all the regression models were 0.000 < 0.05, which indicated their significance. Moreover, the regression models best fit the given observations with a low prediction error. The three confirmation tests also revealed satisfying results with low errors. The range of prediction error for BTE, BSFC, BSCO, BSNOx, BSCO 2 , BSHC, and Smoke were 0.25–3.00%, 2.55–8.20%, 4.61–11.65%, 1.71–12.20%, 1.35–3.52%, 0.02–7.75%, and 0.69–4.34%, respectively. The optimized operating conditions for the maximum engine performance and the minimum emissions was given by 50% biodiesel run at 7 Nm engine load. [ABSTRACT FROM AUTHOR]

• Fuel properties of ABE-diesel blends was for the first time investigated. • ABE can be blended with diesel fuel and fulfil the established fuel standard, EN590. • ABE(3 6 1) can be added with higher percentage compared to ABE(6 3 1) and ABE(1 3 6). • Mathematical correlations to predict ABE's fuel properties are presented. • ABE can be a promising alternative biofuel. Butanol offers more promising results compared to lower carbon alcohol. Yet, it has not been commercially produced as a biofuel due to its expensive recovery process from Acetone-Butanol-Ethanol (ABE) fermentation. If ABE is used directly as a biofuel, the process will be more straightforward, thus eliminating its energy and cost-intensive purification process. Study on ABE as a biofuel has become a growing field for the last five years. Several preliminary studies have reported convincing results of using ABE-diesel blends in diesel engines. However, many of the studies on ABE lacks clarity regarding its fuel properties. In fact, no previous study has investigated the fuel properties of ABE. Therefore, this study aims to quantify some critical physico-chemical properties of ABE-diesel blends. Several important fuel properties were investigated in this study; calorific value, density, kinematic viscosity, distillation characteristics and cetane index. In terms of blending strategy, results from this study indicate that ABE(3 6 1) can be added up to 42% to diesel fuel, while ABE(6 3 1) and ABE(1 3 6) can only be added up to 22% and 23%, respectively. Also, the mathematical correlations to estimate ABE's fuel properties are presented. The equations developed in this study gave have high coefficient of determination values. They can serve as prediction models for future studies. Considering its relatively low-cost production and satisfying physico-chemical properties, ABE has the potential to become a promising alternative biofuel. [ABSTRACT FROM AUTHOR]

[Display omitted] • Presence of volatile impurities in sample A resulted in initial degradation at 348 °C. • DAP3 fuel exhibits a higher HRR compared to DAP1 and DAP2 fuels. • DAP3 resulted in an average reduction of ∼17.14% and 21.86% in CO and smoke. • DAP2 fuels emitted lower NOx than DAP1 due to slower oxidation reactions. • DAP1 and DAP2 showed large accumulation and coarse soot in the PM 10 form at ∼83 nm. Most research into the treats of plastic wastes have concentrated mainly on single-exposure pathways or products. These practices fail to acknowledge that the complications of carbon particles from engines are produced not only by diesel but by any plastic oils due to the vast amount of contaminants. With the potential to significantly weaken the impact of contaminants, the present study investigates the effects of dehalogenation and catalytic pyrolysis on plastic waste, as well as the risks associated with plastic oil blends on diesel engine. Different types of washing were conducted to effectively dehalogenate plastic waste. After pretreatment, odor compounds were analyzed using GC–MS. Subsequently, various types of pretreated plastic samples underwent catalytic pyrolysis with a 5:1 ratio of HDPE to Al 2 O 3 ·2SiO 2 ·2H 2 O. Differences in physico-chemical properties and hydrocarbon compounds of oils were determined. Experiments were performed using different fuel blends in a diesel engine under steady-state conditions, and their effects on combustion, emissions, morphology, and size particles were analyzed. The results show that sample B exhibited a lower toxicity level of 1,3-butadiene compared to other samples, while acetone and terpenes represented the second and third-highest emission levels in flakes, respectively. Sample C started to degrade at low temperatures (<300 °C) due to carbon addition from ethyl acetate solvent into the tertiary carbon chain of the flakes. DAP3 fuel achieved a higher reaction due to its degree of unsaturation and lower viscosity, resulting in the formation of smaller fuel droplets at high injection pressure and heat release rate (HRR). Higher emission levels were observed by DAP1 and D100, exceeding the Euro 5/6 standard limits. However, DAP3 fuel resulted in an average reduction of ∼17.14% and 21.86% in CO and smoke emissions, respectively, accompanied by a slight decrease in NOx and HC levels. Conversely, there were inconsistencies in the emission results observed with DAP2. Compared to D100, both DAP1 and DAP2 exhibited a significant accumulation and coarse particles in the PM 10 forms at a peak of ∼83 nm. Whereas the DAP3 showed a smaller mobility Dp with a low nucleation particle peak, which was prone to absorb the unburned HC soot and later change to accumulation mode particles. [ABSTRACT FROM AUTHOR]

Zinc oxide nano additives of 250 ppm, 500 ppm, and 1000 ppm were blended with diesel fuel. The prepared fuels which were designated as DF-250 ppm ZnO, DF-500 ppm ZnO, and DF - 1000 ppm ZnO were tested for engine characteristics along with diesel fuel (DF) in a standard bench-scale engine. All the tests were carried out at different speeds of the engine ranging between 2000 and 3000 rpm with unvarying engine load and advanced injection timing. The outcomes from these experiments exhibited higher brake thermal efficiency and cylinder pressure for fuels with ZnO nano additives than that of diesel fuel. The emission gas temperature and brake-specific fuel consumption were noticed to be lower for fuels blended with ZnO nano additive than those of diesel fuel. The level of SPM emissions also increased in compression ratio from CR = 15.5 to CR = 16.5, but starting from CR of 17.5, the SPM emissions for all the investigated fuels were relatively constant with a slight decrease at the maximum compression ratio. In addition, at all test conditions, NO and SO2 emissions from the engine tail pipe were higher with ZnO mixed diesel fuel. • ZnO nanoparticles and conventional diesel fuel is successful running CI engines. • Engine was operating 2000–3000 rpm, CR15.5–20.5 and FIT 19.5–24.5° b TDC. • The highest value of NO emission was consistently given by 1000 ppm ZnO. • The highest value of SO2 emission was consistently given by diesel fuel. • PM emissions was decreasing with used of ZnO nanoparticles in the blend. [ABSTRACT FROM AUTHOR]

• Intrrrrroduction of preparation methods and key properties of metal nanoparticle (MNP) • Comparison of engine performance using MNP-laden biodiesel and diesel fuel. • Analysis of combustion and emission characteristics for MNP-laden biodiesel/diesel. • Improvement of tribology behaviors for MNP-laden biodiesel compared to diesel fuel. In recent years, searching for efficient solutions to improve the emission and performance characteristics of diesel engines is considered as one of the essential and urgent work. Metal nanoparticles with a large surface area and high heat transfer coefficient could provide the impressive additive ability to the fuel reactivity and atomization. Therefore, the critical role of metal nanoparticles in the support of diesel engine behaviors using biodiesel and diesel is thoroughly evaluated in this current review. Indeed, preparation methods and critical properties of metal nanoparticles and metal nanoparticles-laden fuels are fully introduced. More importantly, the performance, combustion, emission characteristics, and tribology behaviors of diesel engines running on metal nanoparticles-laden biodiesel are compared to diesel fuel in detail. Generally, metal nanoparticles-included biodiesel facilitates the formation of a more homogeneous oxygen-containing mixture of fuel–air, resulting in a more complete combustion process than that of diesel fuel. As a result, the use of biodiesel with the presence of metal nanoparticles is considered as the potential strategy for promoting spay and atomization, enhancing the combustion process, increasing brake thermal efficiency (BTE), reducing toxic emissions (including carbon monoxide (CO), unburnt hydrocarbon (HC), and smoke), and improving tribology characteristics. However, some drawbacks are also indicated, such as increased NOx emission and brake-specific fuel consumption. In addition, it is also concluded that studies on other environmental impacts (such as PM emission), the stable properties of metal nanoparticles, and economic aspects should be made more extensively before commercial applications of metal nanoparticles in the real world. [ABSTRACT FROM AUTHOR]