Biodiesel Ratio Research Articles

Prediction of Performance and Emissions Diesel Engines Fueled-Biodiesel Using Artificial Neural Network (ANN) Resilient Backpropagation Algorithm (Rprop)

In order to increase energy security and improve environmental quality, the Indonesian Goverment set a target of 23% renewable energy mix in 2025, one of which is the Mandatory Bioediesel Program. A higher biodiesel blending ratio will affect the performance and emissions of diesel engines because biodiesel is chemically different from diesel oil. Research related to the prediction of diesel engine performance and emissions using Artificial Neural Network (ANN) has been conducted, but the author sees a research opportunity for the implementation of the ANN Resilient Backpropagation (Rprop) algorithm. The data used to create the ANN model prediction was secondary data from previous research. The model designed multi input and multi output (MIMO) with 4 input variables and 7 output variables. Model building done by varying the number of neurons and hidden layers. Model evaluation selected based on the largest coefficient of determination parameter R2 and the smallest RMSE or MAPE. The results showed that the ANN single layer 4-20-7 network architecture is the best model for predicting diesel engine performance and emissions with test data R2 , RMSE and MAPE of 0.962532, 6.699428 and 6.0% respectively, while for overall data testing has a performance of 0.982869, 3.908542 and 4.3%. The results also show that based on the ANN prediction results, the increasing biodiesel ratio can increase NOx emissions and decrease HC, CO and CO emissions2 . In terms of performance, the addition of biodiesel can increase BSFC and BP and decrease BTE. The results also show that the addition of ZnO concentration can reduce emissions while in terms of performance it will increase BTE and reduce BSFC and BP.

Investigation on nanostructure, surface functional groups, and oxidation activity of particulate along the exhaust after-treatment of a diesel engine fueled with waste cooking oil biodiesel blends.

In this study, the nanostructure, surface functional groups, and oxidation activity of soot particulate along the exhaust after-treatment system of a heavy-duty diesel engine fueled with waste cooking oil (WCO) biodiesel blends are investigated by TEM, XPS, and TGA respectively. The main findings are as follows: Along the exhaust after-treatment system, fringe length of primary particles of soot particulate emitted from tested heavy-duty diesel engine fueled with B0, B10, B20, and B100, i.e., 0%, 10%, 20%, and 100% ratio of WCO biodiesel blended into petroleum diesel in volume respectively increases, while fringe tortuosity and separation distance of primary particles reduces. The fringe length of B10, B20, and B100 is smaller, but the fringe tortuosity and separation distance are larger than that of B0. The O/C ratio of soot particulate tends to increase firstly and then decrease as the exhaust passes through DOC+cDPF and SCR+ASC in sequence. The O/C ratio of B10, B20, and B100 are also higher than that of B0. Soot particulate at cDPF outlet contains carborundum and biuret is found at SCR+ASC outlet. The sp3/sp2 ratio decreases along the exhaust after-treatment system, and B10, B20, and B100 tend to get higher sp3/sp2 ratio than B0. The C-OH and C=O content of soot particulate from different WCO biodiesel blends show generally similar trends along the exhaust after-treatment system, while the activation energy of soot particulate keeps increasing along the exhaust after-treatment system, but decreases with the increasing of blend ratio. These findings can provide useful references for optimizing the after-treatment system for WCO biodiesel blends.

Thermal (TG/DTA) and mass (GC-HRMS) analysis of waste transformer oil and its blends

ABSTRACT This study investigates the potential use of waste transformer oil (WTO) and its blends as alternative fuels for CI engines. Thermal (TG/DTA) and mass (GC-HRMS) analyses were performed on neat samples of diesel, biodiesel, WTO, and four sets of samples with different volumetric ratios of WTO, diesel, and biodiesel. TG/DTA analysis showed that the blended samples WTO20BD10D70 and WTO30D70 had a lower range of rapid disintegration temperatures (150°C), while WTO30BD20D50 exhibited the lowest temperature range for enthalpy change. The weight loss and enthalpy change of WTO and its blends were similar to those of standard diesel fuel. GC-HRMS analysis revealed that the compounds present in WTO and its blends were n-alkanes, alkenes, aromatics, alcohols, phenols, carboxylic acids, esters, and cyclic compounds, similar to those found in diesel fuel. Sample WTO20BD10D70 showed a narrow range of compounds (C8 to C27) and a similar composition of hydrocarbons to that of neat diesel, indicating its potential as an alternative fuel. Blended samples with higher carbon numbers may be harder to ignite but more stable for long-term storage, and their composition is similar to diesel fuel, suggesting their potential as eco-friendly diesel alternatives.

Biodiesel from Higher Alcohols for Removal of Crude Oil Spills from Coastal Sediments

Throughout the decades, the production, transport, and use of fossil fuels have led to numerous environmental concerns. Crude oil has caused catastrophic accidents after its spillage into the aqueous environment and accumulation on coastal sediments. To tackle this problem in a sustainable manner, researchers have used alternative remediation agents to extract these crude oil spills from the sediments. In this study, the biodiesels fatty acid methyl, ethyl, and butyl esters (FAME, FAEE, and FABE, respectively) were synthesized via transesterification reaction from waste cooking oil and corresponding alcohol in the presence of a catalyst, potassium hydroxide, and used as remediation agents for crude oil extraction. The influence of different experimental conditions on the crude-oil removal efficiency was studied (time of 1, 2, or 4 h; mass ratio of biodiesel to crude oil of 0.5:1, 1:1, or 2:1), with a simulation of coastal effects using a shaker. UV/Vis spectrophotometry was used to determine crude-oil separation efficiency based on the correlation of the residual crude-oil mass fraction and corresponding absorbance. The results show that FAME and FAEE were most effective in the removal of crude oil from sand (removing 88–89%), while FAEE and FABE extracted the most crude oil from gravel (removing 74–77%).

An experimental investigation of the impacts of titanium dioxide (TiO2) and ethanol on performance and emission characteristics on diesel engines run with castor Biodiesel ethanol blended fuel

Investigating the impact of ethanol and TiO2 on the performance and emission characteristics of diesel engines running on a blend of ethanol and castor biodiesel is the primary goal of this study. The nanoparticles of ethanol, biodiesel, and TiO2 diesel fuel were combined at several concentrations. Diesel, B10, B20, B30, B10E10T, B20E10T, B30E10T, B10E20T, B20E20T, and B30E20T were among the various fuels that were investigated. The physiochemical properties of all the sample fuels were assessed, including density, pour point, cloud point, fire point, flash point, and kinematic viscosity. Following this, other engine performance indicators, such as torque, power, and fuel-consumption, were examined. Studies were also carried out on the properties of emissions, including CO, CO2, HC, and NO. Peak braking power and engine torque were found for each fuel under investigation at around 2750 and 2500 rpm, respectively. The addition reduced the brake-specific fuel consumption for B10E20T by 7.41 % while increasing the braking engine's torque and power by 8.64 and 3.86 %, respectively, in compared to blends without the TiO2 additions. When compared to diesel, the exhaust emission data without the addition of TiO2 revealed a decrease in CO and HC emissions but an increase in CO2 and NO emissions. On the other hand, using ethanol blend reduced NO emissions. According to the overall findings, diesel engine performance, combustion characteristics, and exhaust gas emissions were enhanced averagely by 7.43 % when a certain ratio of ethanol, biodiesel, and TiO2 additives (B10E20 + 50 ppm) was used.

Optimization of Biodiesel Production from Jatropha Oil and its Impact on Engine Performance and Emissions Using Response Surface Methodology

This study aims to improve biodiesel production by assessing the effects of biodiesel-diesel fuel blends on engine performance and emissions using response surface methodology (RSM). The biodiesel was produced by the transesterification process. Here we see how the molar ratio (A), catalyst quantity (B), reaction temperature (C), and reaction time (D) affect the biodiesel conversion rate. During optimization, a Box-Behnken design (BBD) based on RSM was employed. Ideal conditions for achieving a biodiesel yield of 98.2069% were a B of 0.811601 wt%, a C of 75.8837°C, a D of 98.2069 min, and A of 10935:1. Adjusting parameters like engine speed and biodiesel fuel mix ratio enhanced engine behavior and condensed exhaust emissions. The trials were structured utilizing the central composite design (CCD) technique grounded on RSM. The optimum operating criteria for the engine were evaluated to be a biodiesel ratio of 12.5845% and speed of engine is 2011.24 rpm. Under these conditions, the power output was 50.0817kW, torque was 254.757 Nm, smoke opacity was 6.48966%, CO emissions were 270.009 ppm, and NOx emissions were 819.573 ppm.

Emulsion liquid membrane pertraction of soap from crude biodiesel using activated carbon and glycol based deep eutectic solvents

Soap removal from crude biodiesel is considered as one of the most challenging biorefinery processes. This study reports a new technique for soap removal incorporating activated carbon (AC) in an emulsion liquid membrane (ELM) system based on deep eutectic solvents (DES-AC-ELM). These DESs were prepared from two salts, namely tetramethylammonium chloride (TMAC) and choline chloride (ChCl), with different hydrogen bond donors (HBDs) such as ethylene glycol (EG), diethylene glycol (DEG) and triethylene glycol (TEG). COSMO-RS modelling was performed in the evaluation of the activity coefficients and capacity at infinite dilution of DESs. The COSMO-RS simulation shows that the DESs with TEG as the HBD are the most effective stripping agents for soap removal which is in accordance with the experimental results. In addition, the σ-profile and σ-potential were used to investigate the interactions between the soap molecules in each phase. The impact of various process parameters on the soap removal such as the salt: HBD ratio, DES:biodiesel ratio, span-20 concentration, mixing speed, extraction time and dosage of AC were evaluated. The proposed technique achieved a soap extraction efficiency of 99.1% (6.856 ppm) and 97.5% (18.773 ppm) for TMAC:TEG(DES3) and ChCl:TEG(DES6), respectively, with a salt: HBD molar ratio of 1:4, DES:biodiesel ratio of 1:1, 2 wt% surfactant concentration, 10 min extraction duration, 400 rpm mixing speed, 0.5 treatment ratio and 0.5 wt% AC dosage. The transport mechanism of soap conforms to a first-order mass transfer behaviour, with a kinetic rate constant of 0.64 min−1 and 0.43 min−1, for DES3 and DES6, respectively. This study illustrated a new cleaner and simple route for purification of crude biodiesel.

Evaluation of Statistical and Machine Learning Analysis on CRDI Engine using Ternary Fuel doped with Cerium Oxide Nanoadditives

At present, diesel engines are confronted with the formidable task of reconciling aggressive emission regulations with the preservation of intended engine performance. In order to tackle this concern, India can implement a comprehensive strategy that includes waste reduction, recycling programs, and the innovative use of waste-to-energy technologies. The potential synergistic effects of combining fuel mixtures with cerium oxide nanoparticles in CRDI diesel engines remain unexplored. This study employs response surface methodology and MLP regression to investigate these effects. This study explores the experimental design includes variation in blend ratios of karanja biodiesel (upto 20 %), compression ratios (18–22), and injection pressure (400–1200 bar), as well as CeO2 nanoparticle concentrations (50–150 ppm) using 10 % biobutanol. A combination of response surface methodology (RSM) and artificial neural network (ANN) techniques is used to assess and optimise the influence of diverse process parameters on engine responses. The machine learning processor (MLP) regressor model is more capable of forecasting engine responses than RSM modelling, as it has lower MAE, RMSE, and higher R2 values. According to the study, the best blend ratio, CR, Injection Pressure, and CeO2 concentration for the best performance and lowest emissions are 9.97 % biodiesel blend, CR of 20, an injection pressure of 797.4 bar, and CeO2 nanoparticle concentration of 100.1 ppm. The MAE value of the MLP regressor-based model ranged from 0.0011 to 0.0119. In terms of RMSE, MLP regressor-based model outputs are within reasonable boundaries. This study highlights the optimization of engine operating parameters and the application of nanotechnology in biodiesel blends. These findings can lead to the development of durable and eco-friendly fuel alternatives for internal combustion engines, promoting sustainable transportation.

Inhibition effect of biodiesel on the formation of oxidized insoluble matter in diesel: characteristics and mechanism

ABSTRACT To address the problem that oxidized insoluble matter in diesel is easily generated in the process of using, we proposed the idea of blending biodiesel into diesel to inhibit the formation of oxidized insoluble matter. We also studied the effect of the biodiesel blending ratio on the generation of oxidized insoluble matter and revealed the mechanism of biodiesel inhibiting the formation of diesel oxidized insoluble matter. According to the results, the color of the blended fuel became darker with the increase in oxidation time for B0–B100 blended fuel. The generation of oxidized insoluble matter during the oxidation of B0–B30 was obvious since the amount increased with the enhancement of biodiesel ratio. The formation phenomenon of oxidizing insoluble matter in diesel disappeared, however,when the addition ratio of biodiesel increased from 0%–30% to 40%–100%. Based on the results from Fourier transform infrared spectroscopy and gas chromatography-mass spectroscopy, the main component of oxidizing insoluble matter was tetralone. At low blending ratios, small molecule compounds such as alcohols, aldehydes, and ketones, were rapidly generated with the oxidation process of biodiesel, which maybe acted as precursors for formation of oxidation insoluble matter, thereby increasing the amount of oxidized insoluble matter. For high blending ratios, oxidized insoluble matter was gradually dissolved in biodiesel, because the polarity between biodiesel and oxidized insoluble matter was similar. The dielectric constant of biodiesel was 3.35, which indicated that biodiesel was a weak polar liquid. Meanwhile the oxidized insoluble matter was a polar substance, and its dielectric constant was 6.28–13.59. The results showed that the blending of biodiesel was expected to slow down the appearance of oxidized insoluble matter in diesel, thereby optimizing the performance of diesel and reducing the carbon emissions of diesel.

Utilization of RSM to optimize the performance and emissions of a single cylinder diesel engine using waste hazelnut biodiesel

One of the environmentally friendly, biodegradable, and renewable alternative fuels widely used around the world is biodiesel. Among vegetable oils, hazelnut oil has great importance in biodiesel production due to its high content of oleic acid. For this study, it is aimed to determine the optimum mixing ratio of biodiesel, produced from waste hazelnut oil (WHB). The tests were carried out on a diesel engine operated with WHB/diesel mixtures at different loads. By means of the design of experimental method (DOE), three different fuel ratios (WHB0, WHB15 and WHB30) were defined and tests have been performed. The results obtained from the tests were analyzed using the response surface method (RSM). Engine load and mixing ratio were determined as input factors while CO, NOx, smoke, indicated thermal efficiency (ITE), ignition delay (ID) and break specific fuel consumption (BSFC) were determined as output factors. In the mathematical model created, the R2 values were found to be 0.98, 0.95, 0.91, 0.98, 0.99 and 0.90 respectively. The high R2 values indicated a strong correlation between the optimization outputs and the real experiments. By using these performance and emission parameters, optimization was performed to identify the optimum blend ratio and load. Based on the results, the optimum inputs were determined as 8.46 Nm load and 4.86 % blend ratio. As a result, with the optimized fuel blend, BSFC (8.03 %), ID (3.57 %), and NO (2.87 %) increased while ITE (7.7 %), CO (18.37 %), and smoke (26.15 %) decreased comparing to WHB0. Despite the slight increase in consumption, the results showed that this blend could be used in an environmentally efficient manner, thanks to the reduction in pollutant emissions.

Multi-objective optimization of the performance and emissions characteristics of a CI engine powered by Pyrus glabra biodiesel as a novel feedstock using response surface method

Finding new renewable sources for the production of biofuels has attracted a lot of attention in recent years due to the reduction of fossil resources. A new biodiesel feedstock as a renewable source is presented in this study. The purpose of this study was to evaluate the performance and emissions of diesel engines powered by diesel and biodiesel fuel blends by volume percentages of 5, 10, 15 and 20. The multi-objective optimization is applied to minimize engine emissions and maximize the performance of the engine. The obtained results revealed that engine load and biodiesel ratio have a significant effect on the engine emissions and parameters at the 5% level. The results revealed that when the diesel engine was operated with an engine load of 70% and biodiesel concentration of 9% as an optimal condition. The optimal value of the BTE, BSFC, brake power, and brake torque were 20%, 307 g/kW.h, 24 kW, and 94 Nm, respectively. The optimal value of engine-out emissions was 12 ppm, 9%, and 209 ppm for HC, CO2, and NOX emissions, respectively. The desirability value was found to be 73% at this optimal engine working condition.

Effects on of Blended Biodiesel and Heavy Oil on Engine Combustion and Black Carbon Emissions of a Low-Speed Two-Stroke Engine

Abstract The effects of heavy fuel oil and biodiesel blends on engine combustion and emissions were studied in a marine two-stroke diesel engine. The engine was operated under propeller conditions using five different fuels with biodiesel blends of 10% (B10), 30% (B30), 50% (B50), and sulphur contents of 0.467% low sulphur fuel oil (LSFO) and 2.9% high sulphur fuel oil (HSFO). Tests have shown that using a biodiesel blend increases the engine fuel consumption due to its lower calorific value. Heavy fuel oil has a high Polycyclic aromatic hydrocarbons (PAH) content, which leads to higher exhaust temperatures due to severe afterburning in the engine. A comparison of engine soot emissions under different fuel conditions was carried out, and it was found that the oxygen content in biodiesel promoted the oxidation of soot particles during the combustion process, which reduced the soot emissions of biodiesel. Compared to HSFO, B10, B30, B50 and LSFO, the soot emission concentrations were reduced by 50.2%, 56.4%, 61% and 37.4%, respectively. In our experiments, the soot particles in the engine exhaust were sampled with a thermal float probe. Using Raman spectroscopy analysis, it was found that as the biodiesel ratio increased, the degree of carbonisation of the soot particles in the exhaust became less than that in the oxygenation process, resulting in a decrease in the degree of graphitisation.

Characterization of renewable diesel, petroleum diesel and renewable diesel/biodiesel/petroleum diesel blends

The physicochemical properties of a renewable diesel (RD) and several petroleum diesel (PD)–dominant diesels were examined to assess the feasibility of identifying and quantifying the presence of RD and biodiesel from PD and their blends. Relative to all PD-dominant diesels, the RD exhibited a lower density, a higher flash point, reduced evaporation loss and a comparable viscosity and water content. The studied RD contained a limited amount of aromatics, with aliphatic hydrocarbons predominantly within the C15 to C18 range. Most individual petroleum hydrocarbons were detected in the PD-dominant diesels, whereas the most abundant hydrocarbons for the RD were alkanes in the <n-C19 carbon range. The typical chemical signature of RD includes clustered peaks within the C15 to C18 range on GC/FID chromatograms coupled with a sharp decline in the abundance of n-alkanes from ∼n-C19 and heavier. These properties are robust indicators of RD, even in RD/PD blends. However, quantifying the RD/PD blending ratios is challenging because of their overlapping chemical compositions. The quantified blending ratios for the blended biodiesel/PD are close to theoretical biodiesel ratios. Our analyses provide valuable insights into the forensic identification of RD, biodiesel, PD and their blends.

قياس انبعاثات الجسيمات الصلبة وتوزيعها الناتجة من الوقود الحيوي في محرك التوربين الغازي المصغر

Atmospheric CO2 has been reported to be on a rapid increase in recent times mainly due to the rising consumption of fossil fuel for anthropogenic activities. Currently the situation is that of the 25% fossil fuel consumption by the transportation sector, aviation sector consumes about 13% of transport fuel consumption, which is the second biggest sector after road transportation. Therefore, the applications of biofuels have been increased in aviation. The aim of this work is to investigate and compare biodiesel and its blends with syntactic kerosene. The pollutants of particulate emissions and their size distributions were analyzed. Jet A1 and blends of Jet A1 and biodiesel in volume ratios of 90:10 (B10), 80:20 (B20), 70:30 (B30), 50:50 (B50) and 30:70 (B70) mixed with 2.5% turbine lubricating oil were tested. The fuels were tested at three load conditions (throttle settings): Full power, 70% and idle condition. Scanning Mobility Particle Sizer has been used to determine the particulate size distribution and the number of concentration of diluted exhaust gases. The results showed that particulates from all throttle settings showed uni-modal distribution characteristics. Particulate number concentration of each fuel increases with the increase in throttle position. The increase in biodiesel ratio in biodiesel blend has also increased the particulate size concentration. More particulates were seen to be produced with Jet A1 and lower blends of biodiesel. The engine also produces a significantly higher number of particles at full power for all fuel types. Keywords: Biodiesel, Micro Gas Turbine Engine, Scanning Mobility Particle Sizer, waste cooking oil, pollutants.

Experimental Investigation and Performance Evaluation of Jatropha Oil-Biodiesel Blending with Kerosene for Domestic Cooking and Lighting Applications.

Reducing indoor air pollution and the related costs requires developing efficient cooking and lighting technologies as well as alternative energy sources. The appropriateness of virgin jatropha (Jatropha curcas) oil, its biodiesel, and the blending of these fuels with kerosene for wick stove lighting and cooking was examined in this study. To describe the fuel performance, a range of blending ratios were examined and characterizations were made of the fuel's density, calorific value, boiling point, viscosity, and rate of fuel consumption. To assess the fuels' thermal degradation behaviors, thermogravimetric and water boiling tests were performed. An air pollution meter was used to describe the levels of indoor air pollution. According to the findings, the virgin oil from Jatropha has a kinematic viscosity of 30.1 mm2/s. The 50% jatropha oil and 80% biodiesel blended with kerosene showed a reduction in viscosity of 72.6% and 46.8%, respectively. The thermal efficiency of the virgin oil, its biodiesel, and blending of these fuels with kerosene was in the range of 10-48%. Complete degradation of jatropha oil, its biodiesel, and 40 : 60 ratio of jatropha biodiesel and kerosene blend was conducted in the temperature range of 480-700 k, 185-280.6 K, and 100-300 K, respectively. The activation energies of jatropha oil, biodiesel, and kerosene blend (40 : 60) were 191.3, 73, and 25 kJ/mol, respectively. The average concentrations of particulate matter and carbon monoxide for pure jatropha oil biodiesel were 209.71 µg/m3 and 5.5 mg/kg, respectively. Thus, jatropha biodiesel and its blending with kerosene are suitable fuels for cooking and lighting operations in rural communities who are living far from the electrical grid compared with virgin oil fuel.

Study on the effect of dimethyl ether and diesel-castor biodiesel blends on emission and combustion characteristics

The biodiesel from Castor was, investigated with a water-cooled four-stroke diesel engine of model CT 110 with B0, B5, and B10 without and with dimethyl ether (DME) of 2 % and with a fixed load of (80 %) to study the combustion and emission. The biodiesel was made by alkaline transesterification with NaOH as a catalyst. Using established test protocols, the fuels' characteristics, including their viscosity, surface tension, heating value, flash point, and elemental makeup, were measured. Experimental research is used to determine how the pressure and heat release rate affect the performance characteristics of both reference fuel and the blends. The combustion studies are conducted with engine speeds of 1800, 2400, and 3000 rpm and emissions were analyzed with engine speeds starting from 1600 rpm to 3000 rpm with exhaust gas analyzer Gunt, CT159.02 digital analyzer. From the combustion analysis when the blend ratio increases the cylinder pressure (CP) and heat release rate (HRR) also increase due to oxygen molecules in the biodiesel. The addition of DME to biodiesel blends reduces carbon monoxide (CO) emissions relative to neat diesel and biodiesel blends. With the increase of diesel castor biodiesel blends, nitrogen oxide (NOX) emissions decreased as a result of the reduction in the HRR. The effect of castor diesel biodiesel blend on the NOX emissions shows, that when the blend ratio increased the NOX emissions also increased. When DME is added to a higher blend ratio of castor biodiesel, the engine is operated only at higher engine speed. Specifically, for B10 NOX emission was detected after engine speed of 2500 rpm. When the engine ran with DME for blends of castor biodiesel the engine was not operated at low engine speed. The increase of diesel castor biodiesel blends in the case of DME mixture unburned hydrocarbon (UHC) emissions increased. The finding of this research work was as the biodiesel blend increased the cylinder pressure and heat release rate also increased. So, using sustainable biodiesel-diesel blends made from castor oil with DME additive it is advisable to operate diesel engines for better emission regulation.

Investigating the fractal dimension of flame fronts of the biodiesel-diesel blends combustion in atmospheric conditions and engine cylinders: An experimental study

The fractal dimension of the flame front is an important parameter that quantifies the degree of flame folding and twisting as well as the instantaneous mass burning rate. Due to the geometric nature of flame surface folding, the fractal approach is also considered one of the most appropriate methods in power law modelling. Although biodiesel fuel is an important renewable fuel, studies on the fractal dimension of the flame during the combustion of biodiesel and its blends are limited. To address this research gap, combustion assays of biodiesel-diesel mixtures were systematically conducted within a coaxial diffusion burner and a diesel engine. High-resolution images of the evolving combustion flames were captured using a high-speed video camera. Digital image processing was applied to facilitate the extraction of key features from these images. Through the differential box counting (DBC) method, the fractal dimensions of the flame fronts were derived. A comprehensive analysis was carried out, revealing the influence of various parameters on the flame's fractal dimensions, including the biodiesel-diesel blend proportion, blend temperature, engine operational speed, and air flow rate. The results highlight that the fractal dimension undergoes a non-monotonic variation as biodiesel content increases. Specifically, the combustion of B25 blend exhibited the minimum fractal dimension, while the B100 blend showed the maximum. Further, in engine environments, peak fractal dimensions were observed to occur earlier at higher speeds (2200 r/min) with an increase in the biodiesel ratio. These insights not only bridge a critical knowledge gap in power-law modeling for biodiesel combustion but also offer a quantitative understanding of how blend ratios and engine conditions affect flame fractal properties.

A Review of Properties, Engine Performance, Emission Characteristics and Material Compatibility Biodiesel From Waste Cooking Oil (WCO)

Biodiesel is one of the renewable energy sources, non-fossil. The chosen feedstock should ideally be low-cost. Using waste cooking oil can reduce synthetic biodiesel's price by up to 70%. However, biodiesel has the advantage of lower heating value and higher density, causing increased fuel consumption and NOx emissions. Biodiesel has physicochemical properties such as a more significant cetane number than fossil diesel, a high flash point, and the absence of sulfur. This study identifies the potential availability of WCO as biodiesel and summarizes recent studies on the physiochemical properties of WCO biodiesel. This study also aims to clarify the use of WCO biodiesel on engine performance and exhaust emission characteristics (H.C., CO, CO2, NOx) when this biodiesel is used. Engine type and biodiesel ratio were identified for all articles. This study also discusses the effect of adding nanoparticles on engine performance and exhaust emissions in WCO biodiesel. This study also clarifies material compatibility (corrosion, wear, and friction). The corrosion rate in various types of materials and corrosion testing methods. Finally, this paper presents the opportunity for WCO biodiesel to be very feasible to reduce fossil diesel use.

Comparison of machine learning algorithms for predicting diesel/biodiesel/iso-pentanol blend engine performance and emissions

In this study, machine learning techniques, namely artificial neural network (ANN), support vector machine (SVM), and extreme gradient boosting (XGBoost), were used to comprehensively evaluate engine performance and exhaust emissions for different fuel blends. To obtain valuable insights on optimizing engine performance and emissions for alternative fuel blends and thus contribute to the advancement of knowledge in this field, we focused on iso-pentanol ratios while maintaining the biodiesel ratios constant. The maximum brake thermal efficiency (BTE) values for the diesel (30.13 %), D85B10P5 (29.92 %), D80B10P10 (29.89 %), and D70B10P20 (29.79 %) blends were achieved at 1600 rpm. At 1600 rpm, the brake-specific fuel consumption (BSFC) values for the diesel, D85B10P5, D80B10P10, and D70B10P20 blends were 189.93, 200.93, 202.93, and 203.95 g kWh−1, respectively. In engine performance prediction, the ANN model exhibited superior performance, yielding regression coefficient (R2), root mean square error, and mean absolute error values of 0.984, 0.411 %, and 0.112 %, respectively, in BTE prediction, and 0.958 %, 6.9 %, and 2.95 %, respectively, in BSFC prediction. In exhaust gas temperature prediction, the SVM model exhibited the best performance, yielding an R2 value of 0.981. Although all models successfully predicted NOx emissions, the ANN model exhibited the best performance, achieving an R2 value of 0.959. In CO2 and hydrocarbon estimation, the XGBoost model exhibited the best performance, yielding R2 values of 0.956 and 0.973, respectively. Therefore, the ANN model can be used to accurately predict engine performance, and the XGBoost model can be used to accurately predict emission parameters.

Emissions and energy/exergy efficiency in an industrial boiler with biodiesel and other fuels

Industrial boilers are significant equipment in industrial operations used to provide steam or heat for production. More than 80% of fire-tube boilers use heavy oil in small and middle industries in Taiwan. Due to biodiesel as a sustainable fuel, the objective of this study is to measure experimentally and evaluated energy and exergy analysis of the fire-tube boiler using biodiesel (BD), undistilled biodiesel (UB), low sulfur oil (LSO), and ultra-low sulfur diesel (ULSD), and the various mixing ratios of undistilled biodiesel and low sulfur oil (UB90, UB70, and UB50) to reduce emissions from fire-tube boilers. Results from BD and UB are comparable, and UB exhibited a high NOx reduction rate of 68.9% and a high SO2 reduction rate of 99.5% compared to LSO. The boiler that employed UB decreased CO2 emissions, NOx, and SO2 emissions. NOx emission increases with increasing LSO content. The boiler’s maximum energy efficiency when using BD is 86.6%, and the overall exergy efficiency is 44.8%. The boiler with UB70 had the lowest energy efficiency of 73.5% and the lowest exergy efficiency of 38.7% because of the increased heat loss. The Benefits of this study are not only for boiler applications but also for government policy references.