Influence of nano additives on Diesel-Biodiesel fuel blends in diesel engine: A spray, performance, and emissions study

Energy Conversion and Management X, Journal Year: 2024, Volume and Issue: 23, P. 100574 - 100574

Published: March 21, 2024

Enhancing the suitability of biodiesel for IC engines with inclusion fuel additives has emerged as a promising avenue research in recent years. Nanoparticles (NPs) have witnessed significant advancements they offer several advantages like higher surface area, improved heat transfer capabilities, and strong catalytic properties. These attributes boost combustion processes reduce exhaust emissions. Consequently, it is utmost importance to comprehensively understand influence NPs when incorporated into its blends. Recent reviews revealed effect nano on performance, combustion, emissions, however, spray characteristics not been clearly understood due scarce literature available. This review includes combined characteristics, thermal incorporating preparation methodologies, analysis stability, properties diesel–biodiesel from last 10 years research. The findings indicate that yield favorable outcomes enhancing atomization quality, optimizing engine mitigating For instance, addition 50 ppm CeO2 diesel-ethanol reduced penetration length increased cone angle by −2.16 % +4.3 contrast 25 CeO2. BTE 1.58 %, 1.62 2.34 40, 80, 120 Fe2O3 Mauha biodiesel. CO emissions decreased 9.78 TiO2 blends, 21.84 Al2O3 17.10 CuO blends 6.38 respect B10. Nonetheless, there remain unresolved challenges, cost production long-term stability standing out critical factor must be addressed establish fuels financially viable alternative source.

Language: Английский

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Statistical and machine learning analysis of diesel engines fueled with Moringa oleifera biodiesel doped with 1-hexanol and Zr2O3 nanoparticles

Scientific Reports, Journal Year: 2025, Volume and Issue: 15(1)

Published: March 1, 2025

This experimental study based on DOE (Design of experiments) explores the performance and emission characteristics Moringa oleifera-based biodiesel blends enhanced with zirconium oxide (ZrO2) 1-hexanol as boosting agents in a slow-speed diesel engine operating at 1500 rpm. The novelty lies synergistic use these additives for improving fuel efficiency reducing emissions, combined advanced statistical machine learning models optimization prediction. Four test were analyzed: 90D5MO5H + 25 ppm ZrO2, 80D10MO10H 50 70D15MO15H 75 100MO 100 ZrO2. A comprehensive methodology involving testing modelling using Gradient Boosting (GBoost), Extreme Learning Machine (ELM), Response Surface Methodology (RSM) was employed. Key findings include brake thermal (BTE) 8.63% higher than consumption reduction 46.13% (0.14 kg/kWh) ZrO2 blend. blend also demonstrated superior combustion characteristics, including peak cylinder pressure 70 bar heat release rate (HRR) 45 J/°CA. Emission analysis revealed significantly reduced hydrocarbon emissions (0.020%) lowest carbon monoxide (10.1%) Among predictive models, ELM exhibited highest accuracy an R2 value 0.9604, outperforming other approaches. suggest that optimized moringa oleifera offer promising solution sustainable cleaner operation, potential applications transportation energy sectors aiming environmental impact.

Language: Английский

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Optimizing engine performance and emission properties with Garcinia indica biodiesel: a holistic RSM-TLBO-DFA strategy

Biofuels, Journal Year: 2024, Volume and Issue: unknown, P. 1 - 18

Published: Dec. 18, 2024

Garcinia indica (GI) feedstock poses high oil content (45.2%) and after transesterification resulted with 94.8% yield. The GI crude oil, biodiesel, their blends were tested for fuel characteristics run in a diesel engine. Response surface methodology based on central composite design experimental matrices was used to model examine the input variables (engine load, injection timing, pressure, blend type) engine performance (brake thermal efficiency (BTE), brake specific consumption (BSFC)) emission (nitrogen oxide (NOx), unburnt hydrocarbon (UHC), carbon monoxide (CO)). All factors showed significant effects (except pressure time NOx) all responses. empirical equations predicted 27 cases 4.75% accuracy. Desirability function approach applied transform output functions (maximize BTE minimize BSFC, CO, NOx, UHC) different weight fractions (WF) single desirability maximization. Teaching learning-based optimization (TLBO) determined optimal condition corresponding case 4 (maximum WF minimum BTE, UHC, resulting highest value (0.9432) percent deviation of 7.09%. developed models assist novice users predicting unknown parametric conditions improving without practical experiments.

Language: Английский

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Effect of hydrogen and diethyl ether addition on 5E attributes of compression ignition engine using papaya seed oil-diesel blend

International Journal of Hydrogen Energy, Journal Year: 2024, Volume and Issue: unknown

Published: Dec. 1, 2024

Language: Английский

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Investigation of in-nozzle flow behavior coupled with spray characteristics of waste cooking oil and castor biodiesel

Energy Conversion and Management X, Journal Year: 2024, Volume and Issue: 24, P. 100787 - 100787

Published: Oct. 1, 2024

Language: Английский

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