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Effects of High-Density Polyethylene (HDPE) and Additives Fuel Blends on Diesel Engine’s Performance and Emissions and NOx Prediction using Boosted Tree Model

EDUCATUM Journal of Science Mathematics and Technology 2024
Mohammad Nor Khasbi Jarkoni, Muhammad Afiq Danial Ramli, Wan Nurdiyana Wan Mansor, Che Wan Mohd Noor, Sheikh Alif Ali, Anuar Abu Bakar, Nurul Huda Abd Kadir, Mohamad Adan Yusof, How‐Ran Chao

Summary

Researchers tested blends of waste-derived HDPE plastic with biodiesel fuel in diesel engines, finding that adding HDPE with chemical additives reduced hydrocarbon and CO2 emissions across engine loads, and that a boosted tree machine learning model accurately predicted NOx emissions with R² of 0.97.

Polymers

The rising demand for eco-friendly and sustainable fuel options has prompted the investigation of alternative energy sources. This study explores the use of blends of High-Density Polyethylene (HDPE), and 7% biodiesel (B7) with additives as a substitute for diesel fuel. The research involves comparing three different mix ratios of HDPE and additives with a conventional B7 blend: a control of 100% B7, a mix of 90% B7 with 10% HDPE, and a blend of 85% B7 with 10% HDPE and 5% additives. Fourier Transform Infrared (FTIR) spectroscopy was employed to identify the fuels' functional groups. The study also measured key performance metrics, including brake-specific fuel consumption (BSFC), brake power (BP), and exhaust emissions of nitrogen oxides (NOx), carbon monoxide (CO), hydrocarbons (HC), and carbon dioxide (CO2). A Boosted Tree Model was used to establish a prediction and analysis of NOx emissions. The findings indicate that incorporating additives into the HDPE blend positively influences both engine performance and emissions. The combination of HDPE and additives with B7 resulted in reduced emissions across various engine loads and speeds, decreasing hydrocarbon and carbon-containing emissions. The Boosted Tree Model, with a configuration of 4 leaf nodes, demonstrated strong predictive accuracy, with a coefficient of determination (R2) of 0.86 and a root-mean-square error (RMSE) of 0.38 for the training dataset, and R2 of 0.97 with RMSE of 0.16 for the validation dataset. The study underscores the benefits of integrating HDPE and additives into diesel blends, highlighting their potential to lower emissions and supporting the search for viable alternative fuels.

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