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<p>The present work is associated with how three operational variables (engine load, rice bran biodiesel blend, and Titanium Dioxide (TiO<sub>2</sub>) nanoparticles) affect diesel engines’ performance and NOx emissions. The objective is to find the optimal combination of these variables that reduces NOx emissions while retaining engine efficiency. The experiment used a Central Composite Design (CCD)-based Response Surface Methodology (RSM) to do this. Analysis of variance (ANOVA) and regression analysis were used to determine the best mathematical relationship between the operational variables and the response, with a 95% confidence level and a 5% significance level. Graphs and response surface plots were utilised to visually represent the relevance of each element and identify the most influential variables. Using the Contour Plot and Surface Plot of response variables, the response optimisation is also done using MINITAB. The experiments on a diesel engine test rig used rice bran biodiesel blends up to 30% and TiO<sub>2</sub> nanoparticles up to 200 ppm. The optimum combination was a 2.00&#xa0;kW engine load, 20 ppm rice bran biodiesel, and 187.78 ppm TiO<sub>2</sub> nanoparticles. This resulted in 317.56 ppm NOx emissions and a brake thermal efficiency of 32.32% with a desirability effect of 78.40%. A validation test confirmed the findings, with a predicted error of less than 4%.</p>

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Engine Load-Centric RSM Optimization of NOx Emissions and Diesel Engine Performance with Titanium Dioxide-Infused Rice Bran Biodiesel

  • 期刊论文

  • 发表日期：

    2026年5月25日

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  • Manoj Kumar Gupta,
  • Ashok Kumar Srivastava

摘要

The present work is associated with how three operational variables (engine load, rice bran biodiesel blend, and Titanium Dioxide (TiO2) nanoparticles) affect diesel engines’ performance and NOx emissions. The objective is to find the optimal combination of these variables that reduces NOx emissions while retaining engine efficiency. The experiment used a Central Composite Design (CCD)-based Response Surface Methodology (RSM) to do this. Analysis of variance (ANOVA) and regression analysis were used to determine the best mathematical relationship between the operational variables and the response, with a 95% confidence level and a 5% significance level. Graphs and response surface plots were utilised to visually represent the relevance of each element and identify the most influential variables. Using the Contour Plot and Surface Plot of response variables, the response optimisation is also done using MINITAB. The experiments on a diesel engine test rig used rice bran biodiesel blends up to 30% and TiO2 nanoparticles up to 200 ppm. The optimum combination was a 2.00 kW engine load, 20 ppm rice bran biodiesel, and 187.78 ppm TiO2 nanoparticles. This resulted in 317.56 ppm NOx emissions and a brake thermal efficiency of 32.32% with a desirability effect of 78.40%. A validation test confirmed the findings, with a predicted error of less than 4%.