• Multi-Objective Optimization Using RSM for a CI Engine Fuelled with Chia Seed The addition of SiO₂ nanoparticles in B20 (CR19) increased BTE by 7.69% and 17.64% reduction in BSFC compared to B20. • B20+SiO₂ at CR16 exhibit relatively lower NOx compared to B20 blend. • B20+SiO₂ at CR18 shows lower CO compared to CR16, CR17, CR19, and B20. • B20+SiO₂ blend at CR18 has the he peak HRR (68.75 kJ/m³) at 4° ATDC. Sustainable biofuels have become a major area of research, mainly because the world must act quickly to reduce GHG emissions and reduce the use of fossil fuels. The research study examines through experiments and statistical analysis how different engine load levels and compression ratio settings affect combustion performance and emissions characteristics of a CI engine fuelled with B20 biodiesel blended with SiO₂ nanoparticles (60 ppm). The experiments conducted using different load levels while testing engines with compression ratios between 16 and 19. The RSM employed to create predictive quadratic models, which enabled them to optimize multiple key engine responses through their analysis. The statistical models demonstrated high reliability and strong predictive capability. The results demonstrated that adding SiO₂ nanoparticles increased combustion efficiency while decreasing hazardous emissions when compared to the standard diesel performance. The study discovered that operating at 75% load and CR 18 produced an optimal performance condition, which resulted in 32.56% BTE, 0.33 kg/kWh BSFC, 67.52 bar cylinder pressure and 68.75 J/°CA net HRR. The emissions measurements showed 0.038% CO, 14 ppm HC, 850 ppm NOx and 7.3% smoke opacity. The experimental validation process confirmed model predictions through a measurement method which showed errors below 5.6%. The results show that SiO₂ nanoparticle-enhanced chia seed biodiesel improves CI engine operation by producing fewer emissions when engine conditions are optimized.
sarathy et al. (2026) studied this question.