RSM modeling of different amounts of nano-TiO2 supplementation to a diesel engine running with hemp seed oil biodiesel/diesel fuel blends. (1st March 2023)

• Record Type: Journal Article
• Authors: Uslu, Samet; Simsek, Suleyman; Simsek, Hatice
• Is Part Of: Energy. Volume 266(2023)
• Publication Date: 2023-03-01
• Subjects: Hemp seed oil -- TiO2 -- Nanoparticle -- Diesel engine -- Biodiesel -- RSM; Power resources -- Periodicals; Power (Mechanics) -- Periodicals; Energy consumption -- Periodicals; 333.7905
• DOI: 10.1016/j.energy.2022.126439
• Languages: English
• ISSNs: 0360-5442

Abstract

Abstract: In this study, experiments were performed on a single-cylinder diesel engine to define the optimum nanoparticle ratio using the response surface methodology. The experimental fuels used were a mixture of hemp seed oil biodiesel (30% by volume) and diesel (70% by volume) mixed with titanium dioxide nanoparticles at various amounts (25, 50, 75, and 100 ppm). The addition of 100 ppm titanium dioxide increased brake thermal efficiency by 29.65% and decreased brake specific fuel consumption by 5.16%. Furthermore, the addition of titanium dioxide up to 50 ppm reduced hydrocarbon emission by 12.07%, and up to 75 ppm reduced the carbon monoxide by 40.15%. In contrast, the titanium dioxide caused an average of 27% increase in nitrogen oxide emissions. On the other hand, the optimum titanium dioxide ratio and engine load were determined as 75 ppm and 2000 W, respectively. Under these conditions, brake thermal efficiency, brake specific fuel consumption, carbon monoxide, hydrocarbon, nitrogen oxide, and smoke emissions are 27.942%, 1081.51 g/kWh, 0.057%, 40.293 ppm, 257.3742 ppm, and 0.7064%, respectively. Optimum results were achieved with an overall high desirability value of 0.7665. A good harmony among the experimental and estimated response values demonstrates the acceptability of the developed models. Highlights: The multi-objective RSM optimization for modified nano fuel is presented. Optimum 75 ppm amount of TiO2 gives the best responses. Predictive capabilities of developed model responses are experimentally validated.