RSM/DFA computation approach for optimization and modeling of CI engine performance and emission characteristics fuelled with preheated fuel blend modified withTiO2 nanomaterial. (2021)

• Record Type: Journal Article
• Authors: Saxena, Vishal; Kumar, Niraj; Kumar Saxena, Vinod
• Is Part Of: Materials today. Volume 38(2021)Supplement Part 1
• Page Start: 350
• Page End: 358
• Publication Date: 2021
• Subjects: Smart energy -- AC biodiesel -- Meta nanoparticles -- RSM/DFA computational approach -- Nanomaterial; Materials science -- Congresses -- Periodicals; 620.1
• DOI: 10.1016/j.matpr.2020.07.421
• Languages: English
• ISSNs: 2214-7853

Abstract

Abstract: Utilization of metal nanoparticles has gained attention in the efficient combustion of biofuels. This approach is effective when nanomaterial, hereafter called as modified nanofluid fuel ("MNF" comprised of AC biodiesel 40 vol%, diesel 60 vol% and 150 mg/litter of TiO2 nanoparticles) injection temperatures and engine operational parameters are simultaneously optimized for best system performance. The present modeling/ optimization work (RSM/DFA) on 3.5 kW diesel engine, considering cumulative effect of MNF fuel preheating and engine operating parameters resulted in notable change in BTE, BSFC, CO and smoke emissions by 3.25%, 18.42%, 38% and 20% respectively. The developed model equations, results are (95.0% confidence interval) statistically fit with closeness in experimental responses and normal distribution of their residuals.