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

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 tempe...

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Published inMaterials today : proceedings Vol. 38; pp. 350 - 358
Main Authors Saxena, Vishal, Kumar, Niraj, Kumar Saxena, Vinod
Format Journal Article
LanguageEnglish
Published Elsevier Ltd 2021
Subjects
AC biodiesel
Meta nanoparticles
Nanomaterial
RSM/DFA computational approach
Smart energy
Smart energy
Meta nanoparticles
AC biodiesel
Nanomaterial
RSM/DFA computational approach
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Summary: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.
ISSN:2214-7853
2214-7853
DOI:10.1016/j.matpr.2020.07.421