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AuthorSiraj, Sayyed
AuthorKumar Das, Randip
AuthorAhmed, Samer F.
AuthorKulkarni, Kishor
AuthorAlam, Tabish
AuthorEldin, Sayed M.
Available date2024-03-25T08:26:29Z
Publication Date2023-09-15
Publication NameAlexandria Engineering Journal
Identifierhttp://dx.doi.org/10.1016/j.aej.2023.08.005
CitationSayyed, S., Das, R. K., Ahmed, S. F., Kulkarni, K., Alam, T., & Eldin, S. M. (2023). Modelling of multiple biodiesel-emitted nitrogen oxides using ANN approach. Alexandria Engineering Journal, 79, 116-125.
ISSN1110-0168
URIhttps://www.sciencedirect.com/science/article/pii/S1110016823006798
URIhttp://hdl.handle.net/10576/53438
AbstractThis research paper focuses on modelling of nitrogen oxides emitted by diesel engine for multiple biodiesel blends. A lot of research work has observed that the properties of biodiesel blends affect the nitrogen oxide emissions. To this aim, total of fifteen blends of multiple biodiesels are prepared on vol. % by using four non-edible category biodiesels. The suitability and quality of the biodiesel and diesel blends are tested through a characterization and found within the permissible limits of ASTM. The experimentation has been carried out on a direct injection compression ignition (DICI) engine with constant speed and varying loading condition from no load to full load in a step of 25%. During the experimentation, the NOx emissions are measured using a Netel MGA-2 exhaust gas analyzer. The study revealed that several properties such as viscosity, density, mean gas temperature, etc. affect NOx emission. In addition, NOx emission increases with an increase in BPs. The artificial neural network (ANN) is performed by considering physicochemical and thermal properties as a function. The ANN predicts the estimated NOx with an accuracy of 0.99.
Languageen
PublisherElsevier
SubjectDiesel
Multiple biodiesel
Blends
NOx
Modeling
ANN
TitleModelling of multiple biodiesel-emitted nitrogen oxides using ANN approach
TypeArticle
Pagination116-125
Volume Number79
Open Access user License http://creativecommons.org/licenses/by-nc-nd/4.0/
ESSN2090-2670
dc.accessType Open Access


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