Modelling of multiple biodiesel-emitted nitrogen oxides using ANN approach

This 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 prepare...

وصف كامل

محفوظ في:
التفاصيل البيبلوغرافية
المؤلف الرئيسي: Siraj, Sayyed (author)
مؤلفون آخرون: Kumar Das, Randip (author), Ahmed, Samer F. (author), Kulkarni, Kishor (author), Alam, Tabish (author), Eldin, Sayed M. (author)
التنسيق: article
منشور في: 2023
الموضوعات:
الوصول للمادة أونلاين:http://dx.doi.org/10.1016/j.aej.2023.08.005
https://www.sciencedirect.com/science/article/pii/S1110016823006798
http://hdl.handle.net/10576/53438
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الوصف
الملخص:This 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.