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@article{147143,
        author = {M AYAZ AFSAR and ashish mahalle},
        title = {Experimental and Neural Network Based Investigation on Externally Scavenged S.I.Engine},
        journal = {International Journal of Innovative Research in Technology},
        year = {},
        volume = {5},
        number = {5},
        pages = {7-10},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=147143},
        abstract = {The present research describes experimental investigation and ANN simulation of two-stroke externally scavenged engine.The two stroke engine is relatively small and has higher Power to weight ratio, simplicity of operation and less cost.  However these engines have high exhaust emission and low brake thermal efficiency due to short circuiting losses and incomplete combustion.To eliminate short circuiting losses,externally scavenged engine is developed in I.C.Engine laboratory.In this study, effects of externally scavenged system on performance and emissions of two stroke engine is investigated at different loads and speeds with ANN simulation.Performance of  externally scavenged engine is compared with crank-cased scavenged engine.Result show that brake power and brake thermal effeciency of externally scavenged engine is improved due to supply of leaner air-fuel mixture to the engine.Simulation of  engine  shows the authenticity of the  investigation carried out experimentally.},
        keywords = {Artificial Neural Network ,Brake power, Externally scavenged engine,Emission  Analysis},
        month = {},
        }