Experimental and artificial neural network approach of noise and vibration characteristic of an unmodified diesel engine fuelled with conventional diesel, and biodiesel blends with natural gas addition


Celebi K. , Uludamar E. , TOSUN E. , YILDIZHAN Ş. , AYDIN K. , ÖZCANLI M.

FUEL, cilt.197, ss.159-173, 2017 (SCI İndekslerine Giren Dergi) identifier identifier

Özet

Replacing conventional diesel fuel has gained great interest owing to environmental issues. Therefore all effect of alternative fuels must be well-known in order to forthcoming engine development concern. In this study acoustic and vibration effect of biodiesel and their blends were investigated on an unmodified diesel engine which enriched with natural gas. Throughout this work, experimental engine was fuelled with conventional diesel, sunflower and canola biodiesel blends with ratio of 20% and 40%, by volume. Furthermore, natural gas was inducted through intake manifold at various flow rates; 5 L/min, 10 L/min, and 15 L/min with intake air. Experiments revealed that, compared to conventional diesel fuel, sunflower and canola biodiesels decreased sound pressure level and vibration of the test engine. Addition of natural gas decreased the values even more. Furthermore, exhaust emission of the engine has been evaluated. Beside experimental study, an artificial neural network model was developed in order to predict sound pressure level and vibration of the engine. Artificial neural network results showed that, generated models were capable of estimation of parameters with high accuracy. (C) 2017 Elsevier Ltd. All rights reserved.

Replacing conventional diesel fuel has gained great interest owing to environmental issues. Therefore all effect of alternative fuels must be well-known in order to forthcoming engine development concern. In this study acoustic and vibration effect of biodiesel and their blends were investigated on an unmodified diesel engine which enriched with natural gas. Throughout this work, experimental engine was fuelled with conventional diesel, sunflower and canola biodiesel blends with ratio of 20% and 40%, by volume. Furthermore, natural gas was inducted through intake manifold at various flow rates; 5 L/min, 10 L/min, and 15 L/min with intake air. Experiments revealed that, compared to conventional diesel fuel, sunflower and canola biodiesels decreased sound pressure level and vibration of the test engine. Addition of natural gas decreased the values even more. Furthermore, exhaust emission of the engine has been evaluated. Beside experimental study, an artificial neural network model was developed in order to predict sound pressure level and vibration of the engine. Artificial neural network results showed that, generated models were capable of estimation of parameters with high accuracy.