Tao Wang was born in the Shandong province of China. He obtained his BS in Thermal Energy and Power Engineering from Beijing Jiaotong University in 2012. He then pursued a PhD in Vehicle Engineering. While a PhD candidate, he has established an experimental platform for studying a direct injection (DI) compressed natural gas (CNG) engine. He has investigated the influence of fuel injection pressure, injection timing, and spark ignition timing in order to improve engine performance through direct injection in gaseous engines.
Beyond experimentation, Tao has worked on using large-eddy simulation methods to numerically study charge flow, high-pressure gaseous injection, and the subsequent combustion process in DI CNG engines. This required the use of an automatic dynamic mesh algorithm especially designed for internal combustion engines. This algorithm was implemented and developed in open source code OpenFOAM along with the high-pressure gaseous injection model and the spark ignition model. The intrinsic mechanism of engine operation parameters such as fuel injection timing was investigated numerically in great detail.
Currently, Tao is a visiting student in the Green Group at MIT. He remain in the group until August 2017. He is learning how to generate a detailed reaction mechanism, specifically focusing on the reaction kinetics of methane. Eventually, he hopes to develop a reduced mechanism for predicating NO formation and soot production in DI CNG engine based on his experience in Green Group.