Government regulations on vehicle tailpipe emissions have steadily become more stringent
in the last few decades, mainly to reduce gaseous and particulate pollutants from internal …

Gasoline compression ignition (GCI) engines are considered an attractive alternative to
traditional spark-ignition and diesel engines. In this work, a Machine Learning-Grid Gradient …

An optimized active pre-chamber geometry was obtained by combining computational fluid
dynamics (CFD) and machine learning (ML). A heavy-duty engine operating with methane …

Hybrid-electric powertrains have been gaining tremendous interest to propel unmanned
aerial vehicles (UAVs) for Advanced Air Mobility. Present UAV powertrains are designed …

In this study, the combustion system of a light-duty compression ignition engine running on a
market gasoline fuel with Research Octane Number (RON) of 91 was optimized using …

A novel design optimization approach (ActivO) that employs an ensemble of machine
learning algorithms is presented. The proposed approach is a surrogate-based scheme …

In recent years, the use of machine learning-based surrogate models for computational fluid
dynamics (CFD) simulations has emerged as a promising technique for reducing the …

Combustion efficiency and exhaust emission of the compression-ignition engines are highly
dependent on the combustion chamber design. In this study, shape optimization was …

The use of machine learning (ML)-based surrogate models is a promising technique to
significantly accelerate simulation-driven design optimization of internal combustion (IC) …

The application of thermal barrier coatings (TBCs) for internal combustion engines has
drawn more research attention in recent years due to the improved coating technology and …