The standard capability of engine experimental studies is that ensemble averaged quantities like in-cylinder pressure from multiple cycles and emissions are reported and the cycle to cycle variation (CCV) of indicated mean effective pressure (IMEP) is captured from many consecutive combustion cycles for each test condition. However, obtaining 3D spatial distribution of all the relevant quantities such as fuel-air mixing, temperature, turbulence levels and emissions from such experiments is a challenging task. Computational Fluid Dynamics (CFD) simulations of engine flow and combustion can be used effectively to visualize such 3D spatial distributions. A dual fuel engine is considered in the current study, with manifold injected natural gas (NG) and direct injected diesel pilot for ignition. Multiple engine cycles in 3D are simulated in series like in the experiments to investigate the potential of high fidelity RANS simulations coupled with detailed chemistry, to accurately predict the CCV.
Cycle to cycle variation (CCV) is expected to be due to variabilities in operating and boundary conditions, in-cylinder stratification of diesel and natural gas fuels, variation in in-cylinder turbulence levels and velocity flow-fields. In a previous publication by the authors [