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Fluid flow in an internal combustion engine presents one of the most
challenging fluid dynamics problems to model. This is because the flow is associated
with large density variations. So, a detailed understanding of the flow and combustion
processes is required to improve performance and reduce emissions without compromising
fuel economy. The simulation carried out in the present work to model DI diesel
engine with bowl in piston for better understanding of the in cylinder gas motion
with details of the combustion process that are essential in evaluating the effects
of ingesting synthetic atmosphere on engine performance. This is needed for the
course of developing a non-air recycle diesel with exhaust management system .
A simulation was carried out using computational fluid dynamics (CFD) code FLU- ENT. The
turbulence and combustion processes are modeled with sufficient generality to include
spray formation, delay period, chemical kinetics and on set of ignition. Results
from the simulation compared well with that of experimental results. The model proved
invaluable in obtaining details of the in cylinder flow patterns, combustion process
and combustion species during the engine cycle. The results show that the model
over predicting the maximum pressure peak by 6%, (p-θ), (p-v) diagrams for different engine loads
are predicted. Also the study shows other engine parameters captured by the simulation
such as engine emissions, fuel mass fraction, indicated gross work, ignition delay
period and heat release rate.
In this paper we present a full-geometry Computational Fluid Dynamics (CFD) modeling of air flow distribution from an automotive engine cooling fan. To simplify geometric modeling and mesh generation, different solution domains have been considered, the Core model, the Extended-Hub model, and the Multiple Reference Frame (MRF) model. We also consider the effect of blockage on the flow and pressure fields. The Extended-Hub model simplifies meshing without compromising accuracy. Optimal locations of the computational boundary conditions have been determined for the MRF model. The blockage results in significant difference in pressure rise, and the difference increases with increasing flow rates. Results are in good agreement with data obtained from an experimental test facility. Finally, we consider Simplified Fan Models which simplifies geometric modeling and mesh generation and significantly reduce the amount of computer memory used and time needed to carry out the calculations. Different models are compared in regards to efficiency and accuracy. The effect of using data from different planes is considered to optimize performance. The effect of blockage on simplified models is also considered.