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Development of a CFD Solver for Primary Diesel Jet Atomization in FOAM-Extend
Technical Paper
2019-24-0128
ISSN: 0148-7191, e-ISSN: 2688-3627
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English
Abstract
Ongoing development of a CFD framework for the simulation of primary atomization of a high pressure diesel jet is presented in this work. The numerical model is based on a second order accurate, polyhedral Finite Volume (FV) method implemented in foam-extend-4.1, a community driven fork of the OpenFOAM software. A geometric Volume-of-Fluid (VOF) method isoAdvector is used for interface advection, while the Ghost Fluid Method (GFM) is used to handle the discontinuity of the pressure and the pressure gradient at the interface between the two phases: n-dodecane and air in the combustion chamber. In order to obtain highly resolved interface while minimizing computational time, an Adaptive Grid Refinement (AGR) strategy for arbitrary polyhedral cells is employed in order to refine the parts of the grid near the interface. Dynamic Load Balancing (DLB) is used in order to preserve parallel efficiency during AGR. The combination of isoAdvector-GFM-AGR-DLB presents a unique framework for diesel jet atomization. The developed numerical framework is preliminarily tested on the Engine Combustion Network (ECN) Spray D geometry and conditions. The unstructured, mostly hexahedral grid is used with the base cell size of 40 micrometres. Four refinement levels are used in the close proximity of the interface in order to attempt to resolve break-up of droplets. The finest cells near the interface have the size of 2.5 micrometres. Part of the nozzle is also considered in the simulation in order to capture the developed jet profile at the entry into the combustion chamber. The temporal evolution of the jet is presented, along with the preliminary comparison of droplet statistics with available results.
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Vukcevic, V., Keser, R., Jasak, H., Battistoni, M. et al., "Development of a CFD Solver for Primary Diesel Jet Atomization in FOAM-Extend," SAE Technical Paper 2019-24-0128, 2019, https://doi.org/10.4271/2019-24-0128.Also In
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