Vapor generation is central to the flow dynamics within fuel injector nozzles. Because the degree of atomization affects engine emissions and spray characteristics, quantification of phase change within diesel fuel injectors is a topic of design interest. Within the nozzle, the large pressure gradient between the upstream and downstream plena induce large velocities, creating separation and further pressure drop at the inlet corner. When local pressure in the throat drops below the fluid vapor pressure, phase change can occur with sufficient time. At the elevated temperatures present in diesel engines, this process can be dependent upon the degree of superheat, motivating the modeling of heat transfer from the wall.
By modeling cavitation and flash boiling phenomena as a departure from equilibrium conditions, the HRMFoam model accurately reproduces canonical adiabatic flows. An experimentally determined relaxation time controls the rate at which vapor is generated, and includes model constants tuned for water and a diesel fuel surrogate. The model is shown to perform well for several benchmark experimental cases, including the work of Reitz, Lichtarowicz, and Nurick.
With the implementation of the Farve-averaged energy equation, the present work examines and validates the transport of enthalpy through the fixed heat flux and fixed wall temperature boundary conditions. The pipe heat transfer experiments of Boelter and Allen are replicated using the kEpsilon, Realizable kEpsilon, and Spalart-Allmaras models. With proper turbulence model selection, Allen's heat transfer coefficient data is reproduced within 2.9%. Best-case bulk temperature rise prediction is within 0.05%. Boelter's bulk temperature rise is reproduced within 16.7%. Turbulent diffusivity is shown to determine radial enthalpy distribution.
Identifer | oai:union.ndltd.org:UMASS/oai:scholarworks.umass.edu:masters_theses_2-1083 |
Date | 07 November 2014 |
Creators | Shields, Bradley J |
Publisher | ScholarWorks@UMass Amherst |
Source Sets | University of Massachusetts, Amherst |
Detected Language | English |
Type | text |
Format | application/pdf |
Source | Masters Theses |
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