An experimental and numerical study of impinging, incompressible, axisymmetric, laminar jets is described, where the jet axis of symmetry is aligned normal to the wall. Particle streak velocimetry ͑PSV͒ is used to measure axial velocities along the centerline of the flow field. The jet-nozzle pressure drop is measured simultaneously and determines the Bernoulli velocity. The flow field is simulated numerically by an axisymmetric Navier-Stokes spectral-element code, an axisymmetric potential-flow model, and an axisymmetric onedimensional stream-function approximation. The axisymmetric viscous and potential-flow simulations include the nozzle in the solution domain, allowing nozzle-wall proximity effects to be investigated. Scaling the centerline axial velocity by the Bernoulli velocity collapses the experimental velocity profiles onto a single curve that is independent of the nozzle-to-plate separation distance. Axisymmetric direct numerical simulations yield good agreement with experiment and confirm the velocity profile scaling. Potential-flow simulations reproduce the collapse of the data; however, viscous effects result in disagreement with experiment. Axisymmetric one-dimensional stream-function simulations can predict the flow in the stagnation region if the boundary conditions are correctly specified. The scaled axial velocity profiles are well characterized by an error function with one Reynolds-number-dependent parameter. Rescaling the wall-normal distance by the boundary-layer displacement-thickness-corrected diameter yields a collapse of the data onto a single curve that is independent of the Reynolds number. These scalings allow the specification of an analytical expression for the velocity profile of an impinging laminar jet over the Reynolds number range investigated of 200ഛ Re ഛ 1400.
Fuel-air mixing in a direct injection spark ignition (DISI) engine occurs in a highly unsteady, turbulent and three-dimensional flow. As a result, any cycle-to-cycle unsteady variation in the mixing process can directly impact the performance of the DISI engine. To study the unsteady process in these engines, we have developed and implemented a large-eddy simulation (LES) approach with an innovative subgrid scalar mixing model based on the linear-eddy mixing (LEM) model into a commercial IC engine code (KIVA-3V). Time-averaged results of the simulations using the new LES version (KIVALES) are compared to the steady-state predictions of the original KIVA-3V. Significantly different in-cylinder turbulent fuel-air mixing is predicted by these two methods. Analysis shows that KIVALES resolves spatial features larger than the grid and that the subgrid kinetic energy adjusts to the LES resolution. As a result, KIVALES captures a highly unsteady, anisotropic fuel-air mixing process whereas a more diffused mixed field is predicted by the original KIVA-3V. This ability of KIVALES is attributed to the subgrid closure which scales the subgrid dissipation with the local grid size and thus, decreases the overall dissipation in the flow.
The process of fuel-air mixing in the Direct Injection Spark Ignition (DISI) engine is highly unsteady and three-dimensional with wide cycle-to-cycle variations involving vaporization of droplets and its interaction with large-scale turbulent flow field. Although the majority of the past numerical studies of mixing in an Internal Combustion (IC) engines have employed Reynolds-Averaged Navier-Stokes (RANS) equations with empirical turbulence model, here we have implemented a Large-Eddy Simulations (LES) with the Linear-Eddy Model (LEM) for subgrid scalar mixing into a commercial IC engine simulation code (KIVA-3V). This study shows that when time-accurate effects are included significantly different results are obtained. These differences between the original KTVA-3V and the new KIVALES in predicting the in-cylinder turbulent fuel-air mixing are discussed. LES shows highly unsteady, anisotropic in-cylinder fuel-air mixing process compared to the original KIVA-3V. The implications for combustion is also discussed.
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