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Numerical Simulation and Visualization of Plug Truncation Effects on Supersonic Turbulent Flow in a Conical Aerospike Nozzle

Abstract

Truncation of aerospike plug nozzles in high-speed propulsion has become widely adopted to reduce structural length and cooling demands. However, it introduces a low-pressure base region and wake losses which can offset performance gains. To explore possible improvements to this mode of propulsion, we present a numerical assessment of truncated conical aerospike nozzles at four plug-length ratios (40%, 50%, 62.5% and 75%) operating at nozzle pressure ratios and . Two-dimensional axisymmetric Reynolds-averaged Navier–Stokes turbulent gas dynamic simulations were performed for supersonic gas dynamics in ANSYS Fluent using a density-based solver with the SST turbulence model. Grid independence was established prior to the parametric study. Flow characteristics were quantified i.e. Mach number contours, static pressure fields, base pressure recovery trends, and net axial thrust/thrust coefficient comparisons. Results show that base pressure recovery increases with plug length; however, thrust does not improve monotonically with truncation ratio. Across both NPR conditions, the 50% truncated configuration delivered the highest net axial thrust (4556.82 N at ; 5204.34 N at ), indicating an optimum compromise between wake/base losses and expansion effectiveness. A simple idealised thrust estimate was used as a consistency check; as expected, CFD predicts lower effective performance due to base/wake losses and viscous/shock effects. The novelties of the present study include a generalization of the plug-length ratios (40%, 50%, 62.5% and 75%), operating at nozzle pressure ratios and , inclusion of a sophisticated turbulence model, and the extensive visualization of multiple scenarios to capture key gas dynamic characteristics, which provide a detailed insight into modern supersonic aerospace propulsion.

Keywords

Aerospike rocket nozzle gas dynamics, Mach contours, Nozzle pressure ratio (NPR), SST k"-" ω turbulence model, Base pressure recovery, ANSYS FLUENT, Wake losses

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