Abstract The present work uses a hybrid Navier–Stokes (NS) and Direct Monte Carlo Simulation (DSMC) with a one-way coupling strategy to simulate a steady-state cold nitrogen flow expanding from a highly pressurised millimetre-sized nozzle into the vacuum. Such methodology was experienced in the context of micro-thrusters by Grabe et al. or La Torre et al.. However, it has some limitations regarding the computational cost as well as the coupling strategy that prevent its use for industrial cases. More specifically, according to common criteria, the area close to the inner nozzle exit wall is defined as a rarefied area with strong gradients and high density involving heavy DSMC computational cost. Moreover, the one-way method requires a supersonic condition at the interface between rarefied and continuous flows, which is not verified close to the nozzle wall. The present study aims to optimise the hybrid methodology by removing the inner nozzle area from the rarefied calculation and studying the influence of the continuous to rarefied flow interface definition. In order to remain as close as possible to the rarefied physics, a Maxwell wall condition is used during NS calculation as an attempt to reproduce the wall bounce on velocity and temperature that might be yielded by rarefied effects. The methodology shows good agreement with micro-thruster available data and its optimisation allows a significant computational cost decrease.

    Highlights The Maxwell wall condition improves nearly rarefied flow Navier–Stokes simulations. Evaluation of continuous to rarefied interface influence. Identification of high angle flow expansion origin. Computation time reduced by new interface definition.


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    Title :

    Optimisation of a hybrid NS–DSMC methodology for continuous–rarefied jet flows


    Contributors:

    Published in:

    Acta Astronautica ; 195 ; 295-308


    Publication date :

    2022-03-06


    Size :

    14 pages




    Type of media :

    Article (Journal)


    Type of material :

    Electronic Resource


    Language :

    English




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