Numerical simulation of flash-boiling through sharp-edged orifices

Abstract

Flash boiling is the rapid phase change of a pressurised fluid that emerges to ambient conditions below its vapour pressure. Flashing of a flowing liquid through an orifice or a nozzle can occur either inside or outside the nozzle depending on the local pressure and geometry. Vapour generation during flashing leads to interfacial interactions that eventually influence the jet.Empirical models in the literature for simulating the inter-phase heat transfer employ many simplifying assumptions, which limits their applicability. Typical models, usually derived from cavitation, fail to describe the physics of heat and mass transfer, making them unreliable for flashing. The Homogeneous Relaxation Model (HRM) is a reliable model able to capture heat transfer under these conditions accounting for the non-equilibrium vapour generation. This approach uses a relaxation term in the transport equation for the vapour. On the basis of the generic compressible flow solver within the open source computational fluid dynamics (CFD) code OpenFOAM, the HRM has been implemented to create a dedicated new solver HRMSonicELSAFoam. An algorithm that links the standard pressure-velocity coupling algorithm to the HRM is used. In this method, a pressure equation is derived which employs the continuity equation including compressibility effects. A relaxation term has been defined such that the instantaneous quality would relax to the equilibrium value over a given timescale. Although it is possible to consider this timescale constant, it is calculated via an empirical correlation in the present study.Validations have been carried out by simulating two-phase flows through sharp-edged orifices. The relatively good agreement achieved has demonstrated that the solver accurately calculates the pressure and vapour mass fraction. This demonstrates the potential of HRMSonicELSAFoam for flash boiling simulations and predicting the properties of the subsequent flash atomisation.

A deep learning computational fluid dynamics solver for simulating liquid hydrogen jets

“…Both the upstream and downstream velocities demonstrated a more uniform flow and larger jet core than the previous case. Similar parabolic shape behavior has been also observed in Lyras et al 14 and Lyras et al 31 Figure 9 compares the axial velocity u with CFD and ML-CFD. Compared to the standard CFD solution, the ML approach captures the flow within the nozzle relatively well, with more significant differences occurring downstream the nozzle, where the ML-CFD gives a smaller jet core.…”

“…( 4) have not been tested before for hydrogen jets. Nevertheless, previous works for superheated R134A and liquid nitrogen 10,30,31 have shown that these expressions can be deployed for other fuels. The changes of the mixture are taken into account in the momentum equation as follows.…”

Machine-learning accelerated turbulence modelling of transient flashing jets

“…The value of Θ tends to decrease with increasing void fraction and non-dimensional pressure 21,23 . The HRM expressions have been used before for superheated R134A and liquid nitrogen 51,52 and are known to work for other superheated liquids as well such as iso-octane 53 and JP8 54 . The model has been shown to perform well without adjustment of constants either in the present work or in former efforts 23,53-55 .…”

Modelling and Simulation of Flash Evaporation of Cryogenic Liquids

“…This model considers the thermal non-equilibrium state of the flashing liquid by introducing a relaxation time and relating the evaporation rate to the deviation of the current mass fraction from an equilibrium value [3]. Finding a suitable description for the relaxation time is a challenging task, yet the model of Downar-Zapolski et al [12], which is an empirical fit to flashing water experiments, has shown a general applicability to several fluids and injection conditions [18,26,29,30]. Nevertheless, the model coefficients may require case specific adaptations which cannot be directly determined a priori and thus, model verification is required for each case [20,33].…”