Testing a simple velocity fluctuation model for one-dimensional simulations of shock-wave particle cloud interaction

FFI-Report 2020

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20/00616

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978-82-464-3277-9

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Bernhard Nornes Lotsberg Andreas Nygård Osnes
Airborne dispersal of toxic substancres in populated regions is a central research topic at the Norwegian Defence Research Establishment (FFI). Such an event can be the result of accidents in industrial areas or during transport. Acts of terrorism are also a possible source of such releases. The ability to model airborne dispersion with sufficient accuracy makes it possible to characterize the threath such events pose. Such modelling can also be used to be better prepared and respond appropriately to an event. This report is a part of a research project that aims to improve models for simulation of dispersal of toxic substances by means of explosive devices. Specifically, this work is part of a research effort to improve models for computing the movement of solid particles under shock-wave acceleration. The purpose of this study is to test a model for velocity fluctuation correlations caused by particle wakes in simulations of shock particle-cloud interactions. Velocity fluctuations are dynamically important in such flows, and accurate models for their correlations are therefore necessary. Improved models for shock wave particle-cloud interaction enable more accurate simulations of various important applications such as shock wave mitigation, explosive dissemination of powders and liquids, heterogeneous explosives and liquid/solid fuel combustion systems. In this work, we have implemented the velocity fluctuation model in an in-house finite-volume Eulerian-Lagrangian compressible flow solver, which is based on the volume-averaged Navier-Stokes equations. The model can be expressed ˜R ˜ u2 Csep p ����� Csep p ; where ˜R is the velocity fluctuation correlation, ˜ u is the mean flow velocity, and p = 1 ����� , where is the gas volume fraction. The model has one parameter, Csep, which we estimate using the ABC-SMC algorithm based on results from a particle-resolved simulation of the same system. Application of the ABC-SMC algorithm for parameter estimation is an interesting approach since the estimated value is optimal for the specific implementation of the dispersed flow model. Depending on whether we use an approximate drag law or the actual forces from the particleresolved simulations, the parameter is estimated to Csep = 1:4 and Csep = 1:6 respectively. The physical meaning of these values is that the average volume of the separated flow behind each particle is 1:4 or 1:6 times larger than the particle volume. The dependence of the estimated parameter value to the choice of drag law implies that to get a physically meaningful value for Csep, we need to use a drag law that accurately represents both the transient and quasi-steady forces on the particles.

About publication

Report number

20/00616

ISBN

978-82-464-3277-9

Format

PDF-document

Size

800.9 KB

Download publication

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