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Sub-cooled and flashing liquid jets and droplet dispersion I. Overview and model implementation/validation
Authors:Henk WM Witlox  Mike Harper  Adeyemi Oke  Philip J Bowen  Peter Kay
Institution:1. Department of Mechanical and Automotive Engineering, Kingston University London, London SW15 3DW, UK;2. School of Engineering, University of Warwick, Coventry, UK
Abstract:Many accidents involve two-phase releases of hazardous chemicals into the atmosphere. This paper describes the results of a third phase of a Joint Industry Project (JIP) on liquid jets and two-phase droplet dispersion. The aim of the project is to increase the understanding of the behaviour of sub-cooled non-flashing and superheated flashing liquid jets, and to improve the prediction of initial droplet size, droplet dispersion and rainout.Phase III of the JIP first included scaled experiments for materials with a range of volatilities (water, cyclohexane, butane, propane and gasoline). These experiments were carried out by Cardiff University including measurements of flow rate and initial droplet size across the full relevant range of superheats. See the companion paper II for further details of these experiments and the derivation of new refined correlations for droplet size distribution and Sauter Mean Diameter. Furthermore large-scale butane experiments were carried out by INERIS (France) to ensure that for more realistic scenarios the derived droplet size correlations are accurate.Model validation and model improvements were carried out by DNV Software, including validation of release rate and initial droplet size against the above scaled and large-scale experiments. New correlations for droplet size distribution and Sauter Mean Diameter (SMD) were implemented into the Phast discharge model. These were compared against a range of other droplet size and rainout correlations published in the literature, in conjunction with validation against an extensive set of experiments. It was shown that the new droplet size correlation agrees better against experimental data than the existing Phast correlation. To further improve the rainout prediction, the Phast dispersion model (UDM) was also extended to allow simultaneous modelling of a range of droplet sizes and distributed rainout (rather than rainout at one point).
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