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Coal gasification technology has the potential to reduce the environmental impact of coal power by enabling technologies like integrated gasification combined cycle (IGCC) and carbon capture for sequestration (CCS) for power generation. Numerical simulations of the various components of a coal gasification plant using validated CFD models enables faster configuration improvement cycles and thereby increased component performance, reliability, and overall cycle efficiency. Many such computations require the simulation of turbulent, multi-phase flows where the atomization and agglomeration of liquids play a critical role in plant processes. This paper focuses on the development and validation of a stochastic droplet breakup and agglomeration model for use in a steady-state RANS simulation of a liquid jet in a turbulent cross-flow. The models aim to accurately predict the trajectories and sizes of liquid droplets without incurring the computational cost of more expensive methodologies such as LES or VOF which are currently too computationally intensive to be used in the design cycle. The model builds on similar models proposed by Apte and Kuan by proposing a new probability density function (PDF) for the break-up process and adapting the methodology to a steady-state framework. The model is then validated against measurements made by Wu. The model shows good qualitative and quantitative agreement with measurement of the downstream mass flux distribution of the liquid droplets. An agglomeration model is added to the simulation which improves the agreement between predicted and measured Sauter-mean diameter (SMD) of the liquid droplets downstream of the initial atomization region.

Validation of a stochastic droplet breakup model applied to a liquid jet in turbulent crossflow