RANS modeling for particle transport and deposition in turbulent duct flows: Near wall model uncertainties

• Near-wall modeling uncertainties in the RANS particle transport and deposition are addressed in a turbulent duct flow.
• Discrete Random Walk (DRW) model and Continuous Random Walk (CRW) model performances are tested.
• Several near-wall anisotropic model accuracy is assessed.
• Numerous sensitivity studies are performed to recommend a robust, well-validated near-wall model for accurate particle deposition predictions.

Dust accumulation in the primary system of a (V)HTR is identified as one of the foremost concerns during a potential accident. Several numerical efforts have focused on the use of RANS methodology to better understand the complex phenomena of fluid–particle interaction at various flow conditions. In the present work, several uncertainties relating to the near-wall modeling of particle transport and deposition are addressed for the RANS approach. The validation analyses are performed in a fully developed turbulent duct flow setup. A standard k − ɛ turbulence model with enhanced wall treatment is used for modeling the turbulence. For the Lagrangian phase, the performance of a continuous random walk (CRW) model and a discrete random walk (DRW) model for the particle transport and deposition are assessed. For wall bounded flows, it is generally seen that accounting for near wall anisotropy is important to accurately predict particle deposition. The various near-wall correlations available in the literature are either derived from the DNS data or from the experimental data. A thorough investigation into various near-wall correlations and their applicability for accurate particle deposition predictions are assessed. The main outcome of the present work is a well validated turbulence model with optimal near-wall modeling which provides realistic particle deposition predictions.