A new computational method is developed for reliable prediction of the impact erosion produced by dense submerged slurry jets. Predicting erosion of dense slurry flows is complex for a number of reasons, including the high computational cost of the two-phase flow models based on the Lagrangian tracking of the particles’ trajectories, the lack of comprehensive models for particle-particle interactions and the lack of confidence in the validity of empirical erosion correlations. A possible frame of work for overcoming these flaws is proposed, consisting in the joint use of a computational approach developed by Messa and Malavasi (2018) for simulating efficiently the fluid dynamic characteristics of dense slurries in the proximity of an eroding wall, and of a strategy proposed by Mansouri et al. (2015a) for calibrating an empirical erosion correlation based on a limited set of numerical and experimental results. Validation against original experimental data confirmed that the combination of the two methods has the potential to be a reliable predictive tool for design purposes, thereby being worthy of consideration for further improvement.
Numerical prediction of the impact erosion produced by dense slurry jets
G. V. Messa;S. Malavasi;
2019-01-01
Abstract
A new computational method is developed for reliable prediction of the impact erosion produced by dense submerged slurry jets. Predicting erosion of dense slurry flows is complex for a number of reasons, including the high computational cost of the two-phase flow models based on the Lagrangian tracking of the particles’ trajectories, the lack of comprehensive models for particle-particle interactions and the lack of confidence in the validity of empirical erosion correlations. A possible frame of work for overcoming these flaws is proposed, consisting in the joint use of a computational approach developed by Messa and Malavasi (2018) for simulating efficiently the fluid dynamic characteristics of dense slurries in the proximity of an eroding wall, and of a strategy proposed by Mansouri et al. (2015a) for calibrating an empirical erosion correlation based on a limited set of numerical and experimental results. Validation against original experimental data confirmed that the combination of the two methods has the potential to be a reliable predictive tool for design purposes, thereby being worthy of consideration for further improvement.File | Dimensione | Formato | |
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