Uncertainty due to discretization on the ALE algorithm for predicting water slamming loads

Abstract Numerical uncertainty due to discretization on the Arbitrary Lagrangian-Eulerian (ALE) Finite Element method is investigated in the study. The paper quantifies uncertainty using two ITTC recommended methods, and also applies a constant Courant-Friedrichs-Lewy (CFL) number based discretization approach, instead of performing the independent grid and time-based discretization recommended by ITTC. As a case study, water entry of a flat bottom rigid and flexible plate is simulated considering various entry velocities. The total slamming loads and structural responses on both the rigid and elastic bottom plates are predicted and validated against available experimental data. Results indicate that numerical errors due to discretization differ in the various parameters and from case to case. They do affect the analysis of slamming loads and associated structural responses, and the hydroelasticity analysis as well. The hydroelasticity effects on the slamming force generally increase as the entry velocity increases, however, the quantitative results differ much for models with different grids. For example, when the hydroelasticity effect is estimated using the finer model, the deviation of the total slamming force on the elastic plate relative to the one on the rigid body are 56%, 57%, and 63% respectively for the three constant entry velocities, whereas the estimations are −27%, −4% and 3% with the coarser model. The study concludes that the uncertainty due to discretization in ALE is not just case-specific, but also parameter specific. The uncertainty quantification procedures with a constant CFL number based refinement are recommended to investigate the uncertainty comparing to the individual grid and time step study, in particular for the ALE solution where the time step is adjusted automatically as the grid changes. Thus, consideration should be given to updating the ITTC guidelines to incorporate the constant CFL based discretization approach.

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