Author(s): Fulkan Kafilah Al Husein; Nieldy Rejekinta Tarigan; Novan Tofany

Linked Author(s):

Keywords: Multiphase flow model; Computational Fluid Dynamics; Adaptive mesh refinement; Surrogate model; Sensitivity Analysis

Abstract: The authors previous study presents an adaptive mesh refinement (AMR) multi-variable integrated into a multiphase-CFD granular flow model to simulate subaerial landslide-induced wave phenomena to optimize the simulation by reducing the mesh. In the other hand, in term of optimizing the simulation, previous study also using parallel computing to maximize the computation capability. previous study presents an adaptive mesh refinement (AMR) multi-variable integrated into a multiphase-CFD granular flow model to simulate subaerial landslide-induced wave phenomena. The AMR approach dynamically adjusts mesh resolution in key areas, reducing computational overhead while maintaining accuracy. The results show that AMR maintains the static-mesh model accuracies while significantly improves computational efficiency. Selecting appropriate AMR parameters for optimal balance between model accuracy and efficiency are needed for revealing its full potential. Through an evaluation based on sensitivity analysis and surrogate model in serial computing mode, this study demonstrates that AMR’s performance can be further improved by optimizing its parameters. The results from the surrogate model have been shown to be consistent with those of the time-consuming conventional sensitivity analysis while giving more efficient alternatives for selecting the best configuration of optimized AMR parameters.

DOI:

Year: 2024