Sloshing Simulation of Single-Phase and Two-Phase SPH using DualSPHysics

*Andi Trimulyono orcid scopus  -  Department of Naval Architecture, Faculty of Engineering, Diponegoro University, Indonesia
S Samuel scopus  -  Department of Naval Architecture, Faculty of Engineering, Diponegoro University, Indonesia
Muhammad Iqbal orcid scopus  -  Department of Naval Architecture, Faculty of Engineering, Diponegoro University, Indonesia
Received: 22 Jan 2020; Revised: 31 May 2020; Accepted: 4 Jun 2020; Published: 30 Jun 2020; Available online: 14 Jun 2020.
Open Access License URL: http://creativecommons.org/licenses/by-sa/4.0

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Abstract

The sloshing phenomenon is one of the free surface flow that can endanger liquid cargo carriers such as ships. Sloshing is defined as the resonance of fluid inside a tank caused by external oscillation. When sloshing is close to the natural frequency of the tank it could endanger ships. Particle method has the advantages to be applied because sloshing is dealing with free surface. One of the particle methods is Smoothed Particle Hydrodynamics (SPH). In this study, compressible SPH was used as a result of the pressure oscillation, which exists because of the effect of density fluctuation as nature of weakly compressible SPH. To reduce pressure noise, a filtering method, Low Pass Filter,  was used to overcome pressure oscillation. Three pressure sensors were used in the sloshing experiment with a combination of motions and filling ratios. Only one pressure sensor located in the bottom was used to validate the numerical results. A set of SPH parameters were derived that fit for the sloshing problem. The SPH results show a good agreement with the experiment’s. The difference between SPH and experiment is under 1 % for sway, but a larger difference shows in roll. Low pass filter technique could reduce pressure noise, but comprehensive method needs to develop for general implementation.

Keywords: Sloshing; SPH; DualSPHysics; low pass filter

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Section: Research Articles
Language: EN
In Vol 17, No 2 (2020): June
Statistics: 733 290
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