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The collision of ships remains a significant cause of accidents, resulting in severe environmental consequences such as oil spillage from oil tankers. Enhancing the crashworthiness of ship structural design is crucial, and one approach being explored is the filling of the double hull structure with granular material [1]. Coating these particles with environmentally friendly materials can optimize their ability to absorb kinetic energy and transfer loads from the outer to the inner hull [2]. However, the mechanical behavior of the coated particles depends on the type of coating material, posing challenges in developing numerical simulation models. To address this, an open-source Discrete Element Method (DEM) code called MUSEN [3] is utilized to numerically model the behavior of coated particles. Furthermore, MUSEN can be extended using the Bonded Particle Method (BPM) to simulate particle breakage through solid bridges. However, the inclusion of coating material in the model increases the number of parameters, as well as computational time and cost. This requires a robust methodology to characterize the mechanical behaviour regardless of the type of coating material with reduced computational cost, keeping in mind the actual application inside the ship double hull. Sensitivity analyses and parametric studies are conducted to understand the effect of input parameters and identify the influential ones. Subsequently, algorithms such as the Particle Swarm Algorithm are employed for parameter optimization. Finally, models of different fidelity are used to compare the results from multi particle compression tests. The findings from these simulations will be presented in this contribution.
Published on 01/12/23
Volume Discrete and Particle Methods in Solid and Structural Mechanics, 2023
Licence: CC BY-NC-SA license
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