Adaptive grid refinement for ship resistance computations. (15th April 2022)

• Record Type: Journal Article
• Authors: Wackers, Jeroen; Deng, Ganbo; Raymond, Clémence; Guilmineau, Emmanuel; Leroyer, Alban; Queutey, Patrick; Visonneau, Michel
• Is Part Of: Ocean engineering. Volume 250(2022)
• Publication Date: 2022-04-15
• Subjects: Mesh adaptation -- Ship resistance -- Uncertainty estimation -- Automated simulation; Ocean engineering -- Periodicals; Ocean engineering; Periodicals; 620.4162
• DOI: 10.1016/j.oceaneng.2022.110969
• Languages: English
• ISSNs: 0029-8018

Abstract

Abstract: This paper studies the possibility of using adaptive grid refinement for routine, automated simulations of ship resistance in calm water. With the increase in maturity and reliability of mesh adaptation methods, the main remaining challenge is the creation of straightforward, universal user guidelines which allow these computations to be run correctly, without resorting to trial and error to set the parameters. The paper uses the mesh adaptation in the flow solver ISIS-CFD. For this solver, a simulation protocol for resistance computation is proposed, which specifies for example the choice of the refinement criterion and the global mesh size. To investigate the reliability and generality of this protocol, it is fine-tuned on one test case and then applied unchanged to three different cases. The tests show that the solutions have good behaviour and compare well with experiments. Furthermore, numerical uncertainty estimation works for these cases, which increases the trustworthiness of the solutions. Where this is tested, the mesh adaptation produces the same solutions as traditional meshing methods with reduced computational costs. As such, it is shown that mesh adaptation for resistance computations is possible today on a routine basis and that it is advantageous compared with other meshing techniques. Highlights: Automated calm-water resistance simulation for displacement hulls is possible with adaptive mesh refinement. Series of meshes created with adaptive refinement provide excellent numerical uncertainty estimations. Compared with non-adapted meshes, the simulations are faster, simpler to perform, and more reliable.