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Roughness effect modelling for wall resolved RANS – Comparison of methods for marine hydrodynamics
FLOWTECH International AB, Sweden; Chalmers University of Technology, Sweden.
RISE Research Institutes of Sweden, Safety and Transport, Maritime department. (SSPA)ORCID iD: 0000-0002-6266-2320
Chalmers University of Technology, Sweden; ISYD AB International School of Yacht Design, Sweden.
2022 (English)In: Ocean Engineering, ISSN 0029-8018, E-ISSN 1873-5258, Vol. 266, article id 112778Article in journal (Refereed) Published
Abstract [en]

This paper deals with several aspects of surface roughness modelling in RANS codes applied to full-scale ship simulations. To select a method that is suitable for wall-resolved RANS solvers and gives reliable results at high Reynolds numbers, five different roughness models are compared. A grid uncertainty analysis is performed and the sensitivity to the grid resolution close to the wall (y+) is investigated. The results are compared to extrapolated results of experiments carried out with rough plates with various heights and roughness types. A correlation factor between the Average Hull Roughness and the equivalent sand roughness height is investigated, and a value of five is deemed the most suitable. The work suggests that the Aupoix-Colebrook roughness model gives the best results for full-scale ship simulations, at least with the current code, and that the near-wall grid resolution required for smooth surfaces can be applied also for the rough case. © 2022 The Authors

Place, publisher, year, edition, pages
Elsevier Ltd , 2022. Vol. 266, article id 112778
Keywords [en]
CFD, Full-scale, Hull, RANS, Roughness, Ship, Uncertainty, Verification, Hulls (ship), Navier Stokes equations, Reynolds number, Uncertainty analysis, Comparison of methods, Effect model, Grid resolution, Roughness effects, Roughness models, Ship simulation, Surface roughness, hydrodynamics, modeling, wall
National Category
Mechanical Engineering
Identifiers
URN: urn:nbn:se:ri:diva-61267DOI: 10.1016/j.oceaneng.2022.112778Scopus ID: 2-s2.0-85140272104OAI: oai:DiVA.org:ri-61267DiVA, id: diva2:1713853
Note

Funding details: Vetenskapsrådet, VR, 2016–07213; Funding details: Energimyndigheten; Funding text 1: The authors declare the following financial interests/personal relationships which may be considered as potential competing interests: Michal Orych reports financial support was provided by Energimyndigheten (Swedish Energy Agency). Michal Orych reports a relationship with FLOWTECH International AB that includes: board membership and employment.; Funding text 2: The authors would like to thank Swedish Energy Agency for the financial support. The computations were enabled by resources provided by the Swedish National Infrastructure for Computing (SNIC) at C3SE, partially funded by the Swedish Research Council through grant agreement no. 2016–07213.

Available from: 2022-11-28 Created: 2022-11-28 Last updated: 2023-04-28Bibliographically approved

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