Review and comparison of methods to model ship hull roughness Show others and affiliations
2020 (English) In: Applied Ocean Research, ISSN 0141-1187, E-ISSN 1879-1549, Vol. 99, article id 102119Article in journal (Refereed) Published
Abstract [en]
There is a large body of research available focusing on how ship hull conditions, including various hull coatings, coating defects, and biofouling, influence the boundary layer, and hence resistance and wake field of a ship. Despite this there seems to be little consensus or established best practice within the ship design community on how to model hull roughness for ship-scale CFD. This study reviews and compares proposed methods to model hull roughness, to support its use in the ship design community. The impact of various types of roughness on additional resistance and wake fields are computed and presented for the well-established test case KVLCC2. The surfaces included in the review are divided into three groups: 1) high quality, newly painted surfaces, 2) surfaces with different extent of poor paint application and/or hull coating damages; and 3) surfaces covered with light slime layers. The review shows the use of a variety of roughness functions, both Colebrook-type and inflectional with three distinct flow regimes, as well as a variety of strategies to obtain the roughness length scales. We do not observe any convergence within the research community towards specific roughness functions or methods to obtain the roughness length scales. The comparison using KVLCC2 clearly illustrates that disparities in surface texture cause large differences in additional resistance, and consequently no strong correlation to a single parameter, e.g. AHR (Average Hull Roughness). This implies that, to be able to select a suitable hull roughness model for a CFD-setup, more details of the surface characteristics are required, such as hydrodynamic characterization of hull coating and expected fouling. © 2020 The Authors
Place, publisher, year, edition, pages Elsevier Ltd , 2020. Vol. 99, article id 102119
Keywords [en]
Fouling, Hull roughness, KVLCC2, Roughness function, Ship-scale CFD, Boundary layers, Coatings, Computational fluid dynamics, Electromagnetic wave propagation in plasma, Ship models, Shipbuilding, Surface roughness, Textures, Wakes, Additional resistances, Comparison of methods, Hydrodynamic characterization, Paint applications, Research communities, Strong correlation, Surface characteristics, Hulls (ship), comparative study, hull, literature review, numerical model, roughness, shipping
National Category
Mechanical Engineering
Identifiers URN: urn:nbn:se:ri:diva-71843 DOI: 10.1016/j.apor.2020.102119 Scopus ID: 2-s2.0-85083896369 OAI: oai:DiVA.org:ri-71843 DiVA, id: diva2:1839257
Note Funding details: National Science Council, NSC; Funding details: Energimyndigheten, 38849-1, 38849-2; Funding details: Trafikverket, TRV 2018/76560; Funding text 1: This research is supported by the Swedish Energy Agency (grant number 38849-1 and 38849-2 ), the Swedish Transport Administration (grant number TRV 2018/76560 ) and Kongsberg Maritime Sweden through the University Technology Centre in Computational Hydrodynamics hosted by the Department of Mechanics and Maritime Sciences at Chalmers. The simulations were performed on resources at Chalmers Centre for Computational Science and Engineering (C3SE) and National Supercomputer Centre in Sweden (NSC), both provided by the Swedish National Infrastructure for Computing (SNIC).; Funding text 2: This research is supported by the Swedish Energy Agency (grant number 38849-1 and 38849-2), the Swedish Transport Administration (grant number TRV 2018/76560) and Kongsberg Maritime Sweden through the University Technology Centre in Computational Hydrodynamics hosted by the Department of Mechanics and Maritime Sciences at Chalmers. The simulations were performed on resources at Chalmers Centre for Computational Science and Engineering (C3SE) and National Supercomputer Centre in Sweden (NSC), both provided by the Swedish National Infrastructure for Computing (SNIC).
2024-02-202024-02-202024-02-20 Bibliographically approved