Ship-scale CFD benchmark study of a pre-swirl duct on KVLCC2
Journal article, 2022

Installing an energy saving device such as a pre-swirl duct (PSD) is a major investment for a ship owner and prior to an order a reliable prediction of the energy savings is required. Currently there is no standard for how such a prediction is to be carried out, possible alternatives are both model-scale tests in towing tanks with associated scaling procedures, as well as methods based on computational fluid dynamics (CFD). This paper summarizes a CFD benchmark study comparing industrial state-of-the-art ship-scale CFD predictions of the power reduction through installation of a PSD, where the objective was to both obtain an indication on the reliability in this kind of prediction and to gain insight into how the computational procedure affects the results. It is a blind study, the KVLCC2, which the PSD is mounted on, has never been built and hence there is no ship-scale data available. The 10 participants conducted in total 22 different predictions of the power reduction with respect to a baseline case without PSD. The predicted power reductions are both positive and negative, on average 0.4 %, with a standard deviation of 1.6 %-units, when not considering two predictions based on model-scale CFD and two outliers associated with large uncertainties in the results. Among the variations present in computational procedure, two were found to significantly influence the predictions. First, a geometrically resolved propeller model applying sliding mesh interfaces is in average predicting a higher power reduction with the PSD compared to simplified propeller models. The second factor with notable influence on the power reduction prediction is the wake field prediction, which, besides numerical configuration, is affected by how hull roughness is considered.

KVLCC2

Pre-Swirl Duct

Benchmark study

Ship-scale CFD

Author

Jennie Andersson

Chalmers, Mechanics and Maritime Sciences (M2), Marine Technology

Abolfazl Shiri

Hydrodynamics

Rickard Bensow

Chalmers, Mechanics and Maritime Sciences (M2), Marine Technology

Jin Yixing

China Ship Scientific Research Center

Wu Chengsheng

China Ship Scientific Research Centre (CSSRC)

Qiu Gengyao

China Ship Scientific Research Center

Ganbo Deng

École Centrale de Nantes

Patrick Queutey

École Centrale de Nantes

Yan Xing-Kaeding

Hamburg Ship Model Basin (HSVA)

Peter Horn

Hamburg Ship Model Basin (HSVA)

Thomas Lücke

Hamburg Ship Model Basin (HSVA)

Hiroshi Kobayashi

National Maritime Research Institute

Kunihide Ohashi

National Maritime Research Institute

Nobuaki Sakamoto

National Maritime Research Institute

Fan Yang

State Key Laboratory of Navigation and Safety Technology

Gao Yuling

State Key Laboratory of Navigation and Safety Technology

Björn Windén

Shortcut CFD

M. Meyerson

University of Michigan

Kevin Maki

University of Michigan

Stephen Turnock

University of Southampton

Dominic Hudson

University of Southampton

Joseph Banks

University of Southampton

Momchil Terziev

University of Strathclyde

Tahsin Tezdogan

University of Strathclyde

Florian Vesting

Chalmers, Mechanics and Maritime Sciences (M2), Marine Technology

Takanori Hino

Yokohama National University

Sofia Werner

SSPA Sweden AB

Applied Ocean Research

0141-1187 (ISSN)

Vol. 123 103134

Improved prediction methods for ships –Energy Saving Devices

Swedish Transport Administration (EF1015,ärende6770), 2019-01-01 -- 2021-12-31.

Subject Categories

Vehicle Engineering

Fluid Mechanics and Acoustics

DOI

10.1016/j.apor.2022.103134

More information

Latest update

4/11/2022