The University of Southampton
University of Southampton Institutional Repository

Ship-scale CFD benchmark study of a pre-swirl duct on KVLCC2

Ship-scale CFD benchmark study of a pre-swirl duct on KVLCC2
Ship-scale CFD benchmark study of a pre-swirl duct on KVLCC2
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.
Benchmark study, KVLCC2, Pre-swirl duct, Ship-scale CFD
0141-1187
Andersson, Jennie
2f7063f9-7f45-4ace-8817-532142f2775f
Shiri, Alex Abolfazl
f629e01c-bd00-4de3-9d78-e26bdd6581f3
Bensow, Rickard E
3d717f1e-beea-4fe7-b342-e95740dfb24e
Yixing, Jin
9edfcfa1-97e3-4d21-ae23-c1059cb5091a
Chengsheng, Wu
2011dd80-3779-4af5-a1a3-2750cc07be3b
Gengyao, Qiu
e07b30b9-1d43-470b-b37f-aa6b82639191
Deng, Ganbo
04adf582-1f64-4e2e-8a73-e385461d1aa9
Queutey, Patrick
638e816b-132f-4071-bd3a-95d613f8ce8e
Xing-Kaeding, Yan
487443f5-8a29-4658-8a24-92d2eec5eb1d
Horn, Peter
7f70e828-9531-4940-b67a-d26dac04d6fe
Lucke, Thomas
54f92436-6887-42a3-81b3-cf8d566418a2
Kobayashi, Hiroshi
c9de7e4a-b038-457f-9507-88cf21767882
Ohashi, Kinihide
70c98b44-0c38-4eae-8a6f-b20b078f99dc
Sakamoto, Nobuaki
195875d7-e023-4f8d-aba0-5cedd2d74ab9
Yang, Fan
e45ef7be-ef46-4d5a-9278-0729ea50de44
Gao, Yuling
143dd5ed-87e5-4970-840c-3611b39f6a0a
Winden, Bjorn
b1093655-db40-4f63-b92f-aa70ed3a70a5
Meyerson, Max G
e437e30d-d640-4d0c-9dbf-b2e6ce280b06
Maki, Kevin J
49d43430-c81c-40c5-a797-39a8d3e4bc3f
Turnock, Stephen
d6442f5c-d9af-4fdb-8406-7c79a92b26ce
Hudson, Dominic
3814e08b-1993-4e78-b5a4-2598c40af8e7
Banks, Joseph
3e915107-6d17-4097-8e77-99c40c8c053d
Terziev, Momchil
938f71d0-02b5-414c-8c2d-9cca8cc87397
Tezdogan, Tahsin
5a9b4f93-44db-4c38-ab36-ecb4472cae29
Vesting, Florian
e498e33a-dc23-45ee-bb93-c74a900673e3
Hino, Takanori
1b47667a-183e-457f-9646-008a06c94c5d
Werner, Sofia
5f136cda-8b9e-4c2f-bb03-0428c7011cbb
Andersson, Jennie
2f7063f9-7f45-4ace-8817-532142f2775f
Shiri, Alex Abolfazl
f629e01c-bd00-4de3-9d78-e26bdd6581f3
Bensow, Rickard E
3d717f1e-beea-4fe7-b342-e95740dfb24e
Yixing, Jin
9edfcfa1-97e3-4d21-ae23-c1059cb5091a
Chengsheng, Wu
2011dd80-3779-4af5-a1a3-2750cc07be3b
Gengyao, Qiu
e07b30b9-1d43-470b-b37f-aa6b82639191
Deng, Ganbo
04adf582-1f64-4e2e-8a73-e385461d1aa9
Queutey, Patrick
638e816b-132f-4071-bd3a-95d613f8ce8e
Xing-Kaeding, Yan
487443f5-8a29-4658-8a24-92d2eec5eb1d
Horn, Peter
7f70e828-9531-4940-b67a-d26dac04d6fe
Lucke, Thomas
54f92436-6887-42a3-81b3-cf8d566418a2
Kobayashi, Hiroshi
c9de7e4a-b038-457f-9507-88cf21767882
Ohashi, Kinihide
70c98b44-0c38-4eae-8a6f-b20b078f99dc
Sakamoto, Nobuaki
195875d7-e023-4f8d-aba0-5cedd2d74ab9
Yang, Fan
e45ef7be-ef46-4d5a-9278-0729ea50de44
Gao, Yuling
143dd5ed-87e5-4970-840c-3611b39f6a0a
Winden, Bjorn
b1093655-db40-4f63-b92f-aa70ed3a70a5
Meyerson, Max G
e437e30d-d640-4d0c-9dbf-b2e6ce280b06
Maki, Kevin J
49d43430-c81c-40c5-a797-39a8d3e4bc3f
Turnock, Stephen
d6442f5c-d9af-4fdb-8406-7c79a92b26ce
Hudson, Dominic
3814e08b-1993-4e78-b5a4-2598c40af8e7
Banks, Joseph
3e915107-6d17-4097-8e77-99c40c8c053d
Terziev, Momchil
938f71d0-02b5-414c-8c2d-9cca8cc87397
Tezdogan, Tahsin
5a9b4f93-44db-4c38-ab36-ecb4472cae29
Vesting, Florian
e498e33a-dc23-45ee-bb93-c74a900673e3
Hino, Takanori
1b47667a-183e-457f-9646-008a06c94c5d
Werner, Sofia
5f136cda-8b9e-4c2f-bb03-0428c7011cbb

Andersson, Jennie, Shiri, Alex Abolfazl, Bensow, Rickard E, Yixing, Jin, Chengsheng, Wu, Gengyao, Qiu, Deng, Ganbo, Queutey, Patrick, Xing-Kaeding, Yan, Horn, Peter, Lucke, Thomas, Kobayashi, Hiroshi, Ohashi, Kinihide, Sakamoto, Nobuaki, Yang, Fan, Gao, Yuling, Winden, Bjorn, Meyerson, Max G, Maki, Kevin J, Turnock, Stephen, Hudson, Dominic, Banks, Joseph, Terziev, Momchil, Tezdogan, Tahsin, Vesting, Florian, Hino, Takanori and Werner, Sofia (2022) Ship-scale CFD benchmark study of a pre-swirl duct on KVLCC2. Applied Ocean Research, 123, [103134]. (doi:10.1016/j.apor.2022.103134).

Record type: Article

Abstract

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.

Text
1-s2.0-S0141118722000839-main - Version of Record
Available under License Creative Commons Attribution.
Download (1MB)

More information

Accepted/In Press date: 9 March 2022
e-pub ahead of print date: 29 March 2022
Published date: 29 March 2022
Additional Information: Funding Information: The organization of the study and the contributions by Chalmers and SSPA was supported by the Swedish Transport Administration (grant number TRV 2018/76544). The contribution by Chalmers was based on simulations performed on resources at the National Supercomputer Centre in Sweden (NSC), provided by the Swedish National Infrastructure for Computing (SNIC). The contribution by University of Strathclyde's were based on results obtained using the Archie-West High Performance Computer (www.archie-west.ac.uk). The contribution by ECN/CNRS was granted access to the HPC resources of IDRIS under the allocation 2021-A0092A01308 made by GENCI, France. Funding Information: The organization of the study and the contributions by Chalmers and SSPA was supported by the Swedish Transport Administration (grant number TRV 2018/76544 ). Publisher Copyright: © 2022 The Authors
Keywords: Benchmark study, KVLCC2, Pre-swirl duct, Ship-scale CFD

Identifiers

Local EPrints ID: 457455
URI: http://eprints.soton.ac.uk/id/eprint/457455
ISSN: 0141-1187
PURE UUID: 3f7d798d-8fcf-49aa-8c2b-2ef441d055df
ORCID for Stephen Turnock: ORCID iD orcid.org/0000-0001-6288-0400
ORCID for Dominic Hudson: ORCID iD orcid.org/0000-0002-2012-6255
ORCID for Joseph Banks: ORCID iD orcid.org/0000-0002-3777-8962

Catalogue record

Date deposited: 09 Jun 2022 16:31
Last modified: 17 Nov 2022 02:40

Export record

Altmetrics

Contributors

Author: Jennie Andersson
Author: Alex Abolfazl Shiri
Author: Rickard E Bensow
Author: Jin Yixing
Author: Wu Chengsheng
Author: Qiu Gengyao
Author: Ganbo Deng
Author: Patrick Queutey
Author: Yan Xing-Kaeding
Author: Peter Horn
Author: Thomas Lucke
Author: Hiroshi Kobayashi
Author: Kinihide Ohashi
Author: Nobuaki Sakamoto
Author: Fan Yang
Author: Yuling Gao
Author: Bjorn Winden
Author: Max G Meyerson
Author: Kevin J Maki
Author: Stephen Turnock ORCID iD
Author: Dominic Hudson ORCID iD
Author: Joseph Banks ORCID iD
Author: Momchil Terziev
Author: Tahsin Tezdogan
Author: Florian Vesting
Author: Takanori Hino
Author: Sofia Werner

Download statistics

Downloads from ePrints over the past year. Other digital versions may also be available to download e.g. from the publisher's website.

View more statistics

Atom RSS 1.0 RSS 2.0

Contact ePrints Soton: eprints@soton.ac.uk

ePrints Soton supports OAI 2.0 with a base URL of http://eprints.soton.ac.uk/cgi/oai2

This repository has been built using EPrints software, developed at the University of Southampton, but available to everyone to use.

We use cookies to ensure that we give you the best experience on our website. If you continue without changing your settings, we will assume that you are happy to receive cookies on the University of Southampton website.

×