Development of a CFD methodology for the numerical simulation of irregular sea-states
Development of a CFD methodology for the numerical simulation of irregular sea-states
This paper aims to investigate and propose a clear methodology for simulating and maintaining irregular sea simulations within Computational Fluid Dynamics (CFD) for all aspects of the marine industry. As the industry becomes ever more conscious of its overall global emissions, there is an increased interest in beginning to model ever more complex and realistic marine environments. The first step in the beginning to model real-ocean and coastal conditions in CFD is to model irregular seas rather than regular waves. Once this has been achieved further conditions defining realistic oceans can be added, such as varying wind speeds, to these CFD simulations.
To achieve the first step in moving towards realistic ocean simulations, this paper proposes a methodology for meshing and time step calculations for completely unknown irregular seas, along with the best practices for such simulations. The methodology is based upon a preliminary statistical analysis of irregular seas, aiming to break down the irregular sea into key points that will define both the meshing and time step methodologies.
Further to this, example simulations solely focusing on the generated free-surfaces are presented, along with a discussion on the methodology’s accuracy and limitations within CFD. These simulations also provide practical data on the modelling and simulating of irregular seas.
Romanowski, Anthony
166fa590-35f5-439b-95f1-e54b4861809f
Tezdogan, Tahsin
7e7328e2-4185-4052-8e9a-53fd81c98909
Turan, Osman
5e66f3ca-4bfa-4a5d-9a35-ba3bdd3b4ee3
22 October 2019
Romanowski, Anthony
166fa590-35f5-439b-95f1-e54b4861809f
Tezdogan, Tahsin
7e7328e2-4185-4052-8e9a-53fd81c98909
Turan, Osman
5e66f3ca-4bfa-4a5d-9a35-ba3bdd3b4ee3
Romanowski, Anthony, Tezdogan, Tahsin and Turan, Osman
(2019)
Development of a CFD methodology for the numerical simulation of irregular sea-states.
Ocean Engineering, 192, [106530].
(doi:10.1016/j.oceaneng.2019.106530).
Abstract
This paper aims to investigate and propose a clear methodology for simulating and maintaining irregular sea simulations within Computational Fluid Dynamics (CFD) for all aspects of the marine industry. As the industry becomes ever more conscious of its overall global emissions, there is an increased interest in beginning to model ever more complex and realistic marine environments. The first step in the beginning to model real-ocean and coastal conditions in CFD is to model irregular seas rather than regular waves. Once this has been achieved further conditions defining realistic oceans can be added, such as varying wind speeds, to these CFD simulations.
To achieve the first step in moving towards realistic ocean simulations, this paper proposes a methodology for meshing and time step calculations for completely unknown irregular seas, along with the best practices for such simulations. The methodology is based upon a preliminary statistical analysis of irregular seas, aiming to break down the irregular sea into key points that will define both the meshing and time step methodologies.
Further to this, example simulations solely focusing on the generated free-surfaces are presented, along with a discussion on the methodology’s accuracy and limitations within CFD. These simulations also provide practical data on the modelling and simulating of irregular seas.
This record has no associated files available for download.
More information
Published date: 22 October 2019
Identifiers
Local EPrints ID: 479142
URI: http://eprints.soton.ac.uk/id/eprint/479142
ISSN: 0029-8018
PURE UUID: 3542dd51-e84d-4edd-bf1f-764460552685
Catalogue record
Date deposited: 20 Jul 2023 16:37
Last modified: 17 Mar 2024 04:18
Export record
Altmetrics
Contributors
Author:
Anthony Romanowski
Author:
Tahsin Tezdogan
Author:
Osman Turan
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