Improved Power Predictions of Ships Using Combined CFD/EFD Methods for the Form Factor
Licentiatavhandling, 2020

Performance prediction of a ship is one of the most important tasks during the design phase. Once the design is finalized, the speed attained at a certain power consumption has to be verified with the most accurate prediction as it is specified at the contract of a new ship order and also required by the legal authorities. Considering the current commercial tendencies and the requirements enforced by legal authorities, towing tank testing and the extrapolation methods recommended by the International Towing Tank Conference (ITTC) are used and regarded as a highly accurate power prediction methodology for common cargo vessels. However, some aspects of this methodology have been questioned such as the scale effects on the form factor and its determination method.

It is argued in this thesis that if a part of the Experimental Fluid Dynamics (EFD) based measure or the extrapolation procedure causes higher uncertainty than the numerical uncertainty and modelling errors of a Computational Fluid Dynamics (CFD) application, the corresponding part of the performance prediction method can be replaced or supplemented by CFD. In this study, the possibility to improve the power predictions by the introduction of a combined CFD/EFD Method was investigated by replacing the experimental determination of the form factor with double body computations based on the Reynolds-Averaged Navier-Stokes (RANS) equations, i.e. CFD based form factors.

As a result of a joint, study where the double body simulations performed with seven different CFD codes, the CFD based form factors compared well with the experimentally determined form factors. Additionally, the standard deviations of the CFD based form factors were similar to the experimental uncertainty of the form factors even though the abundance of unsystematically varied methods and grids.

Following the Quality Assurance Procedure proposed by the ITTC, a best practice guideline has been derived for the CFD based form factor determination method by applying systematic variations to the CFD set-ups. After the verification and validation of the CFD based form factor method in model scale, the full scale speed-power-rpm relations between large number of speed trials and full scale predictions were investigated using the CFD based form factors in combination to the ITTC-57 line and the numerical friction lines. It is observed that the usage of CFD based form factors improves the predictions in general and no deterioration in the prediction accuracy is noted within the limits of this study. Therefore, the combination of EFD and CFD is expected to provide immediate improvements to the 1978 ITTC Performance Prediction Method.

verification and validation

measurement uncertainty

power prediction

Combined CFD/EFD Methods

CFD

form factor

numerical friction line

Opponent: Dr. Hoyte Raven

Författare

Kadir Burak Korkmaz

Chalmers, Mekanik och maritima vetenskaper, Fordonsteknik och autonoma system

Numerical Friction Lines for CFD Based Form Factor Determination Method

MARINE 2019: COMPUTATIONAL METHODS IN MARINE ENGINEERING VIII: VIII INTERNATIONAL CONFERENCE ONCOMPUTATIONAL METHODS IN MARINE ENGINEERING (MARINE 2019),; (2019)p. 694-705

Paper i proceeding

Investigations for CFD Based Form Factor Methods

Numerical Towing Tank Symposium,; (2019)

Paper i proceeding

CFD based form factor determination method

Ocean Engineering,; Vol. In Press(2020)

Artikel i vetenskaplig tidskrift

Verification and Validation of CFD Based Form Factors as a Combined CFD/EFD Method

Journal of Marine Science and Engineering,; Vol. 9(2021)p. 75-

Artikel i vetenskaplig tidskrift

Ämneskategorier

Maskinteknik

Teknisk mekanik

Farkostteknik

Strömningsmekanik och akustik

Styrkeområden

Transport

Energi

Infrastruktur

C3SE (Chalmers Centre for Computational Science and Engineering)

Thesis for the degree of Licentiate – Department of Mechanics and Maritime Sciences: 2021:05

Utgivare

Chalmers tekniska högskola

Online

Opponent: Dr. Hoyte Raven

Mer information

Senast uppdaterat

2021-01-18