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Research Papers: Ocean Engineering

Numerical Uncertainty Analysis in Regular Wave Modeling

[+] Author and Article Information
Monica C. Silva

LabOceano/COPPE,
Federal University of Rio de Janeiro,
Rio de Janeiro RJ 21941-907, Brazil
e-mail: mcsilva@oceanica.ufrj.br

Marcelo A. Vitola, Paulo de Tarso T. Esperança

LabOceano/COPPE,
Federal University of Rio de Janeiro,
Rio de Janeiro RJ 21941-907, Brazil

Luís Eça

Mechanical Engineering Department,
IST-UL,
Lisboa 1049-001, Portugal

Sergio H. Sphaier

LabOceano/COPPE,
Federal University of Rio de Janeiro,
Rio de Janeiro RJ 21941907, Brazil

1Corresponding author.

Contributed by the Ocean, Offshore, and Arctic Engineering Division of ASME for publication in the JOURNAL OF OFFSHORE MECHANICS AND ARCTIC ENGINEERING. Manuscript received April 17, 2017; final manuscript received November 16, 2017; published online February 22, 2018. Assoc. Editor: Marcelo R. Martins.

J. Offshore Mech. Arct. Eng 140(4), 041101 (Feb 22, 2018) (8 pages) Paper No: OMAE-17-1057; doi: 10.1115/1.4039260 History: Received April 17, 2017; Revised November 16, 2017

In recent decades, the use of computational fluid dynamics (CFD) in many areas of engineering as a research and development tool has seen remarkable growth. Recently, an increasing concern with the assessment of the quality of CFD results has been observed. Wave modeling is an important task in many ocean engineering applications. Although numerical modeling studies of waves can be found in the literature for many applications, it is hard to find studies that present the numerical uncertainties of the results. In this study, the numerical uncertainties in mean wave parameters simulated using a viscous model were estimated using a procedure based on grid/time refinement studies and power series expansions. starccm+ software was used to simulate wave propagation. The computational domain was discretized using a trimmer mesh. The results obtained for a regular wave with a wave steepness (H/L) equal to 0.025 are presented. The numerical uncertainties in mean wave height and mean wave period were estimated along the computational domain. The results indicate that the convergence properties of the mean wave parameters with the grid refinement depended on both position in the domain and the selected wave parameter.

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Figures

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Fig. 1

The estimation of discretization error

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Fig. 2

Computational domain

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Fig. 3

Positions of the wave probes

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Fig. 4

Two main regions of the grids

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Fig. 6

Test W103: wave elevation along the domain

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Fig. 7

Test W103: comparison between one period of wave elevation from numerical results and second-order Stokes wave solutions at (a) WP0 (x/L = 0) and (b) WP2 (x/L = 6)

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Fig. 8

Test W105: (a) normalized wave elevation (ζ/A) at WP2, (b) normalized wave height over normalized time (t/T), and (c) normalized wave period over normalized time (t/T)

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Fig. 9

Normalized mean wave period (H¯/H) along the domain: (a) tests W102–W105 and (b) test W102 (mesh with rx = 1) with uncertainty values

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Fig. 10

Normalized mean wave period (T¯/T) along the domain: (a) tests W102–W105 and (b) test W102 (mesh with rx = 1) with uncertainty values

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