Roughness effect modelling for wall resolved RANS – Comparison of methods for marine hydrodynamics

Orych, Michal; Werner, Sofia; Larsson, Lars

doi:10.1016/j.oceaneng.2022.112778

Cited by 4 publications

(2 citation statements)

References 21 publications

(32 reference statements)

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“…The hull roughness effect is modeled by a modification of the boundary conditions for the specific dissipation of the turbulent kinetic energy, 𝜔 and the turbulent kinetic energy, k, Orych et al (2022). The roughness is quantified using the equivalent sand grain roughness height, 𝑘 𝑆 .…”

Section: Calm Water Self Propulsionmentioning

confidence: 99%

Speed and Delivered Power in Waves – Predictions with Cfd Simulations at Full Scale

Orych

Östberg²,

Kjellberg³

et al. 2023

Preprint

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Section: Calm Water Self Propulsionmentioning

confidence: 99%

Speed and Delivered Power in Waves – Predictions with Cfd Simulations at Full Scale

Orych

Östberg²,

Kjellberg³

et al. 2023

Preprint

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“…In all models, the velocity shift is zero in a hydraulically smooth regime. For very small roughness elements, the effects on the flow vanish due to the viscosity [10,78]. Commercial CFD software with wall resolved RANS approaches, such as STAR-CCM+, implement the roughness effect such as Equation ( 21) [79].…”

mentioning

confidence: 99%

Surface Roughness in RANS Applied to Aircraft Ice Accretion Simulation: A Review

Ignatowicz,

Morency,

Beaugendre

2023

Fluids

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Experimental and numerical fluid dynamics studies highlight a change of flow structure in the presence of surface roughness. The changes involve both wall heat transfer and skin friction, and are mainly restricted to the inner region of the boundary layer. Aircraft in-flight icing is a typical application where rough surfaces play an important role in the airflow structure and the subsequent ice growth. The objective of this work is to investigate how surface roughness is tackled in RANS with wall resolved boundary layers for aeronautics applications, with a focus on ice-induced roughness. The literature review shows that semi-empirical correlations were calibrated on experimental data to model flow changes in the presence of roughness. The correlations for RANS do not explicitly resolve the individual roughness. They principally involve turbulence model modifications to account for changes in the velocity and temperature profiles in the near-wall region. The equivalent sand grain roughness (ESGR) approach emerges as a popular metric to characterize roughness and is employed as a length scale for the RANS model. For in-flight icing, correlations were developed, accounting for both surface geometry and atmospheric conditions. Despite these research efforts, uncertainties are present in some specific conditions, where space and time roughness variations make the simulations difficult to calibrate. Research that addresses this gap could help improve ice accretion predictions.

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Speed and delivered power in waves — Predictions with CFD simulations at full scale

et al. 2023

View full text Add to dashboard Cite

Roughness effect modelling for wall resolved RANS – Comparison of methods for marine hydrodynamics

Cited by 4 publications

References 21 publications

Speed and Delivered Power in Waves – Predictions with Cfd Simulations at Full Scale

Speed and Delivered Power in Waves – Predictions with Cfd Simulations at Full Scale

Surface Roughness in RANS Applied to Aircraft Ice Accretion Simulation: A Review

Speed and delivered power in waves — Predictions with CFD simulations at full scale

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