Numerical Simulation of In-Flight Icing Under Uncertain Conditions

Gori, Giulio; Bellosta, Tommaso; Guardone, Alberto

doi:10.1007/978-3-030-64725-4_31-1

Cited by 1 publication

(1 citation statement)

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“…The studies apply to both ice-induced aerodynamic degradation [85,86] and shedding debris [87,88]. Initially carried out experimentally [38,45,89], ice accretion studies have been supplemented by numerical simulations with the increase of computational power [52,90,91].…”

Section: The Ice Accretion Process: a Roughness-dependent Phenomenonmentioning

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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