Numerical Simulation of In-Flight Iced Surface Roughness
hal.structure.identifier | Ecole de Technologie Supérieure [Montréal] [ETS] | |
dc.contributor.author | IGNATOWICZ, Kevin | |
hal.structure.identifier | Institut Polytechnique de Bordeaux [Bordeaux INP] | |
hal.structure.identifier | Certified Adaptive discRete moDels for robust simulAtions of CoMplex flOws with Moving fronts [CARDAMOM] | |
hal.structure.identifier | Institut de Mathématiques de Bordeaux [IMB] | |
dc.contributor.author | BEAUGENDRE, Héloïse | |
hal.structure.identifier | Ecole de Technologie Supérieure [Montréal] [ETS] | |
dc.contributor.author | MORENCY, François | |
dc.date.accessioned | 2024-04-04T02:31:52Z | |
dc.date.available | 2024-04-04T02:31:52Z | |
dc.date.issued | 2023-05-04 | |
dc.identifier.uri | https://oskar-bordeaux.fr/handle/20.500.12278/190336 | |
dc.description.abstractEn | CFD is a primary tool used to assess the in-flight effects of atmospheric icing onaircraft. In-flight ice accretion codes use CFD computed quantities, such as shearstress and heat transfer, to predict ice shape formation over rough surfaces. Theequivalent sandgrain roughness approach is the model commonly used in icingcodes for the prediction of skin friction and heat fluxes over iced surfaces.Additional turbulent Prandtl number corrections can be added to the ReynoldsAveraged Navier-Stokes (RANS) equations turbulence model to refine the heattransfer. Still, uncertainties persist in identifying the roughness parameters toinput into the thermal correction, leaving the characterization of rough surfacesincomplete in terms of research. This chapter develops a methodology for theestimation of roughness input parameters based on the observation of experimentalice accretion. Metamodeling involving Polynomial Chaos Expansion (PCE)and calibration with a Bayesian inversion are employed. The methodology isapplied to a NACA0012 airfoil, yielding a glaze ice cross-sectional area andmaximum thickness with less than a 6% error from experiments. The approachopens perspectives for the estimation of appropriate case-dependent roughnessparameters for RANS-based ice shape predictions. | |
dc.language.iso | en | |
dc.publisher | Springer International Publishing | |
dc.publisher.location | Cham | |
dc.rights.uri | http://creativecommons.org/licenses/by/ | |
dc.source.title | Handbook of Numerical Simulation of In-Flight Icing | |
dc.subject.en | In-flight icing | |
dc.subject.en | Ice accretion simulation | |
dc.subject.en | Iced surface roughness | |
dc.subject.en | Uncertainty quantification in icing | |
dc.subject.en | Polynomial chaos expansion | |
dc.subject.en | Bayesian inversion | |
dc.subject.en | Icing model calibration | |
dc.title.en | Numerical Simulation of In-Flight Iced Surface Roughness | |
dc.type | Chapitre d'ouvrage | |
dc.identifier.doi | 10.1007/978-3-030-64725-4_29-1 | |
dc.subject.hal | Physique [physics]/Mécanique [physics]/Mécanique des fluides [physics.class-ph] | |
dc.subject.hal | Informatique [cs]/Modélisation et simulation | |
dc.subject.hal | Physique [physics]/Mécanique [physics]/Thermique [physics.class-ph] | |
bordeaux.page | 1-48 | |
bordeaux.hal.laboratories | Institut de Mathématiques de Bordeaux (IMB) - UMR 5251 | * |
bordeaux.institution | Université de Bordeaux | |
bordeaux.institution | Bordeaux INP | |
bordeaux.institution | CNRS | |
bordeaux.title.proceeding | Handbook of Numerical Simulation of In-Flight Icing | |
hal.identifier | hal-04358583 | |
hal.version | 1 | |
hal.popular | non | |
hal.audience | Internationale | |
hal.origin.link | https://hal.archives-ouvertes.fr//hal-04358583v1 | |
bordeaux.COinS | ctx_ver=Z39.88-2004&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.btitle=Handbook%20of%20Numerical%20Simulation%20of%20In-Flight%20Icing&rft.date=2023-05-04&rft.spage=1-48&rft.epage=1-48&rft.au=IGNATOWICZ,%20Kevin&BEAUGENDRE,%20H%C3%A9lo%C3%AFse&MORENCY,%20Fran%C3%A7ois&rft.genre=unknown |
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