Effect of Triggering Turbulence on Large-Eddy Simulation of Iced-Wing Aerodynamics

Analyzing iced-wing aerodynamics is important for aircraft safety. However, simulating iced configurations accurately and efficiently is challenging due to the complex geometries and flow topologies involved. To investigate these challenges, wall-modeled large-eddy simulation of a swept wing with leading-edge ice is performed using an unstructured Voronoi mesh paradigm and compared to experimental results. The study focuses on a swept wing featuring high-fidelity and smooth ice shapes at a Mach number of 0.18 and a Reynolds number per mean aerodynamic chord of [Formula: see text]. For the high-fidelity ice shape, good agreement with the experiment is obtained using a moderate level of mesh resolution. For the smooth ice shape, a much finer mesh is required to obtain similar accuracy. However, comparable accuracy is achieved at similar mesh resolutions for the high-fidelity ice and smooth ice when roughness is added to generate resolved turbulence near the leading edge. For the smooth ice, using an equivalent sand-grain roughness estimate to mimic experimental grit roughness gives a factor of approximately 30 reduction in computational cost for similar accuracy compared to simulating the smooth ice without roughness. Finally, the predicted aerodynamic degradation due to icing is quantified using simulations of the tripped wing without ice.

Authors

Institutions

Publication Details

Journal
Journal of Aircraft
Published
2026-09-11
DOI
https://doi.org/10.2514/1.c038931
Primary Topic
Icing and De-icing Technologies
Type
article
Field-Weighted Citation Impact
0.00

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
article

Effect of Triggering Turbulence on Large-Eddy Simulation of Iced-Wing Aerodynamics

David A. Craig Penner, Gerrit-Daniel Stich, Victor Sousa, Jared C. Duensing et al.
Journal of Aircraft
Icing and De-icing Technologies
article

Effect of Triggering Turbulence on Large-Eddy Simulation of Iced-Wing Aerodynamics

David A. Craig Penner, Gerrit-Daniel Stich, Victor Sousa, Jared C. Duensing, Jeffrey A. Housman, K. Ravikumar
article en

Abstract

Analyzing iced-wing aerodynamics is important for aircraft safety. However, simulating iced configurations accurately and efficiently is challenging due to the complex geometries and flow topologies involved. To investigate these challenges, wall-modeled large-eddy simulation of a swept wing with leading-edge ice is performed using an unstructured Voronoi mesh paradigm and compared to experimental results. The study focuses on a swept wing featuring high-fidelity and smooth ice shapes at a Mach number of 0.18 and a Reynolds number per mean aerodynamic chord of [Formula: see text]. For the high-fidelity ice shape, good agreement with the experiment is obtained using a moderate level of mesh resolution. For the smooth ice shape, a much finer mesh is required to obtain similar accuracy. However, comparable accuracy is achieved at similar mesh resolutions for the high-fidelity ice and smooth ice when roughness is added to generate resolved turbulence near the leading edge. For the smooth ice, using an equivalent sand-grain roughness estimate to mimic experimental grit roughness gives a factor of approximately 30 reduction in computational cost for similar accuracy compared to simulating the smooth ice without roughness. Finally, the predicted aerodynamic degradation due to icing is quantified using simulations of the tripped wing without ice.

Journal of Aircraft
Ames Research Center (US)
Aeronautics Research Mission Directorate
Affordable and clean energy
Openalex Percentile: Top 7%
Icing and De-icing Technologies
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.