Experimental Investigation on Dynamic Ice Adhesion Characteristics of Wind Turbine Blade Surfaces After Sand Erosion

To investigate the coupling effect of sand erosion and dynamic icing on ice adhesion strength of wind turbine blades in alpine regions, this study experimentally examines the single-factor and coupling effects of four key factors: separation temperature, icing temperature, loading rate, and surface roughness of eroded blade coatings. Single-factor analyses reveal that dynamic ice adhesion strength is generally lower than static ice but follows the same variation trend. It increases linearly with decreasing separation temperature and increasing sand-eroded roughness, and decreases linearly with increasing loading rate. A nonlinear relationship exists with icing temperature: when the separation temperature is lower than the icing temperature, the dynamic ice adhesion strength increases linearly with the decrease in icing temperature; when the separation temperature is higher than the icing temperature, the dynamic ice adhesion strength decreases linearly with the decrease in icing temperature. Orthogonal array testing demonstrates the hierarchy of influence, separation temperature > loading rate > icing temperature > surface roughness, with the first three factors exerting statistically significant effects. Furthermore, a regression equation of dynamic ice adhesion strength is established, which can provide an estimation basis for ice adhesion strength under untested parameters. These findings provide critical data support for the optimized design of wind turbine blade de-icing systems in alpine regions.

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Publication Details

Journal
Energies
Published
2026-09-30
DOI
https://doi.org/10.3390/en19194629
Primary Topic
Icing and De-icing Technologies
Type
article
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article

Experimental Investigation on Dynamic Ice Adhesion Characteristics of Wind Turbine Blade Surfaces After Sand Erosion

Shaolong Wang, 沈江洁, Yifei Jia, Lei Shi et al.
Energies
Icing and De-icing Technologies
article

Experimental Investigation on Dynamic Ice Adhesion Characteristics of Wind Turbine Blade Surfaces After Sand Erosion

Shaolong Wang, 沈江洁, Yifei Jia, Lei Shi, Hongliang Chen
article en

Abstract

To investigate the coupling effect of sand erosion and dynamic icing on ice adhesion strength of wind turbine blades in alpine regions, this study experimentally examines the single-factor and coupling effects of four key factors: separation temperature, icing temperature, loading rate, and surface roughness of eroded blade coatings. Single-factor analyses reveal that dynamic ice adhesion strength is generally lower than static ice but follows the same variation trend. It increases linearly with decreasing separation temperature and increasing sand-eroded roughness, and decreases linearly with increasing loading rate. A nonlinear relationship exists with icing temperature: when the separation temperature is lower than the icing temperature, the dynamic ice adhesion strength increases linearly with the decrease in icing temperature; when the separation temperature is higher than the icing temperature, the dynamic ice adhesion strength decreases linearly with the decrease in icing temperature. Orthogonal array testing demonstrates the hierarchy of influence, separation temperature > loading rate > icing temperature > surface roughness, with the first three factors exerting statistically significant effects. Furthermore, a regression equation of dynamic ice adhesion strength is established, which can provide an estimation basis for ice adhesion strength under untested parameters. These findings provide critical data support for the optimized design of wind turbine blade de-icing systems in alpine regions.

EnergiesVol. 19(19)
North China University of Science and Technology (CN), Hebei Normal University of Science and Technology (CN)
Affordable and clean energy
Openalex Percentile: Top 8%
Icing and De-icing Technologies
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Experimental Investigation on Dynamic Ice Adhesion Characteristics of Wind Turbine Blade Surfaces After Sand Erosion — Shaolong Wang, 沈江洁, et al. · Energies (2026) | TGRS Research Map | TGRS