Ice accretion and especially ice adhesion greatly influence the performance of different surfaces, materials and structures in many industrial applications, e.g., in aviation, energy and transportation. To reduce ice adhesion, surface engineering plays a crucial role in developing sustainable solutions by tailoring the surface properties. The number of studies on improving and developing anti-icing surfaces and coatings are continuously increasing. Ice adhesion testing methods are used for evaluating de-icing capability of materials and coatings. However, the characterization of ice adhesion strength using standard methods is still lacking. In this research, we focus on investigation of ice adhesion of aluminium alloys and flame sprayed polyethylene coatings with two different ice adhesion test methods: centrifugal ice adhesion test (CAT) and pushing ice adhesion test (PAT). The aim is to compare these test methods using similar ice accretion method and ice type on tested surfaces. An impact ice as a form of mixed glaze ice was accreted by using supercooled water droplets in the icing wind tunnel. This mimics natural ice formation in outdoor conditions. Ice adhesions measured with CAT were higher compared to PAT, which indicates importance to find test specific criteria for ice adhesion levels and icephobicity indicators. Moreover, coated surfaces showed lower ice adhesion, below 100 kPa, with both methods showing their potential as icephobic coatings to be used in de-icing applications. Ice adhesion tests were modelled using finite element method to analyse their stress distributions. Wettability and surface roughness were also evaluated to correlate surface and material properties to icing performance. • Ice adhesion strength measured with CAT was higher than PAT using impact ice. • Ice adhesion strength of FS PE coatings was below 100 kPa with both CAT and PAT. • FE modelling was used to analyse stress distributions in both CAT and PAT.
Building similarity graph...
Analyzing shared references across papers
Loading...
Kamil Khan
Niklas Kandelin
Jarno Jokinen
Cold Regions Science and Technology
Tampere University
Building similarity graph...
Analyzing shared references across papers
Loading...
Khan et al. (Wed,) studied this question.
www.synapsesocial.com/papers/69dc87ea3afacbeac03ea03e — DOI: https://doi.org/10.1016/j.coldregions.2026.104945