Super-cooled large droplet experimental reproduction, ice shape modeling, and scaling method assessment

Edward T. Rocco, Yiqiang Han, Richard Kreeger, Jose Palacios

Research output: Contribution to journalArticlepeer-review

4 Scopus citations


Super-cooled large droplets (SLDs) present a unique experimental challenge for conventional horizontal spray icing wind tunnels due to gravity effects on the droplets and coalescence between the particles. Limited ice accretion shapes in this regime exist, making the verification of modeling tools and the validation of the applicability of scaling methods difficult. Furthermore, SLD accretions often occur in nature in a bimodal icing cloud, providing an additional facility challenge related to the reproduction of such clouds. The objective of this research effort is to expand the available SLD dataset to assess the capability of an existent ice accretion tool (LEWICE 2D) to predict such ice shapes. The effort also attempts to further verify the applicability of ice shape scaling methods in the SLD regime. Finally, bimodal SLD cloud reproduction and ice shape prediction is investigated. The Adverse Environment Rotor Test Stand (AERTS) at Penn State was assessed as an alternative facility to icing wind tunnels for ice accretion testing in the SLD regime. Laser diffraction measurement data analysis demonstrated that the icing nozzles used in the facility can produce an SLD within 11.9% of requested values. Techniques to measure liquid water content (LWC) in the facility are also presented. LWC was controllable within 16%. LEWICE ice shapes predicted were obtained using legacy empirical heat transfer models as well as an updated empirical heat transfer function developed at Penn State. When comparing modeling results to experimental shapes from the literature and the AERTS, LEWICE with the updated heat transfer function provided stagnation thicknesses within 5.6% of experimental values and horn protrusion within 16%. The modified Ruff scaling ice shape method was effective in the SLD regime, providing a mean deviations of 2.5% between reference and scaled ice shape characteristics. Finally, characteristics of a bimodal ice shapes were predicted by LEWICE. When comparing modeling results to experimental shapes, LEWICE with the updated heat transfer function provided predictions within 10.3% of the experimental stagnation thickness measured. It also provided horn angles with discrepancies of less than 12%. Icing limits of a bimodal icing cloud were observed to be that of a single mode SLD cloud of the same MVD, with an overall deviation of 12.1% when comparing the experimental database to LEWICE.

Original languageEnglish (US)
Pages (from-to)1277-1295
Number of pages19
JournalAIAA journal
Issue number4
StatePublished - 2021

All Science Journal Classification (ASJC) codes

  • Aerospace Engineering


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