Studying Arctic ice formation stays in the focus of research groups over the past decades in the context of ice cover changes, thermal budget and climate agenda in general. Nevertheless, the phenomenon's underlying mechanisms are still not completely understood and described. The main reason for the lack in understanding is the limited experimental access to the field data when it comes to the processes that occur below the ice floe. Thus, there is a need to build competent analogies between the natural (ocean water–ice) and laboratory (here: binary alloy) conditions of the experiment as a step of data preparation for the verification of the mathematical model. In the current paper, the existing qualitative models describing the process of melting and crystallization were expanded and the experimental method was developed copying the layering of the natural ocean water–ice mixture. The experimental set-up for studying the solidification within the intermediate zone was designed for Al–Cu alloys being the system with appropriate solidus line for creating a sufficient concentration gradient and by that temperature dependent phase fraction under isothermal conditions. The gained experimental data were used for validating a binary phase-field model for solidification considering moving boundaries. The model includes the description of the free energy of both phases and their respective diffusion coefficients. It allows modeling a binary system at a mesoscopic spatial level by including the concentration-driven phase transition and resolidification in the two-phase region. The novel results will help the quantitative understanding of solidification phenomena and are highly-evaluated from interdisciplinary point of view, including glaciology and geosciences, being ultimately significant for the understanding the global climate change landscape.
Original languageEnglish
Pages (from-to)6853-6867
Number of pages5
JournalMathematical Methods in the Applied Sciences
Issue number8
Publication statusPublished - 30 May 2024

    ASJC Scopus subject areas

  • Engineering(all)
  • Mathematics(all)

    WoS ResearchAreas Categories

  • Mathematics, Applied

ID: 56641303