Data-driven Elucidation of Heat Transfer Mechanisms of Heterogeneous Boiling
Boiling heat transfer, which is arguably the most efficient heat transfer scheme, is critical to thermal management of power-intensive applications such as data centers and nuclear reactors. As the surface heat flux increases, heterogenous boiling goes through the distinctive regimes of isolated bubbles, slugs and columns (fully developed) before triggering the so-called boiling crisis (i.e., the dryout condition), underneath which are interacting processes of bubble nucleation, growth and release. It is the latter that contributes the most to the inherent complexity of boiling heat transfer, which still lacks an accurate physical description. In this work, we aim at developing a comprehensive understanding of the relationship between bubble behavior (three-phase contact line dynamics) in nucleate boiling and physical and chemical surface characteristics using a neural-network-based approach.
Multiscale Modeling of Complex Phase-change Systems
For a multiphase fluid systems such as heterogeneous boiling, new unknown interfacial physics abound as one moves from macroscale to microscale. The presence of solid surface introduces even more complexity, whose full resolution calls for an ‘organic’ modeling approach that facilitates transfer of information across different time and length scales. This research consists of three interdependent numerical efforts to elucidate heat and mass transport in pool boiling: macroscopic full-scale direct numerical simulation of nucleate boiling, mesoscopic diffuse-interface account of contact-line dynamics, and microscopic molecular dynamics description of heterogenous nucleation. The results are expected to shed new light on the underlying multi scale nature of phase-change phenomena.
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