Abstract The processing demands for high-performance computing have increased significantly due to the rapid emergence of Artificial Intelligence (AI) and Machine Learning (ML) applications. This has been enabled by the development of high-powered computer chips that generate significant heat and require improved cooling strategies over traditional singlephase cooling methods. A two-phase evaporative cooling through micropillars is studied here which utilizes the latent heat of vaporization for efficient and rapid heat removal directly from the chip surface. Design of such a system depends on factors such as the physical arrangement of the evaporator micropillars on the chip, the liquid type and flow rates, the temperature difference between the working fluid and chip surface, and the wettability of the pillar surface and substrate material. These factors collectively impact the evaporation rate, thermal resistance, and overall heat transfer capacity. This paper presents an advanced simulation framework that incorporates momentum equations with the two-phase volume of fluid (VoF) method to track interfaces. The energy equation includes a source term for interphase mass transfer, calculated using Schrage’s evaporation model. The CFD model is validated against experimental and theoretical data from the literature, accurately capturing the complex physics of flow wicking through micropillars, the dynamic behavior of the solid-liquid contact angle, and evaporative flux at the interface. The validated model is further extended to explore a micropillararray evaporator configuration. The results highlight the stages of fluid wicking across micropillar structures and the critical roles of micropillar geometry (diameter), spatial arrangement (pitch and distribution), temperature difference, and liquid contact angle in governing heat transfer performance.
Upadhyay et al. (Tue,) studied this question.
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