Simultaneous prediction of dryout heat flux and local temperature for thin film evaporation in micropillar wicks

A Learning-Based Thermal Simulation Framework for Emerging Two-Phase Cooling Technologies

“…Instead, we use a previously established relationship between HTC and thermal resistance to define R hybrid [13], [17]. In addition, we assume the VC itself only contains saturated vapor at a constant temperature [8], [15]. From the COMSOL model, we extract HTC correlations for various nanoporous membranes and microchannel geometries.…”

“…For example, VCs and heat pipes leverage capillary pumping to passively (without active cooling power on the evaporator side) supply the evaporator [1], [14]. Two-phase cooling thermal models are usually designed by calculating the temperaturedependent heat transfer coefficient 1 (HTC) [8], [12], [14], [15]. In these models, pre-computed temperature-dependent HTC correlations embedded in the simulation framework are functions of temperature and cooling parameters (e.g., coolant type, flow velocity, saturation temperature, and structural parameter such as microchannel width and height, micropillar height, diameter, and pitch [12], [15], [17]).…”

“…Two-phase cooling thermal models are usually designed by calculating the temperaturedependent heat transfer coefficient 1 (HTC) [8], [12], [14], [15]. In these models, pre-computed temperature-dependent HTC correlations embedded in the simulation framework are functions of temperature and cooling parameters (e.g., coolant type, flow velocity, saturation temperature, and structural parameter such as microchannel width and height, micropillar height, diameter, and pitch [12], [15], [17]). The HTC correlations are derived either based on in-house prototypes or using computational fluid dynamics (CFD) modules in COMSOL and ANSYS [1], [15].…”

“…In these models, pre-computed temperature-dependent HTC correlations embedded in the simulation framework are functions of temperature and cooling parameters (e.g., coolant type, flow velocity, saturation temperature, and structural parameter such as microchannel width and height, micropillar height, diameter, and pitch [12], [15], [17]). The HTC correlations are derived either based on in-house prototypes or using computational fluid dynamics (CFD) modules in COMSOL and ANSYS [1], [15]. HTC correlations based on prototypes are generally not applicable to the same cooling method with different cooling parameters, or will likely result in accuracy loss [12].…”

Spreading and Drying Dynamics of Water Drop on Hot Surface of Superwicking Ti-6Al-4V Alloy Material Fabricated by Femtosecond Laser

“…Hierarchical wicking materials based on the surface capillary effect offer significantly enhanced cooling performance due to a high velocity of liquid transport, small thickness (<100 µm), and efficient evaporative functionality [ 33 , 34 , 35 , 36 , 37 , 38 ]. Prior studies also show that as compared with wire meshes, sintered powders, and microgroove structures, the micropillar arrays [ 39 , 40 ], especially hierarchical ones [ 41 , 42 ], provide superior heat transfer performance due to their good wicking, large surface area enhancement, and high evaporation rate owing to a large thin-film evaporation area [ 41 , 43 , 44 ]. Previously, surface nano/microstructuring of materials [ 34 , 45 ] using direct laser ablation [ 46 , 47 , 48 , 49 , 50 ] has been successfully applied to fabrication of superwicking silicon [ 36 , 51 ], metals [ 10 , 14 , 33 , 37 , 52 ], glasses [ 53 , 54 ], and polymers [ 38 ] by producing an array of parallel microgrooves on a surface of a material.…”