Microscale Oscillating Heat Pipe Model for Prediction of Startup, Oscillation Dynamics, and Dryout

Abstract

Abstract. Microscale oscillating heat pipes (OHPs) are a promising technology for thermal management of electronic devices, offering high effective thermal conductance and scalability for compact integration. Predictive modeling of OHPs at the microscale remains difficult due to extreme aspect ratios, complex two-phase transport, and transitions across multiple operating regimes. In this study, an efficient one-dimensional (1D) homogeneous model is developed to simulate unsteady two-phase flow dynamics of closed-loop microchannel OHPs, governed by conservation of mass, momentum, and energy. The homogeneous assumption treats liquid and vapor phases as uniform mixtures, enabling use of common variables—temperature, pressure, and velocity—to describe the flow. Thermophysical properties are expressed as functions of internal pressure and temperature, thereby capturing the thermomechanical cycles of vapor compression and expansion that drive OHP operation. The model is applied to multiturn microscale OHPs subjected to varying evaporator-to-condenser temperature differences. Simulations capture three operating regimes—prestartup, oscillation, and dryout—and reproduce the strong dependence of thermal performance on regime. In particular, heat transfer enhancement is observed with the onset of oscillatory flow, consistent with prior experimental findings. The model further demonstrates robustness in predicting oscillations driven solely by internal thermomechanical instabilities, without requiring gravity, capillarity, or other external driving forces. Overall, the proposed framework provides a tool for understanding coupled thermal-fluid dynamics of microscale OHPs and interpreting the transitions between the prestartup, oscillation, and dryout operating regimes. In the future, with calibrated heat transfer parameters from experiments, the model may be extended to accurate heat transfer prediction of OHPs and have potential applications in design optimization.