ASME journal of heat and mass transfer最新文献

Focused ultrasound (FUS) is a thermal therapy used to noninvasively destroy diseased tissues. Computational tools are being explored to plan faster, safer, and more effective focused ultrasound treatments by using simulations to predict their outcomes. For simulations to be used with confidence, the uncertainties in their predicted outcomes must be characterized. This is challenging because the simulations have a large computational cost and performing uncertainty quantification (UQ) typically requires evaluating the simulations many times. Multifidelity uncertainty quantification uses techniques that aim to reduce the computational cost of uncertainty quantification. This is done by combining results from computationally expensive and accurate high-fidelity models with lower-fidelity models that sacrifice some accuracy to reduce computational expense. In this work, a multifidelity uncertainty quantification technique using projection-based reduced order models (ROMs) as the low-fidelity model is used on thermal simulations of two focused ultrasound sonications performed as part of breast cancer treatments. The errors in mean response estimates of multiple quantities of interest (QoIs) using this multifidelity uncertainty quantification technique are compared against those using traditional Monte Carlo uncertainty quantification. The mean, standard deviation, and skewness estimated using the multifidelity and Monte Carlo techniques are fit to Pearson Type III distributions to compare their predictions of quantity of interest distributions. It is found that multifidelity uncertainty quantification predicts the mean response of the quantities of interest with up to 50% lower error while maintaining similar accuracy in distribution predictions when compared to Monte Carlo.

The increasing trend of power densities in high-performance computing, driven by artificial intelligence, machine learning, and cloud computing, necessitates advanced thermal management solutions to maintain operational stability and energy efficiency. This study examines the effectiveness of cooling a 1.5 U simulated copper microchannel chip compared to a plain chip. Both chip types were tested with and without configurations for dual taper microgaps to enhance the heat transfer performance of a boiling chamber (BC). Experimental investigation was conducted using 500 μm wide × 400 μm deep microchannels separated by 200 μm fins. Varying inlet gaps (0.5-4 mm) and taper lengths (8.25 mm and 16.5 mm) with a taper angle of 3 deg were employed in dual taper configuration. Their impact on critical heat flux (CHF) and subcooled boiling dynamics was investigated. Microchannels provided considerable performance enhancement over a plain surface with or without the dual taper microgap. The findings demonstrate that smaller inlet gaps (0.5-1 mm) and longer taper lengths (16.5 mm, with central liquid inlet) significantly enhance nucleate boiling. These configurations improve vapor escape and delay CHF through subcooled boiling and submerged condensation. However, a lower CHF was noted due to vapor agglomeration within the microgap. The 80% fill ratio microchannel chip exhibited the highest CHF as subcooled boiling increased liquid replenishment and prevented vapor stagnation. Similarly, lower coolant temperatures (20-30 °C) enhanced boiling performance, where submerged condensation accelerated bubble collapse and improved heat dissipation efficiency in lower surface temperatures.

Heat transfer in solids has traditionally been described by Fourier's law, which assumes local equilibrium and a diffusive transport regime. However, advancements in nanotechnology and the development of novel materials have revealed non-classical heat transfer phenomena that extend beyond this traditional framework. These phenomena, which can be broadly categorized into those governed by kinetic theory and those extending beyond it, include ballistic transport, phonon hydrodynamics, coherent phonon transport, Anderson localization, and glass-like heat transfer. Recent theoretical and experimental studies have focused on characterizing these non-classical behaviors using methods such as the Boltzmann transport equation, molecular dynamics, and advanced spectroscopy techniques. In particular, the dual nature of phonons, exhibiting both particle-like and wave-like characteristics, is fundamental to understanding these phenomena. This review summarizes state-of-the-art findings in the field, highlighting the importance of integrating both particle and wave models to fully capture the complexities of heat transfer in modern materials. The emergence of new research areas, such as chiral and topological phonons, further underscores the potential for advancing phonon engineering. These developments open up exciting opportunities for designing materials with tailored thermal properties and new device mechanisms, potentially leading to applications in thermal management, energy technologies, and quantum science.