An official website of the United States government
Abstract Power intensification and miniaturization of electronics and energy systems are causing a critical challenge for thermal management. Single-phase heat transfer mechanisms including natural and forced convection of air and liquids cannot meet the ever-increasing demands. Two-phase heat transfer modes, such as evaporation, pool boiling, flow boiling, have much higher cooling capacities but are limited by a variety of practical instabilities, e.g., the critical heat flux (CHF), aka departure from nucleate boiling (DNB) in the nuclear industry, flow maldistribution, flow reversal, among others. These instabilities are often triggered suddenly during normal operation, and if not identified and mitigated in time, will lead to overheating issues and detrimental device failures. For example, when CHF is triggered during pool boiling, the device temperature can ramp up in the order of 150 °C/min. It is thus critical to implement real-time detection and mitigation algorithms for two-phase cooling. In the present work, we have developed an accurate and reliable technology for fault detection of high-performance two-phase cooling systems by coupling acoustic emission (AE) with multimodal fusion using deep learning. We have leveraged the contact AE sensor attached to the heater and hydrophones immersed in the working fluid to enable non-invasive fault detection.
more »
« less
Supervised and Unsupervised Learning Models for Detection of Critical Heat Flux During Pool Boiling
Abstract The rapid growth and scaling of electronics are causing more severe thermal management challenges. For example, the high-performance computing processors are driving the data center power density to unprecedented levels, approaching the limit of conventional air cooling. In electric vehicles (EVs) and hybrid EVs, the power conversion electronics are integrated into a compact space, leading to ultra-high heat fluxes to dissipate. Among the available thermal management mechanisms, two-phase cooling that involves the phase-change process of the working fluid can maintain electronic devices at safe operating temperatures by taking advantage of the high latent heat of the fluid. Particularly, pool boiling plays a critical role in the two-phase immersion cooling of servers and other IT hardware, integrated cooling for three-dimensional electronic packaging, cooling of the core, and used fuel in nuclear reactors. Two-phase coolers are limited by instabilities such as the critical heat flux (CHF). At the critical heat flux, the temperature increases. It is important to be able to identify the CHF in order to prevent overheating. We aim to develop and compare boiling image classification models to distinguish between 2 boiling regimes. We will leverage principal component analysis (PCA) and K-means clustering to investigate the key differences between bubbles during nucleate boiling (pre-CHF) and transition boiling (post-CHF). We will also compare the results of the unsupervised learning model against popular supervised learning models that have been used for boiling regime classification in existing studies, such as convolutional neural networks, multiplayer perceptrons, and transformers. We successfully created 4 supervised and 1 unsupervised learning models to distinguish between the two types of boiling images.
more »
« less
- Award ID(s):
- 1946391
- PAR ID:
- 10497396
- Publisher / Repository:
- American Society of Mechanical Engineers
- Date Published:
- Journal Name:
- Journal of Electronic Imaging
- ISBN:
- 978-0-7918-8579-6
- Format(s):
- Medium: X
- Location:
- Philadelphia, Pennsylvania, USA
- Sponsoring Org:
- National Science Foundation
More Like this
-
-
Two-phase jet impingement cooling is a promising solution for high-heat-flux semiconductor thermal management, as it combines strong convective heat transfer with boiling to remove large heat loads at relatively low flow rates and pressure drops. However, practical deployment is hindered by challenges including inconsistent boiling initiation on smooth surfaces, surface dry-out, vapor-induced flow instabilities, and premature critical heat flux (CHF). Excessive vapor generation within confined geometries can disrupt flow uniformity, causing temperature oscillations and unstable operation. To address these challenges, this work presents a confined, direct-on-silicon two-phase jet impingement cooling approach incorporating a porous-wick-assisted phase separation mechanism. The engineered porous wick enhances nucleate boiling and enables in situ phase separation at the boiling surface. Integrated with a custom three-path manifold, the design routes separated liquid and vapor streams, minimizing vapor accumulation within the confined region and suppressing two-phase instabilities. The porous wick is directly printed onto the silicon substrate using advanced additive manufacturing, eliminating the need for a thermal interface material (TIM) and its associated thermal resistance. Thermal–hydraulic characterization using a low-surface-tension dielectric fluid demonstrates that wick-assisted phase separation reduces thermal resistance by 23–29% compared to configurations without phase separation. Extended testing over more than 200 h of continuous operation confirms stable thermal performance and indicates strong potential for long-term reliability. System-level validation is demonstrated in a 1 U server equipped with an NVIDIA V100 GPU (graphics processing unit) incorporating a direct-on-silicon printed wick.more » « less
-
Abstract This work presents a robust visual diagnostic framework for analyzing pool boiling phenomena, aimed at quantifying relative changes in heat flux and providing a foundation for future predictive models with limited temperature data. Instead of directly estimating heat flux from visual features, the proposed approach focuses on identifying relative changes in boiling visual patterns to detect a shift in heat flux and infer proximity to the critical heat flux (CHF), which is a key threshold beyond which thermal performance rapidly deteriorates. At the core of this framework is a novel metric, morphological similarity, which captures variations in bubble shape and spatial organization using Scale Invariant Feature Transform (SIFT)-based feature matching between image pairs. Experimental validation on two different heated surfaces demonstrates that morphological similarity reliably tracks changes in heat flux and strongly correlates with surface superheat, a key thermal parameter. Requiring only minimal data, this method generalizes across two surfaces and offers a scalable, real-time alternative for thermal diagnostics in electronics cooling systems.more » « less
-
This work presents a robust visual diagnostic framework for analyzing pool boiling phenomena, aimed at quantifying relative changes in heat flux and providing a foundation for future predictive models with limited temperature data. Instead of directly estimating heat flux from visual features, the proposed approach focuses on identifying relative changes in boiling visual patterns to detect a shift in heat flux and infer visual changes that could help in estimating proximity to the critical heat flux (CHF), which is a key threshold beyond which thermal performance rapidly deteriorates. At the core of this framework is a novel metric, morphological similarity, which captures variations in bubble shape and spatial organization using scale invariant feature transform (SIFT)-based feature matching between image pairs. Experimental validation on two different heated surfaces demonstrates that morphological similarity reliably tracks changes in heat flux and strongly correlates with surface superheat, a key thermal parameter. Requiring only minimal data, this method generalizes across two surfaces and offers a scalable, real-time alternative for thermal diagnostics in electronics cooling systems.more » « less
-
Abstract Jet impingement can be particularly effective for removing high heat fluxes from local hotspots. Two-phase jet impingement cooling combines the advantage of both the nucleate boiling heat transfer with the single-phase sensible cooling. This study investigates two-phase submerged jet impingement cooling of local hotspots generated by a diode laser in a 100 nm thick Hafnium (Hf) thin-film on glass. The jet/nozzle diameter is ∼1.2 mm and the normal distance between the nozzle outlet and the heated surface is ∼3.2 mm. Novec 7100 is used as the coolant and the Reynolds numbers at the jet nozzle outlet range from 250 to 5000. The hotspot area is ∼ 0.06 mm2 and the applied hotspot-to-jet heat flux ranges from 20 W/cm2 to 220 W/cm2. This heat flux range facilitates studies of both the single-phase and two-phase heat transport mechanisms for heat fluxes up to critical heat flux (CHF). The temporal evolution of the temperature distribution of the laser heated surface is measured using infrared (IR) thermometry. This study also investigates the nucleate boiling regime as a function of the distance between the hotspot center and the jet stagnation point. For example, when the hotspot center and the jet are co-aligned (x/D = 0), the CHF is found to be ∼ 177 W/cm2 at Re ∼ 5000 with a corresponding heat transfer coefficient of ∼58 kW/m2.K. While the CHF is ∼ 130 W/cm2 at Re ∼ 5000 with a jet-to-hotspot offset of x/D ≈ 4.2.more » « less
