An official website of the United States government
Abstract Boiling is a high-performance heat dissipation process that is central to electronics cooling and power generation. The past decades have witnessed significantly improved and better-controlled boiling heat transfer using structured surfaces, whereas the physical mechanisms that dominate structure-enhanced boiling remain contested. Experimental characterization of boiling has been challenging due to the high dimensionality, stochasticity, and dynamicity of the boiling process. To tackle these issues, this paper presents a coupled multimodal sensing and data fusion platform to characterize boiling states and heat fluxes and identify the key transport parameters in different boiling stages. Pool boiling tests of water on multi-tier copper structures are performed under both steady-state and transient heat loads, during which multimodal, multidimensional signals are recorded, including temperature profiles, optical imaging, and acoustic signals via contact acoustic emission (AE) sensors, hydrophones immersed in the liquid pool, and condenser microphones outside the boiling chamber. The physics-based analysis is focused on i) extracting dynamic characteristics of boiling from time lags between acoustic-optical-thermal signals, ii) analyzing energy balance between thermal diffusion, bubble growth, and acoustic dissipation, and iii) decoupling the response signals for different physical processes, e.g., low-to-midfrequency range AE induced by thermal expansion of liquids and bubble ebullition. Separate multimodal sensing tests, namely a single-phase liquid test and a single-bubble-dynamics test, are performed to reinforce the analysis, which confirms an AE peak of 1.5 kHz corresponding to bubble ebullition. The data-driven analysis is focused on enabling the early fusion of acoustic and optical signals for improved boiling state and flux predictions. Unlike single-modality analysis or commonly-used late fusion algorithms that concatenate processed signals in dense layers, the current work performs the fusion process in the deep feature domain using a multi-layer perceptron regression model. This early fusion algorithm is shown to lead to more accurate and robust predictions. The coupled multimodal sensing and data fusion platform is promising to enable reliable thermal monitoring and advance the understanding of dominant transport mechanisms during boiling.
more »
« less
BubbleID: A deep learning framework for bubble interface dynamics analysis
This paper presents BubbleID, a sophisticated deep learning architecture designed to comprehensively identify both static and dynamic attributes of bubbles within sequences of boiling images. By amalgamating segmentation powered by Mask R-CNN with SORT-based tracking techniques, the framework is capable of analyzing each bubble's location, dimensions, interface shape, and velocity over its lifetime and capturing dynamic events such as bubble departure. BubbleID is trained and tested on boiling images across diverse heater surfaces and operational settings. This paper also offers a comparative analysis of bubble interface dynamics prior to and post-critical heat flux conditions.
more »
« less
- Award ID(s):
- 2323022
- PAR ID:
- 10593819
- Publisher / Repository:
- American Institute of Physics
- Date Published:
- Journal Name:
- Journal of Applied Physics
- Volume:
- 136
- Issue:
- 1
- ISSN:
- 0021-8979
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
More Like this
-
-
Nucleation and bubble dynamics on a heater surface contribute to high heat transfer rate in pool boiling. Introducing two-phase flow in narrow channels further improves heat transfer. Use of expanding taper microgap geometry further enhances heat transfer, and proper balancing of taper angles and flow lengths leads to self-sustained flow boiling in tapered microgap geometries. This paper focuses on understanding the underlying enhancement mechanism by studying the bubble behavior as they expand and accelerate in the direction of increased taper. The present study conducts a 2D simulation analysis of bubble growth in tapered microgaps with numerical simulations to identify the effect of the fluid properties and tapered angle in the bubble and fluid dynamics behavior. Ansys-Fluent is customized with user-defined-functions (UDFs) accounting for the interfacial heat and mass transport, including a sharp interface and direct calculation of mass transfer with temperature gradients. The study was conducted using air injection and boiling simulation from the conception to the departure of a bubble. The tapered angles were 5°, 10°, and 15°, with flowrates between 3 ml/min to 30 ml/min, 1 mm air inlet, and at 1 mm distance from the convergent end. The departure time of 10 subsequent bubbles was recorded to check the configuration with the quickest bubble removal. A critical flowrate and surface tension region was established for the escape direction of the bubble. In addition, the numerical simulation considered the tapered microgap with a nucleating bubble at atmospheric conditions with a wall superheats of 5 K. The results show that the bubble growing over the heated surface creates fluid circulations and interfacial conditions that suppress the thermal boundary layer leading to an increased local heat transfer coefficient within a range of 1 mm from the interface.more » « less
-
Abstract Boiling is arguably Nature’s most effective thermal management mechanism that cools submersed matter through bubble-induced advective transport. Central to the boiling process is the development of bubbles. Connecting boiling physics with bubble dynamics is an important, yet daunting challenge because of the intrinsically complex and high dimensional of bubble dynamics. Here, we introduce a data-driven learning framework that correlates high-quality imaging on dynamic bubbles with associated boiling curves. The framework leverages cutting-edge deep learning models including convolutional neural networks and object detection algorithms to automatically extract both hierarchical and physics-based features. By training on these features, our model learns physical boiling laws that statistically describe the manner in which bubbles nucleate, coalesce, and depart under boiling conditions, enabling in situ boiling curve prediction with a mean error of 6%. Our framework offers an automated, learning-based, alternative to conventional boiling heat transfer metrology.more » « less
-
Heat transfer due to the convective boiling mechanism in the microchannel plays an important role in heat transfer during boiling. Therefore, it is relevant to find ways to manipulate the vapor bubbles such that convection heat transfer is enhanced. This numerical study investigates the effects of different geometrical parameters on bubble movement through a micro tapered gap. The objective is to identify an optimal configuration such that the bubble moves at the fastest possible speed when it travels through the micro gap. To conduct this research a model is created using ANSYS-Fluent which uses the Volume of Fluid (VOF) interface tracking method. The multiphase VOF model tracks the air-water interface. A bubble is generated inside the microchannel in which fluid is flowing. The overall domain of the model consists of the surface at the bottom, having an orifice through which the air bubble is generated. Three different cases of an angled tapered surface are created 5°, 10°, and 15°. The airflow rate is kept constant throughout each simulation. Simulation results show the impact of the tapered angle on the bubble’s flow movement and flow direction. Liquid and air velocity contours can be used to analyze the flow. The impact of the taper angles on the movement and flow direction of the air bubble is discussed. It is observed that the performed simulations help to better understand the experimental observation of bubble motion; the simulations give clear evidence of the fluid dynamic behavior along the tapered microchannel.more » « less
-
Abstract Squeezing bubbles in a tapered microgap has proved to be effective for improving flow stability in flow boiling. A previous study from our research group has successfully demonstrated using tapered microgap for transforming pool boiling into a self-sustained flow boiling-like system for cooling CPU through thermosiphon. To overcome the imaging challenges with nucleating vapor bubbles, the present work investigates the squeezing behaviour of air-injected bubbles between a tapered microgap with taper angles of 5°, 10°, and 15°. The air bubbles are injected at a rate of 3 ml/min, 15ml/min, and 30 ml/min in a pool of water. The bubble squeezing is recorded at 2000fps using a Photron high-speed camera. The experimental analysis compares the displacement and velocity of the advancing and receding bubble interfaces. The analysis found that in certain test cases, multiple bubbles coalesced while exiting the tapered microgap. In all the test cases, the receding interface of the bubble slingshots after detaching pushes the bubble out of the tapered microgap. The result from the current study provides an insight into the bubble flow and squeezing behavior that can be used for optimizing taper microgap geometries to enhance critical heat flux and heat transfer coefficient of two-phase, and air-injected single-phase heat transfer systems.more » « less
