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Research Papers

Transient Data Processing of Flow Boiling Local Heat Transfer in a Multi-Microchannel Evaporator Under a Heat Flux Disturbance

[+] Author and Article Information
Houxue Huang

Laboratory of Heat and Mass Transfer (LTCM),
École Polytechnique Fédérale
de Lausanne (EPFL),
EPFL-STI-IGM-LTCM, Station 9,
Lausanne CH-1015, Switzerland
e-mail: houxue.huang@epfl.ch

Nicolas Lamaison

Laboratory of Heat and Mass Transfer (LTCM),
École Polytechnique Fédérale
de Lausanne (EPFL),
EPFL-STI-IGM-LTCM, Station 9,
Lausanne CH-1015, Switzerland

John R. Thome

Professor
Laboratory of Heat and Mass Transfer (LTCM),
École Polytechnique Fédérale
de Lausanne (EPFL),
EPFL-STI-IGM-LTCM, Station 9,
Lausanne CH-1015, Switzerland

1Corresponding author.

Contributed by the Electronic and Photonic Packaging Division of ASME for publication in the JOURNAL OF ELECTRONIC PACKAGING. Manuscript received July 13, 2016; final manuscript received November 15, 2016; published online January 5, 2017. Assoc. Editor: M. Baris Dogruoz.

J. Electron. Packag 139(1), 011005 (Jan 05, 2017) (10 pages) Paper No: EP-16-1083; doi: 10.1115/1.4035386 History: Received July 13, 2016; Revised November 15, 2016

Multi-microchannel evaporators are often used to cool down electronic devices subjected to continuous heat load variations. However, so far, rare studies have addressed the transient flow boiling local heat transfer data occurring in such applications. The present paper introduces and compares two different data reduction methods for transient flow boiling data in a multi-microchannel evaporator. A transient test of heat disturbance from 20 to 30 W cm−2 was conducted in a multi-microchannel evaporator using R236fa as the test fluid. The test section was 1 × 1 cm2 in size and had 67 channels, each having a cross-sectional area of 100 × 100 μm2. The micro-evaporator backside temperature was obtained with a fine-resolution infrared (IR) camera. The first data reduction method (referred to three-dimensional (3D)-TDMA) consists in solving a transient 3D inverse heat conduction problem by using a tridiagonal matrix algorithm (TDMA), a Newton–Raphson iteration, and a local energy balance method. The second method (referred to two-dimensional (2D)-controlled) considers only 2D conduction in the substrate of the micro-evaporator and solves at each time step the well-posed 2D conduction problem using a semi-implicit solver. It is shown that the first method is more accurate, while the second one reduces significantly the computational time but led to an approximated solution. This is mainly due to the 2D assumption used in the second method without considering heat conduction in the widthwise direction of the micro-evaporator.

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References

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Figures

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Fig. 1

Layout of the facility: (a) schematic diagram and (b) photo

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Fig. 2

Test section: (a) schematic of the microchannel evaporator, (b) photo of the microchannels with inlet orifices [1], (c) photo of the microheaters [1], and (d) photo of the manifold bottom

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Fig. 3

Initial local pressure and temperature profile

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Fig. 4

Mesh types used in the 3D-TDMA model

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Fig. 5

Flowchart for obtaining transient wall heat transfer coefficients with the 3D-TDMA method

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Fig. 6

System identification for Ki and Kp determination

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Fig. 7

Flowchart for obtaining transient wall heat transfer coefficients with the 2D-controlled method

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Fig. 8

Mass flux and inlet pressure response to the sudden heat load disturbance at 0.5 s

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Fig. 9

Transient pressure drop

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Fig. 10

Transient local pressure and temperature at four locations at the widthwise centerline: (a) local pressure, (b) local fluid temperature, and (c) local footprint temperature

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Fig. 11

Time evolution along the widthwise centerline after the heat flux disturbance at 0.5 s for both methods: (a) mean heat transfer coefficient and (b) maximum error on the calculated temperature compared to the experimental data

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Fig. 12

Time evolution of the local wall heat transfer coefficient at four different locations along the widthwise centerline after the heat flux disturbance at 0.5 s for both methods

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Fig. 13

Local wall heat transfer coefficient profiles along the widthwise centerline at five different instants of time

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