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A diagnostic tool for detection of flow-regimes in a microchannel using transient wall temperature signal

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  • Jagirdar, Mrinal
  • Lee, Poh Seng

Abstract

Flow boiling in microchannels has been receiving a lot of attention in recent years because of its high heat flux removal capabilities at low flow rates and low pumping power. An important aspect of flow-boiling experiments is prediction or detection of the prevalent flow-regime. Currently, most researchers use high-speed camera for flow visualization for regime detection. However, in some cases due to limitations of the experimental setup and test-piece, such as multi-layer cooling of 3D IC stack, this may not be feasible. In this paper, the influence of flow-regime on frequency domain of local temperature data of the wetted surface is studied. Experiments have been performed synchronously with high speed flow visualization on a single microchannel with width and length of 2.54mm and 25.4mm respectively. The microchannel heights tested were 0.14,0.28 and 0.42mm. De-gassed, de-ionized water was used as the working fluid. Mass fluxes tested ranged from 200 to 1000kg/(m2s). Depending on the prevalent flow regime, some of the highest of peak amplitudes in the frequency domain were quite distinct. Within the bounds of current experimental parameters, it is concluded that local transient temperature data can be a potential diagnostic tool for detection of flow-regimes. (A shorter version of this paper was presented at the 7th International Conference on Applied Energy (ICAE2015), March 28–31, 2015, Abu Dhabi, UAE (Original paper title: “Temperature transients for detection of flow-regimes in a mini/microchannel” and Paper No.: 430).)

Suggested Citation

  • Jagirdar, Mrinal & Lee, Poh Seng, 2017. "A diagnostic tool for detection of flow-regimes in a microchannel using transient wall temperature signal," Applied Energy, Elsevier, vol. 185(P2), pages 2232-2244.
    • Handle: RePEc:eee:appene:v:185:y:2017:i:p2:p:2232-2244
    DOI: 10.1016/j.apenergy.2015.12.111
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    References listed on IDEAS

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    1. Shao, Liang-Liang & Yang, Liang & Zhang, Chun-Lu, 2010. "Comparison of heat pump performance using fin-and-tube and microchannel heat exchangers under frost conditions," Applied Energy, Elsevier, vol. 87(4), pages 1187-1197, April.
    2. Garimella, Suresh V. & Persoons, Tim & Weibel, Justin & Yeh, Lian-Tuu, 2013. "Technological drivers in data centers and telecom systems: Multiscale thermal, electrical, and energy management," Applied Energy, Elsevier, vol. 107(C), pages 66-80.
    3. Marcinichen, Jackson Braz & Olivier, Jonathan A. & Oliveira, Vinicius de & Thome, John R., 2012. "A review of on-chip micro-evaporation: Experimental evaluation of liquid pumping and vapor compression driven cooling systems and control," Applied Energy, Elsevier, vol. 92(C), pages 147-161.
    4. Marcinichen, Jackson Braz & Wu, Duan & Paredes, Stephan & Thome, John R. & Michel, Bruno, 2014. "Dynamic flow control and performance comparison of different concepts of two-phase on-chip cooling cycles," Applied Energy, Elsevier, vol. 114(C), pages 179-191.
    5. Yuan, Weixing & Yang, Bo & Yang, Yufei & Ren, Kexian & Xu, Jian & Liao, Yibing, 2015. "Development and experimental study of the characteristics of a prototype miniature vapor compression refrigerator," Applied Energy, Elsevier, vol. 143(C), pages 47-57.
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