Prediction Model for Flow Boiling Heat Transfer of Nanorefrigerant in Microchannels
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    Abstract:

    R141b and Al2O3 were selected as base fluid and nanoparticle, respectively, and the two-step method was used to prepare Al2O3-R141b nanorefrigerant. The mass fractions were 0.2%, 0.5% and 0.8%, respectively. The flow boiling heat transfer of Al2O3-R141b nanorefrigerant and R141b refrigerant in rectangular microchannels with hydraulic diameter of 1.33mm was experimentally investigated. Experimental conditions included saturation pressure of 176kPa,inlet subcooling from 6℃ to 12℃,volume flow rate from 20L/h to 50L/h,and heat flux from 11.1kW/m to 26.6kW/m. The experimental results were used to evaluate seven heat transfer models for pure working fluid and two heat transfer models for nanorefrigerant. Results showed that the pure working fluid heat transfer models were not suitable for nanorefrigerant. The Peng-Ding heat transfer model for nanorefrigerant combined with the Kim-Mudawar model for pure working fluid gave relatively good agreement with experimental data, the mean absolute error (MAE) was 17.22%, which reflected the effect of nanoparticles on flow boiling heat transfer. A new nanoparticle impact factor (the ratio of heat transfer coefficient of nanorefrigerant to refrigarant) correlation was proposed based on Peng-Ding model and experimental data, the new correlation had good predictability with MAE of 15.2%, and the new correlation combined with the Bertsch model provided good prediction of heat transfer coefficient for nanorefrigerant in microchannels, and the MAE was decreased to 16.4%.

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History
  • Received:January 18,2016
  • Revised:
  • Adopted:
  • Online: August 10,2016
  • Published: August 10,2016
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