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<p>Pulsating heat pipe (PHP) provides a potential method to dissipate heat for electronic devices. And its heat transfer is comprehensively affected by geometry, operation conditions, and working fluids. Recently, graphene oxide (GO) nanofluid has become more favored in the PHP. Here, response surface methodology (RSM) was adopted to guide experiments for analyzing some critical operating factors on heat transfer, including heating power (<i>Q</i>), filling ratio (<i>FR</i>), and GO concentration (<i>ω</i>). Results showed that PHP performed better at a medium <i>FR</i> (e.g., 50%) and that the thermal resistance was reduced by about 54.4% compared to pure water at <i>Q</i> = 30 W and <i>ω</i> = 0.05 mass%. Based on the RSM, a regression correlation was developed to predict the thermal resistance of the PHP using GO nanofluid, with a high coefficient of determination (0.9274) and a low P-value (0.0031). It was found that <i>Q</i> had the greatest effect on thermal resistance, followed by <i>FR</i> and <i>ω</i>. Meanwhile, <i>Q</i> and <i>FR</i> have a stronger interaction. Furthermore, the PHP was predicted to obtain lower thermal resistances (<i>R</i><sub>pre</sub> ≤ 0.52 °C W<sup>–1</sup>) in a wider operating range (i.e., <i>Q</i> = 58 W ~ 105 W, <i>FR</i> = 45% ~ 75%, <i>ω</i> = 0 ~ 0.089 mass%) with 4.4% mean absolute percentage error of the model, which will be beneficial for the PHP’s effective operation in practical applications.</p>

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Heat transfer improvement and optimization of a pulsating heat pipe with graphene oxide nanofluid using response surface methodology

  • 期刊论文

  • 发表日期：

    2026年2月7日

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  • Yabing Chen,
  • Honghai Yang,
  • Jun Wang,
  • Weixue Kong,
  • Yuhao Liu,
  • Wenxiang Chen

摘要

Pulsating heat pipe (PHP) provides a potential method to dissipate heat for electronic devices. And its heat transfer is comprehensively affected by geometry, operation conditions, and working fluids. Recently, graphene oxide (GO) nanofluid has become more favored in the PHP. Here, response surface methodology (RSM) was adopted to guide experiments for analyzing some critical operating factors on heat transfer, including heating power (Q), filling ratio (FR), and GO concentration (ω). Results showed that PHP performed better at a medium FR (e.g., 50%) and that the thermal resistance was reduced by about 54.4% compared to pure water at Q = 30 W and ω = 0.05 mass%. Based on the RSM, a regression correlation was developed to predict the thermal resistance of the PHP using GO nanofluid, with a high coefficient of determination (0.9274) and a low P-value (0.0031). It was found that Q had the greatest effect on thermal resistance, followed by FR and ω. Meanwhile, Q and FR have a stronger interaction. Furthermore, the PHP was predicted to obtain lower thermal resistances (Rpre ≤ 0.52 °C W–1) in a wider operating range (i.e., Q = 58 W ~ 105 W, FR = 45% ~ 75%, ω = 0 ~ 0.089 mass%) with 4.4% mean absolute percentage error of the model, which will be beneficial for the PHP’s effective operation in practical applications.