4.7 Article

Heat transfer performance and fouling factor analysis of carbon dot nanofluid synthesized using one-step method

期刊

JOURNAL OF THERMAL ANALYSIS AND CALORIMETRY
卷 148, 期 17, 页码 9217-9224

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SPRINGER
DOI: 10.1007/s10973-023-12106-3

关键词

Nanofluid; Fouling; Heat exchanger; Heat transfer coefficient; Response surface methodology

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This paper presents an experimental analysis of the fouling factor and thermal performance of a carbon-dot nanofluid on a double-pipe heat exchanger. The study reveals that the flow rate of the fluid has a significant influence on the heat transfer coefficient, while the temperature has less significance on the performance.
Heat transfer enhancement using nanofluids has been an established technique for the past few decades. However, the practical usage of the nanofluids is limited due to their various colloidal issues viz fouling and colloidal stability. This paper presents an experimental analysis of the fouling factor of carbon-dot nanofluid synthesized using a one-pot synthesis technique. In addition, the thermal performance of this heat transfer fluid/ nanofluid on a double-pipe heat exchanger was studied. Design of experiment concept was adopted to analyse the influence of various parameters like flow rate of hot and cold fluid and the inlet temperature of hot fluid on heat transfer coefficient. The resultant fouling factor observed during the study was 0.000682 m(2) K W-1. In addition, the experimentation on heat transfer performance of double pipe heat exchanger revealed that at optimum flowrates of 85 L h(-1) (Cold and hot fluid) and inlet hot fluid temperature of 48 degrees C a maximum heat transfer coefficient of 369.5 W m(-2) K-1 was observed. As it is well know that the operation conditions of the heat exchanger highly influence the heat transfer performance. This was studied using the response surface methodology, a statistical technique, which reveals that the flow rate of hot fluid highly influence the heat transfer coefficient of the heat exchanger. Whereas the temperature of the hot fluid exhibits less significance on the performance. A regression model has been developed to predict the heat transfer coefficient, which was further validated with the experimental data.

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