Numerical and experimental analysis of performance in a compact plate heat exchanger using graphene oxide/water nanofluid

Abstract

Purpose This study aims to present the experimental and computational performance analysis in compact plate heat exchanger (PHE) using graphene oxide nanofluids at different concentrations and flow rate. Design/methodology/approach Field emission scanning electron microscope and X-ray diffraction were used to characterize graphene oxide nanoparticles. The nanofluid samples were prepared by varying volume concentration. Zeta potential test was done to check stability of samples. The thermophysical properties of samples have been experimentally measured. The experimental setup of PHE with 60° chevron angle has also been developed. The numerical analysis is done using computational fluid dynamics (CFD) model having similar geometry as of the actual plate. Distilled water at fixed temperature and flow rate is used in hot side tank. Nanofluid at fixed temperature with varying concentration and flow rate is used in cold side tank as coolant. Findings The numerical and experimental results were compared and found that both results were in good agreement. The results showed ∼13% improvement in thermal conductivity, ∼14% heat transfer rate (HTR), ∼9% in effectiveness and ∼10% in overall heat transfer coefficient at cost of pressure drop and pumping power using nanofluid. Exergy loss also decreased using nanofluid at optimum concentration of 1 Vol.%. Originality/value The CFD model can be significant to analyze temperature, pressure and flow distribution in heat exchanger which is impossible otherwise. This study gives ease to predict PHE performance with high accuracy without performing the experiment.

Pressure drop and heat transfer characteristics in 60° Chevron plate heat exchanger using Al2O3, GNP and MWCNT nanofluids

“…Similarly, peaks for GnP nanoparticles are 26.478 and 54.52 indexed to (200) and (004), respectively, and MWCNT nanoparticles are 25.689 and 44.28 indexed to (002) and (101), respectively. The diffractions peaks of Al 2 O 3 , GnP and MWCNT were also compared with earlier studies Mirzaei et al (2018), Singh et al (2021a) and Esfe et al (2017), respectively, and are in good agreement.…”

“…Thus, exergy loss is evaluated by varying flow rate displayed in Figure 8(h). An increase in exergy loss is noticed with increasing flow rate (Singh et al , 2021a). However, using nanofluids showed a decrease in exergy.…”

“…Effectiveness increases ranging from 0.688 to 0.7157, 0.7069 to 0.724, 0.7177 to 0.739 using Al 2 O 3 , GnP and MWCNT nanofluids, respectively, between 0.1 and 1 Vol.% as shown in Figure 9(g). Figure 9(h), the exergy loss is minimum for MWCNT nanofluid because of more decrease in entropy generation than GnP and Al 2 O 3 nanofluid (Singh et al , 2021a).…”

“…The spherical and spheroidal nanoparticles improve the performance. Singh et al (2021a) reported experimental and numerical analysis (single-phase) using GO nanofluid in the compact heat exchanger and reported 14 and 10% improvement in HTR and OHTC, respectively. Kanaris et al (2009) used a 3 D CFD model to predict the performance of PHE having design variables such as blockage angle, channel aspect ratio, attack angle, channel and corrugation aspect ratio, herringbone pattern and Reynolds number.…”

An MHD Fluid Flow over a Porous Stretching/Shrinking Sheet with Slips and Mass Transpiration

“…Additionally, graphene is the thinnest as well as the strongest material. Some recent works on graphene are given in [27][28][29].…”