Experimental and support vector machine predictions of entropy generations and exergy efficiency of Fe3O4-SiO2/Water hybrid nanofluid in a plate heat exchanger

Several experiments of Fe3O4-SiO2/water hybrid nanofluids with volumetric concentrations ranging from 0.2 % to 1.0 % circulating in the cold-side of a plate heat exchanger at flow rates ranging from 0.05 kg/s to 0.1166 kg/s are performed. Under these ranges of flow rates and volumetric concentrations, the flow of Fe3O4-SiO2/water hybrid nanofluids remains laminar. The results of these experiments are predicted with support vector machine (SVM) algorithm to determine hybrid nanofluid entropy generation thermal, entropy generation frictional, and effi-ciency of exergy. Fe3O4-SiO2 nanomaterials was synthesized with reduction of chemicals and insitu development techniques, with XRD, FTIR and VSM instruments, characterizations were done. The SVM model gives large precision predictions of the measured data with correlations coefficients of 0.9944, 0.99798, and 0.99428 for frictional entropy generation, thermal entropy generation and exergy efficiency. At a flow rate of 0.1166 kg/s in the cold-side of PHE, the exergy efficiency is found to be 77.96 % for water (Reynolds number of 935.4) and with 1.0 vol% of Fe3O4-SiO2/water hybrid nanofluid in the cold-side of PHE, the efficiency is increased to 82.97 %, respectively. Under similar conditions of 0.1166 kg/s of flow circulation and 1.0 % vol. concentration of hybrid nanofluid, the thermal entropy generation is dropped off to 18.37 %, but the frictional entropy generation is increased by 20.97 %, compared to water, with the results that the total entropy generation drops off by 15.91 %, compared to water data. Preliminary curve-fitting correlations have been developed for the frictional entropy generation, thermal entropy generation, and exergy efficiency.

Automated summary

This study investigates the performance of Fe3O4-SiO2/water hybrid nanofluids in a plate heat exchanger. Experimental results show that the flow of these hybrid nanofluids remains laminar within the tested flow rates and volumetric concentrations. The support vector machine (SVM) algorithm is used to predict the entropy generation and efficiency of the hybrid nanofluids. The results demonstrate that the Fe3O4-SiO2/water hybrid nanofluids can improve the exergy efficiency and reduce the total entropy generation in the heat exchanger.