Heat transfer analysis of a shell and tube heat exchanger operated with graphene nanofluids

Fares, Mohammad N.; Al-Mayyahi, Mohammad A.; Al-Saad, Mohammed

doi:10.1016/j.csite.2020.100584

Cited by 130 publications

(43 citation statements)

References 14 publications

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“…Broadly, NFs have been showing essential enhancement in the overall thermal performance of many engineering systems. Focusing on solar applications, NFs positively improved the heat transfer of numerous systems other than FPSCs such as: Solar desalination systems [34], photovoltaic/thermal systems [35], solar heat exchangers [36], parabolic trough solar collectors [37], evacuated tube solar collectors [38], heat pipe in solar collectors [39], solar thermal energy storage systems [40], etc. The use of NFs in solar thermal systems results in many advantages, which can be summarized as follows:…”

Section: Applications Of Nfs In Solar Systemsmentioning

confidence: 99%

Single and Hybrid Nanofluids to Enhance Performance of Flat Plate Solar Collectors: Application and Obstacles

Al-Yasiri

Szabó

Arıcı

2020

Period. Polytech. Mech. Eng.

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Solar energy represents the best alternative for traditional energy sources used in many thermal energy systems. Among solar thermal systems, Flat Plate Solar Collectors (FPSCs) are the most utilized type implemented in low and medium-level thermal domestic applications. Recently, the usage of nanofluids (NFs) to enhance FPSCs is one of the newest technologies that has drawn the attention of researchers to improve the overall thermal efficiency of solar systems. This paper briefly reviews the recent studies carried on thermal performance enhancement of FPSCs by implementing NFs (single and hybrid NFs) considering the main influential parameters such as particle concentration, particle size, and collector area. Finally, the main obstacles reported by the researchers such as the instability, viscosity, concentration limit, corrosion effect and others are identified, which is believed to be useful for interested newcomers in this research area. Based on the studies investigated in this paper, NFs, even under low concentrations, can remarkably improve the energetic and exergetic efficiency of FPSCs.

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Section: Applications Of Nfs In Solar Systemsmentioning

confidence: 99%

Single and Hybrid Nanofluids to Enhance Performance of Flat Plate Solar Collectors: Application and Obstacles

Al-Yasiri

Szabó

Arıcı

2020

Period. Polytech. Mech. Eng.

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“…It was shown that performance of the plate heat exchanger can be enhanced using MWCNT/water as the working fluid. Fares et al [18] analyzed heat transfer of a shell and tube heat exchanger operating with graphene nanofluids. The results indicated that using graphene/water nanofluids enhanced the thermal performance of the shell and tube heat exchanger.…”

Section: Introductionmentioning

confidence: 99%

Predicting Parameters of Heat Transfer in a Shell and Tube Heat Exchanger Using Aluminum Oxide Nanofluid with Artificial Neural Network (ANN) and Self-Organizing Map (SOM)

et al. 2021

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This study is a model of artificial perceptron neural network including three inputs to predict the Nusselt number and energy consumption in the processing of tomato paste in a shell-and-tube heat exchanger with aluminum oxide nanofluid. The Reynolds number in the range of 150–350, temperature in the range of 70–90 K, and nanoparticle concentration in the range of 2–4% were selected as network input variables, while the corresponding Nusselt number and energy consumption were considered as the network target. The network has 3 inputs, 1 hidden layer with 22 neurons and an output layer. The SOM neural network was also used to determine the number of winner neurons. The advanced optimal artificial neural network model shows a reasonable agreement in predicting experimental data with mean square errors of 0.0023357 and 0.00011465 and correlation coefficients of 0.9994 and 0.9993 for the Nusselt number and energy consumption data set. The obtained values of eMAX for the Nusselt number and energy consumption are 0.1114, and 0.02, respectively. Desirable results obtained for the two factors of correlation coefficient and mean square error indicate the successful prediction by artificial neural network with a topology of 3-22-2.

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“…The heat transfer performance of graphene nanoplatelets in water has been experimentally analyzed in the literature [ 38 , 40 , 41 , 42 , 43 , 44 , 45 , 46 ]. Yarmand et al [ 38 ] analyzed GnP-Ag nanofluids, finding improvements in effective thermal conductivity and heat transfer efficiency compared to the base fluid.…”

Section: Introductionmentioning

confidence: 99%

“…Convective heat transfer coefficients and pressure drops at various mass concentrations of functionalized GnPs, from 0.25 to 1.0 wt%, were obtained; maximum enhancements of 32% in heat transfer coefficients were assessed. Fares et al [ 46 ] studied the convective heat transfer of graphene nanofluids over a vertical shell and tube heat exchanger. Different nanoparticle concentrations, inlet temperatures and flow rates were analyzed, showing a maximum enhancement in the convective heat transfer coefficient of 29% when using 0.2% graphene/water nanofluids.…”

Section: Introductionmentioning

confidence: 99%

Analysis of Heat Transfer Characteristics of a GnP Aqueous Nanofluid through a Double-Tube Heat Exchanger

et al. 2021

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The thermal properties of graphene have proved to be exceptional and are partly maintained in its multi-layered form, graphene nanoplatelets (GnP). Since these carbon-based nanostructures are hydrophobic, functionalization is needed in order to assess their long-term stability in aqueous suspensions. In this study, the convective heat transfer performance of a polycarboxylate chemically modified GnP dispersion in water at 0.50 wt% is experimentally analyzed. After designing the nanofluid, dynamic viscosity, thermal conductivity, isobaric heat capacity and density are measured using rotational rheometry, the transient hot-wire technique, differential scanning calorimetry and vibrating U-tube methods, respectively, in a wide temperature range. The whole analysis of thermophysical and rheological properties is validated by two laboratories. Afterward, an experimental facility is used to evaluate the heat transfer performance in a turbulent regime. Convective heat transfer coefficients are obtained using the thermal resistances method, reaching enhancements for the nanofluid of up to 13%. The reported improvements are achieved without clear enhancements in the nanofluid thermal conductivity. Finally, dimensionless analyses are carried out by employing the Nusselt and Péclet numbers and Darcy friction factor.

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Heat transfer analysis of a shell and tube heat exchanger operated with graphene nanofluids

Cited by 130 publications

References 14 publications

Single and Hybrid Nanofluids to Enhance Performance of Flat Plate Solar Collectors: Application and Obstacles

Single and Hybrid Nanofluids to Enhance Performance of Flat Plate Solar Collectors: Application and Obstacles

Predicting Parameters of Heat Transfer in a Shell and Tube Heat Exchanger Using Aluminum Oxide Nanofluid with Artificial Neural Network (ANN) and Self-Organizing Map (SOM)

Analysis of Heat Transfer Characteristics of a GnP Aqueous Nanofluid through a Double-Tube Heat Exchanger

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