Exergoeconomic analysis of photovoltaic thermal systems based on phase change materials and natural zeolites for thermal management

Kandilli, Canan; Uzel, Mert

doi:10.1007/s10973-021-10574-z

Cited by 10 publications

(2 citation statements)

References 31 publications

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“…Normalized root mean square was used to check and evaluate the performance of the ANN [ 33 ]. Three inputs (L: load, S: speed, D: distance) were used to construct the ANN architecture for all the samples in which weight loss (w) was the output, and the hidden layer indicated that an interaction between the neurons was not visible [ 54 , 55 , 56 , 57 ].…”

Section: Resultsmentioning

confidence: 99%

Multi Ceramic Particles Inclusion in the Aluminium Matrix and Wear Characterization through Experimental and Response Surface-Artificial Neural Networks

et al. 2021

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Lightweight composite materials have recently been recognized as appropriate materials have been adopted in many industrial applications because of their versatility. The present research recognizes the inclusion of ceramics such as Gr and B4C in manufacturing AMMCs through stir casting. Prepared composites were tested for hardness and wear behaviour. The tests’ findings revealed that the reinforced matrix was harder (60%) than the un-reinforced alloy because of the increased ceramic phase. The rising content of B4C and Gr particles led to continuous improvements in wear resistance. The microstructure and worn surface were observed through SEM (Scanning electron microscope) and revealed the formation of mechanically mixed layers of both B4C and Gr, which served as the effective insulation surface and protected the test sample surface from the steel disc. With the rise in the content of B4C and Gr, the weight loss declined, and significant wear resistance was achieved at 15 wt.% B4C and 10 wt.% Gr. A response surface analysis for the weight loss was carried out to obtain the optimal objective function. Artificial neural network methodology was adopted to identify the significance of the experimental results and the importance of the wear parameters. The error between the experimental and ANN results was found to be within 1%.

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Section: Resultsmentioning

confidence: 99%

Multi Ceramic Particles Inclusion in the Aluminium Matrix and Wear Characterization through Experimental and Response Surface-Artificial Neural Networks

et al. 2021

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“…The free convection happens due to the buoyancy-driven forces which emerge because of the distinction in temperature gradients and densities inside the liquid. The convective heat energy transfer has been remained an attractive research field because of its wide scope of uses in engineering and industry, Sowmya et al [1], Nehad Ali Shah et al [2], Kassai et al [3]. The application of an external magnetic field changes the liquid flow shape.…”

Section: Introductionmentioning

confidence: 99%

Numerical modeling on hybrid nanofluid (Fe3O4+MWCNT/H2O) migration considering MHD effect over a porous cylinder

Shah¹,

Saeed

Khan

et al. 2021

PLoS ONE

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The free convective hybrid nanofluid (Fe3O4+MWCNT/H2O) magnetized non-Darcy flow over a porous cylinder is examined by considering the effects constant heat source and uniform ambient magnetic field. The developed coupled PDEs (partial differential equations) are numerically solved using the innovative computational technique of control volume finite element method (CVFEM). The impact of increasing strength of medium porousness and Lorentz forces on the hybrid nanofluid flow are presented through contour plots. The variation of the average Nusselt number (Nuave) with the growing medium porosity, buoyancy forces, radiation parameter, and the magnetic field strength is presented through 3-D plots. It is concluded that the enhancing medium porosity, buoyancy forces and radiation parameter augmented the free convective thermal energy flow. The rising magnetic field rises the temperature of the inner wall more drastically at a smaller Darcy number. An analytical expression for Nusselt number (Nuave) is obtained which shows its functional dependence on the pertinent physical parameters. The augmenting Lorentz forces due to the higher estimations of Hartmann retard the hybrid nanoliquid flow and hence enhance the conduction.

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Exergetic, exergo-economic, and exergo-environmental analyses of a trigeneration system driven by biomass and natural gas

Jalili

Ghasempour

Ahmadi

et al. 2021

J Therm Anal Calorim

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Exergoeconomic analysis of photovoltaic thermal systems based on phase change materials and natural zeolites for thermal management

Cited by 10 publications

References 31 publications

Multi Ceramic Particles Inclusion in the Aluminium Matrix and Wear Characterization through Experimental and Response Surface-Artificial Neural Networks

Multi Ceramic Particles Inclusion in the Aluminium Matrix and Wear Characterization through Experimental and Response Surface-Artificial Neural Networks

Numerical modeling on hybrid nanofluid (Fe3O4+MWCNT/H2O) migration considering MHD effect over a porous cylinder

Exergetic, exergo-economic, and exergo-environmental analyses of a trigeneration system driven by biomass and natural gas

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