Researchers always like to find way for improving the performance of system integrated with PCM. ... more Researchers always like to find way for improving the performance of system integrated with PCM. In this paper, the container was combined with fins and PCM was mixed with nanoparticles to obtain quicker discharging process. Two significant variables related to second technique are fraction of additives ([Formula: see text] and their shapes ([Formula: see text]. To involve these factors in equations, single phase formulation was applied. Low magnitude of velocity of liquid material in freezing leads to simplification of equations of this transient procedure. Galerkin method which was applied for this modeling has good accommodation with previous publication. As [Formula: see text] soars, the solidification time declines from 4802.97s to 4244.61s and 3738.37s when blade shape particles were applied. This means that adding additive can enhance the rate of process about 22.16%. Moreover, augmenting the shape factor to higher level causes time to drop about 5.7%.
This review is about non-Newtonian nanofluid applications for convection in cavities under a magn... more This review is about non-Newtonian nanofluid applications for convection in cavities under a magnetic field. Convection in cavities is an important topic in thermal energy system, and diverse applications exist in processes such as drying, chemical processing, electronic cooling, air conditioning, removal of contaminates, power generation and many others. Some problems occur in symmetrical phenomena, while they can be applicable to applied mathematics, physics and thermal engineering systems. First, brief information about nanofluids and non-Newtonian fluids is given. Then, non-Newtonian nanofluids and aspects of rheology of non-Newtonian fluids are presented. The thermal conductivity/viscosity of nanofluids and hybrid nanofluids are discussed. Applications of non-Newtonian nanofluids with magnetohydrodynamic effects are given. Different applications of various vented cavities are discussed under combined effects of using nanofluid and magnetic field for Newtonian and non-Newtonian ...
In this study, the accuracy of applying artificial neural networks and response surface methodolo... more In this study, the accuracy of applying artificial neural networks and response surface methodology in estimating kSiO2/EG was examined. Thermal conductivity prediction in the temperature range of 5–65 °C and mass fractions of 0.005–5 wt.% was performed. Considering the constraints of minimizing the mean square error (MSE) as well as maximizing the R-squared value, the most appropriate polynomial based on linear regression (for RSM) and the optimal number of neurons were obtained through performing the least squares methodology. Statistical calculations showed that MSE value for ANN and RSM techniques was 0.0000342 and 0.0001577, respectively. Comparing the R-squared values of ANN (0.993) and RSM (0.968) methods, it was found that from this perspective, the artificial neural network is superior. Comparing the results of the simulation and the laboratory, it was observed that both methods are not very accurate at low mass fractions. However, the potential of the ANN technique was greater than RSM one. Also, the usefulness of SiO2/EG nanofluid through helically coiled tube heat exchanger (HCTHE) was challenged from the perspective of the second law of thermodynamics. Performing exergy balance revealed that the exergy destruction is intensified at higher mass fraction and lower temperature. Applying RSM on irreversibility affirmed that the cubic linear regression led to statistical criteria of R2=0.9999\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$R^{2} = 0.9999$$\end{document} and MOD less than 0.008%\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$0.008\%$$\end{document}, and therefore, it is recommended to navigate the exergy destruction through HCTHE.
Researchers always like to find way for improving the performance of system integrated with PCM. ... more Researchers always like to find way for improving the performance of system integrated with PCM. In this paper, the container was combined with fins and PCM was mixed with nanoparticles to obtain quicker discharging process. Two significant variables related to second technique are fraction of additives ([Formula: see text] and their shapes ([Formula: see text]. To involve these factors in equations, single phase formulation was applied. Low magnitude of velocity of liquid material in freezing leads to simplification of equations of this transient procedure. Galerkin method which was applied for this modeling has good accommodation with previous publication. As [Formula: see text] soars, the solidification time declines from 4802.97s to 4244.61s and 3738.37s when blade shape particles were applied. This means that adding additive can enhance the rate of process about 22.16%. Moreover, augmenting the shape factor to higher level causes time to drop about 5.7%.
This review is about non-Newtonian nanofluid applications for convection in cavities under a magn... more This review is about non-Newtonian nanofluid applications for convection in cavities under a magnetic field. Convection in cavities is an important topic in thermal energy system, and diverse applications exist in processes such as drying, chemical processing, electronic cooling, air conditioning, removal of contaminates, power generation and many others. Some problems occur in symmetrical phenomena, while they can be applicable to applied mathematics, physics and thermal engineering systems. First, brief information about nanofluids and non-Newtonian fluids is given. Then, non-Newtonian nanofluids and aspects of rheology of non-Newtonian fluids are presented. The thermal conductivity/viscosity of nanofluids and hybrid nanofluids are discussed. Applications of non-Newtonian nanofluids with magnetohydrodynamic effects are given. Different applications of various vented cavities are discussed under combined effects of using nanofluid and magnetic field for Newtonian and non-Newtonian ...
In this study, the accuracy of applying artificial neural networks and response surface methodolo... more In this study, the accuracy of applying artificial neural networks and response surface methodology in estimating kSiO2/EG was examined. Thermal conductivity prediction in the temperature range of 5–65 °C and mass fractions of 0.005–5 wt.% was performed. Considering the constraints of minimizing the mean square error (MSE) as well as maximizing the R-squared value, the most appropriate polynomial based on linear regression (for RSM) and the optimal number of neurons were obtained through performing the least squares methodology. Statistical calculations showed that MSE value for ANN and RSM techniques was 0.0000342 and 0.0001577, respectively. Comparing the R-squared values of ANN (0.993) and RSM (0.968) methods, it was found that from this perspective, the artificial neural network is superior. Comparing the results of the simulation and the laboratory, it was observed that both methods are not very accurate at low mass fractions. However, the potential of the ANN technique was greater than RSM one. Also, the usefulness of SiO2/EG nanofluid through helically coiled tube heat exchanger (HCTHE) was challenged from the perspective of the second law of thermodynamics. Performing exergy balance revealed that the exergy destruction is intensified at higher mass fraction and lower temperature. Applying RSM on irreversibility affirmed that the cubic linear regression led to statistical criteria of R2=0.9999\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$R^{2} = 0.9999$$\end{document} and MOD less than 0.008%\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$0.008\%$$\end{document}, and therefore, it is recommended to navigate the exergy destruction through HCTHE.
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Papers by Nidal H Abu-Hamdeh