Search

A reduction in the environmental impact of energy consumption can be achieved through the integration of renewable energy with desalination. In this paper, a simulation of a solar desalination plant was performed using the finite element method. A small amount of alumina nanoparticles was added to the salt water in the desalination water. Two-phase method was used for its analysis. By changing the wall height parameters from 5 to 20 cm, the glass angle from 10 to 45° and the ambient temperature from 10 to 55°, the entropy (ENT) values produced in desalination were studied. Thermal ENT, friction ENT and total ENT were studied by changing the parameters and an optimization was done on the parameters to have the lowest ENT production in desalination using machine learning. The results of this study showed that the thermal ENT was greater than the friction ENT in the desalination water. An increase in ambient temperature has reduced some of the ENT production of friction, thermal ENT and total ENT. Increasing the height of the desalination wall has less effect on the ENT production and it can be seen that the increase of the desalination wall height has increased the production of thermal ENT and total ENT, but its further increase has decreased the production of thermal ENT and total ENT. [ABSTRACT FROM AUTHOR]

Human life is being impacted by nanotechnology in many ways, including economics, production, and the environment. The present study has numerically investigated the laminar flow and natural convection heat transfer (NACHT) in a square enclosure filled with nanofluids (NFs), considering the entropy generation (ETG) and Be. The 2D enclosure includes two rectangular fins attached to the left hot wall and a single fin of very high temperature positioned in the middle of the enclosure. A constant magnetic field (MCF) has been applied to the enclosure. The average Nu, maximum value of stream function (MXSF), generated entropy, and Be have been examined by changing the length and thickness of the middle fin and the distance between heated fins (fin spacing). Finally, these parameters have been optimized through machine learning methods to determine the best case with the highest HT rate and lowest ETG rate. A two-phase model based on control volume has been used for NFs flow simulation. Results indicated that increasing fin length (w) increases Be and decreases the MXSF. Also, by increasing the w, the Nu and generated entropy initially decrease and then increase. Increasing the fin thickness (b) and fin spacing lead to a decrease in the MXSF. Increasing thickness for the fin increases the Nu but decreases it for larger fin spacing.Furthermore, the studied model is less harmful to the environment than existing models. [ABSTRACT FROM AUTHOR]

Investigating the entropy production (ETP) and inertial number can help to improve the efficiency of heat transfer devices, for this reason, in this paper, the study of the ETP of nanofluid (NNF) flow in a two-dimensional cavity was studied. The NNF flow is affected by the horizontal magnetic field (MGD). Also, the Bejan number (Be) of the flow was also studied for different states of the mentioned parameters. The cavity had two hot and cold walls and two insulated walls, the cold wall above which was also movable. On the lower warm wall, there are 3 blades in the shape of a triangle, the height of each of which was changed individually from 0.1 to 0.7 and its effect on entropy changes and Be was investigated. Finally, using artificial intelligence, the best conditions for having the lowest Be and ETP for the range of variables were checked. The NNF was simulated in two phases and the simulation was done in FORTRAN software using SIMPLE algorithm. The results of this study showed that the largest amount of Be was present in the longest length of the triangular obstacles, but the lowest value of the Be was in the low values of the height of theobstacles and did not necessarily occur in the lowest values of the heights. The highest amount of entropy was produced at the lowest height of the left obstacle and the highest height of the middle obstacle. Also, the amount of ETP at higher altitudes on the right side of the obstacle was greater than its lower altitudes. [ABSTRACT FROM AUTHOR]

In this article, a numerical study was conducted on the mixed convection (CNV) of nanofluid (NFD) in a two-dimensional rectangular cavity using the control volume method. The upper and lower walls of the cavity were cold and hot, respectively, and its two vertical walls were insulated. The Upper wall has constant velocity and order to create a forced CNV in the cavity. They positioned three triangle-shaped obstacles on the heated wall that were likewise hot. The velocity and temperature graph values in the cavity, the velocity and streamline contours, and the Nusselt number value were examined independently by varying the height (HIT) of each barrier. Using artificial intelligence, the best values of the parameters to have the strongest flow and the most heat transfer (HTF) were checked. Two-phase method was used to simulate NFD flow. The results of this study showed that the middle obstacle with the highest HIT had more HTF. Increasing the length of the obstacle on the right has reduced the amount of HTF and the highest HTF occurred at the lowest HIT of this obstacle. When the obstacle on the left side has the HIT, the amount of HTF is the highest, while its average value has minimized the HTF. An increase in the HIT of the right fin at different HITs of the other two fins reduces the average Nu value [ABSTRACT FROM AUTHOR]

In this article, natural alumina/water nanofluid (NF) convection in an isosceles equilateral rhombus-shaped enclosure was simulated using the Simplex algorithm and the control volume method. The enclosure under study had two insulation walls, i.e., a cold wall and a warm wall. Two blades were installed on the warm wall with a temperature equal to that of the warm wall. There was also a fin in the center of the enclosure with a temperature equal to that of the warm wall. The enclosure was horizontally under a magnetic field at Hartmann number (Ha) of 20. The average Nusselt number (Nu), entropy production, Bejan number (Be), and flow and temperature contours were studied while altering the length and thickness of the blades from 0.1 to 0.8 and 0.05 to 0.15, respectively, and the aspect ratio (AR) of the fin from 0.1 to 0.4. The obtained results were then optimized to catch the best results. The two-phase method was used to simulate nanofluid flow. By altering the width and length of the blades and the fin AR, the average Nu varies from 6.52 to 8.31. According to the results, within the range of the above variables, Nu, entropy production, and Be varied from 5.62 to 8.31, 7.55 to 12.36, and 0.48 to 0.6, respectively. [ABSTRACT FROM AUTHOR]

This paper examines the mixed convective heat transfer (HTR) of nanofluid (NFD) flow in a rectangular enclosure with the upper moving wall numerically. The lower wall has a high temperature and a number of semi-circular obstacles with the same temperature are installed on it. The upper moving wall has a low temperature and the other two walls are insulated. The enclosure can change from horizontal to vertical. Radiation HTR is considered in the enclosure and there is a magnetic field (MGF) that can change the angle from horizontal to vertical affecting the NFD. This study is carried out for different angles of the enclosure and MGF from horizontal to vertical for radiation parameters (RDP) of 0 to 3 and a constant MGF with Hartmann number of 20 and Richardson number of 10. The aim is to estimate the Nusselt number (Nu), entropy generation (ETG), and Bejan number (Be). The SIMPLE algorithm is utilized using FORTRAN software, and optimization is done using artificial intelligence to find the maximum and minimum output values. The results demonstrate that the maximum value of Nu and Bes corresponds to the MGF angle and enclosure angle of 90°. The minimum value of the Nu and the maximum amount of ETG corresponds to the horizontal MGF and horizontal enclosure when the RDP is 1.5. An increment in the RDP enhances the amount of Nu. The maximum amount of ETG, i.e. 12.87, corresponds to the enclosure with an angle of 45° for the horizontal MGF and the absence of RDP. corresponds to the enclosure with an angle of 45° for the horizontal MGF and the absence of RDP. It was also found that most environmental impacts, and hence values for different environmental factors, arise from the production of nanoparticles; thus, it is a significant contributor to environmental impacts. [ABSTRACT FROM AUTHOR]