In many real-life applications e. Internal and external flow can also classify convection. Internal flow occurs when a fluid is enclosed by a solid boundary such when flowing through a pipe. An external flow occurs when a fluid extends indefinitely without encountering a solid surface. Both of these types of convection, either natural or forced, can be internal or external because they are independent of each other. Further classification can be made depending on the smoothness and undulations of the solid surfaces. Not all surfaces are smooth, though a bulk of the available information deals with smooth surfaces.
What’s the Difference Between Conduction, Convection, and Radiation? | Machine Design
Wavy irregular surfaces are commonly encountered in heat transfer devices which include solar collectors, regenerative heat exchangers and underground energy storage systems. They have a significant role to play in the heat transfer processes in these applications. Since they bring in an added complexity due to the undulations in the surfaces, they need to be tackled with mathematical finesse through elegant simplification techniques. Also they do affect the flow and heat transfer characteristics, thereby behaving differently from straight smooth surfaces.
For a visual experience of natural convection, a glass filled with hot water and some red food dye may be placed inside a fish tank with cold, clear water. The convection currents of the red liquid may be seen to rise and fall in different regions, then eventually settle, illustrating the process as heat gradients are dissipated. Convection-cooling is sometimes loosely assumed to be described by Newton's law of cooling. Newton's law states that the rate of heat loss of a body is proportional to the difference in temperatures between the body and its surroundings while under the effects of a breeze.
The constant of proportionality is the heat transfer coefficient. In classical natural convective heat transfer, the heat transfer coefficient is dependent on the temperature. However, Newton's law does approximate reality when the temperature changes are relatively small. The convective heat transfer coefficient is dependent upon the physical properties of the fluid and the physical situation. Values of h have been measured and tabulated for commonly encountered fluids and flow situations. From Wikipedia, the free encyclopedia. Main article: Newton's law of cooling. Joannes Nichols, Isaaci Newtoni Opera quae exstant omnia , vol.
Colorado State University. But in the case of EG based nanofluids the calculated value is very much less than the correlated value. This suggests that there are other mechanisms contribute to the thermal conductivity of EG based f-HEG dispersed nanofluids. Correlation of experiment with theory.
Convective Heat Transfer
Finally electrical conductivity was also measured for some volume fractions of f-HEG dispersed nanofluid. The graph suggests that like thermal conductivity, electrical conductivity also increased with increase in volume fraction and increase in temperature. Figure 7b shows the normalized electrical conductivity of f-HEG dispersed EG based nanofluid for three different volume fractions at varying temperature.
Normalized electrical conductivity of f-HEG dispersed a DI water and b EG based nanofluids for different volume fractions and varying temperatures.
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The heat transfer coefficient, h is a macroscopic parameter describing heat transfer when a fluid is flowing across a solid surface of different temperature. It is not a material property. The convective heat transfer coefficient is defined as.
Equation 3 is based on an assumption of zero heat loss through the insulation layer. To check the reliability and accuracy of fabricated experimental setup, systematic measurements were carried out using DI water as the working fluid for different flow rates. The experimental results obtained for different flow rates were correlated with well-known Shah correlation [ 22 ] and Dittus-Boelter [ 23 ] equation under the constant heat flux boundary condition. The famous Shah correlation is. The experimental values were reasonably in good agreement with the Shah equation as shown in Figure 8a.
The same was observed for other laminar flow rates also. Reynolds number greater than 10, has been correlated with Dittus-Boelter equation given below:. Validity of the experimental heat transfer setup for a low Shah correlation and b high Dittus-Boelter correlation flow rates using water. As shown in Figure 8b , the good coincidence between the experimental results and the calculated values for water reveals that the precision of the experimental system is considerably good.
Having established confidence in the experimental system, systematic experiments were performed at different flow conditions Reynolds numbers for different f-HEG volume fractions under a constant heat flow. From the experiment heat transfer coefficient was calculated and then converts it into corresponding Nusselts number. The Reynolds number is calculated based on the viscosity of the host liquid. Since the calculated Reynolds numbers were greater than , for DI water based nanofluids, the flow was considered to be turbulent. Figure 9a shows the heat transfer measurement of DI water, 0.
Black dotted lines, blue solid lines, and red dashed lines are for DI water alone, 0. For better understanding the change in Nusselts number for different Reynolds number is shown in Figure 9b. Similar measurements on EG based nanofluid for different volume fractions and varying Reynolds number are shown in Figure Black dotted lines, blue solid lines, and red dashed lines are for EG alone, 0. Since the calculated Reynolds numbers were less than , for EG based nanofluids, the flow rates used were laminar.
Convective heat transfer study. Both the DI water and EG based nanofluids results suggests that the presence of nanomaterials dispersed nanofluids increases the Nusselts number significantly, and the increase is considerably more at high volume fractions and high Reynolds numbers. From Figure 9 it is clear that for a given f-HEG volume fraction, the Nusselts number decreases with axial distance. This is as expected for heat transfer in the entrance region. At the end, the values change to about 92 for 0.
Similar trend is observed in the case of EG based nanofluid also. Figure 10 shows the variation of Nusselts number for 0.
From graph it is clear that heat transfer increases with volume fraction. The enhancement in Nusselts number for EG based nanofluids are higher than that of DI water based nanofluids. Figure 9b shows the effect of the Reynolds number on heat transfer. Figure clearly shows that the Nusselts number increases with increasing Reynolds number.
Similar will be the case for EG based nanofluids also figure not given. This suggests that Reynolds number has a significant effect on the heat transfer mechanism. The enhancement in heat transfer is very drastic compared to the enhancement in thermal conductivity. Another important observation is that even though enhancement in thermal conductivity is very low, enhancement in heat transfer is high for EG based nanofluid.
The reason for decrease in heat transfer from entrance to exit of the tube is due to the variation of thermal boundary layer. The boundary layer increases with axial distance until fully developed after which the boundary layer thickness and hence the convective heat transfer coefficient is constant [ 8 ].
Since there is not much enhancement in thermal conductivity, the effect of thickness of thermal boundary may be the reason for this huge enhancement in heat transfer. Ding et al. Similar observations but with less significant enhancement was observed by Xuan and Li [ 24 ] in the turbulent flow regime.