**4.3 Grid generation**

To avoid blurred curved areas, tetrahedral cells are used for meshing the computational domains, as shown in **Figure 4**. Mesh, with around 3,000,000 elements, was decided to represent the domains for the current simulation.

The same way that element numbers in the mesh are important, mesh quality has

The presentation and discussion of results are not based on sub-sectioning the numerical and experimental results. Instead, the results are sub-sectioned based on the hydrothermal parameters, like the velocity, pressure, and thermal performance.

The hydrodynamics analysis of the flow within internal conduits includes the

The flow structure in the pipe is characterized by analyzing the velocity field and the pressure distribution in the flow domain. In the current work, there are four different geometrical configurations including plane pipe flow and another three cases with single, triple, and quintuple twisted tape inserts inside the pipe. CFD is a powerful tool to provide flow visualization and assist in the analysis of the flow field structure. Fields of velocity, predicted by computational simulation, in case of water flowing are depicted in **Figure 7**. The velocity contours shown are taken for

*Velocity contours and streamlines of water flow for; (i) PT, (ii) STT, (iii) TTT, and (iv) QTT.*

a remarkable role in the numerical solution accuracy. Grid quality is commonly identified through orthogonal quality and skewness. Orthogonal quality describes how much the mesh criteria are within the correct range that is valid for physical value prediction. Orthogonal quality is presented in **Figure 5** for the grids performed to represent computational domains. The average orthogonal quality value gained in the present numerical procedure, of 0.8563, is within a very good quality range. Skewness determines how the generated cells are close to the ideal configuration and it governs solution ability to converge, as illustrated in **Figure 6**. The average skewness value of depended grids of 0.22288 is within excellent simulation range.

*Applications of Compound Nanotechnology and Twisted Inserts for Enhanced Heat Transfer*

**5. Results and discussion**

*DOI: http://dx.doi.org/10.5772/intechopen.93359*

**5.1 Hydrodynamics analysis**

velocity and pressure structures.

*5.1.1 Velocity field analysis*

**Figure 7.**

**35**

#### **Figure 4.**

**Figure 5.** *Mesh cell orthogonal quality metrics.*

**Figure 6.** *Mesh cell skewness quality metrics.*

*Applications of Compound Nanotechnology and Twisted Inserts for Enhanced Heat Transfer DOI: http://dx.doi.org/10.5772/intechopen.93359*

The same way that element numbers in the mesh are important, mesh quality has a remarkable role in the numerical solution accuracy. Grid quality is commonly identified through orthogonal quality and skewness. Orthogonal quality describes how much the mesh criteria are within the correct range that is valid for physical value prediction. Orthogonal quality is presented in **Figure 5** for the grids performed to represent computational domains. The average orthogonal quality value gained in the present numerical procedure, of 0.8563, is within a very good quality range. Skewness determines how the generated cells are close to the ideal configuration and it governs solution ability to converge, as illustrated in **Figure 6**. The average skewness value of depended grids of 0.22288 is within excellent simulation range.
