CHAPTER 5
CFD ANALYSIS OF DOUBLE PIPE HEAT EXCHANGER AND SIMULATION
This chapter deals with the computational fluid dynamics (CFD) analysis of the hydrodynamics and thermal behavior of the turbulent flow through a 2 pass Double pipe heat exchanger using ANSYS FLUENT 14.0 software.
5.1 Geometry and Modeling
5.1.1 Specifications of Geometry and Boundary conditions
The analysis is performed on a double pipe heat exchanger with the inner diameter of inner pipe is 0.019 m & outer diameter of inner pipe is 0.025 m, similarly for annulus pipe, the inner diameter of outer pipe is 0.05 m & outer diameter of outer pipe is 0.056 m and the total length of heat exchanger is 2.36 m (2-pass). The mass flow rate of hot water, mh (kg/s), is constant over annulus …show more content…
The element considered is hexahedral shape with number of elements of 876874 to 1240000 as shown in Fig.5.2. Naming selections were also done at required measuring values. Fig. 5.2 Meshing of 2 pass double pipe heat exchanger in ANSYS Workbench

5.3 Scaling (Grid Independence) Test
Grid convergence is the term used to describe the improvement of results by using successively smaller cell sizes for the calculations. A calculation should approach the correct answer as the mesh becomes finer, hence the term grid convergence. The normal CFD technique is to start with a coarse mesh and gradually refine it until the changes observed in the results are smaller than a pre-defined acceptable error. There are two problems with this approach. Firstly, it can be quite difficult with other CFD software to obtain even a single coarse mesh result for some problems. Secondarily refining a mesh by a factor 2 can lead to an 8 fold increase in problem size so even more time is needed. This is clearly unacceptable for a piece of software intended to be used as an engineering design tool operating to tight production deadlines. These and other issues have added greatly to the perception of CFD as an extremely difficult, time consuming and hence costly …show more content…
TABLE 5.3 Properties of Water and Fe3O4 Nanoparticles
S.no Substance Mean Diameter Density (kg/m3) Thermal conductivity (W/m-K) Specific heat(J/kg-k) Kinematic Viscosity (m2/s)
1 Fe3O4 nanoparticle 50 nm 5180 80.4 670 --
2 Water -- 997.5 0.6129 4178 0.000829

The thermo physical properties of Fe3O4 nanofluids such as density (ρ), specific heat (Cp), thermal conductivity (k) and viscosity (μ) are estimated using following empirical correlations developed to determine for density Pak and Cho [], for effective thermal conductivity Hamilton-Crosser relation, for viscosity Brinkman model [] and for Specific heat Xuan and Roetzel equations were used. The particle size of the Fe3O4 nanoparticles is considered as 50 nm. The properties of nanofluid are given in Table 5.3 at 27 °C temperature and 100 kPa pressure. ρ_nf=(1-ϕ) ρ_bf+ϕρ_p (5.1)
C_(p,nf)=((1-ϕ) ρ_bf C_(p,bf)+ϕ ρ_p C_(p,p) )/ρ_nf (5.2) k_nf/k_bf =(k_p/k_bf +(n-1)-(n-1)(1-k_p/k_bf )ϕ)/(k_p/k_bf +(n-1)+(1-k_p/k_bf )ϕ) (5.3) μ_nf=μ_bf/(1-ϕ)^2.5 (5.4)

TABLE 5.4 Steel, Water and Nano fluid properties at 27