Experimental and Numerical Investigation of Swirling Flow on Triple Elbow Pipe Layout

The secondary flow downstream of a triple elbow layout was studied experimentally and numerically to visualize the flow behavior under swirling inlet flow conditions. The inlet swirling condition was generated by a swirl generator, consisting of a rotary pipe and honeycomb assembly. The experiments were carried out in turbulent water flow condition at Reynolds number Re = 1 × 10 4 and inlet swirl intensity S = 1. Ultrasonic measurements were taken at four locations downstream of the third elbow. The two-dimensional velocity field of the flow field was measured using the phased array ultrasonic velocity profiler technique to evaluate the flow field with separation. Furthermore, a numerical simulation was performed and its results were compared with the experimental data. The numerical result was obtained by solving three-dimensional, Reynolds-averaged Navier-Stokes equations with the renormalization group k-ε turbulence model. The experimental results confirmed that the swirling flow condition modified the size of the separation region downstream of the third elbow. A qualitative comparison between the experimental and CFD simulation results of the averaged velocity field downstream of the third elbow showed similar tendency on reverse flow.


Introduction
Turbulent flow through a compact piping system is encountered in a variety of industrial applications and is used in power plants. Complicated [4]. Furthermore, swirling flow enhances flow accelerated corrosion of the pipe wall, thereby causing pipe break accidents in the piping systems of power plants [5] [6] [7]. Hence, investigations into flow structure and velocity fluctuation are essential for pipeline safety management.
A multiple elbow pipe layout can be found in the loop system, i.e., cold-leg piping, of the Japan Sodium-cooled Fast Reactor (JSFR). The cold-leg piping in the JSFR has three successive short elbows. Owing to its complexity, Ebara et al. [8] [9] studied the flow field and pressure fluctuation in the third elbow of a triple elbow piping with small curvature radius using 1/7-scale models of the cold-leg piping of the JSFR.
In previous studies, computational fluid dynamics (CFD) simulation using OpenFOAM® on a 90˚ elbow was performed to characterize the swirling secondary flow downstream of an elbow in a pipe [10]. A comparative study was performed on the selection of turbulence models for analysis. One of the first studies was carried out by Al-Rafai et al. [11], who provided the flow structure through an elbow. They performed experiments on a turbulent flow at Reynolds number Re = 3.4 × 10 4 in two types of elbows (pipe diameter to elbow radius ratio γ = 0.07 and 0.14) using Laser Doppler Velocimetry (LDV) and compared the results with those obtained from the numerical simulations using the k-ε model. They showed the distributions of mean and root mean square velocities in the elbows. The results indicated that secondary flow is magnified in the elbow with increasing pipe diameter to elbow radius ratio γ. Hilgenstock and Ernst [12] tested two well-known turbulence models (k-ε model and renormalization group model known as RNG) and provided acceptable results. An experimental study of turbulent flow in an elbow with imposed swirl was carried out by Kalpakli and Örlü [13]. They used particle image velocimetry (PIV) to study the formation of Dean vortices and swirl motion at values of swirl intensity S in the range 0 -1.2, S being defined as the ratio of circumferential momentum to axial momentum, in the downstream region of an elbow. Chang and Lee [14] also investigated the effects of swirl on the secondary flow field along an elbow at Re values in the range (1.0 -2.5) × 10 4 . In these studies, LDV and PIV were applied to investigate the mean swirling velocity fields and flow structures. However, these systems are limited to flow through transparent pipes owing to optical access, and hence, it is difficult to apply these techniques in the case of actual plant pipes. Therefore, a non-invasive measurement technique should be applied to evaluate the velocity field and velocity fluctuation in an elbow pipe. In this study, an ultrasonic technique is applied to measure the two-dimensional veloc- Takeda [15] developed an Ultrasonic Velocity Profiler (UVP) to measure instantaneous velocity profiles of non-transparent media and opaque liquid flows.
Initially, the conventional UVP method is employed to measure the one-dimensional velocity profile in the measurement line. Two-dimensional velocity vector measurements, Takeda and Kikura [16] investigated the velocity field of mercury flow using the UVP system with multiple transducers. Nevertheless, the measurement system using multiple transducers becomes quite complicated as the number of transducers increases. A phased array UVP system was developed to minimize the effects of this problem [17]. A phased array sensor has multiple ultrasonic piezoelectric elements; an ultrasound beam can be steered to a specific angle by controlling the time delay of ultrasound transmission from each piezoelectric element. Therefore, multiple lines can be measured, and the two-dimensional velocity field can be evaluated by using a single phased array sensor. The performance of phased array UVP in mapping velocity flow was confirmed by Fukumoto et al. [17] for the detection of water leakage from a tank.
In this study, the flow fields downstream of a triple elbow layout were studied experimentally using phased array UVP and numerically using ANSYS® Fluent

Measurement Principle and Hardware System
The working principle of the phased array UVP system is based on Doppler shift frequency detection along ultrasound beam lines. The phased array sensor emits an ultrasonic pulse, and each element of the sensor receives the echo reflected from the surface of a particle. The exciting element emits a spherical ultrasonic wave. When adjacent elements emit waves within a second of each other, interference of wave fronts occurs, as shown in Figure 1(a). A schematic of a phased array sensor is shown in Figure 1 where the Doppler shift frequency is observed at the i th -channel element, e e is the unit vector in the direction of the measurement line, i e is the unit vector in the direction from the particle to the i th -channel element, c is the speed of sound in water, 0 f is a basic frequency of the phased array sensor, and V is the particle velocity. Equation (3) shows that the Doppler shift frequency received at each element depends on the positions of the elements. The first and eighth elements, which are shown in Figure 2, are considered to receive an echo signal each from the particle, and the velocity vector can be reconstructed from the first and eighth elements using Equation (4).
The phased array UVP hardware system used for the two-dimensional velocity field measurement is shown in Figure 3. The National Instrument LabVIEW program was used to control the phased array UVP system and reconstructed the measured velocity into a two-dimensional velocity vector field. The measurement system consists of a 2 MHz phased array sensor with eight piezoelectric elements, an eight-channel pulse receiver, an analog to digital converter and personal computer. The computer was also used to control the pulse receiver and analyzed the echo signal from the digital converter.

Experimental Set-up
The experiment was conducted in a water circulation system, which consists of a cooling system and electromagnetic flow meter as shown in Figure 4    such as rotary pipe, tangential flow injection, and vanes. They have different effects on the velocity distribution of swirling flow [18]. In this study, a rotary pipe was used as the swirl generator [7]. The swirl generator was installed at a dis- where r is the radial distance from the pipe axis, z U is the mean axial velocity, and U θ is the mean circumferential velocity. Equation (5) shows that the swirl intensity can be evaluated directly from the angular velocity ω of the swirl generator when the radius R of the pipe and bulk velocity U of the flow through the pipe is given.
A phased array sensor, with a basic frequency of 2 MHz, was installed on the pipe wall. Thus, there was direct contact between the sensor and water to overcome refraction in the pipe wall and water. The axial, radial and circumferential velocity profiles of the inlet swirling flow were measured at a distance of 7D downstream of the swirl generator. The inlet velocity profile measured was used for the inlet boundary conditions of the CFD simulation. Table 1 shows a summary of the experimental conditions.    Figure 6. The CFD code ANSYS® Fluent (version 16.2) was used to simulate pipe flow through a triple elbow pipe layout as shown in Figure 6(a). The inlet length upstream of the triple elbow was 3D, which was shorter than the experimental inlet length, because the swirl generator was not modeled in the numerical simulation.

Numerical Simulation
Therefore, the experimental data on swirling velocities were directly used as the inlet boundary conditions of the numerical simulation. The pipe length from downstream of the second elbow to the third elbow was set to 6Dwhich was similar to the experimental condition. The mesh type was a polyhedral cell, and the total number of meshes was approximately 1.4 million. A polyhedral cell was used to obtain the proper orthogonal and skewness values. The mesh near the pipe wall had an inflection layer of thickness 0.02 mm which corresponds to the non-dimensional wall distance y+ < 1 and the total number of layer was seven.
The mesh quality of the outlet cross-sectional plane is shown in Figure 6(b).
The RNG k-ε model was used to obtain a converged solution considering calculation time and cost. The RNG k-ε model is preferable for the secondary flow and swirling flow conditions [19]. It is noted that the RNG model has an additional term in its ε equation that significantly improves its accuracy for rapidly  flows (i.e., elbow pipe). A previous study by Kim et al. [3] showed that the RNG k-ε model was in good agreement with experimental results for swirling flow in a 90˚ elbow. The non-equilibrium wall function was applied near the wall. The SIMPLE scheme was used as a coupling scheme between velocity and pressure. The PRESTO! scheme was used for spatial discretization of pressure, and the Quick scheme was applied for other spatial discretization. Table 2 shows the numerical conditions for the calculation of turbulent flow.
The initial condition of turbulent kinetic energy (k) and turbulent dissipation rate (ε) in the CFD simulation were evaluated from the following equations [19]: where 0.0845 C µ = and l is turbulent length scale, 0.07 h l d = (8) I is turbulent intensity which is defined as follows; 1 8 0.16 Re I − = (9) where d h is hydraulic diameter (pipe diameter). The boundary conditions for velocity and pressure were prescribed by the inlet and outlet, respectively. The inlet swirling velocity profiles were imported from the experiment. It is noted that a thermal analysis was not included in the calculation, because the working water temperature was the same as room temperature. The outlet boundary condition was outflow with a static pressure equal to 0 Pa, and the turbulence kinetic energy (k) and dissipation rate (ε) were set to 1 m 2 /s 2 and 1 m 2 /s 3 respectively. Inlet velocity Axial, radial and tangential velocity profiles from the experiment

Axisymmetric Swirling Flow
The axial, radial and tangential velocities of the swirling flow were measured by using a phased array sensor at a distance of 7D downstream of the swirl generator. The sensor position was converted into the axial and cross-sectional planes to measure all the axial, radial and circumferential velocities. Subsequently, these data were used for the inlet boundary conditions of the CFD simulation.

Comparison between Experimental Results and CFD Simulation
Two-dimensional velocity fields are measured to visualize the secondary flow downstream of the third elbow. A time average velocity profile was obtained by averaging 10,000 velocity profiles.    Figure 11(a) and Figure 11

Conclusion
Experimental and numerical investigations were carried out to understand the flow structure and velocity field in a triple elbow pipe layout under an inlet swirling flow condition. The two-dimensional velocity field was measured using the phased array UVP system, which allowed the confirmation of flow separa-