# Numerical and Experimental Investigation on the Spray Coating Process Using a Pneumatic Atomizer: Influences of Operating Conditions and Target Geometries

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## Abstract

**:**

## 1. Introduction

## 2. Experimental Investigation

#### 2.1. Geometry of the Pneumatic Atomizer

#### 2.2. Droplet Size Measurements

#### 2.3. Measurement of Paint Film Thickness on the Target Plate

^{2}—was positioned horizontally. The gun axis was perpendicular to the target surface so that the major axis of the spray pattern was formed along the 800 mm direction. After painting, the panel was put horizontally into an oven for baking. The dry film thickness on the panel was then measured by means of magneto-inductive method. Figure 5 shows the mean values of the measured film thickness distribution with uncertainty bars (standard deviation) for a typical shaping air flow rate of 360 L/min. Spray painting was later also carried out on a more complicated substrate, a 3D-target that consists of four panels. The atomizer was located at the center directly above panel C, moving along the channel. The corresponding film thickness distributions on different panels are shown in Figure 6. The measured film thickness distributions were applied to compare with the simulation results that will be shown in the next section.

## 3. Computational Method

_{D}(

**u**−

**u**

_{p}) and the gravity force

**F**

_{G}(force/unit particle mass) were taken into account. Other forces, such as “virtual mass” and Saffman’s lift force may be neglected, since the density ratio between air and liquid is 1 to 1000, and the mean droplet diameter is about 40 μm in current painting processes. In the above equation,

**u**

_{p}is the particle velocity and

**u**the instantaneous air velocity that was calculated by superimposing the local mean velocity and a fluctuating velocity component corresponding to the local turbulence level, using a stochastic tracking model. The effect of the turbulence dispersion on the droplet motion was thereby taken into account with an integral time scale constant of 0.3. In the current study, the interaction between droplets was neglected due to the low mass flow rate of the liquid. Computational particles—namely droplet parcels, representing a number of real droplets with the same properties—were used. The number of computational particles plays an important role in the Lagrangian tracking method. However, in order to save computation resources, 50,000 particles were used per trajectory calculation, which proved to be sufficiently accurate for current industry applications.

## 4. Simulation Results

#### 4.1. Spray Painting Calculation by Using a Flat Plate

#### 4.2. Spray Painting Calculation for a Complicated Geometry of the Work Piece and an Inclined Atomizer

## 5. Conclusions

## Acknowledgments

## Author Contributions

## Conflicts of Interest

## References

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**Figure 1.**Inlet airflow in the nozzles of the pneumatic atomizer (Computational Fluid Dynamics (CFD) simulation of the atomizer).

**Figure 3.**Individual droplet size distributions in the whole elliptical spray region for the shaping air flow rate of 220 L/min. 0 mm is the measuring position that is located at x = 0 in Figure 2, the spray cone center. ±50 mm are located at the edges of the elliptical spray region (x = ± 50 mm).

**Figure 4.**Measured integral droplet size distributions for three shaping air flow rates: 150, 220, 360 L/min.

**Figure 5.**Measured dynamic film thickness distribution on a flat steel plate with the shaping air flow rate of 360 L/min.

**Figure 6.**Measured dynamic film thickness (µm) on a 3D-target for the shaping air flow rate 360 L/min.

**Figure 7.**Calculated velocity contours colored by velocity magnitude (m/s) in the plane z = 0 (shaping air flow rate: 360 L/min). The static film thickness distribution on the plate is also overlaid.

**Figure 8.**Comparison of measured and calculated dynamic film thickness distributions for three shaping air flow rates: 150, 220, 360 L/min.

**Figure 9.**Calculated velocity contours colored by velocity magnitude (m/s) in the plane z = 0 (shaping air flow rate: 150 L/min). The static film thickness distribution on the plates is also overlaid.

**Figure 10.**Calculated velocity contours colored by velocity magnitude (m/s) in the plane z = 0 (shaping air flow rate: 360 L/min). The static film thickness distribution on the plates is also overlaid.

**Figure 11.**Comparison of the measured and calculated dynamic film thickness distributions: (

**a**) shaping air flow rate 360 L/min; (

**b**) 220 L/min; (

**c**) 150 L/min.

**Figure 12.**Velocity contours (m/s) at a cross section z = 0 overlaid with static film thickness on the target.

**Figure 13.**Comparison of the measured and simulated dynamic film thickness distributions (shaping air flow rate: 360 L/min).

Atomizing Air Flow Rate | Shaping Air Flow Rate | Liquid Flow Rate | Liquid Phase |
---|---|---|---|

260 L/min | 150, 220, 360 L/min | 300 mL/min | Alpine white paint |

© 2017 by the authors; licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC-BY) license (http://creativecommons.org/licenses/by/4.0/).

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**MDPI and ACS Style**

Ye, Q.; Pulli, K.
Numerical and Experimental Investigation on the Spray Coating Process Using a Pneumatic Atomizer: Influences of Operating Conditions and Target Geometries. *Coatings* **2017**, *7*, 13.
https://doi.org/10.3390/coatings7010013

**AMA Style**

Ye Q, Pulli K.
Numerical and Experimental Investigation on the Spray Coating Process Using a Pneumatic Atomizer: Influences of Operating Conditions and Target Geometries. *Coatings*. 2017; 7(1):13.
https://doi.org/10.3390/coatings7010013

**Chicago/Turabian Style**

Ye, Qiaoyan, and Karlheinz Pulli.
2017. "Numerical and Experimental Investigation on the Spray Coating Process Using a Pneumatic Atomizer: Influences of Operating Conditions and Target Geometries" *Coatings* 7, no. 1: 13.
https://doi.org/10.3390/coatings7010013