# Spray Characteristics and Parameter Optimization of Orifice Arrangement for Micro-Sprinkling Hoses

^{1}

^{2}

^{3}

^{4}

^{*}

## Abstract

**:**

^{2}> 0.90 and the standard root mean square error NRMSE < 30%. It was revealed that the fitting parameters of the two-dimensional Gaussian distribution model had physical meaning and were directly related to the strength and location of the water application intensity distributions. Based on the analysis of these fitting parameters, it was found that the water application intensity distribution of an individual orifice was affected by the pressure, spraying angle and orifice area, among which the spraying angle was the most sensitive factor. By establishing a linear relationship between the fitting parameters and the spraying angles, the water application intensity distribution of an individual orifice for any spraying angle could be predicted by the Gaussian model. Therefore, the water application intensity distribution of multiple groups of orifices could be calculated by overlapping the water application intensity distributions of the individual orifices. The Monte Carlo method was used in this study to determine the maximum spraying width and uniformity coefficient by generating different groups of orifice arrangement for micro-sprinkling hoses. Eventually, the optimized orifice arrangement was recommended for the better design of micro-sprinkling hoses.

## 1. Introduction

^{2}in China by the end of 2020, accounting for approximately 31.3% of the total area of water-saving irrigation [2]. Sprinklers, drip irrigation and micro-sprinkler irrigation are used to improve water-use efficiency and ensure yield output with reduced water consumption [3,4,5,6].

## 2. Materials and Methods

#### 2.1. Micro-Sprinkling Hoses

_{1-1}~a

_{1-12}. The two indexes in subscript denote the group number and the orifice number, respectively. It should be noted that the spraying direction was different for odd number orifices and even number orifices.

_{1,}which was calculated by the distance from the orifice center to edge l

_{d}based on the arc length formula. The arc length formula can be derived as:

_{2}, shown in Figure 2b. These two angles ware slightly different, which will be discussed later in this paper.

#### 2.2. Experimental Design

_{3-1}~a

_{3-12}. The micro-sprinkling hose was laid flat and catch cans were placed on the spraying side. The origin of the coordinate system was set at the center of the measured individual orifice, the direction of flowing water in the micro-sprinkling hose was set as the x-axis and the placement direction of the catch cans was set as the y-axis. As shown in Figure 3b, the catch cans were all evenly spaced, where the vertical spacing (in the y direction) was 0.20 or 0.25 m and the parallel spacing (in the x direction) was 0.20 m. The number of catch cans was guaranteed to be sufficient to cover the spraying region of each orifice. During each measurement, the actual spraying angle was carefully measured by a digital angle rule with an accuracy of 0.3°. The spraying angles varied from 40° to 90°, which were adjusted by artificially rotating the micro-sprinkling hose. In order to measure the flow rate of each orifice, a plastic bottle with a drilled hole near the bottom was used to catch the spraying water for 60 s. The tests of the water application intensity distribution lasted for 15 min. Either the water in the plastic bottles or the catch cans was weighed by an electronic scale with an accuracy of 0.01 g.

#### 2.3. Bimodal Two-Dimensional Gaussian Distribution Model

_{3-5}and a

_{3-1}at 41 kPa, the spraying angles of which were 47.8° and 40.7°, respectively. A three-dimensional contour was generated based on the experimental measurement datum represented with black squares. The experimental results on the water application intensity distribution of individual orifices showed unimodal or bimodal patterns in a two-dimensional distribution. The water application intensity characteristics of the 12 orifices at different pressures were complex, and it was difficult to analyze them together between the unimodal and bimodal distributions.

_{x}and μ

_{y}denote the location coordinates of the peak, respectively; σ

_{x}and σ

_{y}denote the dispersion in the x-direction and y-direction, respectively.

_{u}, which also represents the total discharge of the spraying event.

_{1}and k

_{2}are used to quantify the effects of the two unimodal peaks on the bimodal distribution. It should be noted that the two peak values can be calculated by substituting the coordinates of the peak location into Equation 3, which are h

_{b}(μ

_{x}

_{1}, μ

_{y}

_{1}) and h

_{b}(μ

_{x}

_{2}, μ

_{y2}), respectively. μ

_{x}

_{1}and μ

_{x}

_{2}are the peak location near and far away from an individual orifice in the x direction. μ

_{y}

_{1}and μ

_{y}

_{2}are the peak location near and far away from an individual orifice in the y direction. σ

_{x}

_{1}and σ

_{x}

_{2}are the dispersion degree of water distribution near and far away from an individual orifice in the x direction. σ

_{y}

_{1}and σ

_{y}

_{2}are the dispersion degree of water distribution near and far away from an individual orifice in the y direction.

#### 2.4. Optimization Method

_{i}is the measured water application intensity in a rain gauge, mm/h; $\overline{h}$ is the average measured water application intensity of all catch cans, mm/h; and n is the number of catch cans.

_{d}and the orifice angle α

_{1}, as shown in Figure 2a. The orifice arrangement in a group was simplified as a combination of 6 orifice angles within a certain range, and the Monte Carlo method was used to select an appropriate scenario for optimization. Different scenarios were recorded as S

_{i}, and the uniformity coefficient and spraying width of different scenarios for a micro-sprinkle hose were recorded as CU

_{i}and B

_{i}, respectively. The two indicators of a certain scenario reached the maximum at the same time, which meant that optimized orifice arrangement could improve the spraying performance of the micro-sprinkling hose.

## 3. Results

#### 3.1. Model Validation

_{1}and spraying angles α

_{2}of 12 individual orifices in the third group. It was found that the difference between α

_{1}and α

_{2}was small, and the relative errors were within 15%.

^{2}and the standard root mean square error NRMSE of the bimodal two-dimensional Gaussian distribution model were smaller under lower working pressure. Most R

^{2}values were greater than 0.90 and most NRMSE values were lower than 30%, which indicated a good fitting performance by this bimodal two-dimensional Gaussian distribution model.

#### 3.2. Influencing Factor of Water Application Intensity Distribution of an Individual Orifice

_{3-4}at a spraying angle of 54.1°. When the pressure was 41 kPa, 69 kPa and 103 kPa, the distribution mode was bimodal, unimodal and bimodal, respectively, and the spraying region moved further from the orifice as the pressure increased. There was one peak in the measured water distribution at 69 kPa, and it was difficult to compare it with the fitted bimodal peak. In the cases of 41 kPa and 103 kPa, the peak further away from the orifice was always higher. The results showed that the fitting value of the water application intensity distribution was similar to the measured value. The two measured peak values near and far away from an individual orifice were 6.72 and 6.55 mm/h, and the two fitting peak values were 5.94 and 5.95 mm/h at a pressure of 103 kPa. The relative errors of 11.61% and 9.16% indicated that the fitting correlation was in good agreement with the experimental data.

_{1}and k

_{2}and the peak value near the orifice were almost constant. The peak value far away from the orifice decreased at first and then increased slowly, such as the solid line and black square in Figure 6a. When the pressure was 69 kPa or 103 kPa, two peak values were close with the same variation trend of Figure 5a. The results showed that μ

_{x}and σ

_{x}were almost constant at different pressures, while μ

_{y}increased slightly with the pressure. The variation trend of σ

_{y}was complicated and had a mutation at a pressure of 69 kPa. Compare with the other eleven individual orifices under three pressures, further analysis showed that the influence of the pressure on the peak value and the dispersion of the water application intensity was relatively complicated. The coefficients of k

_{1}and k

_{2}, the peak location μ

_{x}and the dispersion degree σ

_{x}kept relatively little variation with the pressure increasing, but the peak location μ

_{y}moved away from an individual orifice.

_{3-6}at the five different spraying angles of 39.0°, 49.1°, 57.5°, 69.5° and 79.0°, when the pressure was at 103 kPa. The distributions were all unimodal at pressures of 41 kPa and 69 kPa, but there were unimodal and bimodal distributions at a pressure of 103 kPa, which was perfect for the demonstration of the proposed bimodal model in this study. The spraying region gradually moved away from the orifice, and the distance between the two peak locations gradually decreased with the increase in the spraying angle. The minimum and maximum peak values of water application intensity occurred at spraying angles of 69.5° and 79.0°, respectively. The fitting value of the water application intensity distribution was similar to the measured value, but there was little difference in the peak value.

_{1}and k

_{2}were not sensitive to the pressure or spraying angle, except at very large spraying angles, as shown in Figure 8. As the spraying angle increased, the two peak values of the water application intensity fluctuated on a small scale. When the spraying angle exceeded 69.5°, the peak value began to increase, and the gap between the two peak values became larger. The peak value of the water application intensity gradually increased with the increase in pressure. μ

_{x}

_{1}and μ

_{x}

_{2}were almost constant, but μ

_{y}

_{1}and μ

_{y}

_{2}decreased with increasing angles, which meant the peak locations moved towards the spraying orifice. At a pressure of 103 kPa, the locations of the two peaks in the vertical direction gradually moved from separation to coincidence, which was consistent with the transition from a bimodal distribution to a unimodal distribution in Figure 7a. The dispersion σ

_{x}was almost unchanged with the varying pressure and spraying angle, and the dispersion σ

_{y}

_{2}gradually decreased from 69 kPa to 103 kPa with the spraying angle increasing. The spraying angle had a great influence on the peak location and the position of the spraying region. With the increase in the spraying angle, the position of the spraying region moved towards the orifice spray hole, which affected the spraying width of the micro-sprinkling hose.

_{3-5}and a

_{3-8}at three pressures. The areas of the two orifices were 0.080 mm

^{2}and 0.116 mm

^{2}, and the spraying angles were 47.8° and 47.7°, respectively. The peak values of the water application intensity of orifice a

_{3-5}were much higher than that of orifice a

_{3-5}, and the patterns were different. Overall, the water application intensity distribution of small spraying angles might be unimodal or bimodal, and that of larger spraying angles were all unimodal. For the same pressure, two distribution modes, including all unimodal distributions and the transition from bimodal to unimodal, occurred with the spraying angle increasing.

#### 3.3. Superposition of Water Application Intensity Distribution

- Determine the spraying region of single-sided orifice groups;
- Divide the spraying region using evenly distributed grid nodes;
- Use coordinate transformation in the treatment of the measured values;
- Apply linear interpolation to calculate the water application intensity of six individual orifices on the spraying region of single-sided orifice groups;
- A summation of the water application intensity on six individual orifices in the same grid nodes is given to calculate the fitted value of single-sided orifice groups;
- Determine the spraying region of the single-sided micro-sprinkling hose;
- Divide the spraying region using evenly distributed grid nodes;
- Use coordinate transformation in the treatment of the calculated values on single-sided orifice groups;
- Apply linear interpolation to calculate the water application intensity of four single-sided orifice groups on the spraying region of the single-sided micro-sprinkling hose;
- A summation of water application intensity on four single-sided orifice groups in the same grid nodes is given to calculate the value of the single-sided micro-sprinkling hose;
- Determine the spraying region of the single-sided micro-sprinkling hose;
- Based on above-mentioned stages, the calculated value of the water application intensity on the other-sided micro-sprinkling hose is calculated in the same way.
- T3 was processed in the following steps:
- Determine the spraying region of the single-sided micro-sprinkling hose;
- Fit the water application intensity of all individual orifices on the single-sided micro-sprinkling hose with the bimodal two-dimensional Gaussian distribution model;
- Use coordinate transformation in the treatment of the fitting formula on each orifice along x-axis, and move the origin of the coordinate system to the first individual orifice in the third group;
- A summation of the fitting formula on all individual orifices is given to calculate the water application intensity with the coordinates on the spraying region of the single-sided micro-sprinkling hose.
- Based on above-mentioned stages, the fitted value of the water application intensity on the other-sided micro-sprinkling hose is calculated in the same way.

^{3}/h. The total discharge was computed by the water application intensity and control area within the distribution region, and the values were 0.025, 0.023 and 0.022 m

^{3}/h for T1, T2 and T3, respectively. This indicated that the overlap method and the 2D bimodal model proposed in this study could be better used to calculate the discharge. In Figure 10, T1, T2 and T3 seemed to have similar patterns in the distribution of the water application intensity. Compared with T1, T2 and T3 captured more distribution details between 0 and 1.0 m in the vertical direction, and the reason was due to the different placement spacing of the catch cans between the orifice and orifice group experiment.

#### 3.4. Optimization Results

_{3-6}. Based on the measured value of the water application intensity distribution of orifice a

_{3-6}at the five different spraying angles of 39.0°, 49.1°, 57.5°, 69.5° and 79.0° at a pressure of 41 kPa, the reasonable range of orifice angle equal to spring angle varied from 39.0° to 79.0°.

_{1}to S

_{50}were calculated in turn. Due to the different dimensions of CU

_{i}and B

_{i}, a weighting method was used to convert the multi-objective problem into a single-objective problem. The following is the calculation formula for multi-objective problem solving:

_{i}is evaluation index; w is weight factor and its value was 0.5; B

_{tar}is the target value of the spraying width in the sample number and its value was 3.0 m; and CU

_{tar}is the target value of the Christianson uniformity coefficient and its value was 50%.

_{i}under different sample numbers. An appropriate sample number was used to reduce computing costs, and Table 3 shows max{

**w**} under different sample numbers. The results presented that max{

_{i}**w**} increased with the sample number increasing. When the sample number exceeded 10,000, max{

_{i}**w**} changed very little, which indicated that 10,000 might be the recommended sample number. The maximum w

_{i}_{i}corresponding to six individual orifices was the optimal orifice arrangement among the 10,000 scenarios, and the other single-sided group of orifices was arranged in the same way. Table 4 shows the orifice arrangement including the spraying angle α

_{2}and the distance from the orifice center to the edge l

_{d}. An optimized orifice arrangement of the micro-sprinkling hose was obtained with a uniformity coefficient up to 58.5%. Compared with drip, sprinkler and micro-sprinkler irrigation, the uniformity coefficient of micro-sprinkling hoses was low. For the sprinkler irrigation system, the uniformity coefficient was calculated by the water distribution of multiple sprinklers [21]. The uniformity coefficient of the micro-sprinkling hose was not considered with the overlapping of multiple micro-sprinkling hoses, whereas its uniformity coefficient in soil can reach 90%, which is beneficial to crop growth [10].

## 4. Conclusions

- The difference between the orifice angles and spraying angles was small. The bimodal Gaussian distribution model performed well on tracking the two-dimensional features of the water application intensity distribution, where R
^{2}> 0.90 and NRMSE < 30%. - The water application intensity distribution of an individual orifice was affected by the pressure, spraying angle and orifice area, of which the spraying angle was the most sensitive factor. The influence of pressure on the peak value, peak location and the dispersion of the water application intensity distribution was relatively complicated. When the spraying angle exceeded 69.5°, the peak value began to increase, and μ
_{y}_{1}and μ_{y}_{2}decreased with increasing angles. - The water application intensity distribution of multiple groups of orifices could be calculated by overlapping the water application intensity distribution of each orifice. The Monte Carlo method was used for the optimization investigation of the orifice arrangement. An optimized orifice arrangement of the micro-sprinkling hose was obtained with a uniformity coefficient up to 58.5%. When the working pressure is 41 kPa, it is recommended that the spraying angles of the 12 individual orifices are 62.5°, 62.5°, 46.0°, 46.0°, 76.8°, 76.8°, 68.5°, 68.5°, 49.1°, 49.1°, 76.0° and 76.0°. Correspondingly, the distance from the orifice center to the edge of the 12 individual orifices are 21.5, 32.5, 15.9, 38.1, 26.5, 27.5, 23.6, 30.4, 16.9, 37.1, 26.2 and 27.8 mm. This study involved the same orifice diameter with a different orifice arrangement in the optimization method, and further research is therefore required.

## Author Contributions

## Funding

## Data Availability Statement

## Acknowledgments

## Conflicts of Interest

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**Figure 2.**Schematic diagram of (

**a**) orifice angle α

_{1}and (

**b**) spraying angle α

_{2}of an individual orifice.

**Figure 4.**The water application intensity distribution of different individual orifices: (

**a**) the individual orifice a

_{3-5}and (

**b**) the individual orifice a

_{3-1}at 41 kPa, spraying angles of which were 47.8° and 40.7°.

**Figure 5.**The water application intensity distribution of the individual orifice a

_{3-4}under different working pressures: (

**a**) the measured value; and (

**b**) the fitting value.

**Figure 6.**Fitting parameters of water application intensity on the individual orifice a

_{3-4}under different working pressures: (

**a**) k and peak value; (

**b**) μ

_{x}and μ

_{y}and (

**c**) σ

_{x}and σ

_{y}. Notes: k

_{1}and k

_{2}were used to quantify the effect of the two unimodal peaks on the bimodal distribution. h

_{b}(μ

_{x}

_{1}, μ

_{y}

_{1}) and h

_{b}(μ

_{x}

_{2}, μ

_{y}

_{2}) are two peak values. μ

_{x}

_{1}and μ

_{x}

_{2}are the peak locations near and far away from an individual orifice in x direction. μ

_{y}

_{1}and μ

_{y}

_{2}are the peak locations near and far away from an individual orifice in y direction. σ

_{x}

_{1}and σ

_{x}

_{2}are the dispersion degrees of water distribution near and far away from an individual orifice in x direction; σ

_{y}

_{1}and σ

_{y}

_{2}are the dispersion degrees of water distribution near and far away from an individual orifice in y direction.

**Figure 7.**The water application intensity distribution of an individual orifice a

_{3-6}under different spraying angles at 103 kPa: (

**a**) the measured value; and (

**b**) the fitting value.

**Figure 8.**Fitting parameters of water application intensity on the individual orifice a

_{3-6}under different spraying angles: (

**a**) k and peak value at 41 kPa; (

**b**) μ

_{x}and μ

_{y}at 41 kPa, (

**c**) σ

_{x}and σ

_{y}at 41 kPa, (

**d**) k and peak value at 69 kPa; (

**e**) μ

_{x}and μ

_{y}at 69 kPa, (

**f**) σ

_{x}and σ

_{y}at 69 kPa, (

**g**) k and peak value at 103 kPa; (

**h**) μ

_{x}and μ

_{y}at 103 kPa and (

**i**) σ

_{x}and σ

_{y}at 103 kPa. Notes: k

_{1}and k

_{2}were used to quantify the effects of the two unimodal peaks on the bimodal distribution. h

_{b}(μ

_{x}

_{1}, μ

_{y}

_{1}) and h

_{b}(μ

_{x}

_{2}, μ

_{y}

_{2}) are two peak values. μ

_{x}

_{1}and μ

_{x}

_{2}are the peak locations near and far away from an individual orifice in x direction. μ

_{y}

_{1}and μ

_{y}

_{2}are the peak locations near and far away from an individual orifice in y direction. σ

_{x}

_{1}and σ

_{x}

_{2}are the dispersion degrees of water distribution near and far away from an individual orifice in x direction; σ

_{y}

_{1}and σ

_{y}

_{2}are the dispersion degrees of water distribution near and far away from an individual orifice in y direction.

**Figure 9.**The measured value of water application intensity distribution under different orifice areas: (

**a**) the individual orifice a

_{3-5}; and (

**b**) the individual orifice a

_{3-8}.

**Figure 10.**Water application intensity of single-sided micro-sprinkling hose composed of odd-numbered individual orifices in different test modes: T1 was the measured value, T2 was the fitting value by overlapping the measured water application intensity of multiple individual orifices and T3 was fitting value with the overlapping and bimodal two-dimensional Gaussian distribution model of multiple individual orifices.

**Figure 11.**Average water application intensity of single-sided micro-sprinkling hose composed of odd-numbered individual orifices in different test modes: (

**a**) y = 0~1 m; (

**b**) y = 1~2 m; (

**c**) y = 2~3 m; (

**d**) y = 3~4 m and (

**e**) y = 4~5 m.

**Figure 12.**Effect for different spraying angles on fitting parameters of water application intensity at 41 kPa: (

**a**) k and peak value; (

**b**) μ

_{x}and μ

_{y}and (

**c**) σ

_{x}and σ

_{y}. Notes: k

_{1}and k

_{2}were used to quantify the effect of the two unimodal peaks on the bimodal distribution. μ

_{x}

_{1}and μ

_{x}

_{2}are the peak locations near and far away from an individual orifice in x direction. μ

_{y}

_{1}and μ

_{y}

_{2}are the peak locations near and far away from an individual orifice in y direction. σ

_{x}

_{1}and σ

_{x}

_{2}are the dispersion degrees of water distribution near and far away from an individual orifice in x direction; σ

_{y}

_{1}and σ

_{y}

_{2}are the dispersion degrees of water distribution near and far away from an individual orifice in y direction.

Parameters | Number of the Individual Orifice | |||||||||||
---|---|---|---|---|---|---|---|---|---|---|---|---|

a_{3-1} | a_{3-2} | a_{3-3} | a_{3-4} | a_{3-5} | a_{3-6} | a_{3-7} | a_{3-8} | a_{3-9} | a_{3-10} | a_{3-11} | a_{3-12} | |

α_{1} (°) | 40.0 | 38.3 | 76.7 | 50.0 | 48.3 | 80.0 | 36.7 | 45.0 | 68.3 | 68.3 | 66.7 | 66.7 |

α_{2} (°) | 40.7 | 41.2 | 74.8 | 54.1 | 47.8 | 82.0 | 34.3 | 47.7 | 73.8 | 70.5 | 63.7 | 74.6 |

Relative error (%) | 1.8 | 7.6 | −2.5 | 8.2 | 1.0 | 2.5 | −7.0 | 5.7 | 8.1 | 3.2 | −4.5 | 11.8 |

**Table 2.**The fitting evaluation parameters of bimodal two-dimensional Gaussian distribution model under three different working pressures for twelve individual orifices.

Working Pressure (kPa) | Parameters | Number of the Individual Orifice | |||||||||||
---|---|---|---|---|---|---|---|---|---|---|---|---|---|

a_{3-1} | a_{3-2} | a_{3-3} | a_{3-4} | a_{3-5} | a_{3-6} | a_{3-7} | a_{3-8} | a_{3-9} | a_{3-10} | a_{3-11} | a_{3-12} | ||

41 | R^{2} | 0.96 | 0.87 | 0.97 | 0.96 | 0.97 | 0.98 | 0.95 | 0.94 | 0.94 | 0.96 | 0.96 | 0.97 |

NRMSE(%) | 26.1 | 20.2 | 20.8 | 23.6 | 28.0 | 12.3 | 20.9 | 25.3 | 18.7 | 24.8 | 28.9 | 17.8 | |

69 | R^{2} | 0.94 | 0.95 | 0.98 | 0.92 | 0.91 | 0.96 | 0.96 | 0.94 | 0.97 | 0.94 | 0.92 | 0.97 |

NRMSE(%) | 30.4 | 23.1 | 20.9 | 32.6 | 44.4 | 26.8 | 21.1 | 32.0 | 10.8 | 31.4 | 33.8 | 18.7 | |

103 | R^{2} | 0.94 | 0.94 | 0.95 | 0.90 | 0.95 | 0.97 | 0.72 | 0.96 | 0.95 | 0.96 | 0.96 | 0.96 |

NRMSE(%) | 35.9 | 28.3 | 29.1 | 38.2 | 34.3 | 26.4 | 39.1 | 29.5 | 13.3 | 28.7 | 32.5 | 18.5 |

**Table 3.**The optimal evaluation index w

_{i}(j) with uniformity coefficient CU

_{i}and spraying width B

_{i}under different sample numbers.

Sample Number | max{w_{i}} | CU_{i}/% | B_{i}/m |
---|---|---|---|

50 | 2.01 | 49.9 | 3.04 |

100 | 2.04 | 52.1 | 2.99 |

500 | 2.04 | 52.1 | 2.99 |

1000 | 2.06 | 54.2 | 2.94 |

5000 | 2.12 | 55.4 | 3.04 |

10,000 | 2.15 | 58.3 | 2.94 |

50,000 | 2.16 | 58.5 | 2.99 |

100,000 | 2.16 | 58.5 | 2.99 |

**Table 4.**The position of 12 individual orifices after orifice arrangement for micro-sprinkling hoses.

Parameters | Number of the Individual Orifice | |||||||||||
---|---|---|---|---|---|---|---|---|---|---|---|---|

1 | 2 | 3 | 4 | 5 | 6 | 7 | 8 | 9 | 10 | 11 | 12 | |

α_{2}/° | 62.5 | 62.5 | 46.0 | 46.0 | 76.8 | 76.8 | 68.5 | 68.5 | 49.1 | 49.1 | 76.0 | 76.0 |

l_{d}/mm | 21.5 | 32.5 | 15.9 | 38.1 | 26.5 | 27.5 | 23.6 | 30.4 | 16.9 | 37.1 | 26.2 | 27.8 |

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## Share and Cite

**MDPI and ACS Style**

Wang, X.; Xu, Y.; Yan, H.; Tan, H.; Zhou, L.
Spray Characteristics and Parameter Optimization of Orifice Arrangement for Micro-Sprinkling Hoses. *Water* **2022**, *14*, 3260.
https://doi.org/10.3390/w14203260

**AMA Style**

Wang X, Xu Y, Yan H, Tan H, Zhou L.
Spray Characteristics and Parameter Optimization of Orifice Arrangement for Micro-Sprinkling Hoses. *Water*. 2022; 14(20):3260.
https://doi.org/10.3390/w14203260

**Chicago/Turabian Style**

Wang, Xiaoshan, Yuncheng Xu, Haijun Yan, Haibin Tan, and Lingjiu Zhou.
2022. "Spray Characteristics and Parameter Optimization of Orifice Arrangement for Micro-Sprinkling Hoses" *Water* 14, no. 20: 3260.
https://doi.org/10.3390/w14203260