Effects of Crossflow Air on Conical Water Spray Structure Using a Laser-Based Imaging Method

Abstract

The interaction between crossflows from sprinkler nozzles and airflow is crucial for engineering applications, particularly affecting the efficiency of sprayed areas. This study investigates the deformation of a continuously injected conical water spray subjected to horizontal airflow, using a planar laser imaging method as a visualisation technique. Experiments were conducted in a wind tunnel at a constant water pressure of 0.2 MPa and four airflow rates (0.1, 0.2, 0.4, and 0.6 m³·s⁻¹) to systematically vary the air-to-water momentum ratio. A grayscale-based analysis method was developed using a per-pixel Look-Up Table (LUT), enabling indirect assessment of droplet concentrations and spray structure. This approach allowed for a detailed examination of changes in the spray cone shape under flowing air. By assessing the water spray across three vertical planes intersecting the spray cone, it became possible to calculate lateral area and cone volume at different air-to-water mass flow ratios. The spray formation region exposed to airflow exhibited larger cone volumes than those with minimal airflow. The changes in apparent spray angles for the tested nozzles were determined to characterize the cone shape. The apparent spray angle varies systematically with the air-to-water mass flow ratio, confirming the dominant role of aerodynamic forces. These findings improve the understanding of spray behavior under crossflow and provide a basis for validating numerical models of air–water interactions.

1. Introduction

Liquid atomization is widely used in virtually every industry, including energy, machinery, environmental protection, agriculture and forestry, transportation, and communications [1,2]. There is a growing need for increasingly better and more specialized atomization devices. The specialization of atomization devices stems from the fact that their use must produce a specific effect in a given working environment [3,4,5,6]. Furthermore, the specificity of atomization devices is constantly evolving, as in addition to water and fuels, non-Newtonian liquids and single- and multiphase mixtures are increasingly being atomized. Each nozzle has specific operating characteristics, meaning that the spray structure depends on pressure, mass flow rate, and the physical properties of the delivered fluid [3,7,8].

Spray nozzle characteristics determine their suitability for specific industrial applications. These characteristics are generally determined under conditions with minimal air movement. Although research on nozzle parameters is extensive, studies focusing specifically on spray behavior and control under the influence of airflow remain relatively limited and constitute a more specialized area of research. Many of these studies employ the particle image velocimetry (PIV) technique.

Several studies [9,10,11], have analyzed liquid droplets sprayed by various nozzle designs. They focus on how changes in flow rate or pressure affect the droplets [12,13,14]. Varii et al. [15] used particle image velocimetry (PIV) to measure droplet density. Dancă et al. [16] demonstrated the usefulness of PIV for water-injected crossflow in air, providing quantitative measurements of complex air–water velocity fields. Prior to water injection from a nozzle, it is crucial to ensure the uniformity of the airflow field in the flow conduit or channel. This can be achieved either by using advanced PIV techniques or, in a simplified approach, by employing a self-built low-cost measurement setup, which can be effectively used to analyze low-velocity fluid flows with acceptable accuracy [17].

Reddy et al. [18] highlighted the potential of PIV for studying flow dynamics, including the behavior of settling droplets under the influence of external airflow. These studies discuss various experimental setups in which PIV is used to measure velocity fields and analyze patterns, such as wake formation, which are essential for understanding droplet dispersion in horizontally flowing air [18].

King et al. [19] investigated droplet size and velocity measurements using a Laser Precipitation Meter (LPM) and photographic methods. They highlighted how different environmental conditions affect the kinetic energy of droplets ejected from sprinklers. Their results revealed significant differences in droplet behavior depending on operating pressure and ambient conditions. This work highlights the influence of airflow on droplet dynamics and entrainment properties.

The kinetic energy of sprinkler-ejected droplets was investigated in King and Bjorneberg’s work [20], who quantified how energy is transferred to the environment during droplet descent and their interaction with air streams. Their study focused on the energy flux associated with droplet size and trajectories—principles that can be extrapolated to understand how fire sprinkler droplets are affected by incoming air streams. Ensuring adequate droplet kinetic energy is crucial for maintaining effective spraying under variable airflow conditions [19,20].

One of the most comprehensive studies of this phenomenon was conducted by Bang and Kim [21], who analyzed the spray characteristics of fire sprinklers using advanced image processing techniques. Their study focused specifically on the effects of droplet size, velocity, and density on fire extinguishing effectiveness. They found that larger droplets were more effective at penetrating flames and reaching combustible materials; therefore, their formation and subsequent entrainment in the airflow were key aspects of their study [21].

A significant number of publications also analyze the effect of liquid spray angle on the efficiency of a given technological process [22,23].

Observations of spray shape and spray angle from nozzles were studied not only using PIV but also using other optical imaging methods to visualize the spray structure in a cross-section illuminated by a laser sheet [24].

Kramm et al.’s research [8] significantly contributed to understanding jet angles by laser diffraction. They analyzed the parameters of dual-fluid nozzles by systematically measuring jet cone angles at various fluid flow rates and nozzle geometries. This provided insight into how these variables interact with ambient air and affect overall jet performance [8]. This reference is important for understanding practical implications of nozzle design in the context of jet patterns.

The influence of air on droplet motion was also highlighted by Zhu et al. [25], who investigated the motion and distribution of water droplets in both still and windy conditions using a 2D-Video distrometer technique. They found that incoming air significantly influenced the way droplets moved and settled on target surfaces, supporting the idea that airflow can enhance droplet dispersion and entrainment.

This study demonstrates the use of PIV-based measurement set as a visualization tool (without using correlation algorithms and determining velocity fields or droplet trajectories). A method was developed to visualize instantaneous two-dimensional droplet distributions in a horizontal wind tunnel, allowing for the capture of droplet flow diagrams and the deformation of the spray cone. A per-pixel Look-Up Table (LUT) method was utilized to analyze individual pixels in the acquired images, enabling the creation of detailed droplet flow diagrams.

The primary objective of this research is to determine how airflow rate impacts the spray formation region by estimating the apparent cone angle under controlled conditions. Apparent cone angles can be derived from a composite image created from multiple images, assuming steady-state conditions are maintained during the specified measurement period.

For this purpose, a specialized test stand was developed to capture instantaneous two-dimensional droplet distributions in airflow by means of planar laser-based imaging method (utilizing PIV-based measurement setup). Experiments were performed with two nozzles operating at different airflow characteristics under constant water pressure. The results indicate that the application of the LUT method for analyzing recorded raw 16-bit grey images facilitates the investigation of variations in spray cone geometry under steady-state airflow conditions, offering valuable insights into droplet entrainment and dispersion.

2. Materials and Methods

2.1. Experimental Set-Up

The measurement stand consists of a specially designed and constructed wind tunnel (Figure 1). Before starting the investigation, the turbulence intensity and flow angularity parameters of the tunnel were checked to confirm stable, repeatable airflow over the analyzed flow range. A water spray nozzle was placed above the center of the chamber.

The nozzle outlet was located 75 mm from the top wall of the measurement chamber. The nozzle was supplied with filtered water from a supply system with pressure and temperature measurement.

Spray structure obtained by means of planar laser-based imaging method, utilizing PIV-based measurement setup (except the seeding generator). The system consisted of a high-speed sCMOS digital camera (5.5 Mpix) and a pulsed Nd:YAG laser (15 Hz repetition rate). The laser sheet was oriented vertically downward, while the camera was positioned perpendicular to both the laser sheet and the airflow direction. The short laser pulse duration (~8 ns) effectively minimized motion blur of the rapidly moving droplets, allowing their instantaneous spatial distribution to be captured with sufficient temporal resolution.

2.2. Nozzle Parameters

Tests were conducted for two spray nozzles (I and II) with different shape of spray formation regions and water jets. Two Spraying System Co. nozzles were used, as shown in Figure 2. The first nozzle was a 1/8SF-CE, SM-CE (Nozzle I), designed for mist spraying, with spray angle of up to 110°, a hollow inner cone, and a nominal spray rate of 1.8 dm³/h at 0.15 MPa. The second nozzle was a 1/8-1 HH (Nozzle II) with spray angle of up to 58°, a solid inner cone, and a vane-shaped internal swirler, with nominal flow rate of 32.4 dm³/h at 0.15 MPa. Both nozzles have an effective operating range of 370 mm. Nozzle I (type 1/8 SF-CE, SM-CE) has a droplet distribution range from 100 to 1900 μm. For nozzle II (type 1/8-1 HH), the range is from 500 to 2800 μm. These ranges correspond to different operating pressures and water temperatures. Manufacturer data indicate that droplet size depends strongly on injection pressure and nozzle capacity, resulting in a broad distribution rather than a single representative diameter. For the purposes of the present numerical analysis, characteristic mean droplet diameters were therefore introduced to represent typical operating conditions prior to shock interaction. Based on the expected pressure regimes and nozzle performance, the initial droplet diameters were set to 500 μm for nozzle I and 1000 μm for nozzle II. These values do not represent exact measured diameters but serve as representative parameters for comparative analysis between the two nozzle types. Nozzle diagrams are shown in Figure 2.

2.3. Test Procedure

To investigate the shape disturbances of the water spray formation region under air crossflow conditions, it was decided to focus on the spray angle, which spray nozzle manufacturers usually specify. The spray angle β in the vertical plane, which passes through the apex and the centre of gravity of the rotating cone, is determined by its two generating lines. Using only PIV-based measurement set limited the ability to accurately determine the spray angle along the cone’s axis, because the spray nozzle obscured the apex. Therefore, the decision was made to conduct measurements in three planes that are offset from the cone axis. However, it is important to note that vertical planes intersecting the cone at a distance from its axis no longer create triangular cone sections; instead, they form hyperbolic sections, as illustrated in Figure 3. Despite this, it can be assumed that the analysis of the apparent spray angle β’ could be conducted similarly to that of a plane passing through the centre of the cone.

With this assumption, measurements were taken in three vertical longitudinal planes: Plane A—offset by 24 mm from the nozzle axis towards the tunnel wall, Plane B—offset by 85 mm from the nozzle axis towards the tunnel wall, Plane C—offset by 150 mm from the nozzle axis towards the tunnel wall.

Four series of measurements were conducted for each nozzle, varying the airflow rates across three measurement planes. The range of measurement series for one vertical plane is detailed in

Table 1. Measuring range for crossflow air and water sprays.

Measurement Series	Series 1		Series 2		Series 3		Series 4
$\mathbf{Airflow} \mathbf{Rate}, {\dot{\mathit{V}}}_{\mathit{G}},$ m3/s	0.1		0.2		0.4		0.6
Nozzle	I	II	I	II	I	II	I	II
Max. free passage diameter, mm	0.65	0.59	0.65	0.59	0.65	0.59	0.65	0.59
Water flow rate for p = 0.2 MPa, ${\dot{V}}_L,$ m3/h	0.002	0.0372	0.002	0.0372	0.002	0.0372	0.002	0.0372
Ratio ${\dot{V}}_L/{\dot{V}}_G$	5.56 × 10−6	1.03 × 10−4	2.78 × 10−6	5.17 × 10−5	1.39 × 10−6	2.58 × 10−5	9.26 × 10−7	1.72 × 10−5
Ratio ${\dot{m}}_G/{\dot{m}}_L$	216	11.6	432	23.2	864	46.5	1296	69.7

. All measurements were conducted for both nozzles spraying water at temperature of 9 °C and pressure of 0.2 MPa. The air density was constant at 1.21 kg/m³. The dynamic viscosity coefficient was 17.8 × 10⁻⁶ Ns/m².

2.4. Method for Creating a Spray Formation Region from the Results of Imaging Analysis

Each measurement series comprised 300 image frames collected over 20 s (the acquisition frequency was 15 Hz). Raw images were further processed using ImageJ 1.54k software [26]. This processing enabled the combination of 300 frames to generate a composite image, as illustrated in Figure 4.

By analyzing pixel values in the composite image, an algorithm was developed to determine the spray structure in the observed cross-sectional area of the plane. The algorithm involved the following steps:

• Creating a composite image as a mean pixel value from 300 measured frames;
• Defining ten threshold pixel value levels using a Look-Up Table (LUT) [27] and applying a false color scale;
• Identifying areas in the processed composite image corresponding to the ten intensity classes based on the adopted LUT.

It is posited that a composite image, defined as the mean pixel intensity calculated across a series of individual frames, can be used to characterize the planar droplet distribution within the measurement domain. This approach does not require precise knowledge of droplet sizes, only their frequency of occurrence at a given location. The measurement technique employed allows for accurate localization of droplets on a plane, but the sizes of the droplets have a limited correlation with the sizes of their images due to the properties of Mie scattering [28]. This means that while the boundaries of the droplet occurrence area within the studied domain can be clearly defined, the values of the probability distribution are only approximate.

To improve visualization and facilitate semi-automated image analyses, the composite images were discretized using the data binning method after background removal and normalization. For grayscale images, this involved implementing a Look-Up Table (LUT), a well-known technique in digital image processing [27,29]. A ten-threshold LUT was employed and combined with a false color technique—predefined pixel intensity ranges in the input images were assigned specific colors in the output images. More specifically, the normalized grayscale range of 0.0 to 100.0 was divided into ten segments, each assigned a unique color according to the following classification:

• Class I—black: no occurrence of water droplets (values < 1.0);
• Class II—red (values 1.0–12.0);
• Class III—yellow (values 13.0–23.0);
• Class IV—orange (values 24.0–34.0);
• Class V—pink-magenta (values 35.0–45.0);
• Class VI—purple (values 46.0–56.0);
• Class VII—green (values 57.0–67.0);
• Class VIII—cyan (values 68.0–78.0);
• Class IX—dark green (values 79.0–89.0);
• Class X—dark blue: areas where water droplets most frequently occur (values ≥ 90.0).

Class I was assigned a relatively high threshold value of <1.0 because, due to scattering from droplets, the background subtraction procedure does not always yield perfect results. However, this does not lead to the omission of the smallest droplets, as even droplets measuring approximately 1 μm are visible in the captured images with a significant intensity that is much higher than the background.

The division into ten classes is sufficient to qualitatively characterize the flat probability distribution of droplets within the measurement domain. The ten-level color scale facilitates detailed observation of spray cone deformation and helps identify areas where airflow influences do not disrupt the spray formation region. According to the proposed qualitative analysis approach, changing the number of classes will not affect the conclusions as long as there are at least three classes.

Figure 5 shows an image obtained using the described procedure. This image aids in identifying areas where pixel values exceed 1.0. By defining the boundaries of these areas, the shape of the spray structure can be estimated.

2.5. Determining the Sprayed Region from the Composite Image

Under still air conditions, droplet distribution forms a uniform cone. The nozzles used in this study are specifically designed to produce a water jet with a predetermined spray angle. Within a specified region, the cone maintains stability and consistent droplet density.

Figure 5. Example image of the filtered and normalized composite image with LUT scale applied.

Figure 5. Example image of the filtered and normalized composite image with LUT scale applied.

When the cone is distorted by crossflow, the apparent spray angle is approximated using tangents to a hyperbolic envelope, analogous to a triangular construction intersecting the cone axis (see Figure 3). This geometric approach enables a consistent reconstruction of the spray boundary from planar image data, despite strong flow-induced asymmetry. For qualitative evaluation, the spray region is defined as the area in which at least 90% of the pixels exhibit gray-level values greater than zero, corresponding to the Classes II-X range. This threshold represents a compromise between sensitivity and robustness: increasing the gray-level criterion in optically dense regions amplifies artificial contrast due to multiple light scattering [30], whereas lowering the pixel fraction obscures low-density regions and leads to underestimation of the spray extent.

Within this framework, both the spray envelope and apparent spray angle β′ were determined for each measurement series. Figure 6 presents the resulting regions where at least 90 percent of pixels have gray values above zero.

3. Results and Discussion

3.1. Analysis of Spray Images

The obtained images of spray structure for both tested nozzles are shown in Figure 7, Figure 8, Figure 9, Figure 10, Figure 11 and Figure 12.

Nozzle I generates a smaller water jet and lower outlet velocity (4.5 m/s) compared to nozzle II (34 m/s), as determined from the maximum free passage diameter and drag coefficient. Nozzle I also produces smaller droplets. Analysis of droplet profiles for nozzle I shows that, at higher airflow velocities, droplets do not reach the bottom of the measurement chamber. This behavior is attributed to secondary breakup and entrainment effects arising from differences in air and water mass flow patterns. As a results, droplets are transported to the upper region of the chamber, where they undergo further fragmentation into smaller particles. This shift in droplet size distribution is not only a flow feature but also a measurement-relevant effect, as it alters light scattering conditions and introduces uncertainty into pixel-based droplet concentration estimates in obtained images. Droplet disintegration into smaller particles occurs when the critical Weber number is exceeded, particularly in cases where the effect of liquid viscosity on the breakup regime is negligible [31]. In this context, the Weber number refers to the diameter-based form, defined as the ratio of inertial forces that tend to disrupt the droplet to the surface tension forces that maintain its integrity. It is expressed as We = ρ_gV²D/σ, where ρ_g is the liquid density, V is the characteristic velocity, D is the droplet diameter, σ is the surface tension. Under the investigated conditions, the parameters are: ρ_g = 1000 kg/m³, V_{nozzle_I} = 4.4 m/s, V_{nozzle_II} = 33.4 m/s, σ = 74.2 mN/m. With initial droplet diameters of 500 μm for nozzle I and 1000 μm for nozzle II, the corresponding Weber numbers are 0.2 and 19, respectively. These values suggest that droplets generated by nozzle II are less susceptible to breakup and exhibit a greater tendency to coalesce than those produced by nozzle I.

The grayscale analysis of the recorded images was used as a qualitative visualization tool to identify relative changes in spray appearance under varying airflow conditions. As shown in Figure 9a–d, increasing airflow for nozzle I is associated with a reduction in the recorded light scattering intensity per pixel. This observation is interpreted as a relative change in spray transparency and droplet spatial distribution under otherwise identical optical conditions. At a mass flow ratio (${\dot{m}}_G/{\dot{m}}_L$, see Table 1) of 216 kg/kg, the spray cone remains stable. However, doubling this ratio disrupts the spray formation region. Increased air velocity alters the direction of the falling droplets.

The spray structure of nozzle II, which operates at a higher water discharge velocity and Weber number, differs significantly from nozzle I (Figure 10). At low airflow velocities, the droplet cone remains clear and undistorted (Figure 10a). In Figure 10, Figure 11 and Figure 12, secondary droplet disruption and entrainment by air are not observed, as indicated by a negligible number of areas with the highest brightness. Notably, these high-brightness regions are consistent across all cases (Figure 10a–d). The analysis of the frequency of objects per pixel, except in series 1, indicates a substantial change in the droplet density spectrum. Comparative images obtained under uniform graphical conditions reveal significant deformation of the spray cone, which may influence surface spraying efficiency and droplet-air particle interactions. The air-to-water mass ratio for nozzle II is approximately 18 times greater than for nozzle I. Increasing the airflow rate maintains a constant ratio between the nozzles. The ${\dot{m}}_G/{\dot{m}}_L$ ratio for individual measurement series ranges from 11.6 in series 1 to 69.7 in series 2.

The analysis of images for nozzle II, particularly in plane B (Figure 11), indicates that air inflow does not cause droplet disintegration. Instead, droplets coalesce into larger conglomerates along the nozzle axis, subsequently falling to the bottom of the measurement chamber. This phenomenon is evidenced by the highest brightness observed in this region compared to other combined images (Figure 10, Figure 11 and Figure 12).

An analysis of spray profiles in three vertical planes enabled the assessment of the spatial distribution of droplets and a comparison of the spray cone surface area and volume of the spray cone as a function of airflow rate.

It was assumed, among other things, that the spray envelope encompasses ≥90% of the image pixels in the unit area (excluding the lowest brightness class I), the airflow is symmetrical, and the spray cone is modeled as a system of 5 mm high cylinders. The method for determining these elements based on projection onto plane A is presented in Figure 13, while the lateral apparent surface of the cone is shown in Figure 14 and Figure 15.

The effect of airflow is significantly more pronounced with nozzle I compared to nozzle II. With nozzle I, an elongation of the droplet zone and intense entrainment near the nozzle are observed, limiting coalescence and reducing the spray height from 370 mm to 170 mm. In contrast, for nozzle II, entrainment is localized, occurring primarily at the cone edge at the highest flow rates (as shown in Figure 15), while maintaining overall stability in the spray structure. In both cases, noticeable intensities of entrainment with increasing airflow are present.

Images analyses from three planes allowed us to determine the changes in the apparent volume along its height (Figure 16). For nozzle I, except for the lowest flow rate, a decrease in volume is observed with increasing mass ratio ${\dot{m}}_G/{\dot{m}}_L$ (Figure 16a). The maximum volume occurs at ${\dot{m}}_G/{\dot{m}}_L$ = 216 kg/kg, while at higher values (432, 864, and 1296 kg/kg), the volume decreases by 5.5%, 6.4%, and 31.8%, respectively, indicating a reduction in the effective spray zone.

For nozzle II, the volume changes are more uniform and do not show significant cone deformation (Figure 16b). Only local flow disturbances are visible within the range of 45–115 mm from the nozzle outlet, and the volume increases with increasing airflow, suggesting secondary droplet fragmentation and coalescence. The maximum volume occurs at a height of approximately 280 mm.

The total cone volume for nozzle II is slightly smaller than for nozzle I, but increases with increasing ${\dot{m}}_G/{\dot{m}}_L$ (by 9%, 30%, and 40% compared to the baseline series), which is due to differences in spray angle and droplet size. This can be seen by comparing Figure 10a,d. This cone is less affected by increases in air velocity within the tested range.

3.2. Analysis of Changes in Apparent Spray Angles

Apparent spray angle values were determined based on the results obtained in individual measurement series for three cross-sectional planes along the flow direction, as indicated in Figure 2.

Table 2. Results of spray angles β′ for individual measurement series.

Plane	Apparent Angle	Series 1, 0.1 m3/s		Series 2, 0.2 m3/s		Series 3, 0.4 m3/s		Series 4, 0.6 m3/s
		Nozzle
		I	II	I	II	I	II	I	II
Plane A	β′, deg	109	47	125	51	136	54	140	58
Plane B	β′, deg	105	23	105	27	107	32	77	35
Plane C	β′, deg	70	20	70	23	71	30	71	33

presents the results of the determined spray angles β′ for both nozzles used in the study.

The angle β′ determined in plane A can be compared to the angle specified by the nozzle manufacturer. At volume flow of 0.1 m³/s, the cone shape is regular for nozzle II, while for nozzle I, it can only be observed at a short distance from the nozzle outlet, as the droplets disintegrate and are entrained by the air. However, in all cases, the spray angle β′ could be determined by finding a point on the boundary of the area with 90% of pixels with a gray value above zero. The second point of the line used to determine the angles was taken at the nozzle outlet.

A comparison of the spray angles indicates that compliance with the manufacturer’s declared values can only be assessed approximately for plane A and the lowest flow rate (0.1 m³/s). For nozzle I, 109° was obtained (110° according to the manufacturer), and for nozzle II, 47° (versus the manufacturer’s 58°). These differences may be due to lower water pressure or limitations of the image-based angle determination method. Nevertheless, the experimental values for plane A can be considered close to the catalog data. Although the measurement technique involved using a laser light sheet positioned approximately 24 mm from the center of the cone, which captured light reflected from both the droplets and the chamber walls, the stable geometry of the system allows for reliable comparisons across different series.

An increase in the spray angle along the vertical nozzle axis was observed, confirming the significant effect of air velocity on droplet distribution and the intensification of their breakup and coalescence. At higher flow rates (0.4 and 0.6 m³/s), a greater number of high-brightness areas are visible than at 0.1 m³/s. The dependence of the β’ angle on the air-to-water mass ratio is shown in Figure 17 and Figure 18.

The β′ angle values are strongly related to droplet size. Nozzle I (approx. 500 μm) exhibits greater angle variability and greater susceptibility to droplet breakup than nozzle II (approx. 1000 μm), which is particularly evident in plane A (Figure 17 and Figure 18). Changes in the angle can increase the droplet spread area, which may lead to a local decrease in process. In planes B and C, changes in β′ are less pronounced due to the high mass ratio ${\dot{m}}_G/{\dot{m}}_L$. Nozzle I exhibits a high sensitivity of the spray angle to distance from the outlet, especially on the windward side of the cone.

In contrast, for nozzle II, the changes in angle are clearly correlated with an increase in ratio ${\dot{m}}_G/{\dot{m}}_L$. As the ratio increases, the spray angle also increases (see Figure 18), despite the spray being deflected in the leeward direction (see Figure 10, Figure 11 and Figure 12). Due to the smaller β′ angle of nozzle II, a significant decrease in angle is observed in planes B and C compared to the value in plane A.

3.3. Scope and Limitations of the Study

The results presented in this study focus on a qualitative characterization of the influence of crossflow air streams on liquid sprays generated by vertically oriented water nozzles. The adopted experimental approach was designed to capture the dominant morphological features of the spray under controlled laboratory conditions, providing a clear representation of spray–airflow interactions within the investigated parameter range.

The experimental methodology was based on imaging techniques supported by PIV instrumentation, which enabled a detailed visualization of the spray structure. This approach was particularly well suited for identifying trends in spray deformation, deflection, and spreading under air crossflow conditions. Accordingly, the findings are applicable to the investigated nozzle types, operating at constant supply pressure, within the considered air crossflow regime.

Although advanced diagnostic techniques for fully quantitative spray characterization are available, the present study deliberately focused on an image-based methodology aimed at qualitative assessment of spray morphology. Such an approach is commonly adopted at an exploratory stage, where the primary objective is to isolate and describe the governing physical effects prior to extending the analysis to more complex measurement frameworks.

The optical analysis relies on instantaneous images of the spray, in which the recorded signal originates from light scattering by droplets. While the intensity and apparent size of image features depend on scattering characteristics, the analysis was not intended to provide a direct measurement of droplet size. Instead, the emphasis was placed on the spatial extent and global structure of the spray, which are sufficiently captured using the applied technique. A quasi-steady interpretation of the spray structure was adopted, based on the acquisition of 300 frames over a 20 s period.

The determination of the spray envelope through image processing, using a criterion including 90% of pixels classified into Classes II–X, provides an operational and reproducible definition suitable for comparative analysis. Further refinement of this criterion through sensitivity analyses may enhance the quantitative robustness of future studies.

The apparent spray angle introduced in this work should be understood as an operational parameter derived for image-based analysis. While the actual spray cross-section exhibits a non-linear profile, its representation using tangent lines provides a practical means of comparing spray behavior under varying airflow conditions.

Similarly, the estimation of spray volume was based a geometric approximation intended for comparative analysis rather than to imply physical symmetry of the spray under cross-flow conditions. While asymmetry along the flow direction was explicitly accounted for, symmetry was assumed with respect to the tunnel centreline, which is justified by the nearly symmetric airflow velocity field in the wind-tunnel cross-section.

Within these methodological boundaries, the presented results provide a consistent and informative qualitative description of the spray region. The application of the LUT-based image analysis approach enabled the identification of the influence of cross-flow air velocity on spray morphology and establishes a solid foundation for future extensions toward quantitative measurements of droplet velocity and size distributions.

4. Conclusions

The study investigated the behavior of a vertical spray cone in air crossflow using planar laser-based imaging method as a visualisation technique. To facilitate the qualitative assessment of droplet distribution from raw image data, simple image-processing techniques were combined and applied. Experiments conducted for two types of nozzles yielded the following conclusions:

• The composite image (mean pixel values across multiple image frames) enables the application of the Look-Up Table (LUT) method to identify droplet regions. The implementation of a ten-threshold color scale provides a clear visualization of droplet distribution within a cross-section of the spray cone.
• In composite images, the spray envelope can be determined by identifying regions where at least 90% of the pixels in a unit area exceed a defined grayscale threshold. This approach offers a simple and effective means of assessing the influence of air velocity on the interaction between crossflow air and sprayed droplets.
• Analysis of the spray cone geometry based on composite images allows for the determination of the apparent spray angle β’ in a given plane, as well as the evaluation of the effect of the air-to-water mass ratio on cone stability under crossflow conditions.

It is important to note that the results presented are preliminary and subject to limitations due to the assumptions made during the study. As such, they allow for only a qualitative assessment of the phenomena investigated. Nevertheless, the data obtained regarding the structure of the spray formation region and its deformation under airflow provide valuable input for addressing issues of spray control. They can also provide a basis for validating numerical modeling and serve as a foundation for further, more advanced studies.