## 3 Characterization of Nanofluid Sprays: An Example  
The droplets in the nanofluid spray have multiple sizes and velocities. The measurement technique used is a 1D Phase-Doppler Interferometer (PDI), which is a single point laser diagnostic technique. Thus, the information provided has a mesh grid defined for the type of spray being characterized. In this case-study, the PDI measurement system retrieves information of radial profiles since the spray issued from a pressure-swirl atomizer is axisymmetric, considering two different measurement planes perpendicular to the spray penetration direction (\(Z\)) below the injector nozzle at \(Z=\)10 mm and \(Z=\) 20 mm. More details on the diagnostic technique can be found in [PERSON] et al. [21]. The first step of every standard spray characterization is to report the mean quantities of size and velocity. Despite the loss of information relative to the size distributions, the quantitative data are useful for validation of numerical simulations in sprays. In addition, it is a picture of the global characteristics of the spray. Figure 7 depicts the mean velocity of the droplets of the hollow cone spray structure for different working fluids and the size of symbols is proportional to drop size. These fluids are distilled water and a water based solution with a surfactant named CTAB-cetyltrimethylammonium bromide (water + 0.05 wg% CTAB). Different metallic nanoparticles added to the base fluid are what forms the so-called nanofluids, i.e., liquid based suspensions of nanometer-sized particles (\(<\)100 nm). The surfactant is added to stabilize the suspension, precluding particles clustering and delaying their deposition. The purpose of nanofluids is to produce liquids with enhanced thermal properties, for example, a higher overall thermal conductivity for thermal management applications like spray cooling of high-power electronic devices. However, the addition of these nanoparticles may change the liquid's thermophysical properties, i.e., the viscosity, thus, is likely to alter the atomization processes and the spray characteristics. In this case, the mean diameter is \(d_{43}\), obtained from a volume-weighted drop size distribution because the application in mind is spray cooling. Therefore, any effect due to the size of droplets is related to the liquid volume of the spray impinging on a heated surface. As to the mean velocity, this is where the effects of adding a surfactant become noticeable. The information given by the average velocities obtained for \(Z=10\) mm and \(Z=20\) mm mainly allows for identifying the region of the faster droplets, after which the variation remains similar regardless of the liquid used. Faster droplets are present in the region of the liquid sheet forming the cone, where the number of droplets is also higher. This is actually the region where one can see some differences between the various working fluids, particularly at \(Z=20\) mm, where the spray is fully developed in terms of breakup atomization mechanisms [21]. The main difference observed is due to the addition of the surfactant, which decreases the surface tension of the base fluid (water and surfactant) in comparison with water. This property affects the size of droplets and, consequently, how these interact with the surrounding environment, leading to changes in momentum transfer expressed by the variations of the mean velocity. Despite their value, reporting mean quantities limits spray characterization. The presentation of the results should increase the informational value of data, and enable the reconstruction of the measured distributions compared to reporting its moments alone. Therefore, one could investigate if probability mathematical functions, such as the Log-Normal, Gamma, Weibull, and Nukiyama-Tanasawa can describe the histograms organizing the spray drop sizes by classes.