Rain Droplets Research Articles

Damage behavior and assessment of aeronautical PMMA subjected to high-velocity water-jet impact

Rain erosion of forward-facing aircraft components such as windshields can lead to a significant reduction in performance, hence a potential hazard to air safety, especially for supersonic fighters exposed to precipitation. To understand such threats, the damage behavior of two types of most commonly used aeronautical PMMA, i.e., oriented and non-oriented, under water droplet impact is investigated. A single-impact jet apparatus based on the one-stage gas gun was established to simulate the rain droplet impact. Two critical variables were evaluated, including water-jet velocities and incident angles. Typical damage characteristic features including annular depression and circumferential cracks were observed on non-oriented PMMA targets. In contrast, on oriented PMMA targets, massive subsurface craze delamination was observed without any sign of surface cracks. The distinct damage features are determined by the different damage behavior of the oriented and non-oriented PMMA targets during the initial stage of the impingement and the shearing effect of the lateral jet. Increasing impact velocity leads to surface peeling and bulk removal, escalating the damage severity. The damage mechanism of subsurface failure was revealed by observing stress wave interaction and the FEM simulation. An impulse method was developed to quantify each impact event and assess the damaged area. A linear relationship between the damaged area and the initial impact stage impulse was established, which can be applied for preliminary evaluation and prediction of the damage caused by high-velocity water droplet impact on aeronautical PMMA.

Microphysical Characteristics of Cyclonic Rainfall: A GPM‐DPR Based Study Over the Arabian Sea

AbstractThe precipitation characteristics of tropical cyclone (TC) formed over the Arabian Sea during the onset phase of the Indian summer monsoon (i.e., late‐May and early‐June months) and in the post‐monsoon season were investigated during the period from 2014 to 2021 using the Global Precipitation Measurement (GPM) satellite level 2 V07 data. For the cyclonic precipitation, 2‐D frequency distribution between liquid water content (LWC) and non‐liquid water content, that is, ice water content (IWC) shows significant variation with the rain type and season. A large proportion of rain droplets are within the LWC (IWC) range of 0–800 (0–350) g/m2 for the stratiform precipitation of TCs in both seasons. The average value of the mass‐weighted mean diameter (Dm), for the stratiform and convective precipitation at 2 km above the mean sea level in the monsoon (post‐monsoon) season is 1.29 (1.27) mm and 1.47 (1.31) mm, respectively. A gradual decrease in the normalized intercept parameters (Nw) is found to occur with an increase in Dm, irrespective of cloud type and season. There is an enormously high concentration of supercooled liquid and ice particles observed above the melting layer during the convection precipitation in both seasons. In the stratiform cyclonic cloud, the contribution of the collision‐coalescence and breaking‐up process is about 36.62% (47.58%) and 52.52% (41.52%) during the monsoon (post‐monsoon) season. However, the collision‐coalescence process (63.45% in monsoon and 70.2% in post‐monsoon) is acting as dominating microphysical process in the convective precipitation as compared to the break‐up process.

Erosion modelling on reconstructed rough surfaces of wind turbine blades

AbstractNumerical simulations of rain droplet impacts on real rough surfaces of leading edges of wind turbine blades are presented. The effect of rough blade surface conditions during liquid impacts on the stress distribution in the protective coating is studied. Realistic rough surfaces of wind turbine blades, obtained from 3D reconstruction of real blades with photogrammetry, as well as artificially generated rough surfaces were introduced into finite element models of the droplet/blade coating interaction. Stress distributions in the protective coating with rough and flat surfaces were studied and compared. The results of the simulations suggest that roughness on the surface of the blade leads to increased stresses in the protective coating.

Visual analysis of model parameter sensitivities along warm conveyor belt trajectories using Met.3D (1.6.0-multivar1)

Abstract. Numerical weather prediction models rely on parameterizations for subgrid-scale processes, e.g., for cloud microphysics, which are a well-known source of uncertainty in weather forecasts. Via algorithmic differentiation, which computes the sensitivities of prognostic variables to changes in model parameters, these uncertainties can be quantified. In this article, we present visual analytics solutions to analyze interactively the sensitivities of a selected prognostic variable to multiple model parameters along strongly ascending trajectories, so-called warm conveyor belt (WCB) trajectories. We propose a visual interface that enables us to (a) compare the values of multiple sensitivities at a single time step on multiple trajectories, (b) assess the spatiotemporal relationships between sensitivities and the trajectories' shapes and locations, and (c) find similarities in the temporal development of sensitivities along multiple trajectories. We demonstrate how our approach enables atmospheric scientists to interactively analyze the uncertainty in the microphysical parameterizations and along the trajectories with respect to the selected prognostic variable. We apply our approach to the analysis of WCB trajectories within extratropical Cyclone Vladiana, which occurred between 22–25 September 2016 over the North Atlantic. Peaks of sensitivities that occur at different times relative to a trajectory's fastest ascent reveal that trajectories with their fastest ascent in the north are more susceptible to rain sedimentation from above than trajectories that ascend further south. In contrast, large sensitivities to cloud condensation nuclei (CCN) activation and cloud droplet collision in the south indicate a local rain droplet formation. These large sensitivities reveal considerable uncertainty in the shape of clouds and subsequent rainfall. Sensitivities to cloud droplets' formation and subsequent conversion to rain droplets are also more pronounced along convective ascending trajectories than for slantwise ascents. The slantwise ascending trajectories are characterized by periods of slower ascent and even descent, during which the sensitivities to the formation of cloud droplets and rain droplets alternate. This alternating pattern leads to large-scale precipitation patterns, whereas convective ascending trajectories do not exhibit this pattern. Thus the primary source for uncertainty in large-scale precipitation patterns stems from slantwise ascents. The strong ascent of convective trajectories leads to large sensitivities of rain mass density to riming and freezing parameters at high altitudes, which are barely present in slantwise ascending trajectories. These sensitivities correspond to uncertainties concerning graupel and hail formation in convective ascents.

A Methodology to Model the Rain and Fog Effect on the Performance of Automotive LiDAR Sensors.

In this work, we introduce a novel approach to model the rain and fog effect on the light detection and ranging (LiDAR) sensor performance for the simulation-based testing of LiDAR systems. The proposed methodology allows for the simulation of the rain and fog effect using the rigorous applications of the Mie scattering theory on the time domain for transient and point cloud levels for spatial analyses. The time domain analysis permits us to benchmark the virtual LiDAR signal attenuation and signal-to-noise ratio (SNR) caused by rain and fog droplets. In addition, the detection rate (DR), false detection rate (FDR), and distance error derror of the virtual LiDAR sensor due to rain and fog droplets are evaluated on the point cloud level. The mean absolute percentage error (MAPE) is used to quantify the simulation and real measurement results on the time domain and point cloud levels for the rain and fog droplets. The results of the simulation and real measurements match well on the time domain and point cloud levels if the simulated and real rain distributions are the same. The real and virtual LiDAR sensor performance degrades more under the influence of fog droplets than in rain.

Quantitative Prediction of Sling Events in Turbulence at High Reynolds Numbers.

Collisional growth of droplets, such as occurring in warm clouds, is known to be significantly enhanced by turbulence. Whether particles collide depends on their flow history, in particular on their encounters with highly intermittent small-scale turbulent structures, which despite their rarity can dominate the overall collision rate. Here, we develop a quantitative criterion for sling events based on the velocity gradient history along particle paths. We show by a combination of theory and simulations that the problem reduces to a one-dimensional localization problem as encountered in condensed matter physics. The reduction demonstrates that the creation of slings is controlled by the minimal real eigenvalue of the velocity gradient tensor. We use fully resolved turbulence simulations to confirm our predictions and study their Stokes and Reynolds number dependence. We also discuss extrapolations to the parameter range relevant for typical cloud droplets, showing that sling events at high Reynolds numbers are enhanced by an order of magnitude for small Stokes numbers. Thus, intermittency could be a significant ingredient in the collisional growth of rain droplets.

Theoretical analysis of acoustic and turbulent agglomeration of droplet aerosols

This study meticulously explores the agglomeration mechanisms in microscale droplet aerosols, specifically focusing on acoustic and turbulent agglomeration mechanisms. Our theoretical analysis reveals a significant impact of orthokinetic and hydrodynamic processes on acoustic agglomeration. The acoustic wake effect elucidates the swift replenishment of small particles subsequent to an orthokinetic phase. An optimal frequency, varying for different droplets, was identified in orthokinetic agglomeration within the 50–250 Hz range. Hydrodynamic agglomeration remained relatively stable at an acoustic frequency exceeding 1000 Hz. The aggregation kernel function, denoted as Kij, exhibited a significant increase with increasing sound pressure levels, reaching up to 10−8 s−1. Environmental temperature had a predominantly positive effect on orthokinetic and Brownian agglomeration, although it exhibited an inhibitory effect on hydrodynamic agglomeration. For raindrops, a correlation was identified between particle spacing and Kij; a larger particle spacing corresponded to a smaller Kij. Despite an increase in particle spacing to 50 times the particle diameter, the hydrodynamic effect persisted. The aggregation kernel function linked to Brownian thermal motion was found to be 3–4 orders of magnitude lower than that of orthokinetic and hydrodynamic interactions. Additionally, the turbulent agglomeration kernel function for fog, cloud, and rain droplets with corresponding parent nuclei of 100 μm was of the same order of magnitude as the acoustic agglomeration kernel function.

Universal alignment in turbulent pair dispersion

Countless processes in nature and industry, from rain droplet nucleation to plankton interaction in the ocean, are intimately related to turbulent fluctuations of local concentrations of advected matter. These fluctuations can be described by considering the change of the separation between particle pairs, known as pair dispersion, which is believed to obey a cubic in time growth according to Richardson’s theory. Our work reveals a universal, scale-invariant alignment between the relative velocity and position vectors of dispersing particles at a mean angle that we show to be a universal constant of turbulence. We connect the value of this mean angle to Richardson’s traditional theory and find agreement with data from a numerical simulation and a laboratory experiment. While the Richardson’s cubic regime has been observed for small initial particle separations only, the constancy of the mean angle manifests throughout the entire inertial range of turbulence. Thus, our work reveals the universal nature of turbulent pair dispersion through a geometrical paradigm whose validity goes beyond the classical theory, and provides a framework for understanding and modeling transport and mixing processes.

Nowcasting Multiparameter Phased-Array Weather Radar (MP-PAWR) Echoes of Localized Heavy Precipitation Using a 3D Recurrent Neural Network Trained with an Adversarial Technique

Abstract We present nowcasts of sudden heavy rains on meso-γ scales (2–20 km) using the high spatiotemporal resolution of a multiparameter phased-array weather radar (MP-PAWR) sensitive to rain droplets. The onset of typical storms is successfully predicted with 10-min lead time, i.e., the current predictability limit of rainfall caused by individual convective cores. A supervised recurrent neural network based on long short-term memory with 3D spatial convolutions (RN3D) is used to account for the horizontal and vertical changes of the convective cells with a time resolution of 30 s. The model uses radar reflectivity at horizontal polarization ZH and the differential reflectivity. The input parameters are defined in a volume of 64 × 64 × 8 km3 with the lowest level at 1.9 km and a resolution of 0.4 × 0.4 × 0.25 km3. The prediction is a 10-min sequence of ZH at the lowest grid level. The model is trained with a large number of observations of summer 2020 and an adversarial technique. RN3D is tested with different types of rapidly evolving localized heavy rainfalls of summers 2018 and 2019. The model performance is compared to that of an advection model for 3D extrapolation of PAWR echoes (A3DM). RN3D better predicts the formation and dissipation of precipitation. However, RN3D tends to underestimate heavy rainfall especially when the storm is well developed. In this phase of the storm, A3DM nowcast scores are found slightly higher. The high skill of RN3D to predict the onset of sudden localized rainfall is illustrated with an example for which RN3D outperforms the operational precipitation nowcasting system of Japan Meteorological Agency (JMA). Significance Statement Temporal extrapolation of radar observations is a means of nowcasting sudden heavy rains, i.e., forecasts with a few tens of minutes and a high spatial resolution better than 500 m. They are necessary to set up warning systems to anticipate damage to infrastructure and reduce the fatalities these storms cause. It is a difficult task due to the storm suddenness, restricted area, and nonlinear behavior that are not well captured by current operational observation and numerical systems. In this study, we use a new high-resolution weather radar with polarimetric information and a 3D recurrent neural network to improve 10-min nowcasts, the current limit of operational systems. This is a first and essential step before applying such a method for increasing the prediction lead time.

ON THE EFFECT OF VISCOSITY RELAXATION ON ELECTROMAGNETIC RADIATION INTENSITY OF AN OSCILLATING CHARGED DROPLET

Theoretical asymptotic calculations linear with respect to small dimensionless amplitude of oscillations have been employed to study the influence of the viscoelastic properties of a charged droplet of an electrically conducting viscous liquid on the intensity of its electromagnetic radiation. It has been shown that allowance for the effect of viscosity relaxation leads to a decrease in the damping decrement value, which is determined by energy losses for electromagnetic wave emission, and the intensity of high-frequency electromagnetic radiation; a substantial reduction in the viscous damping decrement of small cloud droplets; and an essential dependence of the viscous damping decrement on the characteristic relaxation time. It has been found that the viscosity relaxation of a liquid has no significant effect on damped capillary oscillations and electromagnetic radiation of rain droplets. Viscoelasticity and viscosity of the liquid do not influence the conditions critical for the realization of the electrostatic instability of a droplet with respect to its own charge.

Non-planar dielectrics derived thermal and electrostatic field inhomogeneity for boosted weather-adaptive energy harvesting.

Weather-adaptive energy harvesting of omnipresent waste heat and rain droplets, though promising in the field of environmental energy sustainability, is still far from practice due to its low electrical output owing to dielectric structure irrationality and unscalability. Here we present atypical upcycling of ambient heat and raindrop energy via an all-in-one non-planar energy harvester, simultaneously increasing solar pyroelectricity and droplet-based triboelectricity by two-fold, in contrast to conventional counterparts. The delivered non-planar dielectric with high transmittance confines the solar irradiance onto a focal hotspot, offering transverse thermal field propagation towards boosted inhomogeneous polarization with a generated power density of 6.1mW m-2 at 0.2 sun. Moreover, the enlarged lateral surface area of curved architecture promotes droplet spreading/separation, thus travelling the electrostatic field towards increased triboelectricity. These enhanced pyroelectric and triboelectric outputs, upgraded with advanced manufacturing, demonstrate applicability in adaptive sustainable energy harvesting on sunny, cloudy, night, and rainy days. Our findings highlight a facile yet efficient strategy, not only for weather-adaptive environmental energy recovery but also in providing key insights for spatial thermal/electrostatic field manipulation in thermoelectrics and ferroelectrics.

Design of a rainfall simulator for classroom demonstration and field research

AbstractRainfall is a key abiotic factor of ecosystems that can both provide benefits and contribute to negative environmental impacts. Due to spring precipitation levels increasing in the Midwest, there has been increased interest in developing and evaluating practices that can mitigate the effects of heavy rainfall. As this is an area of interest for both agriculture and environmental sciences, demonstrating the actions of severe rainfall can be a powerful tool in the natural sciences classroom as well as in the field. Rainfall simulators are ideal for this demonstration as they can create repeated, uniform rainfall events while introducing limited variability between events. Building on previous literature, we constructed a cost‐effective, easily transportable design that can be utilized in the classroom, the lab, and the field. Here, tests were conducted to measure flow rate, rain droplet size, and uniformity of water dispersion on the cost‐effective and easily obtained solid cone‐style herbicide nozzle. We found no statistically significant differences among rainfall dispersion metrics or in raindrop uniformity analyses. This demonstrates the capability of constructing this type of teaching and research equipment at little cost while producing highly consistent and size‐relevant artificial rainfall.

Surface roughness evolution of wind turbine blade subject to rain erosion

Leading edge erosion of wind turbine blades causes roughening of the blade’s surface, leading to a reduction of energy production. This paper presents a computational model for the prediction of the roughness evolution of the blade’s surface, based on fatigue damage calculations and rain droplet impact simulations. A novel method for the calculation of material roughness due to multiple random liquid impacts was developed, by considering damage concentration in areas where sharpness due to material removal is formed. Material removal was governed by fatigue damage values. The computational model was compared to roughness measurements from a sample tested in a rain erosion tester. The outputs of this model are 3D surfaces resembling the roughness of the protective coating layer as well as the evolution of surface roughness parameters and mass loss throughout time.

Numerical Simulations of the Adverse Effects of Rain on Airfoil And Rotor Aerodynamic Characteristics

There is a significant interest in improving the performance of rotors under adverse operating conditions. However, there is a very limited understanding of the performance implications on two-dimensional (2D) airfoils and rotor blades under adverse effects of rainfall. Furthermore, the fundamental physical phenomena causing the loss in performance are not clearly understood. In this study, low-fidelity models are first developed to rapidly estimate the water layer formation on 2D airfoils and assess the resulting impact on lift and drag characteristics. The low-fidelity simulations are also useful to obtain quick estimates of water layer thickness as a function of liquid water content and droplet diameter. Subsequently, computational fluid dynamics studies for 2D airfoils and a small-scale rotor in hover are done to obtain more accurate estimates of the effects of rain on airfoil performance and match test data where available. Higher fidelity parametric studies for various airfoils were conducted by varying angles of attack, the liquid water content in the rain droplets, and the droplet diameters to capture trends in performance degradation. The resulting trends match the trends from the test data reasonably well. The higher fidelity airfoil loads are subsequently used within a classical combined blade element-momentum model to assess the loss of performance attributable to rain for a small-scale rotor. The present studies indicate a significant loss in thrust production, a rise in the power requirement, and a reduction in the figure of merit for small-scale rotors caused by rain.

Interaction of open-top, short, cylindrical tank with wind-driven rain

Driving rain or wind-driven rain (WDR) is defined as rain, falling in an inclined manner due to the driving force of the wind, inflicting damage to the envelope of building, due to rain droplet impingement, hygrothermal effect, and, rain water ingress. When rain is driven by wind, especially high wind (during storm, cyclone, etc.), the rain droplet impact can increase. There is no availability of literatures on the interaction of shell structures with driving rain, which incurs damage to the thin wall of the tank through droplet impact. This scope is the main motivation behind the present study, which is focused on fluid–structure interaction analysis of an open-top, ground-supported, cylindrical tank with a slenderness ratio of 1.0, affected by wind driven rain. The thickness of the tank wall is varied, and, open terrain condition is considered. The study exhibits that the force coefficient (Cf) of WDR is higher between 0° to 53° peripheral position and decreasing upto 140° circumferential location. Maximum 28% increase of force coefficient of WDR noticed for 45° position in comparison to the wind force coefficient. Also, the top of the tank wall exhibits greater deformation and vulnerable under the effect of wind-driven rain load. Also, it is evident that 0° to 18°, and, 0° to 27° circumferential area exhibit higher deformation for radius: thickness (R/t) ratios 500, and 250, respectively. In case of R/t ratios 125, and 166.67, the higher deformation zone is distributed 0° to 15° and 77° to 82° peripherally. This deformation behaviour of the tank wall, shows that the open-top tanks need to be stiffened at the top to withstand the wind-driven rain force. The magnitude of deformation exhibits increments with the decrease in the thickness of wall of the tank. Maximum deformation is observed for lowest thickness of the tank wall.

Fluid-structure interaction analysis on the response of open-top, squat, circular tank due to wind-driven rain

Wind-driven rain (WDR) is a natural phenomenon, which occurs, when rain droplets descend through a wind flow field, creating an angle with the vertical and affects any structure by impingement through the structural envelope. Existing literatures on wind-driven rain effect on structure, are focused on building envelop only. There is a huge scope, left unexplored, on studying the interaction response of squat, open top, circular tank with wind-driven rain. This available scope is the main motivation of the present authors behind this study. The present study has been conducted through fluid–structure interaction (FSI) analysis, by coupling computational fluid dynamics (CFD) analysis of a multi-phase fluid system involving air and water to simulate wind-driven rain, with the mechanical analysis of the tank structure, by importing the wall pressure, assessed from CFD model of WDR. This study is focused on ground-supported, open-top, squat, circular tank with a slenderness ratio of 0.5. The internal and external pressure distributions on the tank wall have been assessed for WDR and compared with the same caused by wind. The radius (R): thickness (t) ratio of the tank wall has been varied from 125 to 500, in order to understand the impact of wind-driven rain on the tank wall deformation. The comparative study of pressure distribution between WDR and wind (only) cases clearly demonstrates that the wall pressure (internal and external) due to wind-driven rain, is higher than wind (only). It has been observed that the wall deformation is showing an incremental pattern with the decrement of wall thickness. The maximum deformation zone has been observed at the upper half of the frontal area. Higher deformation zone for R/t ratios 500, 250, 166.67, and 125, can be seen for 0° to 40°, 0° to 37°, 0° to 35°, and 0° to 32°, peripherally.

Multi-weather full-body triboelectric garments for personalized moisture management and water energy acquisition

The occurrence of extreme events (such as heatwaves, heavy precipitation) is unprecedented in the observed record and will increase with increasing global warming, leading to severe human health issues. Wearing suitable garments in different weather is one of the solutions for people to ease their physical discomfort in an energy-saving way. However, only one piece of traditional clothes hardly satisfies the demand of the changing weather. Herein, a multi-weather full-body triboelectric garment with a one-way moisture transport structure is presented to keep people feeling cool in the scorching weather while capturing droplet energy in rainy situations. A trilayer progressive wetting structure was designed to effectively transport sweat from the inner layer near the skin to the outer layer to keep the skin dry and comfortable in the muggy air, with a unidirectional transmission index of 1025%. When it starts to rain, the rain droplets quickly roll down the textile surface and generate triboelectric energy with the hydrophobic surface and conductive MXene layer inside. More than that, the scalable fabrication process makes it possible to obtain the textile with enough areas for making a whole garment, which is much more practical in real application scenarios.

Contact Angle on Rough Curved Surfaces and Its Implications in Porous Media

The equilibrium contact angle depends on both the chemistry of the two fluids and solid base and the microstructure on the solid surface. Actual surface of the pore wall in porous media is typically rough and curved, which has not been well-considered in related applications. This work uses a free interfacial energy minimization approach to theoretically derive the equilibrium contact angle on two specific surface structures on flat surfaces and extends the derivation considering the surface curvatures in porous media. Results reveal that the equilibrium contact angle is not dependent on the curvature of spherical surfaces, and we further prove that this conclusion applies to any point along the apparent common line at solid surfaces with any arbitrary curvature. The fundamental physics is the local mechanical balance of a composite contact among three interfacial tensions. Furthermore, the contacting mode can shift from non-wetting to wetting when the pressure difference between two fluids exceeds the entry pressure of the microstructures, which should be considered in relative dynamic scenarios such as rain droplet impact and fluid displacement in porous media. Note that these conclusions are from pure theoretical analysis based on idealistic assumptions, and real circumstances may deviate from these assumptions.

Non‐destructive and contactless defect detection inside leading edge coatings for wind turbine blades using mid‐infrared optical coherence tomography

AbstractLeading edge erosion of wind turbine blades is one of the most critical issues in wind energy production, resulting in lower efficiency, as well as increased maintenance costs and downtime. Erosion is initiated by impacts from rain droplets and other atmospheric particles, so to protect the blades, special protective coatings are applied to increase their lifetime without adding significantly to the weight or friction of the blade. These coatings should ideally absorb and distribute the force away from the point of impact; however, microscopic defects, such as bubbles, reduce the mechanical performance of the coating, leading to cracks and eventually erosion. In this work, mid‐infrared (MIR) Optical Coherence Tomography (OCT) is investigated for non‐destructive, contactless inspection of coated glass‐fiber composite samples to identify subsurface coating defects. The samples were tested using rubber projectiles to simulate rain droplet and particle impacts. The samples were subsequently imaged using OCT, optical microscopy, and X‐ray tomography. OCT scanning revealed both bubbles and cracks below the surface, which would not have been detected using ultrasonic or similar non‐destructive methods. In this way, OCT can complement the existing quality control in turbine blade manufacturing, help improve the blade lifetime, and reduce the environmental impact from erosion.

The capture of airborne particulates by rain

Rain cleans pollution out of the atmosphere, as droplets collide with airborne particles during free fall. Such particle–droplet collisions have been presumed to be capture events, but the details of such collisions lack thorough investigation. We show that rain droplets and pollution particles interact through multiple collision behaviours, including captures on the droplet surface, cavity-forming droplet entries and ricochets. Rain drop diameter and free fall velocity, in addition to pollution particle density, size, wettability and droplet impact location, determine which capture or escape behaviour occurs. Our findings reveal that rain does not capture all airborne pollutants equally even upon collision, and certain pollutants prove more difficult to remove from the air than others. Consequently, we must account for both rain and pollution characteristics to understand pollution capture mechanisms and pollution fluxes in the environment.