Self-assembly is a process in which interacting bodies are autonomously driven into ordered structures. Static structures such as crystals often form through simple energy minimization, whereas ...dynamic ones require continuous energy input to grow and sustain. Dynamic systems are ubiquitous in nature and biology but have proven challenging to understand and engineer. Here, we bridge the gap from static to dynamic self-assembly by introducing a model system based on ferrofluid droplets on superhydrophobic surfaces. The droplets self-assemble under a static external magnetic field into simple patterns that can be switched to complicated dynamic dissipative structures by applying a time-varying magnetic field. The transition between the static and dynamic patterns involves kinetic trapping and shows complexity that can be directly visualized.
•The effect of vapor velocity is investigated during dropwise condensation (DWC) of steam.•Heat transfer coefficient (HTC), droplet departing radius and droplet population are measured.•The ...condensation HTC increases with vapor velocity, while the droplet departing radius is reduced.•For the largest droplets radii, the drop-size distribution is lowered when increasing vapor velocity.•The effect of the vapor velocity on drop-size density and HTC is modeled.
The promotion of dropwise condensation (DWC) has been identified as an effective strategy to significantly improve the heat transfer coefficient (HTC) as compared to filmwise condensation (FWC). Understanding the mechanisms governing dropwise condensation on modified wettability surfaces is crucial for a wide range of energy applications. In the literature, most of the experimental data are collected during DWC with quiescent vapor. On the other hand, in industrial applications, the vapor to be condensed can have a non-negligible velocity which is expected to affect the droplet population on the condensing surface and the heat transfer. However, measurements of heat transfer coefficient and droplet population with flowing steam are rare and the effect of vapor velocity on the drop-size distribution, which is a key parameter in DWC modeling, needs to be investigated.
In the present work, the effect of steam velocity during DWC is experimentally studied on two different specimens: a sol–gel coated aluminum sample and a reduced graphene oxide coated copper sample. HTC, droplet departing radius and drop-size distribution measurements are performed at constant saturation temperature and heat flux, while varying the inlet vapor velocity in the range between 3 and 15.5 m s−1. Due to the increase of the vapor drag force on the droplets, a reduction of the droplet departing radius is observed along with an increase of the condensation HTC. The vapor flow is found to affect the droplet population and, in particular for the largest droplets radii, the drop-size distribution function is lowered when increasing vapor velocity. The experimental data are used to assess a model for the estimation of the droplet departing radius in presence of vapor velocity previously proposed by the present authors. As a second step, the equation for the calculation of the droplet departing radius is coupled with available models for droplet population and heat transfer through a single droplet to model the whole DWC process. The proposed calculation method is able to predict the effect of vapor velocity on the DWC heat transfer coefficient.
In this work, we propose and test the validity of a modified Phase Field Method (PFM), which is specifically developed for large scale simulations of turbulent flows with large and deformable ...surfactant-laden droplets. The time evolution of the phase field, ϕ, and of the surfactant concentration field, ψ, are obtained from two Cahn–Hilliard-like equations together with a two-order-parameter Time-Dependent Ginzburg–Landau (TDGL) free energy functional. The modifications introduced circumvent existing limitations of current approaches based on PFM and improve the well-posedness of the model. The effect of surfactant on surface tension is modeled via an Equation Of State (EOS), further improving the flexibility of the approach. This method can efficiently handle topological changes, i.e. breakup and coalescence, and describe adsorption/desorption of surfactant. The capabilities of the proposed approach are tested in this paper against previous experimental results on the effects of surfactant on the deformation of a single droplet and on the interactions between two droplets. Finally, to appreciate the performances of the model on a large scale complex simulation, a qualitative analysis of the behavior of surfactant-laden droplets in a turbulent channel flow is presented and discussed.
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In order to understand the basic mechanisms affecting emulsion stability, the intrinsic dynamics of the drop population must be investigated. We hypothesize that transient ballistic ...motion can serve as a marker of interactions between drops. In 1G conditions, buoyancy-induced drop motion obscures these interactions. The microgravity condition onboard the International Space Station enable this investigation.
We performed Diffusing Wave Spectroscopy (DWS) experiments in the ESA Soft Matter Dynamics (SMD) facility. We used Monte Carlo simulations of photon trajectory to support data analysis. The analysis framework was validated by ground-based characterizations of the initial drop size distribution (DSD) and the properties of the oil/water interface in the presence of surfactant.
We characterized the drop size distribution and found to be bi-disperse. Drop dynamics shows transient ballistic features at early times, reaching a stationary regime of primarily diffusion-dominated motion. This suggests different ageing mechanisms: immediately after emulsification, the main mechanism is coalescence or aggregation between small drops. However at later times, ageing proceeds via coalescence or aggregation of small with large drops in some emulsions. Our results elucidate new processes relevant to emulsion stability with potential impact on industrial processes on Earth, as well as enabling technologies for space exploration.
In recent years, Doppler radars have been or are being upgraded worldwide with dual-polarization capability, and polarimetric radar data are used extensively in retrieving the raindrop size ...distribution (RSD) to understand the microphysical processes of precipitation. However, the conventional constrained–gamma (C–G) retrieval method for dual-polarization radar is sensitive to local shape–slope (μ–Λ) relationships. This explains the major discrepancies between retrieval results based on different μ–Λ relationships derived from various rain regions of Typhoon Lekima (2019). Three μ–Λ relationships and corresponding differential–horizontal reflectivity (ZDR–ZH) relationships are recategorized according to precipitation types that are dominated by small, midsize, and large raindrops. This linkage is then used to modify the C–G retrieval method with a best-fitting μ–Λ relationship for each of the three ZDR–ZH relationships. The modified method is verified in terms of overcoming deficiencies in the conventional method, such as the insufficiency of retrieved samples when using the μ–Λ relationship from eyewall rain and the underestimation of retrieved raindrop diameters when using the μ–Λ relationship of outer rainbands. The modified method is also more able to elucidate microphysical processes such as collision–coalescence process.
•Three μ–Λ and ZDR–ZH relationships are recategorized according to precipitation types dominated by small, midsize, and large raindrops.•A modified C–G retrieval method is introduced to adopt a best-fitting μ–Λ relationship for each of the three ZDR–ZH relationships.•The modified method overcomes the shortcomings in the conventional method and is more able to elucidate microphysical processes.
•The impact and freezing process of a water droplet on a cold plate were studied experimentally and numerically.•The effects of surface temperature on the dynamic and freezing mechanism of water ...droplets were investigated systematically.•A numerical model was developed to investigate the impact and freezing process of water droplets on ultra-cold surfaces.•The results provide an indication for engineers and scientists to develop efficient anti-icing methods.
Ice accretion on cold solid surfaces presents hazards to a broad range of applications. It is quite essential to understand the dynamic and freezing mechanism of water droplets on a cold solid substrate for the prevention of ice accretion. In this study, the impact and freezing process of water droplets was studied experimentally and numerically. The effects of substrate temperature on the whole processes were investigated through changing the surface temperature from room temperature 25 °C to −30 °C. The results showed that the decrease of surface temperature led to the decrease of retraction rate, equilibrium droplet height after oscillation, freezing delay time and freezing time, while increased the final contact area due to the lower viscous dissipation energy. Also, a numerical model was developed to investigate the impact and freezing process of water droplets on an ultra-cold surface (−100 °C to −40 °C). The predicted droplet impact morphology, dynamic characteristics (spreading factor) and the propagation of freezing front were compared with experimental results, which exhibited good agreements. The numerical results suggested that the final contact area decreased slightly with the drastic decrease in surface temperature when the surface temperature is below −40 °C. Moreover, the influence of surface temperature on freezing front propagation and freezing time were analyzed in detail from the numerical results.
The characterization of a rainfall simulator provides an excellent opportunity to study the potential of soil erosivity without waiting for natural rain. But, precise instrumentation is required to ...estimate the parameters, which is seldom available. To overcome this problem, the empirical and conceptual relationships obtained through physically-based modeling help to correlate the rain parameters contributing to soil erosion. The present laboratory study used five pressurized nozzles of different capacities and a Laser Precipitation Monitor (LPM) to generate different rain intensities (21.0–79.0 mm h−1) and to register drop size distribution, respectively. The sediment transportation induced by rain and runoff was measured with an erosion flume of 2.50 × 1.25 × 0.56 m with an adjustable longitudinal slope. The spatial uniformity, drop size distribution, drop velocity, and kinetic energy were used to evaluate the simulator's performance. The different rain erosivity parameters were correlated and tested statistically using linear and non-linear regression analysis. The rain simulation experiments of different intensities at different pressure ranges were performed on flat, 5, 10, and 15% slopes of the erosion flume to evaluate rain characteristics and record the surface runoff and sediment yield. The median drop sizes produced during the simulator ranged from 0.38 to 2.11 mm, coinciding with natural rain. The empirical relationships were developed to correlate surface discharge and sediment yield with rain intensity by optimizing the parameters for further study of experimental field plots of different slopes. The observed and estimated rain erosivity parameters showed a significant relationship (R2 = 0.75 to 0.93; P < 0.001) in multiple regression analysis, and the metrics used to test the developed regression equations showed lower MAE, MSE, and RMSE errors indicating the adequacy of the relationships. The results indicated that the simulator helps to understand the complex task of soil erosion with hydrologic and geomorphic processes in laboratory experimentation with sufficient accuracy in measuring sediment transport events.
•The simulator's behavior with pressurized nozzles of different sizes has been evaluated.•Laser Precipitation Monitor most accurately described the Drop Size Distribution•Empirical relationships are developed through multiple regressions to correlate surface runoff and sediment yield at different rain intensities.•The study of sediment yield behavior for different rain intensities at different flume slopes was performed.
•Atomization model based on the ligament-mediated spray mechanism.•Self-similarity of cascade breakup with gamma distribution.•Nonlinear relationship of drop size and distribution.
The drop size ...distribution is one of the crucial parameters in liquid atomization. In this study, we develop a ligament-mediated gamma distribution (LMGD) model for coaxial two-fluid air-blast atomization based on cascade breakup and a ligament-mediated spray mechanism that can predict the nonlinear relationship between the drop diameters and drop size distribution at different velocities. The use of a single-parameter gamma distribution for the sizes of fragments produced by liquid ligament breakup is validated by experimental and theoretical results for liquid atomization. The proposed model outperforms the traditional model in enabling the simultaneous calculation of the mean drop size and distribution, as well as the accurate prediction of the nonlinearity of the distribution of drop sizes. The LMGD model has the advantage of being simple and efficient and more realistic than the traditional model.
Abstract
Raindrop size distributions (DSD) and rain rate have been estimated from polarimetric radar data using different approaches with the accuracy depending on the errors both in the radar ...measurements and the estimation methods. Herein, a deep neural network (DNN) technique was utilized to improve the estimation of the DSD and rain rate by mitigating these errors. The performance of this approach was evaluated using measurements from a two-dimensional video disdrometer (2DVD) at the Kessler Atmospheric and Ecological Field Station in Oklahoma as ground truth with the results compared against conventional estimation methods for the period 2006–17. Physical parameters (mass-/volume-weighted diameter and liquid water content), rain rate, and polarimetric radar variables (including radar reflectivity and differential reflectivity) were obtained from the DSD data. Three methods—physics-based inversion, empirical formula, and DNN—were applied to two different temporal domains (instantaneous and rain-event average) with three diverse error assumptions (fitting, measurement, and model errors). The DSD retrievals and rain estimates from 18 cases were evaluated by calculating the bias and root-mean-squared error (RMSE). DNN produced the best performance for most cases, with up to a 5% reduction in RMSE when model errors existed. DSD and rain estimated from a nearby polarimetric radar using the empirical and DNN methods were well correlated with the disdrometer observations; the rain-rate estimate bias of the DNN was significantly reduced (3.3% in DNN vs 50.1% in empirical). These results suggest that DNN has advantages over the physics-based and empirical methods in retrieving rain microphysics from radar observations.
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