Cold climate regions have great potential for wind power generation. The available wind energy in these regions is about 10% higher than in other regions due to higher wind speeds and increased air density. However, these regions usually have favorable icing conditions that lead to ice accumulation on the wind turbine blades, which in turn increases the weight of the blades and disrupts local airflow, resulting in a reduction in wind turbine performance. Considering this problem, plasma actuators have been proposed as devices for simultaneous flow control and deicing. These devices transfer momentum to the local airflow, improving the aerodynamic performances of the turbine blades while producing significant thermal effects that can be used to prevent ice formation. Considering the potential application of plasma actuators for simultaneous flow control and deicing, it is very important to investigate the thermal effects induced by these devices. However, due to the significant electromagnetic interference generated by the operation of these devices, there is a lack of experimental techniques that can be used to analyze them. In the current work, a background-oriented Schlieren system was developed and is presented as a new experimental technique for the thermal characterization of the plasma-induced flow. For the first time, the induced flow temperatures are characterized for plasma actuators with different dielectric materials and different dielectric thicknesses. The results demonstrate that, due to the plasma discharge, the temperature of the plasma-induced flow increases with the increase of the applied voltage and may achieve temperatures five times higher than the room temperature, which proves the potential of plasma actuators for deicing applications. The results are presented and discussed with respect to the potential application of plasma actuators for simultaneous flow control and deicing of wind turbine blades.
The impetus of the current three-dimensional Eulerian–Lagrangian work is to analyze the impact of simultaneously using the inventive high-voltage conductors and Nitrotherm spraying technique for maximizing the industrial painting process efficiency. This investigation employs high-fidelity computational fluid dynamics (CFD) results in deep learning models as an input dataset. The novel conductors are called high-voltage retractable blades (HVRB) and high-voltage adjustable control-ring (HVACR) mounted on the head of the electrostatic rotating bell sprayer. The influence of dominant operational parameters, such as temperature and velocity of injected nitrogen or air, droplets' electric charge values, and their size ranges, and electric field density are examined in the considered database for the Nitrotherm spraying methodology. This broad range of parametric investigation illustrates that the inclusion of shaping nitrogen flow, manipulated electric field density, and droplet charging weights significantly affect the spraying deposition rate. The pressurized clean heated nitrogen flow, which is injected from the nozzles of the atomizers, positively redirects and harmonizes the charged droplets that construct an optimized spray plume pattern with a smaller diameter. Using innovative HVRB and HVACR conductors is manipulated the electric fields and leads to denser distribution, intensifying the acting electric force on the droplets, resulting in higher spraying transfer efficiency (TE) and thicker film formation. Based on the results, employing the introduced conductors in combination with the heated nitrogen instead of air leads to higher TE, rare overspray occurrence, formation of an esthetic paint film, lower paint consumption, and application time. Also, the collected complete database is employed for machine learning investigation to predict flow with high accuracy, aiming to reduce computational time/cost. A convolutional auto-encoder is used to reduce the computational cost with just 10% of the initial CFD computations, with a mean error of 1% on the prediction of the deposited droplet areas of the spray. The analysis revealed that by employing recurrent convolutional layers, superior capturing of the input pattern is obtained, which significantly aids the final prediction.
The stretch of interfacial flows due to the external application of an electric field has considerable importance in several applications. These range from engineering nanofibres to propulsion, the electrified jets bring us an outstanding technique to perform the emission of microdroplets. The present investigation concerns the resolution of interfacial electrohydrodynamic flows from a numerical standpoint using computational fluid dynamics. The reduced form of the Maxwell equations, for an electrostatic field, and a transport equation for the electric charges are coupled to the standard interFoam solvers on OpenFOAM, which resolves an immiscible two-phase flow. A laminar condition is assumed for the flow thus the laminar incompressible Navier-Stokes’s equations are used to compute the hydrodynamic behavior of the flow and, associated with them, electrically induced body forces are incorporated into the hydrodynamic momentum equation. The Maxwell Stress Tensor (MST) describes electrical surface forces acting on the liquid, making it possible to incorporate that effect on the momentum equation. A new efficient geometric Volume-of-Fluid (VoF) method for general meshes, called isoAdvector, was implemented in OpenFOAM, as a substitute for the Multidimensional Universal Limiter for Explicit Solution (MULES). The open literature on the subject presents quantitative benchmarks that demonstrated a significant improvement in the quality with which we can compute sharper interfaces on immiscible two-phase flows (Gamet, L. et al. 2020). Following this approach, we present here an application of that method to the simulation of the breakup of electrified liquids jets. To validate the implementation of the electric field equations, the order of the accuracy of the spatial and time discretization is herein computed. The validation of the discretization of the electric field equations is accomplished with a planar test case that is considered a benchmark test for this class of flows. The test case showed good accuracy on the resolution of the electric potential and electric field having lesser than 0.1% of difference against the theoretical solution. The code is then applied to a Taylor cone jet. This type of jets is at the base of the Electro-hydrodynamic sprays (EHDS) physics. These latter operate by a potential difference between a conductive liquid, usually on the tip of a needle, and an extractor electrode. The numerical model shows a remarkable accuracy on the prediction of the charged droplet size.
Electrohydrodynamic (EHD) jets are a highly promising technology for the generation of three-dimensional micro- and nanoscale structures, but the advancement of this technology is hindered by the insufficient understanding of many aspects of its flow mechanisms, such as the whipping behavior under larger electric potentials. A fully coupled numerical simulation of the three-dimensional electrohydrodynamic jet flow is used here since non-symmetric effects govern most of their EHD regimes. By applying considerable electric capillary numbers (CaE>0.25), we capture radial instabilities that until now no other numerical simulation was able to present. A comparison against previous two-dimensional axis-symmetric and validation with experimental studies of the Taylor cone jet is initially done. An exciting gain in accuracy was obtained, having an error of around 1.101% on the morphology against experimental results. Moreover, our numerical model takes into consideration the contact angle between the surface of the nozzle and the liquid, which is shown to be a very important variable for improved accuracy in the morphologic shape of the Taylor cone. Moreover, the three-dimensional structures and flow dynamics, under different electric capillary numbers, and their connection to the instabilities of the jet are studied. We present a novel visualization of the formation of droplet generation with the receded Taylor cone and the whipping dynamics.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.