Sílvio M. R. Cândido

Sílvio M. R. Cândido

Mechanical Engineer @ [CERN](https://home.cern/)

Publications

On modal decomposition as surrogate for charge-conservative EHD modelling of Taylor Cone jets

Published in International Journal of Engineering Science, 2023

The dynamics of the interface of a fluid jet subjected to an external electrostatic field forming a Taylor cone jet is investigated using a numerical approach. A charge-conservative electrohydrodynamic model is used. In this model, the reduced form of Maxwell’s equations for an electrostatic field, a transport equation for electric charges and the Navier-Stokes equations for a laminar flow are solved. The connection between the electric field and the hydrodynamic flow is established by the Maxwell stress tensor, which ensures the description of the electric surface forces. To analyse the dynamics of the flow, it is proposed to use decomposition methods such as Proper Orthogonal Decomposition (POD) and Dynamic Mode Decomposition (DMD) using snapshots of the flow field. The dynamic structures formed by the velocity field and the dynamics of the electric charge determine the fundamental dynamics of the droplet emission. An analysis of the sensitivity of the modes to the sampling frequency is performed. The influence of different inlet velocities on the decomposition is analysed in the spatial and frequency domain. A reduced-order model (ROM) is interpolated from the base POD, and we demonstrate that it can be used to successfully construct the velocity and electric charge along the field. We anticipate numerous applications of this new type of ROM, such as for accelerating electrohydrodynamic calculations as surrogate models in digital twins.

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Optimization of painting efficiency applying unique techniques of high-voltage conductors and nitrotherm spray: Developing deep learning models using computational fluid dynamics dataset

Published in Physics of Fluids, 2023

The impetus of the current 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. A convolutional auto-encoder is used to reduce the computational cost with just 10% of the initial three-dimensional CFD Eulerian–Lagrangian 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.

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Dynamics of three-dimensional electrohydrodynamic instabilities on Taylor cone jets using a numerical approach

Published in Physics of Fluids, 2023

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.

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Development of a Background-Oriented Schlieren (BOS) System for Thermal Characterization of Flow Induced by Plasma Actuators

Published in Energies, 2023

This study introduces the development of a background-oriented Schlieren (BOS) system, used to explore the thermal effects and potential deicing capabilities of plasma actuators. These actuators are promising devices for dual flow control and deicing purposes, as they transfer momentum to the local airflow and induce significant thermal changes. However, their analysis has been limited due to considerable electromagnetic interference. For the first time, using the BOS system, we investigated the induced flow temperatures across plasma actuators with varied dielectric materials and thicknesses.

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