4.6 Article

A Hybrid Metaheuristic Based on Neurocomputing for Analysis of Unipolar Electrohydrodynamic Pump Flow

Journal

ENTROPY
Volume 23, Issue 11, Pages -

Publisher

MDPI
DOI: 10.3390/e23111513

Keywords

unipolar pump flow; electrohydrodynamic; nonlinear systems; sine-cosine algorithm; sequential quadratic programming; dynamic parameters; electric potential; neurocomputing; charge density

Funding

  1. Direccion General de Investigaciones of the Universidad Santiago de Cali [01-2021]

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A study on unipolar electrohydrodynamic (UP-EHD) pump flow was conducted with a hybrid metaheuristic solver, evaluating the performance through comparison with reference solutions and executing a large data set of experiments to demonstrate superior technique.
A unipolar electrohydrodynamic (UP-EHD) pump flow is studied with known electric potential at the emitter and zero electric potential at the collector. The model is designed for electric potential, charge density, and electric field. The dimensionless parameters, namely the electrical source number (Es), the electrical Reynolds number (ReE), and electrical slip number (Esl), are considered with wide ranges of variation to analyze the UP-EHD pump flow. To interpret the pump flow of the UP-EHD model, a hybrid metaheuristic solver is designed, consisting of the recently developed technique sine-cosine algorithm (SCA) and sequential quadratic programming (SQP) under the influence of an artificial neural network. The method is abbreviated as ANN-SCA-SQP. The superiority of the technique is shown by comparing the solution with reference solutions. For a large data set, the technique is executed for one hundred independent experiments. The performance is evaluated through performance operators and convergence plots.

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