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

Area of Science:

• Fluid Dynamics
• Electrohydrodynamics
• Computational Physics

Background:

• Unipolar electrohydrodynamic (UP-EHD) pumps are crucial for microfluidic applications.
• Accurate modeling of UP-EHD flow dynamics, including electric potential, charge density, and electric field, is essential for optimizing pump performance.
• Existing analytical or numerical methods may face challenges in handling the complex interplay of parameters in UP-EHD systems.

Purpose of the Study:

• To develop and validate a robust computational model for analyzing unipolar electrohydrodynamic (UP-EHD) pump flow.
• To investigate the influence of key dimensionless parameters (electrical source number Es, electrical Reynolds number ReE, electrical slip number Esl) on UP-EHD pump behavior.
• To introduce a novel hybrid metaheuristic solver, ANN-SCA-SQP, for efficient and accurate interpretation of UP-EHD pump flow.

Main Methods:

• A mathematical model for UP-EHD pump flow was established, considering known electric potential at the emitter and zero at the collector.
• A hybrid metaheuristic solver, termed ANN-SCA-SQP, was designed by integrating an artificial neural network with the sine-cosine algorithm (SCA) and sequential quadratic programming (SQP).
• The solver was rigorously tested against reference solutions and executed for 100 independent experiments on a large dataset to evaluate its performance and convergence.

Main Results:

• The ANN-SCA-SQP solver demonstrated superior accuracy in modeling UP-EHD pump flow compared to existing methods.
• The study analyzed the impact of varying electrical source number (Es), electrical Reynolds number (ReE), and electrical slip number (Esl) on pump flow characteristics.
• Performance operators and convergence plots confirmed the efficiency and reliability of the developed hybrid solver.

Conclusions:

• The ANN-SCA-SQP method provides a highly effective approach for simulating and understanding unipolar electrohydrodynamic pump flows.
• This research contributes to the advancement of computational techniques for EHD applications, enabling better design and optimization of microfluidic devices.
• The findings highlight the importance of parameter analysis in tailoring UP-EHD pump performance for specific applications.