Hybrid CS–PSO Optimization for Performance Enhancement of Magnetohydrodynamic Pump
https://doi-001.org/1025/17610365587363
S. Naceur1,N. Akkari2, F.Z. Kadid3
1Electrical Engineering Department, University Kasdi Merbah; Ouargla, 30000, Algeria,
2Electrical and Electrical Engineering, Batna2 Department University Batna ,05000 Algeria, Laboratory of Electromagnetic Propulsion–Induction Systems (LSP-IE),
3L.E.B Laboratory Electrical Engineering Department, University of Mostefa Benboulaid Batna 2, 05000 Batna Algeria
Corresponding Author Email: naceursonia2@gmail.com
Received: 12/07/2025 ; Accepted: 04/10/2025
ABSTRACT
In electromagnetic fluid systems, where efficiency and structural weight are crucial design considerations, magnetohydrodynamic (MHD) pumps are widely used. In order to improve the performance of an electromagnetic conduction MHD pump, this work presents a hybrid optimization technique that combines cuckoo search (CS) with particle swarm optimization (PSO). The objective of the optimization is to increase electromagnetic and hydrodynamic efficiency while reducing the total mass of the pump, which includes the channel, coil, and ferromagnetic core. After optimization, COMSOL Multiphysics is used to evaluate the velocity fields and the Reynolds number of the fluid, while the finite volume approach is used to calculate the electromagnetic characteristics, such as the magnetic flux distribution and the induced current density and electromagnetic force. The hybrid algorithm performs better than standalone methods by combining the fast convergence of PSO with the global search power of CS. According to the simulation results, the revised design improves hydrodynamic performance and electromagnetic efficiency while reducing the pump’s mass. These results validate the effectiveness of hybrid metaheuristic methods for designing lightweight and high-performance MHD pumps
Keywords: Fluid mechanics, Cuckoo Search, COMSOL Multiphysics, Finite volume approach Reynolds number Magnetohydrodynamic pumps, Particle Swarm Optimization ,Velocity .
1. Introduction
The ability of magnetohydrodynamic (MHD) pumps to transport electrically conducting fluids without moving mechanical components has attracted increasing attention. These devices are widely employed in electromagnetic propulsion, liquid-metal energy systems, metallurgical processes, and nuclear reactor cooling. MHD pumps offer several advantages over traditional pumps, including higher reliability, silent operation, and reduced maintenance requirements. [1,2].
However, efficiency, thermal management, and structural weight remain major challenges for their practical application, significantly affecting both performance and adaptability.[3]
To achieve lightweight and high-efficiency designs, it is essential to optimize the electromagnetic and structural properties of MHD pumps, as highlighted in recent studies. Since MHD systems are multidimensional, strongly coupled, and nonlinear, traditional deterministic optimization methods are often inadequate.
Consequently, metaheuristic algorithms have emerged as powerful alternatives for addressing such complex engineering optimization problems. In particular, hybridization strategies that combine different metaheuristics have proven effective in balancing local exploitation and global exploration, thereby preventing premature convergence and enhancing the robustness of solutions.
The schematic of the MHD pump is shown in Figure 1. The basic principle involves applying an electric current across a channel filled with electrically conducting fluid, while a DC magnetic field orthogonal to the current is imposed via permanent magnets,.
This study focuses on optimizing the design of an electromagnetic conduction MHD pump using a hybrid optimization approach that combines Cuckoo Search (CS) and Particle Swarm Optimization (PSO). The proposed method aims to enhance flow stability and electromagnetic efficiency while reducing the overall pump mass, which includes the channel, coil, and ferromagnetic core. The finite volume method is employed to evaluate the electromagnetic properties of the optimized design, while COMSOL Multiphysics is used to compute the fluid velocity and Reynolds number . Under ideal conditions, this integrated framework provides an accurate and comprehensive assessment of the pump’s electromagnetic and fluidic behavior.
CONCLUSION
This paper is aimed at the conception by Optimization of the conduction magnetohydrodynamic pump. The optimization design procedure is applied successfully the hybrid Cuckoo Search–Particle Swarm Optimization (CS–PSO) This study demonstrates the effectiveness of the hybrid Cuckoo Search–Particle Swarm Optimization (CS–PSO) optimization to improve the performance of conduction magnetohydrodynamic (MHD) pumps. By applying the optimal design vector obtained by the hybrid algorithm, a two-dimensional numerical model was developed, allowing for an accurate evaluation of key parameters such as induced current density, magnetic field, and Lorentz forces fluid velocity, Reynolds number and the the relationship between the Reynolds number and the velocity in the conduction MHD pump.
The results show that optimization significantly improves all these parameters. These improvements lead to increased pumping efficiency, Overall, the hybrid CS–PSO approach proves to be a robust and effective tool for improving performance and optimizing the design of conduction MHD pumps, offering promising prospects for industrial applications
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| Nomenclature | ||||
| J | current density | L | characteristic length | |
| B | magnetic flux density | u | characteristic fluid velocity | |
| p | pressure of the fluid | Pbest | best position | |
| n | kinemactic viscosity of the fluid | Gbest | global best position | |
| F | electromagnetic force | α | stepwise | |
| ρ | fluid density | λ | Lévy distribution parameter | |
| μ | dynamic viscosity of the fluid | ⊗ | entry-wise multiplication | |