A computational and experimental study of flow-induced vibration and structural dynamics in topology-optimized redox flow battery channels

Jacer  Hamrouni; Leila  Abdelgader; Chafaa  Hamrouni

doi:10.59400/sv3944

A computational and experimental study of flow-induced vibration and structural dynamics in topology-optimized redox flow battery channels

Jacer Hamrouni
Advanced Fluid Dynamics, Energetics and Environment Laboratory, Department of Mechanical Engineering, National School of Engineers of Sfax, University of Sfax, Sfax 3039, Tunisia
Leila Abdelgader
Department of Computer Sciences, Taif University–Khurma University College, Al-Khurma 2935, Saudi Arabia
Chafaa Hamrouni
Department of Computer Sciences, Taif University–Khurma University College, Al-Khurma 2935, Saudi Arabia

Article ID: 3944

Keywords: topology optimization; flow-induced vibration; fluid-structure interaction; structural dynamics; computational fluid dynamics (CFD); redox flow battery design; dynamic stability analysis

Abstract

Unlike conventional flow field designs that prioritize electrochemical performance at the expense of mechanical reliability, the proposed framework uniquely embeds vibration control as a co-objective within the topology optimization process, demonstrating for the first time that mass transfer enhancement and flow-induced vibration suppression can be achieved simultaneously. This dual-objective innovation, validated by a 41% reduction in vibration velocity and a 23% improvement in reaction rate, establishes a new paradigm for integrating structural dynamics into electrochemical system design, directly addressing a critical gap in grid-scale energy storage reliability. This study introduces a vibration-aware topology optimization framework for the flow fields of vanadium redox flow batteries (VRFBs), targeting the mitigation of flow-induced vibration without compromising electrochemical performance. We demonstrate that optimized interdigitated flow fields fundamentally alter the fluid-structure interaction, suppressing the unsteady vortex shedding that drives mechanical excitation. Experimental validation on laboratory-scale prototypes confirms a 41% reduction in root-mean-square vibration velocity alongside a 23% improvement in electrochemical reaction rate. This work establishes a validated, CAE-driven pathway to embed vibration engineering into the earliest stages of electrochemical system design, addressing a critical gap in the development of reliable, next-generation renewable energy infrastructure.

Published

2026-04-16

How to Cite

Hamrouni, J., Abdelgader, L., & Hamrouni, C. (2026). A computational and experimental study of flow-induced vibration and structural dynamics in topology-optimized redox flow battery channels. Sound & Vibration, 60(2). https://doi.org/10.59400/sv3944

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Vol. 60 No. 2 (2026): in progress

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Article

This work is licensed under a Creative Commons Attribution 4.0 International License.

References

[1]Liu X, Yu H, Deng X, et al. Machine Learning–Guided Solvation Engineering of Chiral Viologens for Durable Neutral Aqueous Organic Flow Batteries. Angewandte Chemie International Edition. 2026; 65(7): e22442. doi: 10.1002/anie.202522442

[2]Reid MJ, Alexandersen J, ElSayed MSA. Influence of fluid flow models on the topology optimization of a passively cooled heatsink. Structural and Multidisciplinary Optimization. 2026; 69(1): 11. doi: 10.1007/s00158-025-04217-2

[3]Wang ML, Jin H, Zheng LJ, et al. Exploratory analysis of a liquid-cooled cold plate thermal management system using dual-objective topology optimization. International Communications in Heat and Mass Transfer. 2026; 172: 110315. doi: 10.1016/j.icheatmasstransfer.2025.110315

[4]Gadhewal R, Patnaikuni VS, Ananthula VV. Computational study on effect of geometric shape of flow channel and oscillatory gas supply on hot spot mitigation in PEM fuel cell with a 3D model of reconstructed gas diffusion layer. International Communications in Heat and Mass Transfer. 2026; 171: 110155. doi: 10.1016/j.icheatmasstransfer.2025.110155

[5]Jaiswal M, Rajanna MR, Islam MdR, et al. Weak wall boundary conditions for compressible flows. Engineering with Computers. 2026; 42(1): 16. doi: 10.1007/s00366-025-02232-x

[6]Janpetch N, Prasongdai N, Changpradit S, et al. Engineered flow fields for enhanced vanadium redox flow battery performance using topology optimization. Journal of Power Sources. 2026; 666: 239181. doi: 10.1016/j.jpowsour.2025.239181

[7]Zhang Q, Yi B, Liu R, et al. Topology optimization of porous electrodes for enhanced mass transport and electrochemical performance. Chemical Engineering Journal. 2026; 528: 172718. doi: 10.1016/j.cej.2026.172718

[8]Laermann P, Diamant H, Roichman Y, et al. Emergent signatures of the glass transition in colloidal suspensions. Nature Physics. 2026; 22(2): 265–274. doi: 10.1038/s41567-025-03140-z

[9]Ansari AF, Verma VK, Nivedita, et al. Thermal and magnetohydrodynamic analysis of micropolar fluid flow through an anisotropic porous channel with radiation and viscous dissipation. Physics of Fluids. 2026; 38(1): 013106. doi: 10.1063/5.0304087

[10]Zhang T, Wang Y, Li R. State-of-charge estimation for vanadium redox flow battery using a multi-head attention-based LSTM network. Journal of Energy Storage. 2026; 143: 119667. doi: 10.1016/j.est.2025.119667

[11]Liu H, Qi X, Shao X, et al. Design and performance study of a novel topology-optimized heat exchanger with sinusoidal waveform excitation. International Journal of Heat and Mass Transfer. 2026; 256: 128086. doi: 10.1016/j.ijheatmasstransfer.2025.128086

[12]Liu M, Lu L, Zhan J, et al. Layout optimization of compliant mechanism with embedded components using moving morphable component (MMC) method. Mechanism and Machine Theory. 2026; 219: 106301. doi: 10.1016/j.mechmachtheory.2025.106301

[13]Zhang RZ, Lu MY, Yang WW, et al. Performance evaluation of multiple-parallel-channel serpentine-like flow fields for vanadium redox flow battery: Simulation and experiment. Journal of Energy Storage. 2026; 150: 120513. doi: 10.1016/j.est.2026.120513

[14]Hamrouni J, Khatir Kabashi K, Hamrouni C, et al. Hybrid calculation-estimation modeling for flow field optimization: Enhancing efficiency of biomimetic vanadium redox flow batteries. Advances in Differential Equations and Control Processes. 2026; 33(1): 3793. doi: 10.59400/adecp3793

[15]Zhu YC, Wu SH, Xiong W, et al. Bayesian operational modal analysis considering environmental effect. Mechanical Systems and Signal Processing. 2025; 223: 111845. doi: 10.1016/j.ymssp.2024.111845

[16]Fan F, Tang S, Zhang D, et al. Characterization of high efficiency convective mass transfer for the proton exchange membrane fuel cell: Optimization of the flow field by imitating the spider web morphology. International Journal of Hydrogen Energy. 2025; 156: 150421. doi: 10.1016/j.ijhydene.2025.150421

[17]Calborean A, Máthé L, Bruj O. Phase Change Materials for Thermal Management in Lithium-Ion Battery Packs: A Review. Batteries. 2025; 11(12): 432. doi: 10.3390/batteries11120432

[18]Hu H, Han M, Liu J, et al. Strategies for improving the design of porous fiber felt electrodes for all-vanadium redox flow batteries from macro and micro perspectives. Energy & Environmental Science. 2025; 18(7): 3085–3119. doi: 10.1039/D4EE05556J

[19]Wang Q, Shan X, Liu H, et al. Mass transfer in micro-nano porous electrodes: A crucial role in optimizing vanadium redox flow battery performance. Journal of Colloid and Interface Science. 2026; 705: 139465. doi: 10.1016/j.jcis.2025.139465

[20]Yang WW, Bai XS, Zhang WY, et al. Numerical examination of the performance of a vanadium redox flow battery under variable operating strategies. Journal of Power Sources. 2020; 457: 228002. doi: 10.1016/j.jpowsour.2020.228002

[21]Liu X, Pan L, Rao H, et al. A review of transport properties of electrolytes in redox flow batteries. Future Batteries. 2025; 5: 100019. doi: 10.1016/j.fub.2024.100019

[22]Shoaib M, Vallayil P, Jaiswal N, et al. Advances in Redox Flow Batteries—A Comprehensive Review on Inorganic and Organic Electrolytes and Engineering Perspectives. Advanced Energy Materials. 2024; 14(32): 2400721. doi: 10.1002/aenm.202400721

[23]Guo Z, Ren J, Sun J, et al. A split convection-enhanced flow field for stack-scale redox flow batteries. Chemical Engineering Journal. 2025; 511: 161937. doi: 10.1016/j.cej.2025.161937

[24]Cheng Q, Li MJ, Wang RL, et al. Design and optimization of guide flow channel for vanadium redox flow battery based on the multi-field synergy. Journal of Power Sources. 2025; 650: 237526. doi: 10.1016/j.jpowsour.2025.237526

[25]Huang Z, Liu Y, Xie X, et al. Design and optimization of a novel flow field structure to improve the comprehensive performance of vanadium redox flow batteries. Journal of Power Sources. 2025; 640: 236736. doi: 10.1016/j.jpowsour.2025.236736

[26]Li X, Yuan C, Chen X, et al. Temperature-dependence of Zn deposition/stripping behavior in aqueous Zn-based flow batteries. Journal of Energy Chemistry. 2025; 107: 260–268. doi: 10.1016/j.jechem.2025.03.049

[27]Basavaraju SK, Chavati GB, Sannaobaiah MB, et al. Investigation of CeVO4-decoracated activated carbon-nanocomposite as a bifunctional electrode material for vanadium flow battery and supercapacitor applications. Composite Structures. 2025; 371: 119524. doi: 10.1016/j.compstruct.2025.119524

[28]Agyekum EB, Abdullah M, Odoi-Yorke F, et al. A state-of-the-art review of electrolyte systems for vanadium redox flow battery—Status of the technology, and future research directions. Energy Conversion and Management: X. 2025; 27: 101180. doi: 10.1016/j.ecmx.2025.101180

[29]Huang Z, Xuan L, Liu Y, et al. Numerical analysis of asymmetric biomimetic flow field structure design for vanadium redox flow battery. Future Batteries. 2025; 5: 100017. doi: 10.1016/j.fub.2024.100017

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