Simulation-driven Electrical Impedance Tomography for buoyancy-driven electrolyte mixing: A hybrid hydrodynamic–circuit modeling framework

Journal
Measurement  
Volume
261
Article Number
119745
Citation
Measurement 261: 119745 (2026)
Publisher DOI
10.1016/j.measurement.2025.119745
Publisher
Elsevier BV
Is Supplemented By
10.15480/882.16259
We present a modular, end-to-end simulation benchmark for Electrical Impedance Tomography (EIT) in chemical reactor monitoring. The goal is to enable controlled and repeatable evaluation of EIT reconstruction methods in a realistic, physics-based setting. The framework integrates the full pipeline—from hydrodynamic transport and electrochemical modeling to hardware emulation and image reconstruction. For this purpose, aqueous HCl mixing is modeled using Stokes–Boussinesq flow coupled with advection–diffusion; local conductivity is computed via the Debye–Hückel–Onsager approximation and mapped to resistor networks simulated in SPICE with a 32-electrode EIT analog front-end. Boundary voltages are generated and processed using the Complete Electrode Model (CEM) in EIDORS and reconstructed with NOSER and Total Variation (TV). The modular design enables independent refinement of each module for task-specific front-ends and reconstructions. A comparison of FEM/CEM and SPICE simulations under matched hardware configurations shows close agreement in voltage measurements, validating circuit translation. For homogeneous measurements, simulated voltages were further validated against data from a self-built EIT device, confirming consistency across both simulation paths. Moreover, by modifying hardware-specific parameters in SPICE, we demonstrate how design choices influence measurement behavior, supporting targeted front-end optimization. This simulative benchmark thus provides a validated, reusable testbed for studying physics–algorithm–hardware interactions and for standardized, quantitative evaluation of EIT methods in reactor-relevant settings. It integrates electrical modeling, reconstruction algorithms, and engineering aspects into a coherent cross-domain framework that highlights how modeling and reconstruction choices shape interpretation across applications.
DDC Class
600: Technology