Electrochemical Machining Multiphysics Model-Fidelity Validation: Data and Reproducible Code

This dataset provides experimental data, numerical models, simulation results, and reproducible source code supporting the study of validation-driven multiphysics model-fidelity selection for electrochemical machining (ECM) under uncertainty. The dataset includes: Experimental measurements transcribed and digitized from W. G. Clark's 1974 doctoral research on electrochemical machining. A hierarchy of one-dimensional ECM models (M0, M0g, M1, and M2) incorporating electrical, thermal, and gas-evolution effects. Model calibration, uncertainty quantification, sensitivity analysis, and Monte Carlo simulation results. Statistical model-adequacy assessments and virtual validation experiments for determining the minimum sufficient level of model fidelity. Operating-regime maps, generalization analyses, and robustness studies examining the influence of uncertain parameters and model assumptions. Two-dimensional ANSYS Fluent simulations, equilibrium-profile results, numerical verification, and grid-convergence analysis. Python source code, ANSYS Workbench scripts, Fluent user-defined functions (UDFs), and supporting documentation. The dataset supports reproducibility, independent verification, and further development of uncertainty-aware multiphysics modeling approaches for electrochemical machining. The experimental source is W. G. Clark's doctoral thesis, University of Strathclyde (1974). The original thesis is not redistributed. Version: 1.0.2 Licensing: Data and documentation are distributed under Creative Commons Attribution 4.0 International (CC BY 4.0). Source code is distributed under the MIT License. The corresponding license files and attribution requirements are included in the archive.