Evidence matrix for machine-learning surrogate modelling in vertical-axis wind turbine aerodynamics

Description

This dataset provides the study-level evidence matrix underlying the critical review “Machine-Learning Surrogate Modelling for Vertical-Axis Wind Turbine Aerodynamics: A Critical Review of Computational Fidelity, Optimisation, Uncertainty and Validation.” It contains metadata for 102 retained records classified into four evidence categories. Extended methodological appraisal is provided for the 42 direct wind-driven VAWT surrogate studies, including aerodynamic-data credibility, surrogate-validation rigour and independent optimisation verification.

Institutions

• University of Greater Manchester

  England, Bolton

Categories

Funders

• University of Greater Manchester

  England, Bolton

Licence