Statistically characterized and experimental validation based guidelines for the use of computational fluid dynamics for the prediction of performance in Francis turbines

• Development of cost-effective Computational Fluid Dynamics (CFD) evaluation methods. • Systematically evaluates the influence of important parameters on key turbine performance metrics (efficiency, torque, axial velocity, pressure pulsations). • Validates CFD predictions against experimental data and formulates practical guidelines to improve the reliability of Francis turbine performance assessment. • Support for sustainable small-scale hydropower innovation. Hydropower is a contributor to sustainable development. Innovation in hydraulic turbine design is often restricted by proprietary practices and high costs, particularly for small manufacturers. While large companies employ advanced computational fluid dynamics (CFD), laboratory and field validation to optimise turbine performance, smaller manufacturers are forced to use outdated designs that result in poor efficiency and site-specific operational problems. The lack of economically viable model testing and standardised CFD guidelines has created a need for accessible performance evaluation techniques. This study investigates CFD methodologies as a cost-effective alternative for small hydro turbine design, systematically analysing how various simulation parameters, such as mesh types, turbulence models, and flow regimes, affect operational metrics, including efficiency, torque, axial velocity, and pressure pulsations (FFT analysis). By comparing computational outcomes with experimental results, the research proposes practical guidelines to enhance predictive reliability and performance optimisation for the Francis turbines. The findings aim to facilitate the broader adoption of CFD-based approaches, enhance design practices among small manufacturers, and contribute to the development of affordable, clean energy solutions that align with the UN Sustainable Development Goals.