This study presents a CFD-based performance evaluation of a bulb turbine reconstructed from high-resolution 3D scanning of the prototype runner in Namgang hydropower plant. Multi ple scans acquired under controlled blade-pitch and phase conditions were processed to capture key geometric features, including leading/trailing edges, the anti-cavitation fin and tip-clearance regions. Based on these data, a reverse-engineered model satisfying the IEC 60193 geometric-similarity tolerance was generated and scaled to model dimensions. Steady RANS simulations were carried out for maximum, rated and minimum head conditions consistent with model test conditions. The predicted hydraulic efficiencies agreed with the test results within ±3%, reflecting the combined uncertainties associated with scanning, reconstruction and CFD modeling. The results demonstrate that prototype-based geometry acquisition significantly enhances prediction reliability and provides a robust modeling approach for performance assessment. The established workflow offers a practical basis for future studies on cavitation behavior, operating-point optimization and digital-twin development for hydropower turbines.
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Soo-Hwang Ahn
Jong-Woong Choi
Yong Cho
The KSFM Journal of Fluid Machinery
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Ahn et al. (Mon,) studied this question.
www.synapsesocial.com/papers/69df2a4be4eeef8a2a6af7d7 — DOI: https://doi.org/10.5293/kfma.2026.29.2.071
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