In a significant stride for turbomachinery design, researchers have demonstrated the critical role of surface roughness in accurately predicting the performance of Francis turbines using computational fluid dynamics (CFD). The study, led by Thaithat Sudsuansee from Kalasin University’s Faculty of Engineering and Industrial Technology in Thailand, sheds light on how realistic modeling of wall roughness can significantly enhance the accuracy of CFD predictions, particularly at off-design conditions.
Francis turbines, a type of reaction turbine commonly used in hydroelectric power plants, operate under varying conditions. The study found that incorporating realistic surface roughness (ranging from 0.045 to 0.18 mm) was crucial for accurate performance prediction. Simulations achieved agreement within 1-2% of experimental measurements across rotational speeds from 400 to 1000 rpm. This level of accuracy is a game-changer for the maritime and energy sectors, where efficient turbine performance is paramount.
The research, published in the International Journal of Thermofluids (which translates to the International Journal of Heat and Fluid Flow), employed the Grid Convergence Index (GCI) methodology to quantify numerical uncertainty. The finest mesh achieved GCI values of 0.42% for power output, with hydraulic efficiency demonstrating grid independence. This means that the simulations were robust and reliable, providing a solid foundation for further studies and practical applications.
Sudsuansee and his team conducted steady-state Reynolds-Averaged Navier-Stokes simulations using the SST k-ω turbulence model and the Multiple Reference Frame approach. They found that the turbine’s operational characteristics varied significantly with speed. At 400 rpm, the turbine showed a flat efficiency profile (49-51%), indicating viscous-dominated flow. At 700 rpm, the efficiency peaked at 75.5%, showing transition behavior. At 1000 rpm, the turbine demonstrated broad high-efficiency operation (>80%), confirming design optimization.
The study also revealed detailed flow field analysis, showing progressive evolution of blade loading patterns and pressure differentials increasing from 90 kPa to 220 kPa across the speed range. Draft tube flow exhibited progression from stable columnar vortices at low speed to precessing vortex rope structures at high speed, with corresponding pressure recovery efficiency varying from 65% to 75%.
For maritime professionals, the implications are substantial. Accurate CFD predictions can lead to more efficient turbine designs, reducing energy costs and environmental impact. As Sudsuansee noted, “The validated numerical framework provides reliable performance prediction capabilities for Francis turbine design optimization and operational analysis.” This means that industries relying on hydroelectric power can expect more efficient and cost-effective solutions.
The study also highlights the importance of considering wall roughness in CFD simulations. As Sudsuansee explained, “Wall roughness modeling is essential for accurate turbomachinery CFD predictions, particularly at off-design conditions where boundary layer effects significantly influence overall performance.” This insight can guide engineers and designers in creating more precise and effective turbine models.
In summary, this research offers valuable insights into the performance of Francis turbines and the critical role of surface roughness in CFD predictions. For the maritime and energy sectors, the findings present opportunities for improved efficiency, cost savings, and environmental benefits. As the world continues to seek sustainable energy solutions, accurate and reliable turbine design becomes increasingly important, and this study is a significant step in that direction.