Cavitation control in Francis turbines by design optimization across variable operating conditions

Abstract

Cavitation is a critical challenge which significantly affects performance of hydro turbines leading to inefficient operation. Cavitation primarily arises due to improper design and frequent variations in operating conditions. Prediction or maintaining cavitation within controlled limits is crucial and challenging task in turbines yet it is essential for employing effective mitigation strategies to ensure the efficient and reliable operation of turbines. In this study, computational fluid dynamics (CFD) analysis of Francis turbine runner employed at DulHasti Power Station (DPS) was conducted using Ansys CFX for 3 different loading conditions (Underload, Full load and Over load) to identify and mitigate cavitation prone areas. Blade loading profiles were analysed to detect the sudden pressure drops responsible for manifesting cavitation and Elliptic Ratio, the key blade design parameter was optimized to control sudden pressure drops and enhance cavitation resistance of runner. The effectiveness of the modified design was validated using Thoma’s cavitation number to ensure improved resistance against cavitation. Our study concluded that the modified runner exhibited reduced cavitation intensity demonstrating the potential for improved operational reliability. This novel framework, optimizing the elliptic ratio of blade to mitigate cavitation, establishes a benchmark for cavitation control in Francis turbine and can be extended to other reaction turbines as well.