Numerical and experimental investigation of erosive wear in Francis runner blade optimized for sediment laden hydropower projects in Nepal

Abstract

The design of the Francis turbine aims to maximize its performance in terms of efficiency. This design approach has overlooked effects on the turbine due to sediment erosion for power plants operating under high sediment load. In this paper, a multi-objective design procedure to develop a Francis turbine runner for maximizing efficiency, as well as minimizing sediment erosion is discussed. Parameterized runner designs obtained from the design algorithm are implemented in the Design of Experiment (DOE) to get sample runners. These sample runners are investigated using a commercial CFD tool and validating with an experiment in a model turbine test rig to obtain efficiency and sediment erosion data. Subsequently, a Multi-Objective Genetic Algorithm (MOGA) is implemented to generate the optimized runner blades. Two different optimized runners are selected after the optimization. The optimized runner generated from this technique is further investigated experimentally in the laboratory scale sediment erosion test rig. From both numerical and experimental results, it is found that the optimized runner blade has improved erosion handling capability. Implementation of the procedure discussed in this article can be a crucial step for designing the turbines which are vulnerable to sediment erosion.

Numerical and experimental investigation of erosive wear in Francis runner blade optimized for sediment laden hydropower projects in Nepal