Hydropower has stood as a clean and sustainable energy source since the late 19th century. Many turbines were built 50 to 70 years ago and require refurbishment. It is important to assess the efficiency of turbines before and after refurbishment to meet performance guarantees .However, the flow rate makes such estimation challenging. Moreover, determining the volumetric flow rate is crucial to specify the hydraulic performance characteristics of hydraulic turbines. The pressure-time method allows measuring the flow rate in hydraulic turbines, according to the IEC 60041 standard, based on transforming momentum into pressure during the deceleration of a liquid mass. The flow rate is obtained by integrating the differential pressure and the pressure loss history between two cross-sections.

This method assumes a one-dimensional flow (1D) and is limited to straight pipes with a uniform cross-section and specific restrictions on length (L>10 m), velocity (U.L>50 m2s-1) and distance between the measurement sections from any irregularities in the pipeline. However, challenges arise when applying this method in low-head hydropower plants due to the short lengths, irregularities like bends, variation in cross section and developing flows in the intake. This thesis aims to improve the performance of the method out of IEC standards for conditions similar to low-head conditions.

The thesis is divided into the numerical simulation of the fluid during the pressure-time method transient, experimental measurement, and a combination of both. The physics in the pressure-time method is studied to compare different assumptions to estimate the viscous losses for both developed and developing flow. Moreover, a test rig has been developed to extend the method’s applicability. The test rig is designed to study the pressure-time method for developing flow conditions, small measurement lengths, variable cross-section and the presence of bend close to measurement sections, which could be similar to low-head turbine conditions.

Finally, the data are evaluated using the new approach combining the 1D pressure-time method and three-dimensional computational fluid dynamics (3D CFD).