Phd in ENERGY AND ENVIRONMENT

Thesis title: Analysis of the Water Injection Process in Industrial Gas Turbines Axial Compressor

In this work, the water injection process in the AXial COmpressor (AXCO) of industrial Gas Turbines (GT) has been analyzed to identify the benefits on the GT operation and the associated risks for GT and AXCO mechanical integrity. Water injection is a technique in which a flow of water is injected and dispersed at the suction of industrial Gas Turbines. This technique has been largely used either for washing purposes or to improve GT output power in specific conditions. In the water washing application, the water injection allows to recover the performance losses due to fouling of the GT internals, while in the power augmentation application, water injection is used to increase GT power output. Although the water injection has shown to be effective in both applications, site experiences demonstrated that it could yield to components erosion with most of the damages detected in the Leading Edge section of the AXCO first stage rotor blades. Since the control and reduction of performance detriment due to AXCO fouling is of paramount importance for an industrial GT operation, the present work is focused on the water washing application; however, some of the results could be extended also to power augmentation application. Through the analyses of the present work, the leading design parameters of the water injection system have been identified to provide a design guideline for the optimized design and optimized operation of the water washing devices. The effects of the water washing have also been assessed in terms of carbon footprint reduction of a typical industrial GT. To identify the effects of the water injection on the GT AXCO, a dedicated Water Droplets Erosion (WDE) model has been developed and assessed against the available models. The WDE has been developed considering the effects of a wide range of droplets diameters combined with the introduction of specific materials properties characterized through a dedicated experimental campaign. The model demonstrated a clear improvement compared to the models available in literature, improving the main limitations related to the droplets dimeters and blades material selection. The novel WDE has shown consistency with experimental results when considering a wide range of droplets diameters and when considering specific GT AXCO material characteristics. To reduce the number of variables to be considered in the performance and design space definition, a sensitivity analysis on the WDE leading parameters has been performed on simplified GT geometries through means of CFD simulations. The results highlighted the role of the injection time and of the angle and velocity of injection as the parameters with larger effect on the washing efficiency. The injection location and the droplet size distribution seem to be the leading parameters to control the water droplets distribution on the AXCO blade. Based on the results of the sensitivity analyses, the novel WDE has been applied on a real case where the complete geometry of a real GT has been considered form the inlet plenum up to the outlet of the first AXCO rotor. The results of CFD analyses coupled with the new WDE have been compared with field data and the shop analyses of a GT subjected to several water washing cycles. The comparison of the numerical results with the experimental field data has shown good qualitative agreement, with the ability of highlight the impact regions and of predicting the overall component erosion. Based on the design and operations space highlighted through the simplified geometry analyses and based on the experimental verification of the model, a complete mapping of the water washing design and operation has been created. This mapping is currently being used to create a design tool for the design optimization of the water washing devices and a monitoring and diagnostic analytic to provide indications on the optimum settings of the water washing during operation. This analytic, will be able to provide real time guidance on the optimum water washing cycles, predicting GT efficiency recovery, highlighting mechanical integrity risks and, thanks to the LCA analyses and mapping, providing information on the resulting carbon footprint of the GT.