Leading edge protection (LEP) coating systems are applied to protect turbine blade edges from rain erosion. The performance of a LEP system is assessed in an accelerated rain erosion test (RET) as a metric for industrial application, but these tests are expensive. Modelling methods are available to predict erosion, based on fundamental material properties, but there is a lack of validation. The Springer model (1976) is analysed in this work to assess it as a tool for using material fundamental properties to predict the time to failure in a rain erosion test. It has been applied, referenced and industry validated with important partial considerations. The method has been applied successfully for erosion damage by wear performance prediction when combined with prior material data from rain erosion test (RET), instead of obtaining it directly from fundamental properties measured separately as Springer proposed. The method also offers accurate predictions when coupled with modified numerical parameters obtained from experimental RET testing data. This research aims to understand the differences between the experimental data used by Springer and the current industry approach to rain erosion testing, and to determine how it may introduce inaccuracies into lifetime predictions of current LEP systems, since they are very different to those tested in the historic modelling validation. In this work, a review of the modelling is presented, allowing for the understanding of key issues of its computational implementation and the required experimental material characterisation. Modelling results are discussed for different original application issues and industry-related LEP configuration cases, offering the reader to interpret the limits of the performance prediction when considering the variation in material fundamental properties involved.

Achieving European climate neutrality by 2050 requires further efforts not only from the industry and society, but also from policymakers. The use of high-efficiency cogeneration facilities will help to reduce both primary energy consumption and CO₂ emissions because of the increase in overall efficiency. Fuel cell-based cogeneration technologies are relevant solutions to these points for small- and microscale units. In this research, an innovative and new fuel cell-based cogeneration plant is studied, and its performance is compared with other cogeneration technologies to evaluate the potential reduction degree in energy consumption and CO₂ emissions. Four energy consumption profile datasets have been generated from real consumption data of different dwellings located in the Mediterranean coast of Spain to perform numerical simulations in different energy scenarios according to the fuel used in the cogeneration. Results show that the fuel cell-based cogeneration systems reduce primary energy consumption and CO₂ emissions in buildings, to a degree that depends on the heat-to-power ratio of the consumer. Primary energy consumption varies from 40% to 90% of the original primary energy consumption, when hydrogen is produced from natural gas reforming process, and from 5% to 40% of the original primary energy consumption if the cogeneration is fueled with hydrogen obtained from renewable energy sources. Similar reduction degrees are achieved in CO₂ emissions.