Increasing turbine life through novel blade coating

Jet engine

Industry experts and leading academics across the country utilised high performance computing at Loughborough University to model turbine component degradation and discover novel coating solutions to extend its service life.


Gas turbine engines are widely used in industrial power generation and will continue to be a significant part of the UK energy portfolio for the foreseeable future. Demands placed on these engines are changing, including the requirement to cycle more frequently, to utilise increasingly variable fuels, and to operate with increased efficiencies to reduce emissions.

These engines require materials which can withstand high temperatures and aggressive operative environments which can cause oxidation and corrosion. Nickel-based superalloys are employed for turbine blades, but increasingly rely on the performance of coating systems for high temperature degradation protection. However, the movement of elements between the coating and the superalloys can affect the blade’s usable service life, making it essential to optimise the choice of coating to best suit the operative conditions.


Inspection of power plant components is extremely costly but it is crucial for plant operators to know when a particular component needs to be replaced. This project, involving over a dozen academic and industry partner organisations, simultaneously modelled and experimentally characterised the environmental degradation of selected coated turbine blade systems in order to improve life prediction and failure assessment methods.

Access to high performance computing and the experts at Loughborough University has enabled the team to develop a novel kinetic model to predict the microstructure of a coated blade system as a function of composition, time and service temperature as well as develop novel coatings aimed at increasing service lifetimes. The complex model has been validated by experimental quantification using a range of advanced analytical techniques made possible through HPC.


The predictive techniques and data generated are already being used to aid design, quantify operational risks, and improve component inspection, repair and replacement in operational environments. In addition, novel compositions of single and multi-layer coatings are in the advanced stages of testing and are likely to deliver industrial benefits in the future.

Acknowledgement: We also acknowledge the valuable contributions made to the project by these additional organisations: Praxair Surface Technologies, QinetiQ, Doosan Power, Rolls Royce, University of Bristol, Cranfield University and University of Nottingham.