High combustion temperatures are required in gas-turbine engines to achieve high cycle efficiencies. With increasing temperature, however, the life span of the turbine components are reduced. The ability to accurately predict engine component temperature as a function of combustion temperature is required to strike this balance correctly. An experimental heat transfer measurement technique is developed in this thesis, which builds on a large body of existing literature. The technique enables a detailed quantification of turbine heat transfer on test rigs which closely represent gas-turbine engine configurations. Fundamental improvements are made to existing methods, in the definition of the ‘semi- infinite limit’ for transient measurement techniques, in Infra-red camera calibration, and in thermal effusivity measurement. The improvements were developed from first principles, verified experimentally, and have been used on a world leading heat transfer rig (the FACTOR combustor-turbine interaction rig, run on the NG-Turb facility at DLR Göttingen). It was found that optimisation of a number of measurement parameters was required to minimise the measurement uncertainty. It is shown that the optimum measurement parameters are dependant, and sensitive to the specific configuration of the test rig. An experimental procedure was developed and tested, which has been ‘tuned’ for measurements on the FACTOR test rig. Despite the challenging measurement environment on the FACTOR rig, it was found that state-of-the-art heat transfer measurement uncertainties of approximately 5%, could nevertheless still be achieved, by using the new methods. General principles and rules are established which can be used to guide the design of future heat transfer measurements, with the aim of minimising measurement uncertainty.
| Identifer | oai:union.ndltd.org:bl.uk/oai:ethos.bl.uk:744728 |
| Date | January 2018 |
| Creators | Playford, William |
| Contributors | Atkins, Nick |
| Publisher | University of Cambridge |
| Source Sets | Ethos UK |
| Detected Language | English |
| Type | Electronic Thesis or Dissertation |
| Source | https://www.repository.cam.ac.uk/handle/1810/274997 |
Page generated in 0.0016 seconds