The validation of life predictions of gas turbine engines is usually based on an engine test where the temperature response is measured during a representative mission cycle. A thermal model of the test engine is developed which is then validated by the measured temperature data to within certain datamatch acceptance criteria (steady state and transient) which will provide acceptably accurate predictions of creep life and low-cycle fatigue (LCF). Once the thermal model has been validated, the predicted temperature data are used as boundary conditions for the mechanical (stress) model. This allows the prediction of the fatigue life due to LCF and due to creep. Since it is often almost impossible to validate the mechanical (stress) model by reliable means, it is of great importance to validate the thermal model to within the greatest accuracy possible. Therefore, the tolerances to within which the thermal model is validated has a direct effect on the quality of the predicted life and hence engine reliability. This paper describes the development and implementation of datamatch acceptance criteria (DMAC) for the validation of a thermal model against measured data. The validated thermal model then forms the basis for reliable predictions of the component’s life in terms of LCF and creep. The datamatch acceptance criteria take into account spatial variations of the life-temperature sensitivity as different areas of the rotor are exposed to different temperature gradients and levels. In the following, both life-limiting mechanisms, LCF and creep, will be considered individually. This will result in different datamatch acceptance criteria for steady state and transient conditions, the former relating to creep life and the latter to LCF. The quality of the datamatch is then assessed in terms of a colour code (green/yellow/red) where the various colours represents different levels of acceptance for the thermal model.

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