Due to the change of the energy sector (wind, solar...) in recent years, the hydroelectric power plant must expand the operating range which is far from the Best Efficiency Point condition in order to regularize and stabilize the electrical grid. These expanded operating conditions increase the fatigue damage on the runner due to higher dynamic strain/stress fluctuation. To estimate the damage, it is imperative to have the stress levels over all the different operating conditions. However, this information is not available, hence an interpolation model, which allows estimations with sufficient accuracy of cyclic stress levels at a given operating condition, is needed. In analyzing of runner fatigue, strain measurements by gauges plays an essential role. However, due to the high cost and time constraint, these experimental measurements can only cover certain points, with finite number, on the possible range of turbine operating conditions. Therefore, this thesis concentrates on the development of prediction tools for the strain/stress covering every possible operating condition. A mathematical process based on the kriging methods is developed, which allows the interpolations and then the reconstructions of stress/strain signals at non-measured operating conditions using the measured ones. The experimental signal is pre-processed and transformed into different forms (e.g., stochastic process or components involved in the signal...) for adapting to each interpolation strategy. The developed interpolations are validated by cases studies from the industrial application. This thesis contributes to response to an actual industry need of the hydraulic turbine designer and operator for the reduction of experimental measurement or numerical simulation costs, and for a better estimation of residual lifetime.
| Date | 10 Jan 2022 |
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| Original language | French |
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| Awarding Institution | - École de technologie supérieure
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| Supervisor | Antoine Tahan (Supervisor) & Jérôme Antoni (Supervisor) |
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Pham, Q. H. (Author),
Tahan (Supervisor) & Antoni (Supervisor),
10 Jan 2022Student thesis: Doctoral thesis › Doctorate in Engineering: Engineering