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Toward a numerical predictive method based on fatigue analysis for droplet impingement erosion

Abstract : The goal of this work is the comprehension and the numerical simulation of erosion caused by repeated droplet impact on Pelton turbine buckets, to predict the lifetime of these components. First, waves propagation phenomenon inside fluid and solid domains are presented, which allows determining the time evolution and spatial distribution of contact pressure, and the birth of lateral microjets by supersonic ejection of the fluid on the contact. Experimental studies of erosion by droplet impact highlight a fatigue cracking-based erosion mechanism. Then, coupled FSI computation are performed. The solid subdomain is discretized by the Finite Element Method (FEM), and the fluid subdomain by the Smoothed Particle Hydrodynamics (SPH), which is a particle method (meshless) effectively recommended for large distortions and free surface tracking. Stress analysis confirms the cyclic nature of the damage mechanism, and erosion simulation is performed using multiaxial fatigue criteria. The first selected criterion is a general one from the American Society of Mechanical Engineers (ASME) using principal values of stress differences over time. The second one is the Dang van 2 criterion, belonging to the family of critical plane criteria. This criterion considers separately the effects due to hydrostatic stress on one hand, and the ones induced by maximum local shear on the other. These two criteria are used to building the equivalent eroded zones of the solid subdomain for a given number of impacts, which allows to qualify this procedure as a predictive predictive. Finally, a parametric study for different droplet sizes and velocites is computed, and the effects of a coating layer are investigated.
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  • HAL Id : tel-02063381, version 1

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Guillaume Coudouel. Toward a numerical predictive method based on fatigue analysis for droplet impingement erosion. Fluids mechanics [physics.class-ph]. Université de Lyon, 2017. English. ⟨NNT : 2017LYSEI101⟩. ⟨tel-02063381⟩

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