Simulating nucleation and short crack propagation using cellular automaton in gradient microstructures

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The proposed research is a continuation of previous discovery grants dedicated to the development of Cellular Automata (CA) methods applied to micromechanics. Thanks to this support, CA have been used to simulate cold creep / fatigue interactions in titanium alloys and localise stress distributions at the microstructural scale in polycrystals. In the present proposal, CA will be further develop to investigate crack initiation and propagation in material including microstructure gradients. This will help developing statistical based models for the fatigue life prediction of surface treated parts. CA, which are fully discrete, spatial-distributed, dynamical systems, serve as an alternative framework for mathematical descriptions and analysis of physical systems. Despite providing computational advantages, CA have not been extensively used in the framework of material science and mechanical engineering and the present candidate is a leader in this domain. The principal and long-term objective of the proposal is to developed CA models able to calculate the crack initiation and propagation from the stress and strain heterogeneities induced by surface treatment processes and applied loads, allowing the development of a statistical approach. Secondary objectives include further development of experimental techniques to calibrate and validate the developed models by documenting the adaptation of the microstructures during fatigue tests for various microstructures and alloys. Surface treatment such as machining, surface peening (hammer or shot), carburizing or induction hardening will be investigated as they are some of the surface treatments investigated by the candidate. Experimental validations will also be covered by the present proposal. The scale at which the measurements have required the development of original and precise techniques that are now available for further material investigation. The statistical results gathered by the CA models will be integrated to various microstructural-based model for fatigue life prediction.