Integrated Computational Scheme for the Characterization Modeling and Prediction of Microstructure Evolution and Fatigue Response in Titanium Alloys

Project: Research project

Project Details


The growing demands in national security have raised great challenges in the development of advanced materials such as low-cost high fatigue-resistant titanium alloys. Here, the PI proposes a computational scheme that integrates (i) microstructure quantification via spatial correlation functions, (ii) physics-based modeling of structure evolution during manufacturing process, (iii) analysis of fatigue response via lattice-particle simulation, and (iv) reliability-based stochastic modeling (see Fig. 1) for modeling Ti alloys. Such a scheme will enable one to directly tie the processing parameters such as laser power density and annealing time to time-dependent fatigue response of the alloy and thus, the component life, via alloy microstructure quantification and modeling. Our project includes two major tasks: 1) Structure quantification and evolution modeling, which focuses on developing a novel quantification scheme for alloy microstructures using the minimal set of spatial correlation functions that capture the salient geometrical and topological features of the materials phases. Quantitative analysis of microstructure evolution based on experimental data, with the aid of physics-based models (e.g., phase-field modeling), will be used to establish quantitative relations between the processing parameters (e.g., laser power density, annealing time) and time-dependent correlation functions that characterize the structural evolution. 2) Fatigue analysis and reliability-based stochastic optimization, which focuses on establishing quantitative relations between processing conditions and fatigue response of the alloy. First, a novel lattice-particle simulation method will be employed for the arbitrary fatigue damage initiation, accumulation and propagation in a heterogeneous alloy. Then, a reliability-based stochastic framework is proposed for establishing the processingstructure- performance relationship under uncertainties.
Effective start/end date9/9/149/8/17


  • DOD: Defense Advanced Research Projects Agency (DARPA): $466,990.00

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