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The elasto-plastic material behavior, material strength and failure modes ofmetals fabricated by additive manufacturing technologies are significantlydetermined by the underlying process-specific microstructure evolution. In thiswork a novel physics-based and data-supported phenomenological microstructuremodel for Ti-6Al-4V is proposed that is suitable for the part-scale simulationof selective laser melting processes. The model predicts spatially homogenizedphase fractions of the most relevant microstructural species, namely the stable$\beta$-phase, the stable $\alpha_{\text{s}}$-phase as well as the metastableMartensite $\alpha_{\text{m}}$-phase, in a physically consistent manner. Inparticular, the modeled microstructure evolution, in form of diffusion-basedand non-diffusional transformations, is a pure consequence of energy andmobility competitions among the different species, without the need forheuristic transformation criteria as often applied in existing models. Themathematically consistent formulation of the evolution equations in rate formrenders the model suitable for the practically relevant scenario oftemperature- or time-dependent diffusion coefficients, arbitrary temperatureprofiles, and multiple coexisting phases. Due to its physically motivatedfoundation, the proposed model requires only a minimal number of freeparameters, which are determined in an inverse identification processconsidering a broad experimental data basis in form of time-temperaturetransformation diagrams. Subsequently, the predictive ability of the model isdemonstrated by means of continuous cooling transformation diagrams, showingthat experimentally observed characteristics such as critical cooling ratesemerge naturally from the proposed microstructure model, instead of beingenforced as heuristic transformation criteria.

A Novel Physics-Based and Data-Supported Microstructure Model for Part-Scale Simulation of Laser Powder Bed Fusion of Ti-6Al-4V