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Abstract Distortion in laser-based additive manufacturing (LBAM) is a critical issue that adversely affects the geometric integrity of additively manufactured parts and generally exhibits a complicated dependence on the underlying material. The differences in properties between distinct materials prevent the immediate application of a distortion model learned for one material to another, which introduces the challenge in LBAM of learning a distortion model for a new material system given past experiments. Current methods for investigating the distortion of different material systems typically involve finite element analysis or a large number of experiments in an empirical study. However, these methods do not learn from previous experiments and can incur significant costs in terms of computation, time, or resources. We propose a Bayesian model transfer methodology that is both physics-based and data-driven to leverage past experiments on previously studied material systems for more efficient distortion modeling of new systems. This method transfers distortion models across distinct materials based on the statistical effect equivalence framework by formulating the differences between two materials as a lurking variable. Our method reduces the experimentation and effort needed for specifying distortion models for new material systems. We validate our methodology in a case study of distortion model transfer from Ti–6Al–4V disks to 316L stainless steel disks. This case study is the first instance of model transfer between material systems and illustrates the ability of the Bayesian model transfer methodology to address the issue of comprehensive distortion modeling across varying material systems in LBAM. 

The multiplication of dislocations determines the trajectories of microstructure evolution during plastic deformation. It has been recognized that the dislocation storage and the deformation-driven subgrain formation are correlated—the principle of similitude, where the dislocation density (ρ i ) scales self-similarly with the subgrain size (δ): $\delta \sqrt {{\rho _{\rm{i}}}}$ ∼ constant. Here, the robustness of this concept in Cu is probed utilizing large strain machining across a swathe of severe shear deformation conditions—strains in the range 1–10 and strain-rates 10–10 3 /s. Deformation strain, strain-rate, and temperature characterizations are juxtaposed with electron microscopy, and dislocation densities are measured by quantification of broadening of X-ray diffraction peaks of crystallographic planes. We parameterize the variation of dislocation density as a function of strain and a rate parameter R , a function of strain-rate, temperature, and material constants. We confirm the preservation of similitude between dislocation density and the subgrain structure across orders-of-magnitude of thermomechanical conditions.