Speaker
Description
Cryogenic structural components, including collars, bladders, and keys for superconducting magnets, as well as elements for liquid hydrogen storage systems, are often fabricated from austenitic stainless steel (e.g., 316L) due to favorable mechanical properties and corrosion resistance. However, producing these complex geometries through traditional methods is challenging. Additive manufacturing presents a promising alternative, though the numerical understanding of material behavior under extreme cryogenic conditions remains limited. This study advances the numerical simulation of deformation-induced martensitic transformation (DIMT) in additively manufactured fused filament fabricated (FFF) 316L stainless steel. Central to this effort is the prediction of tensile behavior at temperatures ranging from ambient down to 4K. Supporting experiments—including tensile tests and microstructural characterization via scanning electron microscopy (SEM) and computed tomography (CT)—provide essential input parameters and validation data for the numerical framework.
The numerical modelling in this study is based on a nonlinear, temperature-dependent finite element approach incorporating a newly developed constitutive material law. This law couples a phase-kinetic description of the martensitic transformation with a mixed kinematic/isotropic plastic hardening formulation. By solving the underlying conservation laws and boundary conditions while considering temperature-dependent material parameters, the model provides a realistic representation of stress-strain states and evolving martensitic phase fractions across a wide range of thermal conditions. The implementation within a commercial finite element software relies on user-defined subroutines that integrate the constitutive relations and transformation kinetics. The simulations use adaptive time-stepping and iterative strategies to handle highly nonlinear, cryogenic loading scenarios efficiently. After parameter identification through experimental data, the numerical results are systematically compared with measured values from tensile tests and microstructural analyses. This iterative validation process continuously enhances the predictive capability of the model.
By merging advanced material-theoretical concepts with robust numerical methods, the presented framework offers deeper insight into the mechanical behavior of additively manufactured austenitic steels under extreme thermal conditions. Ultimately, it supports the targeted design and optimization of cryogenic lightweight components and contributes to the fundamental understanding of material modeling challenges in applied mechanics.
