On the dynamic response of additively manufactured 316L stainless steel and the development of an orthotropic Johnson-Cook viscoplastic strength model
Keywords: stainless steel
additive manufacturing
constitutive modelling
high strain-rate
viscoplasticity
dynamic response
orthotropic
finite element analysis
Johnson-Cook

Materials produced using additive manufacturing (AM) techniques are becoming evermore prevalent within industry, especially where complex designs render conventional manufacturing (CM) norms economically impractical. Understanding the mechanical response of these novel materials to loads encountered during their lifetimes will allow for improved material selection and performance optimisation through microstructural design. A more detailed knowledge of the nascence and evolution of failure will also allow for an increased awareness of safety margins facilitating further optimisation of component design, especially where the AM microstructure significantly deviates from traditional CM equivalents.
The mechanical response of AM materials to quasi-static loading and fatigue are already the subject of significant academic study, however currently there is a relative lack of research focused on the high strain rate mechanical behaviour (both constitutive response and failure mechanisms). This dearth of research is especially prevalent at strain rates exceeding 1000 /s likely due to the increased experimental complexity. As such, how AM components behave under such extreme conditions is poorly understood.
This thesis focuses on the mechanical response at strain rates ranging from 1E2 /s to 1E8 /s of AM 316L stainless steel, a corrosion resistant austenitic steel alloy widely used throughout engineering. It establishes links between observed material characteristics in AM samples, notably the spatial distribution of porosity defects, and both their dynamic response and failure modes with comparison against widely available CM equivalents. Precision impact testing to interrogate dynamic behaviour was achieved through means of reverse Taylor impact and plate impact spallation testing. This testing was undertaken on two distinct batches of AM 316L stainless steel, one possessing porosity just above 1 % on average, and a second with a porosity two orders of magnitude less, both were compared to CM equivalents for context. Reverse Taylor impacts revealed not only the role of oriented, layered, porosity defects in the dispersion of localised stress fronts, but also their role in varying the directional constitutive strength at high strain rates when compared to both the behaviour of dense AM material and also the CM counterparts. Spallation testing on porous AM highlighted a radically atypical and potentially directional tensile failure response at high strain rates. In comparison dense AM samples showed a typical pull-back response and a directional variance in the high strain rate tensile strength across loading directions, with intralayer mechanical performance exceeding interlayer responses in agreement with similar testing available within literature.
Augmenting experimental work, an associative non-tabulated orthotropic constitutive strength model combining the widely used Johnson-Cook strength model with a numerical routine harnessing abstract deviatoric stress eigenspaces to improve computational efficiency was developed. This model seeks to address limitations of already implemented alternatives that either offer limited capabilities, or require complex parametrisation workflows that limit widespread adoption. Following conception, the model was implemented as a custom user-material into the commercial finite element package LS-DYNA, where it successfully recreated observed experimental responses. This achievement showcased the improvement to predictive capabilities for independently orthotropic strain, strain rate and temperature sensitive material responses, reducing the need going forward for large scale high strain rate component level testing of as-built AM material, a known challenge facing industry. The developed constitutive model sees direct applicability to as-built powder-bed AM material and also to the wider field of dynamic material behaviour modelling.
Applying the developed constitutive model, digital twins of experiments were created and optimised to experimental behaviour from two distinct batches of AM material, each with differing defect distributions, using machine learning techniques. The optimised model parameters offer insight into the role of layered porosity in the dynamic behaviour in AM materials, revealing that porosity not only reduces specific strength closer to that seen in CM equivalents, but also exacerbates the microstructural orthotropy present within the dense as-built material. These results underline the need for consistent defect-free AM as a baseline capability, and show the potential to leverage defect distributions in deliberately altering the dynamic response and failure modes of AM components.