Data-Driven Constitutive Model for the Inelastic Response of Metals: Application to 316H Steel

Abstract

Predictions of the mechanical response of structural elements are conditioned by the accuracy of constitutive models used at the engineering length-scale. In this regard, a prospect of mechanistic crystal-plasticity-based constitutive models is that they could be used for extrapolation beyond regimes in which they are calibrated. However, their use for assessing the performance of a component is computationally onerous. To address this limitation, a new approach is proposed whereby a surrogate constitutive model (SM) of the inelastic response of 316H steel is derived from a mechanistic crystal plasticity-based polycrystal model tracking the evolution of dislocation densities on all slip systems. The latter is used to generate a database of the expected plastic response and dislocation content evolution associated with several instances of creep loading.From the database, a SM is developed. It relies on the use of orthogonal polynomial regression to describe the evolution of the dislocation content. The SM is then validated against predictions of the dead load creep response given by the polycrystal model across a range of temperatures and stresses. When the SM is used to predict the response of 316H during complex non monotonic loading, extrapolating to new loading conditions, it is found that predictions compare particularly well against those from the physics based polycrystal model.

High-Temperature Creep Test Suite for Grizzly

“…The SM uses polynomial regression to fit an orthogonal basis of Legendre polynomials to the synthetic database generated by the CP model. Results using this SM are in close agreement to VPSC results [20 ]. Parameter ranges and values used for these simulations are given in Table 3 .…”

“…The SM is derived from a database of polycrystal simulations using the CP model in the VPSC framework, see Reference [20 ] for details. The synthetic database contains homogenized creep responses of Fe-Cr alloys for a range of inelastic strains, stresses, temperatures, and microstructures as reflected by the MX phase content and densities of wall ( ) and cell dislocations ( ).…”

Engineering-scale Modeling of High-Temperature Creep and Creep Crack Growth in Alloy 316H

“…However, it has been challenging to apply the outcomes of mesoscale simulations to models that can be practically applied at the engineering scale. The Los Alamos Reduced Order Models for Advanced Nuclear Constitutive Equations (LAROMance), developed by Los Alamos National Laboratory (LANL), address this need by employing data analytics to represent the viscoplastic behavior of representative volumes of a material predicted by sophisticated mesoscale models in a way that is usable in engineering-scale simulations [ 102 ]. This approach enables the effects of unique material processing conditions and environmental exposure to be directly accounted for, rather than relying on re-fitting of phenomenological models under the full range of possible conditions.…”