Surrogate Modeling of Viscoplasticity in Steels: Application to Thermal, Irradiation Creep and Transient Loading in HT-9
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https://doi.org/10.1007/s11837-020-04402-2
Ó 2020 This is a U.S. government work and not under copyright protection in the U.S.; foreign copyright protection may apply AUGMENTING PHYSICS-BASED MODELS IN ICME WITH MACHINE LEARNING AND UNCERTAINTY QUANTIFICATION
Surrogate Modeling of Viscoplasticity in Steels: Application to Thermal, Irradiation Creep and Transient Loading in HT-9 Cladding AARON E. TALLMAN ,1,2 M. ARUL KUMAR,1 CHRISTOPHER MATTHEWS,1 and LAURENT CAPOLUNGO1 1.—Materials Science and Technology Division, Los Alamos Laboratory, Los Alamos, NM, USA. 2.—e-mail: [email protected]
National
The use of structural metals in extreme environments relies both on the characterization of the mechanical response and microstructure changes in service and on modeling predictions. Data scarcity creates a need for predictive constitutive models that can be used in regimes outside calibration domains. While crystal plasticity models can be applied to non-monotonic loads and complex environments, their computational cost typically prohibits use at the level of an engineering structure. As an alternative, the present study introduces a surrogate constitutive model derived from crystal-plasticity predictions of the mechanical response of HT9 subjected to irradiation, stresses and temperatures. The surrogate law is then tested in the cases of uniaxial straining, stress cycling, thermal cycling and thermal ramping. Finally, using this constitutive relationship, finite element simulations of a pressurized tube subjected to a stress and thermal transients are performed and analyzed.
INTRODUCTION The use of metals under extreme environments (e.g., nuclear), for which testing is necessarily limited/complex, stresses the need for engineeringscale models that predict the mechanical response and microstructure evolution of materials in conditions largely departing from those under which a constitutive model can be fully calibrated. For example, in many of the advanced nuclear reactors currently being developed,1 accident scenarios involving cladding failure generally result from high temperature excursions,2–5 heightened chemical attacks via fuel-cladding chemical interaction6 or corrosion.7,8 Such accident scenario initiators are difficult to reproduce in a laboratory environment, and the number of tests simultaneously subjecting samples to temperature, multi-axial stresses and irradiation is limited by cost and time. Consequently, constitutive models are relied upon to predict cladding strain evolution.9 The accuracy of
(Received July 10, 2020; accepted September 22, 2020)
these models is exceedingly important; underestimations in cladding strain would lead to designs promoting premature cladding failure, while overestimations result in increased safety margins and decreased reactor profitability. Given the complex environment the cladding material is subjected to, i.e., temperature, stress, irradiation dose, dose rates and data scarcity (i.e., irradiated samples), a simple empirical model fit to the experimental data w
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