Evaluating and modeling rate sensitivity in advanced reactor structural materials: 316H, Gr. 91, and A617

摘要

Advanced reactor systems operate at high temperatures to achieve better thermal efficiency. During transients from lower temperatures to high operating temperatures structural metals transition from rate insensitive behavior to rate dependent behavior. In the rate dependent regime creep and plastic deformation are not separable hence requiring a unified treatment with a viscoplastic model. Several bounding design methods in the ASME Boiler and Pressure Vessel Code, Section III, Division 5, Subsection HB, Subpart B assume a decoupled treatment of creep and plasticity so establishing the boundary of the rate insensitive regimes for advanced reactor structural materials is necessary to set limits for the use of these bounding design methods. In the rate sensitive regime new bounding methods or fully inelastic analysis are required for the design of Division 5 Class A components. During temperature transients these components may operate in both the rate insensitive and rate sensitive regions, requiring computational models that can represent both types of behavior. This work establishes criteria for material rate sensitivity and develops a new composite method for modeling constitutive response in both the rate sensitive and rate insensitive regimes for three Division 5, Class A materials: 316H austenitic stainless steel, Grade 91 ferritic-martensitic steel, and Alloy 617, a nickel-based alloy. Both the criteria and new modeling strategy apply the concept of a normalized activation energy for thermally activated mechanisms developed by Kocks, Mecking, and co-workers. This work quantifies the average rate sensitivity of the three materials from an experimental database collected from the literature. Additionally, this work develops rate sensitivity criteria and a complete model for each material that can transition between both deformation regimes and provides several example simulations demonstrating the accuracy of the models and the numerical performance of the composite modeling method.