The Grizzly software application is being developed under the Light Water Reactor Sustainability (LWRS) program to address aging and material degradation issues that could potentially become an obstacle to life extension of nuclear power plants beyond 60 years of operation. Grizzly is based on INL's MOOSE multiphysics simulation environment, and can simultaneously solve a variety of tightly coupled physics equations, and is thus a very powerful and flexible tool with a wide range of potential applications. Grizzly, the development of which was begun during fiscal year (FY) 2012, is intended to address degradation in a variety of critical structures.The reactor pressure vessel (RPV) was chosen for an initial application of this software. Because it fulfills the critical roles of housing the reactor core and providing a barrier to the release of coolant, the RPV is clearly one of the most safety-critical components of a nuclear power plant. In addition, because of its cost, size and location in the plant, replacement of this component would be prohibitively expensive, so failure of the RPV to meet acceptance criteria would likely result in the shutting down of a nuclear power plant.During service, the RPV is subjected to intense neutron flux. This flux, combined with thermal aging affects, has an embrittling effect on the RPV steel, which is manifested as an increase in the brittle/ductile transition temperature of that material. This means that at a given temperature, aging effects cause the steel to have a lower toughness and tend to fracture in a more brittle manner.The current practice used to perform engineering evaluations of the susceptibility of RPVs to fracture is to use the ASME Master Fracture Toughness Curve (ASME Code Case N-631 Section III), which provides the fracture toughness as a function of temperature. This is used in conjunction with empirically based models that describe the evolution of this curve due to embrittlement in terms of a transition temperature shift. These models are based on an extensive database of surveillance coupons that have been irradiated in operating nuclear power plants, but this data is limited to the lifetime of the current reactor fleet. This is an important limitation when considering life extension beyond 60 years. The currently available data cannot be extrapolated with confidence further out in time because there is a potential for additional damage mechanisms (i.e. late blooming phases) to become active later in life beyond the current operational experience.To improve our understanding of the degradation of RPV steels under the conditions that would be seen under extended service life, science-based predictive modeling at the atomistic scale is needed. This modeling, combined with the limited applicable experimental data in the regime of interest, can provide understanding of the fundamental degradation mechanisms, with the goal of eventually informing models that can be useful for engineering-scale evaluations of RPVs.