Extending MOOSE Capabilities with Discrete and Combinatorial Shape and Topology Optimization for Nuclear Engineering Applications

We present the development and application of a C++ computational tool for physics-based shape optimization that we designed and implemented for NEAMS tools.The optimization tool leverages MOOSE's various systems, including the MultiApp transfer and reporter systems, among others, enabling seamless integration within the MOOSE framework.Our primary goal is to enable optimization of the shape and topology of nuclear reactor components within MOOSE, starting from the pin-level up to the core level.By integrating our tool into the extensive MOOSE's application library, it can be readily applied to any existing MOOSE modules or applications across thermal hydraulics, neutronics, structural mechanics, and other physics-based solvers in MOOSE.The flexibility of applying this new capability is illustrated by using different single-physics modules and apps in MOOSE.Two major types of shape and topology optimizations are applied in this paper to different engineering design examples, combinatorial and discrete optimizations.We demonstrate the tool on a 2D pin-cell model in an infinite lattice based on the traditional pin-cell d esigns.By implementing specific constraints and physics-based objective functions, we show how the state-space search algorithm embedded in our tool can propose optimized pin-cell designs including annular fuel pins.Verification of the algorithm's effectiveness at proposing relevant Loading Patterns (LP) and exploring the shape design space is illustrated using a fuel shuffling topology optimization problem adapted based on the IAEA-2D benchmark.