3D high-fidelity automated neutronics guided optimization of fusion blanket designs

The compact fusion pilot plant has been recently identified by the scientific community as the next step in fusion energy demonstration. Such a plant will include a 50 MWe peak net electricity production, Q_e greater than 1, and at least 3 hours of continuous operation. This FPP will be a test bed enabling materials, designs, and fuel management assessment, and it will represent an engineering challenge because of its high fusion power and compact design targets. Previous reactor data are limited to experiments operating in different design space ranges. Therefore, design iterations and assessments should rely on high-fidelity first-principles theoretical and computational models. The high-fidelity integrated modeling of the plasma is a fundamental part of fusion energy research. However, whole-device modeling is often neglected, or utilizes low-fidelity, system-level analysis. Recently, the need for high-fidelity multiphysics modeling was recognized, resulting in a selection of integrated tools. Autonomous design optimization requires a streamlined framework that perturbs the design point, reruns the analysis, and examines the outputs. However, high-fidelity analysis requires complex geometry specification that is difficult to perturb. This work presents the parametric computer-aided design (CAD) generation tool, Tracer and a new neutronic workflow. Tracer allows the perturbation of the geometry representation, creating geometry files ready for further analysis. The streamlined neutronic workflow allows efficient and accurate calculations. The two new tools coupled together were used to perform a 3D high-fidelity multi-objective, multi-input optimization of an “ARC Class” compact tokamak design. The workflow was driven by an optimization driver for full automation.