Digital engineering is reshaping fusion R&D, and the in-development Divertor Digital Twin Environment (DDTE) aims to provide an end-to-end, open-source workflow that shortens the path from late-stage divertor design to plant operation readiness. The DDTE is organised around three complementary flavours, each deliberately modular so that best-in-class community codes can be swapped in as...
Design activities for pilot fusion power plants are progressing worldwide, with the objective of demonstrating stable, reliable energy production and economic viability. The transition from ITER to next-generation fusion power plants marks a pivotal shift from a science-driven initiative to an industry- and technology-oriented programme. Consequently, future demonstration reactors, such as...
Fusion is fundamentally cutting-edge, and to achieve economic fusion energy the field must advance the understanding of engineering, materials, and plasma phenomena through experiments and test facilities. When designing a facility or experiment, traditional approaches of diagnostics, control, or experimental setup can often rely on manual or intuitive decision making. This can often be very...
Iterative simulations and analyses are required during a conceptual design of fusion reactor with continuous changes of the design. It is important to keep track of physical and engineering rationale for the design modifications with systematic linkages of back data. This becomes increasingly more important as the design processes become semi-automatic employing advanced design optimization...
High Repetition Rate High Energy Density (HED) physics facilities are rapidly becoming a cornerstone for the development of next-generation compute, control, and optimization infrastructures required by emerging Inertial Fusion Energy (IFE) platforms. As the demand for more sophisticated and responsive experimental setups grows, the ability to efficiently process and analyze vast amounts of...
Despite the existence of physics-based turbulent transport models, new tokamaks have historically initially been designed using empirical scaling laws due to the large computational expense of physics-based models. However, these empirical models do not capture the full changes caused by alterations to the plasma composition and geometry. Here, we optimize the ARC tokamak (Howard, et al., JPP,...
A. Ho1, L. Zanisi2, B. de Leeuw3, V. Galvan1, P. Rodriguez-Fernandez1, N. T. Howard1
1MIT Plasma Science and Fusion Center, Cambridge, MA, USA
2Culham Centre for Fusion Energy – United Kingdom Atomic Energy Authority, Abingdon, UK
3Radboud University, Nijmegen, Netherlands
This study applies uncertainty-aware neural network architectures in combination with active learning (AL) techniques...
