Peer Review Report For: The Paramak: automated parametric geometry construction for fusion reactor designs. [version 1; peer review: 2 approved]
Year: 2021
Type: peer-review
Abstract: During the conceptual design process of fusion reactors it is useful to rapidly prototype different design concepts and assess their suitability against a range of high level requirements. Rapid prototyping allows the 'fail early' mantra of other fields to be applied to engineering design. Furthermore, the rapid generation of low fidelity analysis allows fast exploration of design space, which enables better decisions to be made during concept selection and the detailed design phase. The Paramak is an open-source tool that aims to provide automated parameter driven 3D CAD models for fusion reactor components and magnetic fusion reactors. The geometry produced is compatible with several analysis workflows and this allows iterative automated model building and analysis to help steer the design concept optimisation process. The Paramak uses CadQuery 2 to create the 3D CAD model. The Paramak framework is used to create a few example reactor configurations including: a spherical reactor, a regular large radius tokamak and a compact submersion tank reactor. Input parameters for the various reactors that the Paramak can generate generally fall into three categories: continuous ranges such as blanket thickness, integer ranges such as number of toroidal field coils and categorical parameters such as type of divertor. The Paramak facilitates parameter studies where users can investigate the impact of input design parameters on the reactor performance. The use of modern software practices allows the geometry to be continuously tested in analysis workflows to ensure it is fit for purpose. The generation of output metrics from input parameters lends itself to the use of data science and machine learning approaches in order to steer the design. The Paramak provides rapid construction of analysis ready CAD in a manner that allows the designer to save time when exploring the design space for design studies and facilitate automated generative design.
Authors: Jonathan Shimwell, John Billingsley, Rémi Delaporte-Mathurin, Declan Morbey, Matthew Bluteau, Patrick Shriwise, Andrew Davis
Institutions: Culham Centre for Fusion Energy, Culham Science Centre, Centre National de la Recherche Scientifique, Commissariat à l'Énergie Atomique et aux Énergies Alternatives, Université Sorbonne Paris Nord, CEA Cadarache, Laboratoire des Sciences des Procédés et des Matériaux, Swansea University, Argonne National Laboratory
Language: English
Subfield: Materials Chemistry
Field: Materials Science
Domain: Physical Sciences
Open Access status: gold
OpenAlex ID: W4416634065
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