Multiphysics analysis with CAD-based parametric breeding blanket creation for rapid design iteration

Abstract

Breeding blankets are designed to ensure tritium self-sufficiency in deuterium–tritium fusion power plants. In addition to this, breeder blankets play a vital role in shielding key components of the reactor, and provide the main source of heat which will ultimately be used to generate electricity. Blanket design is critical to the success of fusion reactors and integral to the design process. Neutronic simulations of breeder blankets are regularly performed to ascertain the performance of a particular design. An iterative process of design improvements and parametric studies are required to optimize the design and meet performance targets. Within the EU DEMO program the breeding blanket design cycle is repeated for each new baseline design. One of the key steps is to create three-dimensional models suitable primarily for use in neutronics, but could be used in other computer-aided design (CAD)-based physics and engineering analyses. This article presents a novel blanket design tool which automates the process of producing heterogeneous 3D CAD-based geometries of the helium-cooled pebble bed, water-cooled lithium lead, helium-cooled lithium lead and dual-coolant lithium lead blanket types. The paper shows a method of integrating neutronics, thermal analysis and mechanical analysis with parametric CAD to facilitate the design process. The blanket design tool described in this paper provides parametric geometry for use in neutronics and engineering simulations. This paper explains the methodology of the design tool and demonstrates use of the design tool by generating all four EU blanket designs using the EU DEMO baseline. Neutronics and heat transfer simulations using the models have been carried out. The approach described has the potential to considerably speed up the design cycle and greatly facilitate the integration of multiphysics studies.

Parametric study of hydrogenic inventory in the ITER divertor based on machine learning

“…5 . In order to obtain this continuous field, more than 600 simulations randomly distributed on the parameter plane were run and analysed using a Gaussian process machine learning algorithm 20 as in 21 based on the python package inference-tools 22 . In Fig.…”

Influence of interface conditions on hydrogen transport studies

“…These components are often made of several materials joined together. This is the case for the monoblock geometry used for the ITER divertor which is made of a W armour, a CuCrZr cooling pipe jointed by a Cu inter-layer but also for DEMO breeding blankets since current designs involve W and EU-ROFER but Lithium, Beryllium, and other materials can also be found in some designs [8]. This study focuses on the interfaces between these materials, the physics at stake and their approximations.…”

The Paramak: automated parametric geometry construction for fusion reactor designs.

“…The use of these models in automated workflows has yet to be demonstrated in a publication but this would be the next logical stage in the process and the authors plan to publish a range of use cases for the parametric geometry in the future. Future work will, amongst other improvements, incorporate detailed parametric blanket models which have previously been created 1 .…”

“…Following the conclusion of analysis, feedback can be provided and the design cycle can be iterated to refine and optimise the design. Automating the analysis can help to rapidly develop a design as shown in 1 . While some automated analysis remains a challenge in certain disciplines, progress is being made on the automation of a number of domains used in the analysis of fusion reactors.…”