Future fusion devices such as ITER and DEMO will produce high-energy neutron radiation as part of their normal operation. This radiation will be contained inside the plasma vessel (called a ”tokamak”). Every few years, regular maintenance work will involve the removal and replacement of many types of components, for example tokamak wall (”blanket”) segments damaged by the neutron radiation. The neutrons also activates the components, causing them to emit gamma-radiation for many years. As a consequence, these irregularly-shaped radioactive components will need to be stored for several decades in order to allow the radiation to decay away before final disposal and/or recycling. In order to minimise costs by facilitating more efficient transportation and storage, these components will need to be cut up and packed into containers in the fastest, safest and most space-efficient way possible. Due to the safety hazards arising from handling nuclear components, the solution to this challenge will involve robotic cutting, grasping, and packing of these components. This work will need to be done as quickly as possible and with minimal human supervision in order to reduce costs.
This problem is a non-linear, multi-objective optimisation problem. The project will build on existing methodologies in geometric topology, computational geometry, mathematical optimisation and optimisation solution algorithms to develop computer based solutions and explore the relationship between the multiple objectives.
About GREEN
The GREEN Centre for Doctoral Training (GREEN CDT) is a a consortium of five universities: The University of Manchester, Lancaster University, The University of Leeds, The University of Liverpool and The University of Sheffield, which aims to train the next generation of expert nuclear scientists and engineers.
Students within the GREEN CDT are invited to undertake a four-year PhD programme. Students will attend taught courses (Year 1) in various subject of nuclear technology followed by subject specific training (Year 1) leading to research activities (Year 2-Year 4).
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