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UKAEA-CCFE-PR(25)3852025
The fusion research facility ITER is currently being assembled to demonstrate that fusion can be used for industrial energy production, while several other programmes across the world are also moving forward, such as EU-DEMO, CFETR, SPARK and STEP. The high engineering complexity of a tokamak makes it an extremely challenging device to optimise,…
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UKAEA-CCFE-PR(25)3502024
A key aspect in the modelling of magnetohydrodynamic (MHD) equilibria in tokamak devices is having access t…
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UKAEA-CCFE-PR(25)3072024
We are introducing FAIR-MAST, a data management system designed for historical diagnostic data from the Mega Ampere Spherical Tokamak (MAST) fusion experiments. Following the FAIR (findability, accessibility, interoperability, and re-usability) principles, our system aims to address current accessibility issues with data that supports artificial in…
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UKAEA-CCFE-CP(25)262023
Model-based plasma scenario development lies at the heart of the design and operation of future fusion powerplants. Including gyrokinetic turbulence in integrated models is essential for delivering a successful roadmap towards operation of ITER and the design of DEMO-class devices. Given the highly iterative nature of integrated models, fast machin…
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UKAEA-CCFE-PR(23)1912023
ITER is of key importance in the European fusion roadmap as it aims to prove the scientific and technological feasibility of fusion as a future energy source. The EUROfusion consortium of labs is contributing to the preparation of ITER scientific exploitation and operation and aspires to exploit ITER outcomes in view of DEMO. The paper provides …
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UKAEA-CCFE-PR(23)1232023
Classical sequential models employed in time-series prediction rely on learning the mappings from the past to the future instances by way of a hidden state. The Hidden states characterise the historical information and encode the required temporal dependencies. However, most existing sequential models operate within finite-dimensional Euclidean spa…
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UKAEA-CCFE-PR(25)2782022
Physics-Informed Neural Networks have shown unique utility in parameterising the solution of a well-defined partial differential equation using automatic differentiation and residual losses. Though they provide theoretical guarantees of convergence, in practice the required training regimes tend to be exacting and demanding. Through the course o…
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UKAEA-CCFE-PR(22)172022
As the international tokamak ITER is being built, non-linear MHD simulations are playing an essential role in active research, understanding, and prediction of tokamak plasmas for the realisation of a fusion power plant. The development of MHD codes like JOREK is a key aspect of this research effort, and provides invaluable insight into the plasma …
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UKAEA-CCFE-CP(23)142021
The high heat fluxes to the divertor during edge localised mode (ELM) instabilities have to be reduced for a sustainable future tokamak reactor. A solution to reduce the heat fluxes could be the Super-X divertor, this divertor configuration will be tested on MAST-U. ELM simulations for MAST-U Super-X tokamak plasmas have been obtained, using JOR…
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UKAEA-CCFE-CP(21)082021
The pedestal plays an important role in determining the confinement in tokamak H-mode plasmas. However, the steep pressure gradients in this transport barrier also lead to edge localized modes (ELMs) [1]. There is good understanding of the pedestal in type I ELM regimes [2], however, type I ELMs are known to damage plasma facing components and f…
Showing 1 - 10 of 27 UKAEA Paper Results