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UKAEA-CCFE-PR(24)062023
We describe the parameterization of a tungsten-hydrogen empirical potential designed for use with large-scale molecular dynamics simulations of highly irradiated tungsten containing hydrogen isotope atoms, and report test results. Particular attention has been paid to getting good elastic properties, including the relaxation volumes of small def…
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UKAEA-CCFE-PR(24)052022
Effects of neutron irradiation on materials are often interpreted in terms of atomic recoils, initiated by neutron impacts and producing crystal lattice defects. We find that, in addition, there is a remarkable two-step process, strongly pronounced in heavy elements, involving the generation of energetic γ-photons in non-elastic collisions of n…
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UKAEA-CCFE-PR(23)1312022
We derive a simple analytical line integral expression for the relaxation volume tensor of an arbitrary interconnected dislocation network. This quantity determines the magnitude of dislocation contribution to the dimensional changes and volumetric swelling of a material, and highlights the fundamental dual role of dislocations as sources of intern…
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UKAEA-CCFE-PR(23)1722023
Neutrons interacting with atomic nuclei in most of the materials included in the current fusion reactor designs—notably tungsten, ferritic and stainless steels, copper alloys—generate a γ-photon flux that is comparable in magnitude and e…
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UKAEA-CCFE-PR(23)1712023
We simulate effects of irradiation on nanocrystalline tungsten in the athermal high dose limit using the creation-relaxation algorithm, where microstructural evolution is driven not by thermally activated diffusion, but by fluctuating stresses resulting from the production and relaxation of defects. Over the entire interval of radiation exposure sp…
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UKAEA-CCFE-PR(23)1402023
We investigated the athermal irradiation-induced swelling and creep in iron subjecting to the application of external uniaxial stress. We studied this through atomic scale simulations using the creation-relaxation algorithm. We also calculated the defect relaxation volume density tensors (or eigenstrain) as a function of external uniaxial stress. B…
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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(23)822019
One of the biggest challenges to achieve the goal of producing fusion energy in tokamak devices is the necessity of avoiding disruptions of the plasma current due to instabilities. The Disruption Event Characterization and Forecasting (DECAF) framework has been developed in this purpose, integrating physics models of many causal events that can …
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UKAEA-CCFE-PR(22)622022
We have devised a new type of feedforward neural network. It is equivariant with respect to unitary operators $U(n)$. The input and output can be vectors in $\\mathbb{C}^n$ with arbitrary dimension~$n$. No convolution layer is required in our implementation, and we also avoid errors due to truncated higher order terms in Fourier-like transformat…
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UKAEA-CCFE-PR(22)612022
Showing 1 - 10 of 28 UKAEA Paper Results