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UKAEA-CCFE-PR(23)1792023
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UKAEA-CCFE-PR(23)1802023
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UKAEA-CCFE-PR(23)1812023
During the DTE2 campaign in the JET tokamak we performed a parameter scan in T and D-T complementing existing pulses in H and D. For the different main ion masses H-modes at fixed plasma current and magnetic field can have the pedestal pressure varying by a factor of 4 and the total pressure changing from betaN = 1.0 to 3.0. Based on this wide data…
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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-RACE-CP(23)102023
In the nuclear industry, the need for improved reliability in current and future technology hinders the deployment of autonomous robotic systems. The following research aims to develop a method of reliably mapping a large environment and abstracting the map into a sparse node graph to create a more efficient data form. The proposed data form all…
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UKAEA-RACE-PR(23)072023
This paper reports on the analysis of potential rail-based maintenance systems when implemented into a Helical Advanced Stellarator (HELIAS) 5-B device. The main purpose of such a system would be to handle and exchange the internal vessel components, namely the breeding blanket segments, which are expected to be the largest and heaviest componen…
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UKAEA-RACE-CP(23)092023
When transferring a Deep Reinforcement Learning (DRL) model from simulation to the real world, the performance could be unsatisfactory since the simulation cannot imitate the real world well in many circumstances. This results in a long period of fine-tuning in the real world. This paper proposes a self-supervised vision-based DRL method that al…
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UKAEA-RACE-CP(23)082023
Many complex domains would benefit from the services of Large-scale, Safety-verified, Always-on (LSA) robotic systems. However, existing large-scale solutions often forego the complex reasoning required for safety verification and prescient reasoning in favour of scalability. We propose a method of partitioning the task domain to enable scalabil…
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UKAEA-RACE-CP(23)072023
We consider planning problems where a robot must visit a large set of locations to complete a task at each one. Our focus is problems where the difficulty of each task, and thus its duration, can be predicted, but not fully known in advance. We propose a general Markov decision process (MDP) model for difficulty-aware problems, and propose varia…
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UKAEA-RACE-CP(23)062023
Sim-and-real training is a promising alternative to sim-to-real training for robot manipulations. However, the current sim-and-real training is neither efficient, i.e., slow convergence to the optimal policy, nor effective, i.e., sizeable real-world robot data. Given limited time and hardware budgets, the performance of sim-and-real training is …
Showing 421 - 430 of 2527 UKAEA Paper Results