We present an ultrafast neural network (NN) model, QLKNN, which predicts core tokamak transport heat and particle fluxes. QLKNN is a surrogate model based on a database of 300 million flux calculations of the quasilinear gyrokinetic transport model QuaLiKiz. The database covers a wide range of realistic tokamak core parameters. Physical features such as the existence of a critical gradient for the onset of turbulent transport were integrated into the neural network training methodology. We have coupled QLKNN to the tokamak modelling framework JINTRAC and rapid control-oriented tokamak transport solver RAPTOR. The coupled frameworks are demonstrated and validated through application to three JET shots covering a representative spread of H-mode operating space, predicting turbulent transport of energy and particles in the plasma core. JINTRAC-QLKNN and RAPTOR-QLKNN are able to accurately reproduce JINTRAC-QuaLiKiz T i,e and n e profiles, but 3 to 5 orders of magnitude faster. Simulations which take hours are reduced down to only a few tens of seconds. The discrepancy in the final source-driven predicted profiles between QLKNN and QuaLiKiz is on the order 1%-15%. Also the dynamic behaviour was well captured by QLKNN, with differences of only 4%-10% compared to JINTRAC-QuaLiKiz observed at mid-radius, for a study of density buildup following the L-H transition. Deployment of neural network surrogate models in multi-physics integrated tokamak modelling is a promising route towards enabling accurate and fast tokamak scenario optimization, Uncertainty Quantification, and control applications.

Certain limitations exist in autonomous software and guidance, navigation, and control architectures developed for extraterrestrial planetary exploration rovers in regard to fault tolerance, changes in environment, and changes in rover capabilities. To address these limitations, this paper outlines a self-reconfiguring guidance, navigation, and control architecture, using an ontology-based rational agent to enable autonomous reconfiguration of mission goals, software architecture, software components, and the control of hardware components during the run time. This new architecture was evaluated through implementation onboard a rover and tested in challenging, Mars-like environments, both simulated and real world, and was found to be highly reliable, fault tolerant, and adaptable

This position paper describes ongoing work at the Universities of Liverpool, Sheffield and Surrey in the UK on developing hybrid agent architectures for controlling autonomous systems, and specifically for ensuring that agent-controlled dynamic reconfiguration is viable. The work outlined here forms part of the Reconfigurable Autonomy research project.

The hedgehog (Erinaceus europaeus) population is in decline in the UK and they are the most frequently admitted mammal to British Wildlife Rehabilitation Centres (WRCs). Whilst successful, UK rehabilitation is time-consuming and expensive and few large-scale studies into UK WRC admission and survival rates have been published in the last decade. This paper examines admission and survival trends in 19,577 hedgehogs admitted to Royal Society for the Prevention of Cruelty to Animals centres over a 13 year period (2005–2017) to gauge the state of Britain’s hedgehogs in WRCs and to gain indirect insight into the wild population. During the studied period, admissions more than doubled. Admission weights were greater in later than early litter juveniles. The survival improved 26% overall, and 33% in juveniles. Twenty two percent of animals died or were euthanased within 48 h of admission. Kaplan–Meier analysis gave survivor functions of 0.78 at 2 days, 0.66 at 10 days, 0.62 at 20 days, and 0.53 at 80 days. Survival was independent of admission weight in each age category. In particular, survival was greater in early litter juveniles than in adults or late litter juveniles; and across the breeding season diminished in juveniles and increased in adults. These data suggest factors impacting hedgehog survival have remained stable despite population decrease; that care methods have improved; and that late litters are more vulnerable than early. For WRCs this reaffirms that current methods are successful, but that further resources could be directed towards late litters.

The present paper offers an overview of the potential of ion cyclotron resonance heating (ICRH) or radio frequency (RF) heating for the DEMO machine. It is found that various suitable heating schemes are available. Similar to ITER and in view of the limited bandwidth of about 10M Hz that can be achieved to ensure optimal functioning of the launcher, it is proposed to make core second harmonic tritium heating the key ion heating scheme, assisted by fundamental cyclotron heating 3 He in the early phase of the discharge; for the present design of DEMO-with a static magnetic field strength of B o = 5.855T-that places the T and 3 He layers in the core for f = 60M Hz and suggests to center the bandwidth around that main operating frequency. In line with earlier studies for hot, dense plasmas in large-size magnetic confinement machines it is shown that good single pass absorption is achieved but that the size as well as operating density and temperature of the machine cause the electrons to absorb a non-negligible fraction of the power away from the core when core ion heating is aimed at. Current drive and alternative heating options are briefly discussed and a dedicated computation is done for the traveling wave antenna, proposed for DEMO in view of its compatibility with substantial antenna-plasma distances. The various tasks that ICRH can fulfill are briefly listed. Finally, the impact of transport and the sensitivity of the obtained results to changes in the machine parameters is commented on.