Nuclear fusion using magnetic confinement, in particular in the tokamak configuration, is a promising path towards sustainable energy. A core challenge is to shape and maintain a high-temperature plasma within the tokamak vessel. This requires high-dimensional, high-frequency, closed-loop control using magnetic actuator coils, further complicated by the diverse requirements across a wide range of plasma configurations. In this work, we introduce a previously undescribed architecture for tokamak magnetic controller design that autonomously learns to command the full set of control coils. This architecture meets control objectives specified at a high level, at the same time satisfying physical and operational constraints. This approach has unprecedented flexibility and generality in problem specification and yields a notable reduction in design effort to produce new plasma configurations. We successfully produce and control a diverse set of plasma configurations on the Tokamak à Configuration Variable1,2, including elongated, conventional shapes, as well as advanced configurations, such as negative triangularity and ‘snowflake’ configurations. Our approach achieves accurate tracking of the location, current and shape for these configurations. We also demonstrate sustained ‘droplets’ on TCV, in which two separate plasmas are maintained simultaneously within the vessel. This represents a notable advance for tokamak feedback control, showing the potential of reinforcement learning to accelerate research in the fusion domain, and is one of the most challenging real-world systems to which reinforcement learning has been applied.

Abstract-The success of wireless sensor networks and their pervasive use is somehow constrained by energy supply which, generally provided by batteries, is a finite resource. Energy harvesting mechanisms must hence be taken into account to grant a long time operational life, with solar energy being the most interesting one in outdoor deployments due to its relatively high power density. In this paper we propose a low-power maximum power point tracker (MPPT) circuit specifically designed for wireless sensor nodes (hence effective, flexible, low cost and power-aware), i.e., a power transferring circuit for optimally conveying solar energy into rechargeable batteries even in not optimal weather conditions. High efficiency is granted by an ad hoc adaptive algorithm which, by keeping the MPPT electronics in its optimal working point, maximizes energy transfer from the solar cell to the batteries. The suggested implementation is particularly effective in critical weather conditions where traditional solutions do not work and is characterized by a flexible enough design for immediately hosting, in a plug in fashion, different solar panels and battery typologies.Index Terms-Adaptive algorithms, maximum power point tracker (MPPT) circuits, power converters, solar energy harvesting, wireless sensor networks.

The paper proposes an environmental monitoring framework based on a wireless sensor network technology characterized by energy harvesting, robustness with respect to a large class of perturbations and real-time adaptation to the network topology. The fully designed and developed ad hoc system, based on clusters relying on a star topology, encompasses a sensing activity, a one-step local transmission from sensor nodes to the gateway, a remote data transmission from the gateway to the control center, data storage in a DB and real-time visualization. Hw and Sw modules have been either carefully selected or designed to guarantee a high quality of service, optimal solar energy harvesting, storage and energy awareness. A monitoring system integrating the outlined framework has been deployed in Queensland, Australia, for monitoring the underwater luminosity and temperature, information necessary to derive the health status of the coralline barrier. At the same time, acquired data can be used to provide quantitative indications related to cyclone formations in tropical areas.Index Terms-Adaptive communication protocol, distributed environmental monitoring systems, energy harvesting, wireless sensor networks (WSNs).

The paraxial WKB code TORBEAM [E. Poli et al., Comp. Phys. Comm. 136 (2001), 90] is widely used for the description of electron-cyclotron waves in fusion plasmas, retaining diffraction effects through the solution of a set of ordinary differential equations. With respect to its original form, the code has undergone significant transformations and extensions, in terms of both the physical model and the spectrum of applications. The code has been rewritten in Fortran 90 and transformed into a library, which can be called from within different (not necessarily Fortran-based) workflows. The models for both absorption and current drive have been extended, including e.g. fully-relativistic calculation of the absorption coefficient, momentum conservation in electron-electron collisions and the contribution of more than one harmonic to current drive. The code can be run also for reflectometry applications, with relativistic corrections for the electron mass. Formulas that provide the coupling between the reflected beam and the receiver have been developed. Accelerated versions of the code are available, with the reduced physics goal of inferring the location of maximum absorption (including or not the total driven current) for a given setting of the launcher mirrors. Optionally, plasma volumes within given flux surfaces and corresponding values of minimum and maximum magnetic field can be provided externally to speed up the calculation of full driven-current profiles. These can be employed in real-time control algorithms or for fast data analysis.

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