M. Valisa

Bio: M. Valisa is an academic researcher from ENEA. The author has contributed to research in topics: Tokamak & Magnetic confinement fusion. The author has an hindex of 21, co-authored 27 publications receiving 1862 citations. Previous affiliations of M. Valisa include Helsinki University of Technology & Max Planck Society.

Self-organized helical equilibria as a new paradigm for ohmically heated fusion plasmas

Abstract: A reversed-field pinch is a toroidal device for magnetically confining plasmas, and a potential alternative to the tokamak for a future fusion reactor. Observations of the evolution of a reversed-field-pinch plasma towards a self-organized single-helicity state suggest that instability problems, which have previously hindered the development of these devices, could now be overcome.

The ITER full size plasma source device design

Abstract: In the framework of the strategy for the development and the procurement of the NB systems for ITER, it has been decided to build in Padova a test facility, including two experimental devices: a full size plasma source with low voltage extraction and a full size NB injector at full beam power (1 MV). These two different devices will separately address the main scientific and technological issues of the 17 MW NB injector for ITER. In particular the full size plasma source of negative ions will address the ITER performance requirements in terms of current density and uniformity, limitation of the electron/ion ratio and stationary operation at full current with high reliability and constant performances for the whole operating time up to 1 h. The required negative ion current density to be extracted from the plasma source ranges from 290 A/m2 in D2 (D−) and 350 A/m2 in H2 (H−) and these values should be obtained at the lowest admissible neutral pressure in the plasma source volume, nominally at 0.3 Pa. The electron to ion ratio should be limited to less than 1 and the admissible ion inhomogeneity extracted from the grids should be better than 10% on the whole plasma cross-section having a surface exposed to the extraction grid of the order of 1 m2. The main design choices will be presented in the paper as well as an overview of the design of the main components and systems.

Overview of the JET results in support to ITER

Abstract: The 2014-2016 JET results are reviewed in the light of their significance for optimising the ITER research plan for the active and non-active operation. More than 60 h of plasma operation with ITER first wall materials successfully took place since its installation in 2011. New multi-machine scaling of the type I-ELM divertor energy flux density to ITER is supported by first principle modelling. ITER relevant disruption experiments and first principle modelling are reported with a set of three disruption mitigation valves mimicking the ITER setup. Insights of the L-H power threshold in Deuterium and Hydrogen are given, stressing the importance of the magnetic configurations and the recent measurements of fine-scale structures in the edge radial electric. Dimensionless scans of the core and pedestal confinement provide new information to elucidate the importance of the first wall material on the fusion performance. H-mode plasmas at ITER triangularity (H = 1 at β N ∼ 1.8 and n/n GW ∼ 0.6) have been sustained at 2 MA during 5 s. The ITER neutronics codes have been validated on high performance experiments. Prospects for the coming D-T campaign and 14 MeV neutron calibration strategy are reviewed.

Tungsten transport in JET H-mode plasmas in hybrid scenario, experimental observations and modelling

Abstract: The behaviour of tungsten in the core of hybrid scenario plasmas in JET with the ITER-like wall is analysed and modelled with a combination of neoclassical and gyrokinetic codes In these discharges, good confinement conditions can be maintained only for the first 2?3?s of the high power phase Later W accumulation is regularly observed, often accompanied by the onset of magneto-hydrodynamical activity, in particular neoclassical tearing modes (NTMs), both of which have detrimental effects on the global energy confinement The dynamics of the accumulation process is examined, taking into consideration the concurrent evolution of the background plasma profiles, and the possible onset of NTMs Two time slices of a representative discharge, before and during the accumulation process, are analysed with two independent methods, in order to reconstruct the W density distribution over the poloidal cross-section The same time slices are modelled, computing both neoclassical and turbulent transport components and consistently including the impact of centrifugal effects, which can be significant in these plasmas, and strongly enhance W neoclassical transport The modelling closely reproduces the observations and identifies inward neoclassical convection due to the density peaking of the bulk plasma in the central region as the main cause of the accumulation The change in W neoclassical convection is directly produced by the transient behaviour of the main plasma density profile, which is hollow in the central region in the initial part of the high power phase of the discharge, but which develops a significant density peaking very close to the magnetic axis in the later phase The analysis of a large set of discharges provides clear indications that this effect is generic in this scenario The unfavourable impact of the onset of NTMs on the W behaviour, observed in several discharges, is suggested to be a consequence of a detrimental combination of the effects of neoclassical transport and of the appearance of an island

Theoretical description of heavy impurity transport and its application to the modelling of tungsten in JET and ASDEX Upgrade

Abstract: The effects of poloidal asymmetries and heated minority species are shown to be necessary to accurately describe heavy impurity transport in present experiments in JET and ASDEX Upgrade. Plasma rotation, or any small background electrostatic field in the plasma, such as that generated by anisotropic external heating can generate strong poloidal density variation of heavy impurities. These asymmetries have recently been added to numerical tools describing both neoclassical and turbulent transport and can increase neoclassical tungsten transport by an order of magnitude. Modelling predictions of the steady-state two-dimensional tungsten impurity distribution are compared with tomography from soft x-ray diagnostics. The modelling identifies neoclassical transport enhanced by poloidal asymmetries as the dominant mechanism responsible for tungsten accumulation in the central core of the plasma. Depending on the bulk plasma profiles, turbulent diffusion and neoclassical temperature screening can prevent accumulation. Externally heated minority species can significantly enhance temperature screening in ICRH plasmas.

Fast-wave heating of a two-component plasma

Abstract: The use of the compressional hydromagnetic mode (also called the magnetosonic or, simply, the fast wave) is examined in some detail with respect to the heating of a tritium plasma containing a few percent deuterium. Efficient absorption of wave energy by the deuteron component is found when ω = ωC (deuterons), with Qwave 100. Reasonable efficiencies are found also for electron heating, but coherence effects between transit-time and Landau damping for electrons reduce the total absorption for both processes to one-half of the transit-time power, calculated separately.The fusion output of a two-component neutral-injected plasma can be enhanced by selective heating of the injected deuterons. Also, selective deuteron absorption may be used for ion-tail creation by radiofrequency excitation alone, as an alternative to neutral injection. The dominant behaviour of the high-energy deuteron distribution function is found to be f(v) ~ exp[(3/2)∫vdv / ], where is the Chandrasekhar-Spitzer drag coefficient, and is the Kennel-Engelmann quasi-linear diffusion coefficient for wave-particle interaction at the deuteron cyclotron frequency. An analytic solution to the one-dimensional Fokker-Planck equation, with r.f.-induced diffusion, is developed, and using this solution together with Duane's fit to the D-T fusion cross-section, it is found that the nuclear-fusion power output from an r.f.-produced two-component plasma can significantly exceed the incremental (radiofrequency) power input.

Density limits in toroidal plasmas

Abstract: In addition to the operational limits imposed by MHD stability on plasma current and pressure, an independent limit on plasma density is observed in confined toroidal plasmas. This review attempts to summarize recent work on the phenomenology and physics of the density limit. Perhaps the most surprising result is that all of the toroidal confinement devices considered operate in similar ranges of (suitably normalized) densities. The empirical scalings derived independently for tokamaks and reversed-field pinches are essentially identical, while stellarators appear to operate at somewhat higher densities with a different scaling. Dedicated density limit experiments have not been carried out for spheromaks and field-reversed configurations, however, `optimized' discharges in these devices are also well characterized by the same empirical law. In tokamaks, where the most extensive studies have been conducted, there is strong evidence linking the limit to physics near the plasma boundary: thus, it is possible to extend the operational range for line-averaged density by operating with peaked density profiles. Additional particles in the plasma core apparently have no effect on density limit physics. While there is no widely accepted, first principles model for the density limit, research in this area has focussed on mechanisms which lead to strong edge cooling. Theoretical work has concentrated on the consequences of increased impurity radiation which may dominate power balance at high densities and low temperatures. These theories are not entirely satisfactory as they require assumptions about edge transport and make predictions for power and impurity scaling that may not be consistent with experimental results. A separate thread of research looks for the cause in collisionality enhanced turbulent transport. While there is experimental and theoretical support for this approach, understanding of the underlying mechanisms is only at a rudimentary stage and no predictive capability is yet available.

Model for the sawtooth period and amplitude

Abstract: A model for sawtooth oscillations in tokamak experiments is outlined. A threshold criterion for the onset of internal kink modes and a prescription for the relaxed profiles immediately after the sawtooth crash have been implemented in a transport code that evolves the relevant plasma parameters. In this paper, applications of this model to the prediction of the sawtooth period and amplitude in projected ITER discharges are discussed. It is found that sawteeth can be stabilized transiently by the fusion alpha particles in ITER for periods that are long on the energy confinement timescale (). The sawtooth period depends on the amount of reconnected flux at the preceding sawtooth crash. When Kadomtsev's full reconnection model is used, the period can exceed 100 s. The sawtooth mixing radius following long duration sawtooth ramps can easily exceed half the plasma minor radius, raising questions about the desirability of transient sawtooth suppression.

A Theory-Based Transport Model With Comprehensive Physics

Abstract: A new theory-based transport model with comprehensive physics (trapping, general toroidal geometry, fully electromagnetic, electron-ion collisions, impurity ions) has been developed. The core of the model is the new trapped-gyro-Landau-fluid (TGLF) equations, which provide a fast and accurate approximation to the linear eigenmodes for gyrokinetic drift-wave instabilities (trapped ion and electron modes, ion and electron temperature gradient modes, and kinetic ballooning modes). The new TGLF transport model is more accurate, and has an extended range of validity, compared to its predecessor GLF23. The TGLF model unifies trapped and passing particles in a single set of gyro-Landau-fluid equations. A model for the averaging of the Landau resonance by the trapped particles makes the equations work seamlessly over the whole drift-wave wave-number range from trapped ion modes to electron temperature gradient modes. A fast eigenmode solution method enables unrestricted magnetic geometry. The transport model uses...

Predicting disruptive instabilities in controlled fusion plasmas through deep learning

Abstract: Nuclear fusion power delivered by magnetic-confinement tokamak reactors holds the promise of sustainable and clean energy1. The avoidance of large-scale plasma instabilities called disruptions within these reactors2,3 is one of the most pressing challenges4,5, because disruptions can halt power production and damage key components. Disruptions are particularly harmful for large burning-plasma systems such as the multibillion-dollar International Thermonuclear Experimental Reactor (ITER) project6 currently under construction, which aims to be the first reactor that produces more power from fusion than is injected to heat the plasma. Here we present a method based on deep learning for forecasting disruptions. Our method extends considerably the capabilities of previous strategies such as first-principles-based5 and classical machine-learning7–11 approaches. In particular, it delivers reliable predictions for machines other than the one on which it was trained—a crucial requirement for future large reactors that cannot afford training disruptions. Our approach takes advantage of high-dimensional training data to boost predictive performance while also engaging supercomputing resources at the largest scale to improve accuracy and speed. Trained on experimental data from the largest tokamaks in the United States (DIII-D12) and the world (Joint European Torus, JET13), our method can also be applied to specific tasks such as prediction with long warning times: this opens up the possibility of moving from passive disruption prediction to active reactor control and optimization. These initial results illustrate the potential for deep learning to accelerate progress in fusion-energy science and, more generally, in the understanding and prediction of complex physical systems. Using data from plasma-based tokamak nuclear reactors in the US and Europe, a machine-learning approach based on deep neural networks is taught to forecast disruptions, even those in machines on which the algorithm was not trained.