Fusion nucléaire

vignette|Le Soleil est une étoile de la séquence principale, dont l'énergie provient de la fusion nucléaire de noyaux d'hydrogène en hélium. En son cœur, le Soleil fusionne de tonnes d'hydrogène chaque seconde. La fusion nucléaire (ou thermonucléaire) est une réaction nucléaire dans laquelle deux noyaux atomiques s’assemblent pour former un noyau plus lourd. Cette réaction est à l’œuvre de manière naturelle dans le Soleil et la plupart des étoiles de l'Univers, dans lesquelles sont créés tous les éléments chimiques autres que l'hydrogène et la majeure partie de l'hélium. Elle est, avec la fission nucléaire, l’un des deux principaux types de réactions nucléaires appliquées. La fusion nucléaire dégage une quantité d’énergie colossale par unité de masse, provenant de l’attraction entre les nucléons due à l’interaction forte (voir énergie de liaison nucléaire). La masse du ou des produits d'une réaction de fusion étant inférieure à la somme des masses des noyaux fusionnés, la différence

À propos de ce résultat

Cette page est générée automatiquement et peut contenir des informations qui ne sont pas correctes, complètes, à jour ou pertinentes par rapport à votre recherche. Il en va de même pour toutes les autres pages de ce site. Veillez à vérifier les informations auprès des sources officielles de l'EPFL.

Publications associées (100)

Publications associées

Chargement

Personnes associées (80)

Personnes associées

Chargement

Unités associées (19)

Unités associées

Chargement

Concepts associés (172)

Concepts associés

Chargement

Cours associés (92)

Cours associés

Chargement

Séances de cours associées (234)

Séances de cours associées

Chargement

Spillover benefits from controlled nuclear fusion technology - A patent analysis

Daniel Kunz, Heinz Mueller, Christian Soltmann, Minh Quang Tran

Elsevier2012

Chargement

Magnetic control of tokamak plasmas through deep reinforcement learning

Jonas Buchli, Francesco Carpanese, Stefano Coda, Jonas Degrave, Basil Duval, Ambrogio Fasoli, Federico Alberto Alfredo Felici, Cristian Galperti, Antoine Pierre Emmanuel Alexis Merle, Jean-Marc Moret, Federico Pesamosca, Olivier Sauter, Cristian Sommariva

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.

2022

Chargement

Disruption Prediction Approaches Using Machine Learning Tools in Tokamaks

Alessandro Pau

Nuclear fusion is one of the best options to achieve a virtually limitless energy source in the future. However, sustaining burning plasma reactions is very challenging because disruptive events cause the loss of plasma confinement and damages to the tokamak machine. Thus, reproducing a nuclear fusion reaction on Earth represents an actual scientific and technical challenge. Next generation machines must be able to predict, mitigate or avoid the disruptions but the present understanding of the phenomenon has not yet gone so far as to provide a physical model describing their root cause. On the contrary, a large quantity of experimental disruption data exists. For these reason, in the last decades, machine learning techniques have been applied to design alarm systems both for mitigating or to actively avoid approaching disruptions. More recently, the disruption predictor concept has been evolving toward a more complex system, able to detect the proximity of the plasma state to the boundaries of the operational space free from disruptions in order to schedule avoidance strategies rather than mitigation actions. This system should also be able to determine which type of disruption is about to occur in order to efficiently take suitable disruption avoidance actions. This paper reports an overview of machine learning algorithms as tools for disruption prediction and classification at JET, the world's largest operational plasma physics experiment, located at Culham Centre for Fusion Energy in Oxfordshire, UK. Both traditional neural network models for disruption prediction and manifold learning approaches as a tool for plasma operational space mapping and visualization, disruption prediction and classification, are described.

IEEE2019

Chargement

Neutron

Le neutron est une particule subatomique de charge électrique nulle. Les neutrons sont présents dans le noyau des atomes, liés avec des protons par l'interaction forte. Alors que le nombre de proto

Fission nucléaire

redresse=1.67|vignette|Schéma animé (simplifié) d'une fission nucléaire. Un atome (énorme rond rouge) est percuté par un neutron (point bleu). Celui-ci se scinde en deux atomes. La réaction émet d'aut

Tritium

Le tritium (/tʁi.sjɔm/ ou /tʁi.tjɔm/), noté H ou T, est l'isotope de l'hydrogène dont le nombre de masse est égal à 3 : son noyau atomique, appelé triton, compte et avec un spin 1/2+ pour une masse

ME-409: Energy conversion and renewable energy

This course presents an overview of (i) the current energy system and uses (ii) the main principles of conventional and renewable energy technologies and (iii) the most important parameters that define their efficiency, costs and environmental impacts.

PHYS-443: Physics of nuclear reactors

In this course, one acquires an understanding of the basic neutronics interactions occurring in a nuclear fission reactor as well as the conditions for establishing and controlling a nuclear chain reaction.

PHYS-424: Plasma II

This course completes the knowledge in plasma physics that students have acquired in the previous two courses, with a discussion of different applications, in the fields of magnetic confinement and controlled fusion, astrophysical and space plasmas, and societal and industrial applications.