Acceleration of an Algorithm Based on the Maximum Likelihood Bolometric Tomography for the Determination of Uncertainties in the Radiation Emission on JET Using Heterogeneous Platforms

Ruiz, M.; Nieto, J.; Costa, Víctor; Peluso, E.; Vega, J.; Murari, A.

doi:10.3390/app12136798

Cited by 9 publications

(7 citation statements)

References 20 publications

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“…This takes a few tens of seconds on a usual computer in the MATLAB environment. As it has been recently shown, an accelerated version, implemented in C and using a compatible ITER fast controller platform with the Ubuntu 18.04 or the ITER Codac Core System distributions (6.1.2), achieves the final reconstruction in a few seconds [35]. Therefore, the method is compatible with inter-shot analysis.…”

Section: Resultsmentioning

confidence: 96%

Maximum likelihood bolometry for ASDEX upgrade experiments

Craciunescu,

Peluso,

Murari

et al. 2023

Phys. Scr.

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Bolometry is an essential diagnostic for calculating the power balances and for the understanding of different physical aspects of tokamak experiments. The reconstruction method based on the Maximum Likelihood (ML) principle, developed initially for JET, has been implemented for ASDEX Upgrade. Due to the availability of a limited number of views, the reconstruction problem is mathematically ill-posed. A regularizing procedure, based on the assumption of smoothness along the magnetic surfaces, given by plasma equilibrium, must also be implemented. A new anisotropic smoothing technique, which acts along locally oriented kernels, has been implemented. The performances of the method have been evaluated, in terms of shapes, resolution and of the derived radiated power, and compared with the bolometry method used routinely on ASDEX Upgrade. The specific advantage of the ML reconstruction algorithm consists of the possibility to assess the uncertainties of the reconstruction and to derive confidence intervals in the emitted radiation levels. The importance of this capability is illustrated.

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Section: Resultsmentioning

confidence: 96%

Maximum likelihood bolometry for ASDEX upgrade experiments

Craciunescu,

Peluso,

Murari

et al. 2023

Phys. Scr.

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“…Completing the calculations for a single time slice typically requires several seconds, a time span far too long for the task of predicting the occurrence of disruptions. Acceleration techniques are under investigation but the deployment of the ML tomography in feedback remains far in the future 74 . The ML tomography algorithms are therefore utilised in the present work only as a benchmark.…”

Section: Methodsmentioning

confidence: 99%

A control oriented strategy of disruption prediction to avoid the configuration collapse of tokamak reactors

Murari,

Rossi,

Craciunescu

et al. 2024

Nat Commun

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The objective of thermonuclear fusion consists of producing electricity from the coalescence of light nuclei in high temperature plasmas. The most promising route to fusion envisages the confinement of such plasmas with magnetic fields, whose most studied configuration is the tokamak. Disruptions are catastrophic collapses affecting all tokamak devices and one of the main potential showstoppers on the route to a commercial reactor. In this work we report how, deploying innovative analysis methods on thousands of JET experiments covering the isotopic compositions from hydrogen to full tritium and including the major D-T campaign, the nature of the various forms of collapse is investigated in all phases of the discharges. An original approach to proximity detection has been developed, which allows determining both the probability of and the time interval remaining before an incoming disruption, with adaptive, from scratch, real time compatible techniques. The results indicate that physics based prediction and control tools can be developed, to deploy realistic strategies of disruption avoidance and prevention, meeting the requirements of the next generation of devices.

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“…It has also to be stated in fact that radiative events play a very important role, since they can influence the initial phases and the growth of MHD instabilities [16] which then can lead to a disruption. What stated above then, stresses the importance of the work done by Mariano et al [17], devoted to the acceleration of a Maximum Likelihood (ML) algorithm for bolometric tomographies in a ITER compatible environment. The ML algorithm has been implemented and validated on JET [18], and more recently on AUG [19] also.…”

Section: Overview Of the Issuementioning

confidence: 97%

New Challenges in Nuclear Fusion Reactors: From Data Analysis to Materials and Manufacturing

2023

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The construction and operation of the first generation of magnetically controlled nuclear fusion power plants require the development of proper physics and the engineering bases. The analysis of data, recently collected by the actual largest and most important tokamak in the world JET, that has successfully completed his second deuterium and tritium campaign in 2021 (DTE2) with a full ITER like wall main chamber, has provided an important consolidation of the ITER physics basis. Thermonuclear plasmas are highly nonlinear systems characterized by the need of numerous diagnostics to measure physical quantities to guide, through proper control schemes, external actuators. Both modelling and machine learning approaches are required to maximize the physical understanding of plasma dynamics and at the same time, engineering challenges have to be faced. Fusion experiments are indeed extremely hostile environments for plasma facing materials (PFM) and plasma-facing components (PFC), both in terms of neutron, thermal loads and mechanical stresses that the components have to face during either steady operation or off-normal events. Efforts are therefore spent by the community to reach the ultimate goal ahead: turning on the first nuclear fusion power plant, DEMO, by 2050. This editorial is dedicated at reviewing some aspects touched in recent studies developed in this dynamic, challenging project, collected by the special issue titled “New Challenges in Nuclear Fusion Reactors: From Data Analysis to Materials and Manufacturing”.

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Acceleration of an Algorithm Based on the Maximum Likelihood Bolometric Tomography for the Determination of Uncertainties in the Radiation Emission on JET Using Heterogeneous Platforms

Cited by 9 publications

References 20 publications

Maximum likelihood bolometry for ASDEX upgrade experiments

Maximum likelihood bolometry for ASDEX upgrade experiments

A control oriented strategy of disruption prediction to avoid the configuration collapse of tokamak reactors

New Challenges in Nuclear Fusion Reactors: From Data Analysis to Materials and Manufacturing

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