Dealing with artefacts in JET iterative bolometric tomography using masks
Bolometric tomography is a widely applied technique to infer important indirect quantities in magnetically confined plasmas, such as the total radiated power. However, being an inverse and ill-posed problem, the tomographic algorithms have to be carefully steered to converge on the most appropriate...
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Veröffentlicht in: | Plasma physics and controlled fusion 2022-04, Vol.64 (4), p.45013 |
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Sprache: | eng |
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Zusammenfassung: | Bolometric tomography is a widely applied technique to infer important indirect quantities in magnetically confined plasmas, such as the total radiated power. However, being an inverse and ill-posed problem, the tomographic algorithms have to be carefully steered to converge on the most appropriate solutions, and often specialists have to balance the quality of the obtained reconstructions between the core and the edge of the plasma. Given the topology of the emission and the layout of the diagnostics in practically all devices, the tomographic inversions of bolometry are often affected by artefacts, which can influence derived quantities and specific studies based on the reproduced tomograms, such as power balance studies and the benchmarking of gyrokinetic simulations. This article deals with the introduction of a simple, but very efficient methodology. It is based on constraining the solution of the tomographic inversions by using a specific estimate of the initial solution, built with the data from specific combinations of detectors (called ‘masks’). It has been tested with phantom and with real data, using the Maximum Likelihood approach at JET. Results show how the obtained tomograms improve sensibly both in the core and at the edge of the device, when compared with those obtained without the use of masks as the initial guess. The correction for the main artefacts can have a significant impact on the interpretation of both the core (electron transport, alpha heating) and the edge physics (detachment, SOL). The method is completely general and can be applied by any iterative algorithm starting from an initial guess for the emission profile to be reconstructed. |
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ISSN: | 0741-3335 1361-6587 |
DOI: | 10.1088/1361-6587/ac4854 |