Abstract
Infrared (IR) diagnostics are used to measure plasma-facing components (PFC) surface temperature in fusion devices. However, the interpretation of such images is complex in all-reflective environments because of unknown emissivity and multiple reflections issues. In order to assess these challenges an iterative inversion method based on a fast photonic model, the radiosity method, has been developed. This method is applied to two different direct models based on different geometries, Sec-Tore and RADIOS, in order to estimate temperatures from experimental-like data simulated with a Monte Carlo ray-tracing code with diffuse reflective surfaces or specularly reflective surfaces. RADIOS allows retrieving temperature on colder targets (lower than 200°C) with errors of 33% and the peak temperatures with errors of 6%.
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