Parametric identification using photothermal data inversion: application to a nonlinear thermal system

Military structures, devices and vehicles used on battlefields are likely to be exposed to heavy thermal aggressions, such as fires or explosions. Protection of personnel and material engaged in combat against such aggressions is a top priority, and needs the use of adapted and optimized systems. Intumescent paints have the ability to swell up when they are heated, building a thick multi-layered coating which provides efficient thermal insulation to the underlying material. In order to evaluate such coating´s efficiency in a military framework and to identify its physical properties, experimental tests were carried out. A mathematical model describing intumescent paints behavior under several types of thermal aggressions was developed for system state evaluation in the case of long lasting fires. The model structure has been validated for thermal fluxes induced by several fire configurations and by brief, violent explosions. However, in order to supply the model with reliable input parameters, those must be identified. Thus, a whole identification process was carried out (modeling, sensitivity analysis, experiment, cost function minimization). The identification method is based on the frequency analysis of the heat waves generated by a modulated thermal excitation on the material´s surface.