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- Learning from Objects: the use of advanced numerical methods to exploit a complete set of information from experimental data, for the Mona Lisa's Digital-Twin hal link

Auteur(s): Riparbelli Lorenzo, Brémand Fabrice, Dionisi-Vici Paolo, Dupré Jean-Christophe, Goli Giacomo, Jullien D., Mazzanti Paola, Togni Marco, Ravaud Elisabeth, Uzielli Luca, Gril J.

Conference: Heritech (Florence, IT, 2020-10-14)


Ref HAL: hal-03053193_v1
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Résumé:

The approach to wooden artefacts of historical importance, and panel paintings in particular, is a task that requires a multidisciplinary approach based on experimental observation of the artwork and advanced techniques to make these data actually useful for the knowledge and preservation of the object. This study illustrates how a series of scientific observations and instrumental analyses can be used to construct a numerical simulation that allows a deeper understanding of the physical structure and behaviour of the object itself, namely to construct a hygro-mechanical predictive model (a “Digital-Twin”) of Leonardo da Vinci's Mona Lisa panel. Based on specific request from the Louvre Museum, a group of experts with different and complementary skills cooperated and are still cooperating to construct a complete set of experimental observation and non-invasive tests; so, the integration of the collected data made the construction possible of the panel’s Digital-Twin. This paper also specifically examines how the Digital-Twin can be used to compare two framing conditions of the panel; although the two experimental configurations are not inherently comparable, the comparison is made possible by the introduction of a technique of projection of the fields obtained as results of the two analyses, named the Projected Model Comparison (PMC), which has been developed specifically for this research.



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