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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

Abstract : 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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https://hal.archives-ouvertes.fr/hal-03053193
Contributor : Joseph Gril <>
Submitted on : Thursday, December 10, 2020 - 10:22:53 PM
Last modification on : Wednesday, February 24, 2021 - 4:16:03 PM
Long-term archiving on: : Thursday, March 11, 2021 - 9:20:09 PM

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  • HAL Id : hal-03053193, version 1

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Lorenzo Riparbelli, Fabrice Brémand, Paolo Dionisi-Vici, Jean-Christophe Dupré, Giacomo Goli, et al.. 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. Heritech, Oct 2020, Florence, Italy. ⟨hal-03053193⟩

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