2022 Volume 3 Issue 2 Pages 11-18
The conservation of Cultural Heritage (CH) requires the integration of experimental data in the computational models in order to improve the robustness of the structural analyses. In this scenario, the paper introduces recent results of experimental activities carried out on the Galleria dell’Accademia di Firenze (GDA-FI), a famous Italian museum complex. The work aims to investigate the dynamic behaviour of one of the Structural Units (SU) which compose the museum: the Tribuna, where the Michelangelo’s David is exhibited to the public. The experimental layout was composed by two triaxial stations roving in different positions carefully designed by considering both the architectonic features of the structure and the location of the masterpieces collected in the Tribuna, such as paintings and sculptures, which could not be moved during the measurements. The investigation activity was performed in the framework of a wider research project, DAVID "Defense of cultural heritage and Assessment of Vulnerability through Innovative technologies & Device", co-founded by Tuscany Region and Galleria dell’Accademia di Firenze with the aim to preserve the museum complex and the works of art inside. A computational model is herein proposed to illustrate the process of calibration, and its advantages in terms of model reliability, through the comparison between the experimental results and the model output itself. More in detail, the research deal with the issue related to the analyses of a portion of the structure, extracted from the whole complex, and the boundary conditions which need to be assigned in order to represent the actual interaction with the surrounding buildings. The workflow discussed in this paper is applied to the case study of GDA-FI and it represents a meaningful test bench in order to draw general remarks on the topic of historical museum complex conservation as well as the employment of Historical Building Information Modelling (HBIM) to link different sources of information to the computational models.