3D Heterogeneous Dataset for Structural Analysis of Historic Buildings. A Discussion on Process Pipelines

Main Article Content

Umair Shafqat Malik
https://orcid.org/0000-0003-2942-1063
Andrea Garzulino
https://orcid.org/0000-0001-9010-1662
Davide Del Curto
https://orcid.org/0000-0001-6877-8554

Abstract

This paper presents a methodology for creating a comprehensive heterogeneous 3D dataset for the structural evaluation of a historic building by using both non-destructive and destructive surveys combined with historical information. The availability of adequate data on the actual conditions is crucial when assessing the seismic vulnerability and structural behavior of a historic building and validating the results. A reliable 3D dataset must accept different kinds of data, e.g., the results of destructive/non-destructive surveys, historical information, etc., which can be interrogated and enriched at any time. Therefore, creating such a 3D dataset may present several challenges in terms of data-gathering pipeline, comprehensiveness/redundancy, interpretation, organization, and integration with other heterogeneous data. The methodology we present in this paper includes 3D laser scanning, thermal imaging, and endoscopy combined with information regarding the state of conservation, construction history, materials, and techniques. We tested such methodology to create a dataset that was later used for Finite Element Modeling (FEM) to assess the seismic vulnerability of Diotti Palace, a neoclassical building that has been the seat of the Prefect of Milan since 1859. The results are analytically presented here. In conclusion, we highlight the pros and cons of the proposed methodology by means of a comparative discussion with the state of the art about 3D documentation pipelines for historic buildings and sites.

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How to Cite
Malik, U. S., Garzulino, A., & Del Curto, D. (2023). 3D Heterogeneous Dataset for Structural Analysis of Historic Buildings. A Discussion on Process Pipelines . Studies in Digital Heritage, 7(1), 17–46. https://doi.org/10.14434/sdh.v7i1.36296
Section
Research Articles

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