Parametric HBIM Procedure for the Structural Evaluation of Heritage Masonry Buildings

Abstract

In the architecture, engineering and construction sectors, Building Information Modeling (BIM)-based procedures have become adopted more and more. In fact, the development of suitable BIM models facilitates the management of the design and construction phases and improves the efficiency of the maintenance policies during the life cycle of the building. Although the BIM method is mostly implemented in the building industry for new constructions, in recent years, the deployment of this technology has also attracted increasing attention for existing structures to rebuild their geometry and gather relevant data, especially for historical buildings; in this case, we refer to Heritage BIM (HBIM). A HBIM procedure requires a multidisciplinary approach involving not only historical, conservation, and restoration considerations but also suitable maintenance and repair plans, duly balancing the structural needs with the preservation of the historical value of the building and its content. Although the integration of the structural assessment in the HBIM process would be highly beneficial, its practical implementation is often in the early stages. In the paper, an original parametric procedure for the assessment of existing masonry buildings is proposed in the BIM environment. The procedure combines E-PUSH, a software program for the structural analysis of masonry structures under seismic and non-seismic actions with an appropriate BIM approach, so improving the management of gathered data through cognitive phases. The assessment process is, thus, simplified since data required for the structural analysis are directly retrieved from the BIM model, and the structural analyses and verifications are performed without using external programs. The proposed BIM workflow is finally illustrated and discussed referring to a relevant case study, the seismic vulnerability assessment of the “Bernardo Rucellai” school in Florence (Italy).

Machine Learning and Deep Learning for the Built Heritage Analysis: Laser Scanning and UAV-Based Surveying Applications on a Complex Spatial Grid Structure

“…Then, multiple decorrelated decision trees are combined to make predictions on the class or label of each point of the 3D point cloud, and the final predictions are made through a voting scheme. Concerning the state-of-the-art on the topic, Teruggi et al [34] extended this ML classification method by proposing a multi-scale and multi-resolution approach, hierarchically classifying 3D data at different geometric resolutions to ease the learning process and optimize the classification results. The cited references always referred to either the case of land surveying or architectural ancient heritage.…”

“…The related studies regarding geometric feature importance are discussed by [30,31]. The ML-MR method, which relies on a hierarchical classification approach, follows the procedure proposed by [34] for the case of heritage objects. The classification method was derived from the successful tests by [43][44][45] on the application of the RF for the point cloud classification of heritage objects.…”

“…The related studies regarding geometric feature importance are discussed by [30,31]. The ML-MR method, which relies on a hierarchical classification approach, follows the procedure proposed by [34] for the case of heritage objects.…”

Achieving Universal Accessibility through Remote Virtualization and Digitization of Complex Archaeological Features: A Graphic and Constructive Study of the Columbarios of Merida

“…The aim of this research is to generate a methodology that allows us to unify, codify, and standardise the documentary and graphic management of cultural heritage and make it accessible to technicians who develop projects in the future. The application of the HBIM method to heritage projects offers great advantages when it comes to obtaining information, ordering and systematising existing documentation, and obtaining data with greater reliability [1][2][3][4].…”

“…information, ordering and systematising existing documentation, and obtaining data with greater reliability [1][2][3][4].…”