The contribution explores the application of Building Information Modelling (BIM) to the documentation and conservation of historical heritage, with a focus on degradation phenomena. The analysis of historical architecture and archaeological sites requires a methodical and integrated approach to manage the information collected over time. The introduction of BIM and semantic modelling makes it possible to gather and structure data in a unified environment, improving efficiency in heritage management. The research focuses on the development of a workflow for the analysis of degradation, through a parameterisation of data aimed at interrelating heterogeneous information and providing an exhaustive description of the alteration phenomena that can affect architectures. The experimentation made it possible to test the proposed solutions, applying numerical evaluation methods to classify defects and determine the vulnerability of architectural elements. The proposed methodology departs from purely graphic approaches, using a vulnerability index to facilitate information management and the planning of restoration work. The results show that the quantitative and modular approach adopted, although with some limitations, offers a solid basis for the integration of information and predictive management of conservation interventions.
Protocolli BIM per la parametrizzazione dei fenomeni di degrado
Marco Limongiello
;Andrea di Filippo;
2025
Abstract
The contribution explores the application of Building Information Modelling (BIM) to the documentation and conservation of historical heritage, with a focus on degradation phenomena. The analysis of historical architecture and archaeological sites requires a methodical and integrated approach to manage the information collected over time. The introduction of BIM and semantic modelling makes it possible to gather and structure data in a unified environment, improving efficiency in heritage management. The research focuses on the development of a workflow for the analysis of degradation, through a parameterisation of data aimed at interrelating heterogeneous information and providing an exhaustive description of the alteration phenomena that can affect architectures. The experimentation made it possible to test the proposed solutions, applying numerical evaluation methods to classify defects and determine the vulnerability of architectural elements. The proposed methodology departs from purely graphic approaches, using a vulnerability index to facilitate information management and the planning of restoration work. The results show that the quantitative and modular approach adopted, although with some limitations, offers a solid basis for the integration of information and predictive management of conservation interventions.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.


