The evolution of the tools and techniques of survey of the historical built heritage has reached technological levels that allow the acquisition of a huge volume of data in an increasingly limited time. This inversely proportional relationship between capability and acquisition time places the issue of managing the survey data more and more at the center of research. From this perspective, this work aims to offer systems and processes that can optimize the management, use, and analysis of a large amount of data in the field of historical architecture. In detail, the problem was addressed in two distinct areas: at the urban scale and at the scale of the building. At the urban scale, the goal was to implement and improve an existing management system within the company that hosted the PhD. Through case studies on historical centers such as Ascoli Piceno and Venice, instruments have been optimized, testing them in the particularly challenging context of the representation of historical architecture. As for the scale of the building, the research investigated the possibility of using the point cloud for the purposes of finite element structural analysis, through the generation of a semi-automatic process that allows to exploit the point cloud for the generation of the structural model. The case studies, on which the methodology was studied, focused on the typology of historic masonry towers. In both research areas addressed, the proposed solutions have been validated: in the urban environment the platform has been tested by its use in a professional environment; while in the building environment a comparison was made between the results provided by the structural model, obtained through the proposed methodology, and the experimental data recorded in the field.
L’evoluzione degli strumenti e delle tecniche di rilievo del patrimonio storico costruito hanno ormai raggiunto livelli tecnologici tali da permettere l’acquisizione di un enorme volume di dati in un tempo sempre più limitato. Questo rapporto inversamente proporzionale tra capacità e tempo di acquisizione pone sempre più al centro della ricerca il tema della gestione del dato di rilievo. In questa ottica il presente lavoro mira a offrire sistemi e processi in grado di ottimizzare la gestione, l’uso e l’analisi di una grande mole di dati nel campo dell’architettura storica. Nel dettaglio la problematica è stata affrontata in due ambiti distinti: alla scala urbana e alla scala dell’edificio. Alla scala urbana l’obiettivo è stato quello di implementare e migliorare un sistema di gestione esistente all’interno della azienda che ha ospitato il dottorato di ricerca. Attraverso casi studio su centri storici come Ascoli Piceno e Venezia, si sono ottimizzati strumenti, testandoli nell’ambito particolarmente sfidante della rappresentazione dell’architettura storica. In quanto alla scala dell’edificio la ricerca ha indagato la possibilità di utilizzare la nuvola di punti ai fini dell’analisi strutturale ad elementi finiti, attraverso la generazione di un processo semi-automatico che consenta di sfruttare la nuvola di punti per la generazione del modello strutturale. I casi studio, su cui la metodologia è stata studiata, si sono concentrati sulla tipologia delle torri storiche in muratura. In entrambi gli ambiti di ricerca affrontati, le soluzioni proposte sono state validate: nell’ambito urbano la piattaforma è stata testata dall’uso della stessa in ambiente professionale; mentre nell’ambito dell’edificio è stato condotto un confronto tra i risultati forniti dal modello strutturale, ottenuto attraverso la metodologia proposta, e i dati sperimentali registrati in campo.
Il dato di rilievo digitale per la conoscenza, valutazione e gestione del patrimonio storico costruito / Lucidi, Alighiero. - (2021 May 28).
Il dato di rilievo digitale per la conoscenza, valutazione e gestione del patrimonio storico costruito
LUCIDI, ALIGHIERO
2021-05-28
Abstract
The evolution of the tools and techniques of survey of the historical built heritage has reached technological levels that allow the acquisition of a huge volume of data in an increasingly limited time. This inversely proportional relationship between capability and acquisition time places the issue of managing the survey data more and more at the center of research. From this perspective, this work aims to offer systems and processes that can optimize the management, use, and analysis of a large amount of data in the field of historical architecture. In detail, the problem was addressed in two distinct areas: at the urban scale and at the scale of the building. At the urban scale, the goal was to implement and improve an existing management system within the company that hosted the PhD. Through case studies on historical centers such as Ascoli Piceno and Venice, instruments have been optimized, testing them in the particularly challenging context of the representation of historical architecture. As for the scale of the building, the research investigated the possibility of using the point cloud for the purposes of finite element structural analysis, through the generation of a semi-automatic process that allows to exploit the point cloud for the generation of the structural model. The case studies, on which the methodology was studied, focused on the typology of historic masonry towers. In both research areas addressed, the proposed solutions have been validated: in the urban environment the platform has been tested by its use in a professional environment; while in the building environment a comparison was made between the results provided by the structural model, obtained through the proposed methodology, and the experimental data recorded in the field. File | Dimensione | Formato | |
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