Knowledge Methods to Extend the Service Life of Historic Timber Roofs
DOI:
https://doi.org/10.6092/issn.2036-1602/8828Keywords:
construction history and preservation, terrestrial laser scanning, parametric modeling and reconstruction, timber hygroscopic and rheological behavior, service lifeAbstract
The analysis of historical timber roofs is a topic widely dealt with in literature both in the disciplinary field of “theory of construction” and “construction technologies”, and in that of architectural technology and restoration. The specialist literature, however, has often simplified the constructive conception and evolution of these artifacts that, even when they stand still to date, show the signs of a long life, often hidden and little-known, even with regard to frequent changes over time. This paper aims to outline a methodological approach for an in-depth assessment of historic timber roofs, in order to extend their service life. In a holistic conception, digital technologies collaborate to identify mechanical, rheological and hygroscopic phenomena on wood elements over time, highlighting displacements, deformations and, generally, decay. Some case studies analyzed in the territory of Bologna were a useful starting point to achieve a thorough understanding of these artifacts, primarily based on survey, digital modeling and structural analysis. This academic approach, based on generative algorithms, is useful to attempt a more in-depth and transversal understanding of the behavior of these wooden structures, focusing on geometric surveying and constructive analysis. Developing and following a methodology accelerates modeling procedures and brings on new tools for analyzing these structural systems surveyed through Terrestrial Laser Scanning (TLS) devices. It also enables to store acquired results in BIM models in order to perform further analyses over time. The acquired knowledge of the structural behavior of timber structures is fundamental for their maintenance and for potential renovation.
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Copyright (c) 2018 Luca Guardigli, Giovanni Mochi, Davide Prati
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