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- W4205273360 abstract "Historic timber structures are frequently composed by elements with irregular sections. Moreover, due to abiotic and biotic agent action, wood is especially vulnerable to decay, which can lead to destruction of external layers of the element. Due to this, a beam's resistant cross-section, which is the healthy section part that supports the structure, and the beam external apparent cross-section may not coincide. This can lead to an improper structural assessment regarding the load-capacity of that element. HBIM technology is currently being used for the representation and analysis of historic timber constructions' structural health. In this work, a methodology is proposed and applied that, based on the combination of LIDAR data with non-destructive tests, allows to obtain a single 3D HBIM model of decayed irregular wooden structures. This HBIM model contains both the apparent parametric model, that represents the structure external geometry and collects all necessary data for construction's conservation analysis, and also a parametric resistant model, that represents the beam's undamaged section, allowing to carry out a more accurate structural analysis. In this work, the methodology was first applied to an irregular and decayed beam at laboratory conditions for framework calibration, and then applied to a case study for validation. With respect to the storage space, the volume difference between the rendered models and the proposed parametric models was on average 3.2%, whereas the occupied memory space was 10 times lower in the parametric models. The case study was the Guimarães chamber roof (Portugal) which structure is made up of several truss systems composed by irregular beams, several of which with signs of past decay activity." @default.
- W4205273360 created "2022-01-26" @default.
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- W4205273360 date "2022-05-01" @default.
- W4205273360 modified "2023-10-14" @default.
- W4205273360 title "Apparent and resistant section parametric modelling of timber structures in HBIM" @default.
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- W4205273360 doi "https://doi.org/10.1016/j.jobe.2022.103990" @default.
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