Parameter evaluation in historical construction: from sensitivity analysis to the test planning

12th International Conference on Structural Analysis of Historical Constructions(2021)

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摘要
Uncertainties play a key role in the structural assessment in the existing buildings. They are mainly associated with materials, geometries and loads. The reduction of these uncertainties is one of the main challenges for researchers who approach this type of project. The aim of this work is the reduction of uncertainties through a sensitivity analysis. These analyses allow understanding the structural overall behaviour and they are useful to the in-situ test planning. The proposed sensitivity analysis is used as cognitive evaluation, analyzing the influences of each parameter on the structural behaviour, and as improvement assessment, evaluating the effectiveness of the intervention proposals. Furthermore, such approach reduces the impact of the experimental campaign and the intervention proposals, in terms of invasiveness, time and cost. The research is carried out through the selection of a case study, the "Quartel da Tropa" (SC), Brazil. It is used to show how the proposed approach can be applied for the structural assessment of historical buildings. The information collected was elaborated with Historical Building Information Modeling (H-BIM) and analyzed through finite element method software. The proposed research allows increasing the level of knowledge of the historical construction of the Quartel da Tropa, through the sensitivity analysis and the experimental test design of the structure. Such an approach suggests how not only the longitudinal Young's Modulus (E) and the specific weight (w) of the masonry are the main parameters to avoid significant errors in the results in terms of structural assessment. Indeed, type of wooden species, type of structural connection, different types of masonry characteristic in different structural elements must be considered.
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关键词
H-BIM,Historical Buildings,Masonry Structures,Sensitivity Analysis
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