Structural diagnosis of masonry heritage: contributions to non-destructive testing, structural health monitoring and risk assessment
- Autores: Nirvan Chandra Makoond
- Directores de la Tesis: Luca Pela (dir. tes.), Climent Molins Borrell (codir. tes.)
- Lectura: En la Universitat Politècnica de Catalunya (UPC) ( España ) en 2020
- Idioma: español
- Materias:
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- Resumen
Many cultural heritage sites across the globe consist of masonry structures. To ensure the preservation of such structures, an accurate evaluation of their current structural condition is often of utmost importance. However, recurrent uncertainties regarding material properties and the complex interaction among structural elements often makes this a challenging task. As a consequence, there has been a considerable research effort on the development of methods and tools that can facilitate this task, and experts responsible for the evaluation of unique masonry structures usually need to weigh information from various diagnosis activities before deciding the best course of action for preservation. In a first instance, the research work presented in this thesis contributes to the enhancement of some key methods for the analysis of masonry structures. Specific topics dealing with materials testing, full-scale vibration testing, and static structural health monitoring (SHM) are addressed. Subsequently, this is built upon to develop specific decision support tools that can assist decision-making for risk mitigation.
The research in materials testing involved an experimental study on the dynamic elastic properties of brick masonry constituents, which are known to differ from their static counterpart. Despite being a fundamental deformation property, experimentally determining the static elastic moduli of brick masonry constituents remains a challenging task. Following an experimental campaign, this research proposes a robust procedure based on the synergy of two non-destructive testing methods to reliably estimate the dynamic elastic and shear moduli of such materials. In addition, an empirical expression to estimate the static elastic modulus of constituents from its dynamic counterpart is also provided.
With respect to vibration testing, the present study deals specifically with masonry bell towers and the operational modal analysis (OMA) techniques used to extract modal parameters from test acquisitions. Despite significant advances in OMA techniques, the accuracy of resulting estimates from vibration tests are still highly dependent on test conditions, acquisition quality, and on the techniques employed for modal parameter estimation. This work first aimed to design a suitable acquisition system and program for the vibration testing of the bell tower of Seu Vella in Lleida, Catalonia. Several system identification and modal analysis techniques were investigated and the most suitable ones for identifying particular modal parameters under varying acquisition conditions are discussed.
The SHM research component is particularly focused on data analysis for static SHM systems, which involve the continuous measurement of key slow-varying parameters over long time periods. Although such systems have the potential to identify slow irreversible deterioration mechanisms in masonry structures at a very early stage, the interpretation of acquired data can be difficult, particularly due to the influence of environmental factors. This research proposes a fully automated data analysis procedure able to filter out reversible environmental effects and classify monitored responses in pre-defined evolution states. The procedure has successfully been used to identify vulnerable areas in two important medieval heritage structures in Spain, namely the cathedral of Mallorca and the church of the monastery of Sant Cugat.
Finally, all the findings in specific topics are built upon to elaborate multi-criteria decision-making (MCDM) tools meant to improve the objectivity, clarity, and transparency of risk mitigation decisions for masonry heritage. A systematic risk assessment procedure is proposed involving the computation of two MCDM indices: an index related to the estimated risk of damage, and another to the uncertainty behind this estimation. Applications to several case studies are also included to demonstrate the usefulness of the proposed tools.
