Multi-level numerical modelling and analysis of tile vaults

The complex structural behaviour of masonry, with its brittle response in tension, frictional response in shear, and anisotropy, makes it challenging to model accurately. Tile vaults, with their unique features such as different binders and bricks placed flat, have distinctive structural performance, and determining the most suitable assessment method is still a subject of debate in both academic and professional circles. This paper presents a study on the structural analysis of tile vaults, aiming at evaluating different numerical approaches for this type of structure. The examination of these approaches and their effectiveness in capturing the structural behaviour of tile vaults intends to offer valuable insights to researchers and professionals in this field. Experimental research was initially carried out in order to provide data for the calibration of the structural models. Two full-scale vaults were tested. Furthermore, several material characterization tests were also performed. The numerical assessment was carried out through limit analysis and non-linear static analysis with numerical models based on the Finite Element Method (FEM). Two FEM models were prepared using different modelling approaches for masonry, namely the macro-modelling and the simplified micro-modelling approaches. The results of the limit analysis presented a load capacity significantly lower than the ultimate load obtained from the experimental tests. The calibrated FEM models presented good results in comparison to the experimental results, namely in terms of damage pattern and load capacity. This research, together with the APC, were funded by the Swiss National Science Foundation (“Schweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung”), grant number P2EZP2_181591. This work was supported by the FCT/MCTES through national funds (PIDDAC) under the R&D Unit Institute for Sustainability and Innovation in Structural Engineering (ISISE), under reference UIDB/04029/2020, and under the Associate Laboratory Advanced Production and Intelligent Systems ARISE under reference LA/P/0112/2020.