RAMBEA SIGNED

Project "RAMBEA" data sheet

The following table provides information about the project.

 Partnership

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Map

 Project objective

The RAMBEA project will develop a novel computational strategy for accurate and efficient simulations of historical masonry bridges subject to extreme environmental actions, including loadings induced by earthquakes and flooding. The aim is to provide a comprehensive tool for realistic assessment with the potential of transforming current practice related to strengthening of critical assets, contributing to an increased resilience of the built environment and the preservation of important elements of the architectural heritage, thus responding to the safety and socio-economic needs highlighted in Horizon 2020. Old masonry bridges still play a critical role within the European transportation system. Moreover, they belong to the architectural heritage representing a valuable expression of past construction technology. Many of these structures are located in seismic regions and in areas subject to floods and hydrogeological instability which have been aggravated by climate change. Thus they can be exposed to extreme environmental actions which may potentially lead to bridge failure causing significant economic damage and the loss of structures with cultural and historical value. Currently, the response of masonry bridges under extreme loading is evaluated using simplified models due to the lack of efficient detailed models. However, these approaches do not allow for the complex 3D behaviour potentially leading to unrealistic and unsafe predictions. The main challenge of this project is the development of a more advanced strategy, based on a novel numerical description allowing for the 3D interaction between the different bridge components under extreme loading. More specifically, I will develop an efficient 3D finite element representation with macro-elements for the masonry parts of the bridge, an accurate description for the physical interface between masonry and backfill and an effective model calibration strategy utilising the results of non-destructive tests.