Nonstructural components (NSCs) are not part of the structural load-resisting system but are relevant for building functionality. Typical examples are partition walls or parapets in ordinary buildings or artistic pieces in monumental ones.Damage to NSCs is a recurring topic, even when considering seismic intensities lower than those producing structural damage, and its repercussions are critical from a monetary loss and life-safety risk perspective. NSCs are classified depending on their sensitivity to accelerations, deformations, or both. The NEWTON (NEW TOols to compute the seismic demand on Non-structural components) project focuses on the acceleration-sensitive ones. The seismic demands on acceleration-sensitive NSCs are usually considered by using a floor response spectrum (FRS) approach. According to this approach, the trickiest aspect is the proper definition of the seismic input in terms of FRS to be used to verify NSCs. FRS are greatly influenced by the properties of the seismic input, the NCS itself, and the main building. The latter acts as a filter, by amplifying in the elastic phase the seismic input in correspondence of its natural periods. In the last few decades, significant efforts have been made to better understand the parameters influencing FRS, and to propose and validate expressions for their prediction, but is still far from straightforward to derive systematic trends. In this framework, NEWTON aims to understand the seismic amplification phenomenon better and to implement new tools to predict the seismic demands on NSCs. Employing this opportunity, the project methodology will combine theoretical and numerical approaches, validated with the results of shaking table tests planned and performed on scaled prototypes of ordinary reinforced concrete (r.c.) and unreinforced masonry (URM) building typologies.
Name: NEWTON - NEW TOols to compute the seismic demand on Non-structural components
Start date: 28.09.2023
End date: 28.09.2025
Duration: 24 months
Funded by the Italian Ministry of University and Research within the 2022 PRIN
Participants: University Federico II of Naples and University of Genoa