Dataset for the paper "Monitoring of civil structures with nonlocal theory under instantaneous nonstationary loads" G. Miraglia

Abstract: Structural monitoring is an active field of research that aims to provide knowledge to preserve the built environment. Commonly, structural health monitoring involves mechanical characterization and damage identification steps that require the assumption of physical laws describing structural behaviour. Data-driven and model-driven approaches have been pursued for this purpose. However, while the former present problems in allowing an in-depth understanding of the physics behind the structural behaviour, the latter are characterized by problems related to uncertainty and the discrepancy of the model compared to reality. Peridynamics is a modern non-local theory capable of managing long-range forces and discontinuities in materials, which generalizes the classical continuum and particles theory in a single simpler theory. In the paper, Peridynamics is used to bridge the gap between data- and model-driven approaches and define synergistic approaches to structural health monitoring since the theory is able to describe a wider range of complex nonlinear behaviours, such as rocking and cracking, with a smaller number of physical parameters. In the paper, the author proposes and validates with experiments a new method for damage identification through the time-frequency distributions estimate of peridynamic parameters, where parameter values are also provided over the frequency domain, expanding the time-domain estimate. This dataset contains the codes and data used to verify and validate the methods reported in the paper "Monitoring of civil structures with nonlocal theory under instantaneous nonstationary loads" G. Miraglia.