Experimental Dataset on Ghost Hammering Phenomena in Nonlinear Shell Structures under Stochastic Excitation

This dataset supports the experimental investigation presented in the paper "Ghost Hammering in Randomly Excited Nonlinear Dynamical Systems" by Prof. Francesco Pellicano and Prof. Antonio Zippo. The research focuses on the emergence of complex vibrational phenomena in nonlinear shell structures subjected to stochastic excitation. Notably, the dataset captures high-amplitude, irregular spikes—termed Ghost Hammering—that mimic impact-like responses in the absence of any actual external impulses.

These ghost spike events exhibit strong analogies with Extreme Events, Stochastic Resonance, and Spiking Oscillations, as studied in Neuroscience and Physics. The dataset includes time series measurements of structural response variables, such as velocity and acceleration, recorded under well-defined experimental conditions. A detailed description of the experimental setup—including structural configuration, excitation characteristics, sensor placement, and material properties—is provided in the associated paper.

The study demonstrates that traditional linear modeling approaches fail to represent such nonlinear phenomena, whereas nonlinear dynamical models like the van der Pol and FitzHugh–Nagumo oscillators offer more accurate and insightful representations of the system's behavior. This dataset underscores the potential of applying cross-disciplinary stochastic nonlinear models to challenges in Structural Mechanics.