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Flexible roofs are sensitive to wind actions because they are light, and their deformability can induce local or global instability. In most cases, their design requires experimental wind tunnel testing to investigate the aeroelastic phenomena and the structural response under the wind. However, the reduced scale necessary in wind tunnels makes the dynamic identification of the test model difficult. Several approaches of multi-modal dynamic identification can be used, even if a specific approach is not defined for geometric nonlinear flexible roofs. Many times, the choice of the position of the sensors is affected by the unknown roof dynamics. This paper investigates the ambient vibration time-dependent accelerations for a flexible roof scaled model through Singular Value Decomposition (SVD) and their spatial correlations with the purpose of analyzing the signal structure and its acquisition to perform the dynamic identification of the test model.

The aeroelastic wind tunnel testing of flexible roofs made of hyperbolic paraboloid cable nets is a challenging task for designers and researchers, with very limited documented experiences in the literature. The reduced-scale model construction and its dynamic identification are the main issues to address when approaching this problem, mainly because of (i) the very small mass of the roof, (ii) the strict aeroelastic criteria to satisfy and (iii) a large number of very closely spaced significant natural frequencies. To suggest an approach to follow to investigate the wind—structure interaction for this structural typology, this paper discusses the aeroelastic scaling, the aeroelastic model construction, the dynamic modal identification and the FEM predictive numerical modelling of hyperbolic paraboloid roofs (HPRs) with square, rectangular and circular plan shapes and two different curvatures. Modal identification is especially challenging due to the presence of several closely spaced modes and it is here tackled by different methods such as Welch’s method, random decrement technique (RDT), Empirical mode decomposition with a time-varying filter (TVF-EMD) and frequency domain decomposition method (FDD). The satisfying accuracy of the aeroelastic scaling has been verified by comparing the wind-induced vertical displacements of the prototypes against those of the experimental models. Furthermore, an extensive qualitative investigation of the natural mode shapes has been carried out revealing that test models reproduce most of the prototype modes.