## 5 Conclusions  
Acquisition time dependence of significant magnitudes, such as singular values, eigenvectors and correlation coefficients of wind-induced floor accelerometric signals acquired on a scale model of a high-rise building, is discussed by examining their variability from one time interval to another.  
The entire wind tunnel data acquisition process was subdivided into fifteen 10 min recording sessions.  
The SVD was calculated for two wind angles, along and across wind, and for thirteen wind velocities for all recording sessions. It was found that variability of the singular value increases when the wind velocity increases and that there is a significant difference between along and across wind values. Across wind variability is much smaller than along wind. The same trend was noted for the eigenvectors. The probability density function (CDF) of the eigenvectors for different velocities and at different levels was fitted through numerical CDF. It was found that the GEV distribution gave the best fitting even if it was not satisfactory according to the Kolmogorov-Smirnov test. The three-dimensional trend of standard deviation as a function of building levels and wind velocities shows that the variability of the eigenvectors assumes its maximum along wind value at the building top and for the highest velocities.  
Likewise, the correlation coefficient between the top and the other levels was calculated, and its variability for the fifteen 10 min recording sessions was investigated. It was found that these values are closely affected by the randomness of the flow because it varies significantly from one time interval to another. The correlation coefficient at the building top between along and across wind measurements was calculated and was found to vary slightly more for velocities in the range from 40 m/s to 80 m/s and for low levels.  
The results discussed here show that uncertainty due to the randomness of wind tunnel wind flow affects structural response during aeroelastic tests. The dependence of results from the acquisition time length was confirmed and nonnegligible variability was observed. In particular, it was observed that the variability of the eigenvectors under wind increases with the wind velocity and distant from the ground along wind, whereas this trend flattens across wind. This uncertainty should be taken into account during experiments and output processing, examining the cumulative probability trends and assuming a reliable level of confidence for the estimated crucial magnitudes, such as the modal shapes, frequencies and damping ratio.  
This research was supported by the Italian Ministry of Education.  
The data used to support this research are available from the corresponding author upon request.  
The Author thanks [PERSON] and [PERSON] for their significant support during the experimentation sessions in the DICCA Wind Tunnel of the University of Genoa and [PERSON], University of Sannio (Benevento), for his support during shaking table experiments. He is also grateful to [PERSON] for his support during the model construction and to the company H-Sign srl for its support of this research.  
The author declares no conflict of interest.