## 3 Environmental Vibration Test and Linear-Elastic Modeling  
The experimental tests were performed on the instrumented hospital building in 2023. Five Raspberry Shake-based sensors (four RS4D and one RS3D models) were deployed within the hospital (hereafter called the HVB building). The RS4D sensor contains a three-axis MEMS accelerometer and a 4.5 Hz vertical sensor (with a sensitivity of 3.36 counts/meter/second), while the RS3D sensor contains three orthogonal 4.5 Hz sensors (with a sensitivity of 3.60 counts/meter/second). Additional technical details can be found at [[https://manual.raspberryshake.org/_downloads/RSGlobalTechnicalSpecificationsDocument.pdf#page=19](https://manual.raspberryshake.org/_downloads/RSGlobalTechnicalSpecificationsDocument.pdf#page=19)]([https://manual.raspberryshake.org/_downloads/RSGlobalTechnicalSpecificationsDocument.pdf#page=19](https://manual.raspberryshake.org/_downloads/RSGlobalTechnicalSpecificationsDocument.pdf#page=19)) (accessed on 11 December 2024). Figure 3 shows the location of the monitored building, as well as the permanent installation scheme and photographs of installed measurements, and Table 1 describes the main characteristics of the instrumented building. With the aim of evaluating the efficiency of the installed stations of Vega Baja hospital, recordings prior and during the Algorfa event shown in Table 2 were analysed. \begin{table}
\begin{tabular}{c c c c c c} \hline \hline
**Building Code** & **Construction Year** & **Structure Type** & \begin{tabular}{c} **Building** \\ **Configuration** \\ \end{tabular} & \begin{tabular}{c} **Sensors** \\ **Installed** \\ \end{tabular} & \begin{tabular}{c} **Location of the** \\ **Sensors** \\ \end{tabular} \\ \hline HVB & 1988 & \begin{tabular}{c} Reinforced \\ concrete, \\ mid-rise with RC \\ walls at the \\ basement \\ \end{tabular} & \
\begin{tabular}{c} 3 floors + stair \\ room (4 th floor) \\ \end{tabular} & 4 RS4D + 1 RS3D &
\begin{tabular}{c} 1 at 1 st floor, four \\ at 3 rd floor \\ \end{tabular} \\ \hline \hline \end{tabular}
\end{table} 
Table 1: Main characteristics of the instrumented building. \begin{table}
\begin{tabular}{c c c c c c c} \hline \hline
**Date** & **Hour** & **Latitude** & **Longitude** & **Depth** &
\begin{tabular}{c} **Magnitude** \\ **(mbLg)** \\ \end{tabular} & **Location** \\ \hline
10 July 2023 & 04:21:45 & 38.0623 & \(-\)0.8024 & 5.0 & 1.4 &
\begin{tabular}{c} SW \\ ALGORFA. A \\ \end{tabular} \\ \hline \hline \end{tabular}
\end{table} 
Table 2: Characteristics of the Algorfa event (10 July 2023). Table 2 provides a summary of the Algorfa event recordings, including details such as the recording date, time, and specific measurements collected by the stations. The parameters include the value of the latitude, longitude, depth, distance to hospitals, magnitude, and location. Since the environmental test techniques involve placing sensors in strategic locations, these would allow for the direct measurement of natural frequencies and vibration modes. The frequency response shows the spectral contents of the signal by showing both the presence and strength, as well as the distribution of different frequency components, which by using techniques such as Fourier analysis are able to identify specific frequencies. Indeed, exhaustive analysis has resulted in summarising the fundamental frequencies of the recorded signals in Table 3. Such information can define the basic features of the signals; therefore, it may lead to deeper insight and wide applicability in various domains. A critical step in developing an accurate structural model is calibration against real-world data. In this study, we leveraged valuable information from sensors. Table 3 presents the fundamental frequencies of the three velocity components recorded by sensor HVB04, located at the top of the building, both during and before the event. Additionally, the table includes the fundamental frequencies of velocity components for sensors HVB05, HVB02, and HVB01, also positioned at the top of the building, during and before the event.