## 2 Materials and Methods
### Soil Sample Preparation and Model Setup  
The most tasking part of the model preparation procedures is shown in Figure 6. As per the preliminary sample preparations, the clean sand (ECS) and the industrial kaolinite were oven-dried between 50 and 70 \({}^{\circ}\)C for 24 h. Dry mixing by utilizing the mechanical mixer, as shown in Figure 6a, produced the mixed samples derived from both ECS and \begin{table}
\begin{tabular}{l l l l l l l} \hline \hline
**Sample ID** & \(C_{u}\) & \(C_{e}\) & **PI** & **Fines (\%)** &
\begin{tabular}{l} **Classification Based on** \\ **ASTM D2487-17 [13]** \\ \end{tabular} & **USCS Description and Symbol** \\ \hline ECS00 & 1.63 & 0.96 & NA & NA & \(C_{u}<6.0\) and \(C_{e}<1.0\) & Poorly graded sand (SP) \\ \hline ECS05 & NA & NA & NA & 5 & \(C_{u}<6.0\) and \(C_{e}<1.0\) & Poorly graded sand (SP) \\ \hline ECS10 & NA & NA & 2 & 10 & 5-12\% fines & Poorly graded sand with clay (SP-SC) \\ \hline ECS15 & NA & NA & 5 & 15 & \(>\)12\% fines & Clayey sand (SC) \\ \hline ECS20 & NA & NA & 7 & 20 & \(>\)12\% fines & Clayey sand (SC) \\ \hline ECS30 & NA & NA & 9 & 30 & \(>\)12\% fines & Clayey sand (SC) \\ \hline KK00 & NA & NA & 15 & 100 & _PI_ \(>7\) plots above the “A” line & Lean/inorganic clay (CL) \\ \hline \hline \end{tabular}
\end{table} 
Table 1: The derived unified soil classification system (USCS) of all studied soil specimens. Figure 5: SEM micrographs of kaolinite and east coast sand (ECS00). sand-kaolinite sand matrix mixtures. For all the studied soil samples, dried specimens were pluviated into the soil container using a manual pluviator, as shown in Figure 6b. Pluviated samples were then saturated with de-aired water from the side of the model and left to equilibrate for a minimum time of 72 h [14]. The de-aired water with 72 h resting time was used to ensure saturation, since it is impractical to carry out a B-value check to confirm the degree of saturation for the soil specimen. The soil specimens were covered by plastic wrap during this time to prevent the evaporation and further aeration of the de-aired water. The combined influence of effective confining stress and density/void ratios directly determines the liquefaction behavior of particulate materials, such as sand. Soil models were prepared with the configuration of low densities to simulate the in-situ evolution of dynamic excess PWP characteristics of liquefiable deposits in the laboratory. This approach was selected to make up for the effect of low confining stress and was similar to similar research found in the literature [15; 16]. Most of the prototype model setup procedures followed the guidelines of the liquefaction experiments and analysis project (LEAP) [14; 17] to ensure the replicability and repeatability of the sample preparation. The utilized national instruments chassis is the model PXIe-1078 coupled with suitable VI data cards and other hardware, as schematically shown in Figure 7a; the plan and longitudinal view of the test instrumentation are shown in Figure 7b,c, respectively. The applied instrumentation includes accelerometers of model 4030-series, manufactured by TE Connectivity (TE.com/sensorsolutions accessed on 20 July 2022), and flush pressure sensors of SS402 series, manufactured by Sendo-Sensor (sendo-sensor.com accessed on 20 July 2022). An accelerometer installed on the shaking table base allowed us to measure/capture the input base motion of the acceleration-time histories. Another accelerometer was placed at approximately 200 mm depth at the near-surface level inside the soil models to study the amplification and attenuation characteristics of the tested soils. Two PWP transducers  
Figure 6: Sample preparations for shaking table experiment. (**a**) Dry mixing of east coast sand and kaolinite. (**b**) Dry pluviation of soil samples into the instrumented soil box. were installed on the soil box at depths of about 100 mm and 200 mm to capture the PWP at the model's mid-depth and near-surface levels, respectively. All the sensors were connected and calibrated with the LabView DAQ system.