## 3 Results and Discussion  
The purpose of the soft ground embankment analysis was to verify the model parameters of the smear effect using the numerical method. In back-analysing drain behaviour, only parameters related to drainage behaviour were adjusted in order to fit the measured data. In order to fit the measured data, the permeability in the smear zone varied, and the values were back-calculated. The soil permeability values in Tables 3 and 4 were determined from Equations (1) and (6) for the development of numerical simulation models. The simulation results were compared with the measured data in Figure 5 in order to evaluate the smear effect parameter's performance. According to Figure 5a, 0.084 m of settlement was observed after 177 days of consolidation in model 2 with \(\eta=1\), while adopting \(\eta=300\) may result in a reduction of 0.061 m in consolidation settlement after the same elapsed time, thereby indicating that variations in the smear zone properties can affect the consolidation rate. Thus, it is clear that the \(\eta\) is a key factor in estimating the total of settlements in PVD analysis. Figure 5: Performance of ground settlement between predicted and measured for 177 days consolidated: (**a**) SMI; (**b**) SM2. As can be seen from Figure 5a,b, Model 1's prediction and measurement approximately equalled those of the \(\eta=1\) to \(\eta=300\) cases, thereby providing the best fit to the field-measurement comparisons of Model 2. On the other hand, the graph of Model 1 indicates that the total settlement was consistent with the different values of the smear effect parameters. In contrast to Model 2, the graph shows the existence of a smear effect parameter value of 20, which is a significant decrease. The values were once again relatively consistent until a \(\eta\) value of 40 was reached. The predicted values of total settlement at the \(\eta\) values of 100 were quite similar in both models. Interestingly, these predicted models are found to have a relatively same total of settlement at \(\eta=300\) as the measured values. Furthermore, it must be noted that the predictions made by both values of 300 were relatively close to the measured value. Therefore, with the existence of such alignments in values, it can be concluded that the models have similar disturbance rates. Hence, the magnitude of smear characteristics is also relatively the same as those measured in the smear zones. In order to assess the performance of numerical model prediction, the \(R^{2}\) and \(PD_{average}\) statistical parameters were employed. As shown in Figure 6, the \(R^{2}\) was generated from the graph, where the line y = x, in addition to the datasets of the total settlement, were depicted. This was to display a reasonable correlation between predicted and measured values. It is evident from this figure that Model 1's \(R^{2}\) exceeds 0.99 at two different locations. As expected, the \(R^{2}\) values in Model 2 increased with the permeability ratio. However, the \(\eta\) from 20 to 40 has an \(R^{2}\) of 0.97 and increases after \(\eta=100\). The analysis indicates that \(\eta\) at 300 for the models was found to have a similar and accurate prediction of \(R^{2}=0.99\). From the graph in Figure 7, it can be observed that the highest \(R^{2}\) is 0.9985 at \(\eta=1\) at the right of the embankment, while at \(\eta=300\), the \(R^{2}\) value of 0.9974 is at its lowest and is at the left of the embankment. Furthermore, the values of \(\eta\) at 6, 10 and 40 had a similar \(R^{2}\) value of 0.9983 at two different locations. This clearly indicates that the coefficients of these three parameter values are of high reliability and efficiency. Further analysis revealed that \(\eta=1\) for model 2 had the highest \(PD_{average}\) of about 90 to 100%, as shown in Figure 8. Nonetheless, the lowest \(PD_{average}\) for model 2 was found at \(\eta=200\) at about 5%. On the other hand, the best prediction performance was obtained in model 1, with a \(PD_{average}\) of about 1 to 10%.