## 4 Results
### Regression Analysis
#### 4.1.4 Interpretation of Results  
The regression analysis elucidates the significant roles of the Froude number (\(Fr\)), squat ratio (\(Sq\)), squared time (\(t^{2}\)), and floating object type (\(Obj\_T\)) in predicting sediment resuspension, aligning with the findings from the numerical simulations. Specifically, higher Froude numbers substantially increase sediment resuspension due to enhanced flow velocities and shear stresses on the seabed. Similarly, the squat ratio (\(Sq\)) exhibits a positive and significant relationship with sediment concentration, indicating that higher squat ratios amplify sediment resuspension. This is consistent with the observed increase in flow velocities beneath the floating object as the squat effect intensifies. Additionally, the floating object type (\(Obj\_T\)) demonstrates a significant negative impact on sediment resuspension, suggesting that naked bow designs (\(Obj\_T\) = 1) are more effective in mitigating sediment disturbance compared to blunt bows (\(Obj\_T\) = 0). Also, the interaction term between the Froude number and object type (\(Fr\times Obj\_T\)) further refines this relationship, showing a negative coefficient of \(-\)0.7154 (\(p\) = 0.018). This interaction implies that the impact of the Froude number on sediment resuspension is moderated by the bow shape. This finding corroborates the hydrodynamic analyses, where blunt bows were observed to generate higher flow velocities beneath the object due to increased water displacement at the front. Figure 24: Normal Q-Q plot of model residuals. 4.1.5. Implications for Design and Operation  
The regression model provides a valuable predictive tool for estimating sediment resuspension based on operational parameters and floating object characteristics. The strong positive relationship between the Froude number and sediment resuspension underscores the importance of optimizing towing speeds and clearance heights to mitigate environmental impacts. Lowering the Froude number by reducing towing speeds or increasing clearance heights can effectively decrease suspended sediment concentrations, thereby minimizing ecological disruptions in sensitive marine habitats. The significant positive association of the squat ratio with sediment concentration emphasizes the need for careful consideration of floating object deformation under operational conditions. Designing floating structures with optimal squat ratios can reduce their propensity to disturb sediments. This can be achieved by selecting hull geometries that minimize deformation or by implementing structural features that stabilize the object's position relative to the seabed. Incorporating raked bow geometries can enhance the environmental performance of floating structures, making them more suitable for deployment in areas with sensitive benthic ecosystems. Overall, the regression model serves as a valuable predictive tool that informs design choices and operational practices aimed at minimizing sediment resuspension. By leveraging the relationships identified in the model, engineers and operators can develop strategies that balance operational efficiency with environmental stewardship, fostering sustainable maritime activities. 4.1.6. Limitations and Future Work  
While the regression model demonstrates strong predictive capabilities, it is important to acknowledge potential limitations. The dataset, comprising 84 simulation scenarios, while comprehensive, may not fully capture the diversity of real-world conditions encountered in marine environments. Expanding the dataset to include a broader range of operational scenarios and environmental conditions would enhance the model's generalizability and robustness. Additionally, the model's reliance on simulated data necessitates empirical validation through field studies to corroborate its predictive accuracy in natural settings.