## 2 Methodology
### Numerical Setup  
The numerical setup closely reproduced the experimental conditions, with two exceptions: i.e., the swing gate was approximated by using an instantaneous release of the water in the reservoir at \(t=0\) s and the gate structure was modelled as two 0.08 \(\times\) 0.05 m rectangular columns as shown in Figure 1. Note that the coordinate axis in the transversal direction of the flume is mirrored with respect to the one used by [PERSON] et al. [22]. First, the hydrodynamics was calibrated to define the best combination of parameters to accurately simulate the experimental hydrodynamic conditions. All the most relevant parameters defined after initial calibration are summarised in Table 1, for the remaining fundamental parameters default values were used. A final particle spacing (\(dp\)) of 0.01 m was chosen as 0.02 m resulted in a higher tip of the flow (due to the larger size of the particles). A convergence test showed that results for \(dp<0.01\) m converged to those for \(dp=0.01\) m at the expense of a significant increase in computational time by increasing from 28 \(\times\) 10\({}^{6}\) particles with \(dp=0.01\) m to 54 \(\times\) 10\({}^{6}\) particles with \(dp=0.008\) m. \(dp=0.01\) m was also used as the dimensions of every element of the numerical setup is a multiple of \(dp\), allowing correct element sizes. Here the relationship, \(h_{l}=\) Coeft \(\sqrt{3 dp^{2}}\), was used to calculate the smoothing length \(h_{l}\) with Coeft being a calibration coefficient. Here Coeft \(=1\) was used since was already validated for dam-break flows. Note that, this value resulted in a ratio between the smoothing length and the particle spacing \(h_{l}/dp=1.73\) (Table 1) which was also chosen by [PERSON] et al. [32] to \begin{table}
\begin{tabular}{c c} \hline \hline
**Parameter** & **Value** \\ \hline \(dp\) (m) & 0.01 \\ Total number of particles & 28.9 \(\times\) 10\({}^{6}\) \\ Smoothing kernel & [PERSON], 1995 [50] \\ \(h_{l}/dp\) & 1.73 \\ Dissipative term & Artificial viscosity [44] \\ \(\alpha_{ff}\) & 0.04 \\ \(visc_{bf}\) & 9 \\ Density diffusion term & [PERSON] et al. 2020 [51] (only between fluid particles) \\ \hline \hline \end{tabular}
\end{table} 
Table 1: DualPSHysics parameters and formulations used. Figure 1: Numerical domain in (**a**) 3D view and (**b**) top view for OR1. simulate landslide tsunamis and considered suitable for the problem at hand. In this work no sensitivity analysis on the effect of this ratio on the modelling was carried out. In this study, to account for dissipation, i.e., to compute the \(\Gamma\) term in Equation (2), the artificial viscosity formulation [44] is applied since it was also successfully used to model other extreme hydrodynamic phenomena such as landslide-tsunami [52; 53]. The artificial viscosity parameter between fluid particles \(\alpha_{ff}\) was defined as 0.04 after initial calibration to ensure a coherent velocity of the dam break in relation to the experimental values. An additional calibration was performed for the viscosity between fluid and boundary particles \(\alpha_{fb}=visc_{bf}\times\alpha_{ff}\), with \(visc_{bf}\) being a viscosity multiplication factor. In this study \(visc_{bf}\) = 9 was used to approximate the roughness of the flume floor, which was covered in a paint/sand mixture, resulting in an estimated Darcy-Weisbach friction factor \(n\) = 0.014 [49]. \(visc_{bf}\) was calibrated making sure that velocity with the distance and arrival time of the flow to each wave gauge was reproduced accurately. Additionally, a density diffusion term was added to the continuity equation, i.e., Equation (6) by using the formulation of [PERSON] et al. [51] on the fluid particles. This additional term is commonly used to deal with density oscillations that are distinctive of SPH often resulting in incorrect and unstable pressure on boundaries or floating bodies. The container was simulated with dimensions of 0.15 \(\times\) 0.06 \(\times\) 0.06 m and a mass of 0.226 kg [22].