## 5 Discussion  
The novelty of this study lies in its integrated simulation framework, which, for the first time, incorporates non-spherical particles, such as thin plates and rods, into a coupled DEM-FEM model for simulating water flow in heterogeneous porous media. This approach \begin{table}
\begin{tabular}{l c c c c c} \hline  & \multicolumn{2}{c}{**DEM Filling Simulation**} & \multicolumn{2}{c}{**FEM Fluid Simulation**} \\ \cline{3-6}  & \multicolumn{2}{c}{**Complex Time**} & \multicolumn{2}{c}{**Image**} & \multicolumn{2}{c}{**Mesh Count**} & \multicolumn{2}{c}{**Required**} & \multicolumn{2}{c}{**CPU Time**} \\  & \multicolumn{2}{c}{**CPU Time**} & \multicolumn{2}{c}{**Processing Time**} & \multicolumn{2}{c}{**Mesh Count**} & \multicolumn{2}{c}{**Memory**} & \multicolumn{2}{c}{**CPU Time**} \\ \hline Case 1 & Uniform particles & 0.5 h & 5 min & 553,858 & 30 GB & 3 min \\ Case 2 & Particle size distribution & 6 h & 18 h & 29,784,789 & 312 GB & 1 h \\ Case 3 & Mixed plates and bars & 3 h & 6 min & 1,646,887 & 24 GB & 58 min \\ \hline \end{tabular}
\end{table} 
Table 1: Computational resources required for each case study in DEM-FEM simulations, including CPU time, memory usage, and mesh resolution. Case 2, with a wide range of particle sizes, resulted in the highest computational demand due to increased mesh complexity. addresses a significant gap in previous research, where most DEM-based simulations have been limited to spherical or simplified particle geometries. By considering more realistic particle shapes, the proposed model more accurately reproduces the variability in pore structure and the resulting water channel flow behavior often observed in landfill layers. Another important contribution of this framework is its ability to overcome the limitations of conventional experimental methods such as X-ray computed tomography (CT). In the analysis of landfill waste, X-ray CT has limitations, such as a penetration depth of only a few centimeters, sensitivity to noise from metals, and the inability to study heterogeneities at actual scales. In contrast, the numerical approach in this study enables the large-scale three-dimensional reconstruction of pore structure and fluid flow fields using adjustable parameters and controlled geometric shapes. Despite its strengths, several limitations need to be addressed in future work to improve the applicability and reliability of this method. First, the current framework is proposed as a proof of concept and has not yet reached the stage of providing statistically representative results. To make quantitative conclusions, multiple simulations under specific conditions will be required to evaluate the variability in the flow paths and extract meaningful averages. Second, the virtual porous media in this study were generated by freefalling deposition with simplified and fixed DEM parameters. Frictional effects were intentionally neglected to reduce the computational effort. However, in real landfills, compaction processes, particle deformability, and non-uniform loading conditions significantly affect pore connectivity. Therefore, further development should include sensitivity analyses for DEM parameters and the implementation of more realistic boundary conditions and scaling considerations. In addition, experimental validation of the simulated flow structures is a major challenge. Real-time, three-dimensional visualization of water channel flow remains technically challenging. Techniques such as time-lapse electrical resistivity tomography (ERT) [23] or particle image velocimetry (PIV) [24] can provide validation but are often expensive and require specialized instrumentation. Thus, the development of simplified yet effective methods for validating water channels in porous media remains an open research frontier.