| Flooding is a concern tonuclear power plants and can cause extensive damage. Unfortunately, flooding cannot be prevented, but the damage can be mitigated. To mitigate the damage, potential flooding events can be simulated. One method for simulating fluid flow is Smoothed Particle Hydrodynamics (SPH). SPH is a particle-based method. However, one issue is that there is no guidance on particle spacing selection, which affects the resolution of the simulation. The selection of particle spacing for a simulation is typically chosen by a brief parametric study. While a parametric study provides some information, it does not guarantee that the optimum particle spacing is being used.To determine the optimum particle spacing, a convergence optimizer was developed in Python. The goal of theconvergence optimizer was to determine the largest particle spacing that provided a converged result. A Neutrino model of fluid in a box was constructed with the fluid height analyzed using the convergence optimizer results as well as sphere packing arrangements. After analyzing the optimizer results and sphere packing results, it was determined that the Neutrino height method provides an assumption of a simple cubic arrangement resulting in overestimating the fluid height.An improvedmethod for fluid height analysis was constructed in the form of a Python dynamic expression script and was validated using the flow over an ogee spillway comparison. The improved fluid height analysis method provides between a 15% to43% improvement compared to the Neutrino results. Finally, the model was reanalyzed using the convergence optimizer and improvedfluid height analysis method. From those results, a particle spacing protocol of 12 particles per the smallest dimensionwas determinedand verified. |