Abstract:
This thesis presents a novel methodology for urban flood risk assessment, leveraging a state
of-the-art 3D urban flood modeling technique. Utilizing the Volume of Fluid (VOF) method within
ANSYS Fluent, this approach innovatively simulates and analyzes complex flooding scenarios in
urban environments. The model's accuracy is critically evaluated using the Mean Absolute
Relative Error (MARE), ensuring precise and reliable results. At the heart of this study is an in
depth analysis of three variations of the K-epsilon turbulence model: Standard, RNG (Re
Normalization Group), and Realizable. Each is rigorously tested within the context of the 'Model
City Flooding Experiment', providing a comprehensive comparison. The research further explores
the influence of urban building configurations, examining both aligned and staggered layouts, and
their effects on flood behavior. Advanced statistical methods, including Nash-Sutcliffe Efficiency
(NSE) and the R2 coefficient of determination, are employed to validate the superior performance
of the Realizable K-epsilon model in capturing urban flooding complexities. Additionally, a
sensitivity analysis is conducted, focusing on the interaction between key factors such as the
roughness model, the choice of turbulence model, and the level of grid refinement. This analysis
reveals that increased roughness height, implementation of the K-epsilon model, and a denser grid
significantly enhance the model’s fidelity, albeit increasing the simulation time. This research not
only introduces a sophisticated tool for refined urban flood risk assessment but also lays the
groundwork for future enhancements in the precision and application of urban flood models,
especially in complex terrains prone to rapid or dam-break flooding.
Keywords: ANSYS; numerical Simulation; Computational fluid dynamics (CFD); Urban
flooding; 3D flood inundation modeling; flash flood experiment
