The rise in urban flooding events poses a threat to public safety, property, and economic
stability. To prevent urban flooding and manage stormwater effectively, relying solely on …

The computational expensiveness of the hydrodynamic models and the complexity of the
rainfall-runoff transformation process presents a pressing need to shift to machine learning …

Large-scale hydrodynamic models generally rely on fixed-resolution spatial grids and model
parameters as well as incurring a high computational cost. This limits their ability to …

Hydromechanical behaviour of unsaturated expansive soils is complex, and current
constitutive models failed to accurately reproduce it. Different from conventional modelling …

Hydrodynamic models can accurately simulate flood inundation but are limited by their high
computational demand that scales non-linearly with model complexity, resolution, and …

Mitigating severe losses caused by pluvial floods in urban areas with dense population and
property requires effective flood prediction for emergency measures. Physics-based models …

Urban floods pose a significant threat to human communities, making its prediction essential
for comprehensive flood risk assessment and the formulation of effective resource allocation …

Climate change and urbanization have increased the frequency and severity of flood
disasters. Effective flood risk assessment is essential to develop management measures …

Data center thermal management requires a good understanding of critical cooling airflow
path. While CFD modeling excels at portraying airflow and temperature fields, it is often …

Study on soil classification using piezocone penetration test (CPTU) has accumulated a
considerable number of research findings. Inspired by the rapid developments in machine …