There has been a strong tendency in recent decades to develop real-time urban flood
prediction models for early warning to the public due to a large number of worldwide urban …

Surrogate models replace computationally expensive simulations of physically‐based
models to obtain accurate results at a fraction of the time. These surrogate models, also …

Recent breakthroughs in artificial intelligence (AI), and particularly in deep learning (DL),
have created tremendous excitement and opportunities in the earth and environmental …

In many fields, such as environmental risk assessment, agronomic system behavior,
aerospace engineering, and nuclear safety, mathematical models turned into computer code …

The rapidly growing global need for environmentally friendly energy solutions has inspired
extensive research and development efforts aimed at harnessing the potential of hydrogen …

Efforts to diagnose the risks of a changing climate often rely on downscaled and bias-
corrected climate information, making it important to understand the uncertainties and …

Urban energy poverty remains a critical challenge affecting millions worldwide, with
significant implications for socio-economic development and sustainability. This study …

The model-based system engineering approach consists of assembling subsystems
together to model a complete system. In this context, some functional blocks can have a …

Surrogate models are indispensable tools in uncertainty quantification and global sensitivity
analysis. Polynomial chaos expansion (PCE) is one of the most widely used surrogate …

Urban flooding is a major problem for cities around the world, with significant socio-
economic consequences. Conventional real-time flood forecasting models rely on …