The scope of the research activity of our group can be split into two fields:
On the one hand, a research line focused in the hydrologic aspects of dam safety. Inside this general topic we include research about failure mechanisms caused by overtopping and the design of protections that increase the dam safety in an efficient way. The other line within this topic is the increase of the discharge capacity of the dams using non-conventional spillways.
On the other hand, we have a research field focused on the increase of the structural safety of dams by means of applying machine learning techniques for the interpretation of the data from dam monitoring combined with numerical methods. We aim to develop accurate models to characterize the dam behavior in order to evaluate the safety levels. To do so, techniques such as Artificial Intelligence, Machine Learning, Data Mining and Finite Element Methods are used. The final goal is to provide numerical tools that can ease the exploitation engineers to perform a quick detection of anomalies that could trigger damages or the failure of the structure.