Structural Health Monitoring of Dams Based on Acoustic Monitoring, Deep Neural Networks, Fuzzy Logic and a CUSUM Control Algorithm.

Internal erosion is the most important failure mechanism of earth and rockfill dams. Since this type of erosion develops internally and silently, methodologies of data acquisition and processing for dam monitoring are crucial to guarantee a safe operation during the lifespan of these structures. In this context, artificial intelligence techniques show up as tools that can simplify the analysis and verification process not of the internal erosion itself, but of the effects that this pathology causes in the response of the dam to external stimuli.

Enhanced landfill's characterization by using an alternative analytical model for diffusion tests.

Landfills have been extensively used as waste deposits in most of the big cities in the world. Therefore, considerably large urban areas have contamination threats. Engineering solutions applied to prevent or contain soil, and water contamination often involve the application of liners, which are low permeability barriers made of materials such as compacted clay and geomembranes.

Modelling the spread of covid-19 in the capital of Brazil using numerical solution and cellular automata.

The novel coronavirus disease 2019 (COVID-19) still challenges researchers due to its spread and deaths. Hence, the classical epidemic SIR and SEIRD models inspired by the epidemic's outbreak are widely used to predict the evolution of the disease. In addition to classical approaches, describing complex phenomena through Cellular Automata (CA) is a highly effective way to understand the iterations on a populated system.