Avaliação qualitativa de registros de monitoramento geotécnico e modelagem numérica de um aterro sanitário experimental - Michelle Granha Giorgini (2019)
Landfill monitoring is an important tool because it allows to assess its geomechanical behavior and environmental performance, enabling the identification of changes in predicted behavior and the proposition of preventive and corrective measures, guiding the work of conservation and maintenance. Interpretation of geotechnical and environmental monitoring data, when obtained in a systematic and continuous way, allows the understanding of the behavior and a continuous assessment of landfill performance, mainly concerning geotechnical (stability) and environmental (contamination of the environment) safety, as well as contributes to the development of models for landfill behavior. Municipal solid waste is a very heterogeneous material with complex geomechanical and hydraulic behavior. From the geotechnical point of view, the main feature of MSW that makes it difficult to study its behavior, is the biodegradability, which causes a continuous change in geomechanical and hydraulic properties. In this context, this work analyzed data from 13 years of monitoring of an experimental sanitary landfill aiming to calibrate models and predict long-term settlements; evaluate qualitatively the relationships between precipitation, flow and the levels of liquid accumulated within a landfill; assess the applicability of computational models to predict long-term emissions of landfills, emphasizing settlements and the generation and quality of leachate. The results of the qualitative analysis indicated a reduction of discharges and an increase in minimum liquids levels in time, which may be related to a reduction of waste permeability and clogging of the drainage system. The results of the settlements models confirmed the need of using long periods of monitoring data to predict values closer to those observed in field. The results obtained with hyperbolic and rheological models significantly underestimate the settlements, regardless the period of data used in the calibration. The best fits were obtained with the composite model. The computational HBM model showed that it is able to produce results similar to those observed in the field.