RESUMO Desde 2010, o governo brasileiro exige que as barragens que se enquadram na política nacional de barragens apresentem um plano de segurança que, entre outros tópicos, deve abordar a definição de hipóteses e possíveis cenários de desastre. Para isso, a mancha de inundação causada pelo possível rompimento deve ser modelada para a classificação da barragem quanto ao Dano Potencial Associado (DPA). A mancha de inundação é resultado de fenômenos hidráulicos complexos e difíceis de caracterizar. Diante da demanda por análises de DPA e da indisponibilidade de dados, a Agência Nacional de Águas (ANA) propôs uma metodologia simplificada para geração da zona de inundação. Este artigo propõe uma implementação em Python para esta metodologia com uma interface gráfica amigável ao usuário para a modelagem simplificada de manchas de inundação causadas pelo rompimento de barragens. Nossa implementação é baseada em software livre e de código aberto. Os resultados são similares aos produzidos pela implementação original e podem ser gerados consideravelmente em menor tempo e com menos interação do usuário.

ABSTRACT Since 2010, the Brazilian government has required that dams that fall within the national dam policy must present a safety plan, which, among other topics, must address the definition of the hypotheses and possible disaster scenarios. To achieve it, the flood zone due to an eventual failure must be modeled for the Hazard Potential (Dano Potencial Associado – DPA) classification. The flood zone is the result of complex hydraulic phenomena that are difficult to characterize. Given the demand for DPA analysis and the data unavailability, the National Water Agency (Agência Nacional de Águas - ANA) proposed a simplified methodology for generating the flood zone., This paper proposes a Python implementation for this methodology with a user-friendly Graphical User Interface. Our implementation relies on free and open-source software. The results are similar to those produced by the original implementation and can be generated considerably in less time and with less user interaction.

Abstract The creation of tridimensional models that represent the quality and geomechanical characteristics of the rock mass to be excavated can be made by using spatial interpolation techniques. The aim of this research is to improve the safety in underground activities, as well as to spread and popularize the use of spatial interpolation methods to represent both the spatial continuity of the quality of the rock mass and the geomechanical variables through geostatistical methods. This article presents and demonstrates the viability of using Q-System block models estimated from the borehole data for previous classification of the rock mass surrounding the underground excavation and rock support design. The block model for the support design of galleries is justified because it allows to previously forecast the kind and quantity of support necessary for the stability of the excavation, as well as the costs with these devices, besides increasing the safety in the operations. Techniques of indicator kriging and ordinary kriging were used to build the Q-System index block model. The model was validated through the techniques of visual inspection and cross validation. The data used in this study were collected from the geotechnical description of 39 borehole core samples with a total measurement of 4,015 meters in Fazenda Brasileiro Mine, located in the town of Teofilândia, Bahia State, Brazil.

Abstract Evaluating mineral resources requires the prior delimitation of geologically homogeneous stationary domains. The knowledge about the ore genesis and geological processes involved are translated into three dimensional models, essential for planning the production and decision-making. The mineral industry usually considers grade uncertainty for resource evaluation; however, uncertainty related to the geological boundaries are often neglected. This uncertainty, related to the location of the boundary between distinct geological domains can be one of the major sources of uncertainty in a mineral project, and should be assessed due to its potential impact on the ore tonnage, and consequently, on enterprise profitability. This study aims at presenting three different methodologies capable of generating multiple geomodel realizations and thus, assessing uncertainty. A real dataset with high geological complexity is used to illustrate the methodology. The results are compared to a deterministic model used as a reference scenario.

Abstract Prior to every geostatistical estimation or simulation study there is a need for delimiting the geologic domains of the deposit, which is traditionally done manually by a geomodeler in a laborious, time consuming and subjective process. For this reason, novel techniques referred to as implicit modelling have appeared. These techniques provide algorithms that replace the manual digitization process of the traditional methods by some form of automatic procedure. This paper covers a few well established implicit methods currently available with special attention to the signed distance function methodology. A case study based on a real dataset was performed and its applicability discussed. Although it did not replace an experienced geomodeler, the method proved to be capable in creating semi-automatic geological models from the sampling data, especially in the early stages of exploration.