Abstract in English:

Abstract The shearing behavior of discontinuities is one of the factors with major influence on rock slope stability analysis, which is predictable when adopting different analytical models. However, these methodologies, generally of a purely deterministic nature, do not allow an assessment of the influence of the variability of the input parameters of the models on the shear behavior of unfilled rock discontinuities and, consequently, on the risk involved in the rock slope stability analyses. The purpose of this article is to present a methodology for rock slope risk assessment based on the development of a model to predict the shear behavior of unfilled rock discontinuity considering the variability of its input parameters, using a Mamdani fuzzy controller. The input variables of the model are the boundary normal stiffness and initial normal stress acting on the discontinuity, its roughness, the uniaxial compressive strength, the basic angle of friction of the intact rock and the shear displacement imposed on the discontinuity. The model outputs are the membership functions for the shear strength and dilation of the unfilled rock discontinuity, and from which the membership function can be defined for the factor of safety of the rock slope considering the failure mechanism governed by discontinuity. The results reveal the use and importance of fuzzy logic and fuzzy number operations in assessing the risk in rock slopes and may be used even in situations where there are major uncertainties on the existing information of the characteristics of the unfilled discontinuities.

Abstract in English:

Abstract One of the solutions in civil construction to increase the life cycle of buildings is the ventilated facade due to its technical characteristics. Large porcelain tiles are used as a coating in this system, raising questions about its performance. This study used real size porcelain tiles (590 mm × 1190 mm) for pressure tests to evaluate the deformation suffered by the material at different pressure points, according to NBR 10821. In addition, the strength of the glass fiber-reinforced ceramic tiles has been tested against the impacts of rigid and soft bodies in a hidden clamp ventilated system, according to NBR 15575. Due to the wind, the system presented maximum deformation of 1.7 ±0.4 mm. When subjected to impacts, the system functioned within the norm for hard body strikes (20 J), meeting the requirements against minor proportions and wind pressures of up to 1480 Pa. Unsatisfactory performance when impacted by a soft body was observed. Such results show that the system needs to improve regarding resistance to major impacts.

Abstract in English:

Abstract Among several works, constructions in rock masses are the most complex in engineering, due to many uncertainties of the environment. Tunnel construction is a case in point. A common problem found in tunnel excavations with the use of explosives is the occurrence of overbreak beyond the boundary line of the tunnel. Many researchers worldwide have proposed forecasting techniques based on the use of regression models or machine learning, however, these require many samples and variables, such as the explosive rate and rock mass. Predicting overbreak before blasting is essential in project management, as it can modify parameters of the blasting plan, design, schedule and employee safety. Therefore, this study sought to employ an exponential smoothing model, which could predict the percentage (%) of overbreak in a tunnel section, based solely on the previous overbreak values. This time series methodology has never been used before in tunnel excavations, although it is used in the financial market. The technique was tested in one Brazilian tunnel. The model proved to be very efficient in predicting overbreak in tunnel construction, since it can be adjusted at each advance. The model can be adjusted as a function of α: where α is close to zero, the model prioritizes past events, while for α close to 1, it prioritizes recent events. The best fit occurred with α = 0.9; 0<α<1.

Abstract in English:

Abstract Fluorspar (CaF2) is the most used flux in hot metal desulfurizing mixtures. However, its use can cause refractory wear and environmental contamination, prompting research efforts to develop alternative desulfurizing mixtures. This study aims to investigate the replacement desulfurizing mixtures containing fluorspar by other desulfurizing mixtures containing a new flux developed without fluorspar named MIX. The influence of varying the mass of these desulfurizing mixtures, temperature, and stirring of the system on the efficiency of hot metal desulfurization was also studied. The desulfurization experiments were carried out in an electric resistance furnace, at a temperature of 1370°C. Hot metal samples were taken to measure the change in sulfur content in the experiments. FactSage 8.0 software, was used to determine the phases present in the desulfurizing mixtures, and these phases were correlated with the hot metal desulfurization efficiency. The efficiency of the desulfurizing mixtures was also correlated with the Desulfurization Factor. The results showed that desulfurizing mixtures containing fiuorspar are the most efficient mixtures. However, fluorspar-free desulfurizing mixtures containing MIX can achieve similar efficiencies with increases in mass, temperature, and system stirring. The results also showed that the most efficient desulfurizing mixtures are those with higher percentages of solid CaO and lower percentages of the solid phases 3CaO.SiO2 and CaS and, consequently, a higher Desulfurization Factor.

Abstract in English:

Abstract Linked to important pillars of the Brazilian economy, studies related to mining and the use of UAVs (unmanned aerial vehicles) have been gaining ground in recent years, especially related to the geotechnics of dams and precision agriculture. However, the interdisciplinarity needed to carry out more robust analyses are still lacking in some areas, which brings up good opportunities to be explored. In this sense, the present study combined products obtained through different activities and methodologies, aiming at a solution that provides predictability to the mining dam management process, specifically linked to modeling and obtaining data on solid content in the tailings, arising from the processing of bauxite, based on geoprocessing. The activities necessary to achieve the sought objectives covered, briefly: 2021 tailings sampling campaign carried out in the Plateau Disposal System (RP1), laboratory analyses (humidity), aerial survey with Unmanned Aerial Vehicle (UAV), geoprocessing for the extraction of luminosity values of images and statistical analysis of dispersion. As a result, it was observed that the increase in the number of drying cracks (highlighted in the images by dark pixels) is directly related to the drying of the waste (increase in the percentage of solids), whose quadratic model presents an excellent relationship between the values of the pixels in the images and percentage of solids from laboratory data, implying a determination coefficient of 91.74%. Furthermore, gains in security, predictability and economy for the processes stand out, when compared to the traditional methods applied, in addition to an excellent potential to be developed in future studies.

Abstract in English:

Abstract This article aims to compilate stability measurement tests for explosive emulsions (EE), which were developed and used in the last decades. So, it could serve as a stability guide for EEs. The main methodologies to evaluate the condition of the emulsion’s matrix is through microscopy, DLS, viscosity, and rheology, which can preview the stability of a freshly manufactured emulsion within maximum 30 days, since it can undergo physically (centrifugation, compression, and direct contact with water). Thermal tests for (freeze-thaw) can also be performed.

Abstract in English:

Abstract The geotechnical monitoring of tailings dams combined with a suitable application of geophysical electrical methods can improve their structure evaluation, allowing several correlations between direct analyses and the resistivity anomaly pattern. Considering this synergy, twenty-three electrical resistivity sections (ERT) were acquired along the beach, abutments, and central part of a dam, totalizing 10,776 m of dataset. After the interpretation of each ERT section, comparing the anomaly ranges with the water level meters measurements, three resistivity zones were defined: Zones of low resistivity (<64 ohm-m), correlated to regions of high humidity; zones of high resistivity (> 357 ohm-m), interpreted as dry zones, and regions with intermediate resistivity values, located between these limits. The groundwater surface generated from the interpretation of the electrical resistivity dataset and the groundwater surface acquired from the water level gauges were almost coincident. On the right abutment, the conductive anomalies showed remarkable continuity, suggesting a high moisture content in this region with strong gradients (200 mV) directed towards the zone of low resistivity values identified in the sections. The analysis showed a robust correlation of the ERT data with localized physical geotechnical measurements, valuable for monitoring dam integrity, overseeing the structure's response to climate and operational changes, and ultimately mitigating the risks of failure. The results of this study support the adoption of a seasonal 4D electrical resistivity survey as an effective tool to monitor and manage surface and high humidity zones, key indicators of dam integrity throughout the entire structure.