Abstract Predicting the pile’s load capacity is one of the first steps of foundation engineering design. In geotechnical engineering, there are different ways of predicting soil resistance, which is one of the main parameters. The pile load test is the most accurate method to predict bearing capacity in foundations, as it is the most accurate due to the nature of the experiment. On the other hand, it is an expensive test, and time-consuming. Over the years, semi-empirical methods have played an important role in this matter. Initially, many proposed methods were based on linear regressions. Those are still mainly used, but recently the use of a new method has gained popularity in Geotechnics: Artificial Neural Network. Over the past few decades, Machine Learning has proven to be a very promising technique in the field, due to the complexity and variability of material and properties of soils. Considering that, this work has reviewed and mapped the literature of the main papers published in journals over the last decades. The aim of this paper was to determine the main methods used and lacks that can be fulfilled in future research. Among the results, the bibliometric and protocol aiming questions such as types of piles, tests, statistic methods, and characteristics inherent to the data, indicated a lack of works in helical piles and instrumented pile load tests results, dividing point and shaft resistance. s design resistance parameters foundations experiment hand timeconsuming. timeconsuming time consuming. consuming time-consuming years semiempirical semi empirical matter Initially regressions Geotechnics Network decades field soils research results data

Abstract The characterization of unsaturated soils using hydromechanical methods is an essential requirement in soil science. However, current laboratory techniques used to obtain soil water retention and unsaturated hydraulic conductivity curves are time-consuming. To address this issue, a method based on indirect measures (electrical resistivity/electrical conductivity) was developed to quantitatively characterize soils. A novel unsaturated semi-empirical hydrogeophysical model of soils was developed by incorporating the hydrodynamic, geophysical, and petrophysical characteristics of soils. The model assumes that the parameters influencing the variation in the volumetric water content with matric suction and electrical resistivity are the same. The electrical resistivity characteristic curve (ERCC) defines a function that correlates environmental variables, electrical resistivity, soil water status, matric suction, hydraulic and petrophysical parameters, and fluid electrical resistivity. Model validation confirmed that the proposed approach can estimate the soil water retention curve (SWRC) via the indirect measures, and the results agreed with the experimental data. This indicates that it is possible to determine the SWRC and unsaturated hydraulic conductivity function of soil using the described approach.

Abstract This paper explores the potential of machine learning techniques to predict the soil water retention curve based on physical characterization parameters. Results from 794 water retention and suction points obtained from 51 different soils were used in the algorithm. The soil properties used are the percentages of gravel, sand, silt, and clay, the plasticity index, the porosity, and the relation between the volumetric water content and total suction. The data were used as input for machine learning estimators to predict the volumetric water content of a soil with specified physical characterization parameters and suction, the techniques of artificial intelligence were developed in python. Results show that an extremely randomized trees' estimator can reach a coefficient of determination of 0.99 in the training dataset, with a coefficient of 0.90 in the cross-validation and testing dataset, which measures the generalization capacity. Furthermore, a continuous function can be obtained by fitting a model such as Cavalcante & Zornberg, or van Genuchten, or Costa & Cavalcante (bimodal) to the predictions of the machine learning for use in numerical methods. These results indicate that the proposed machine learning estimator can become an interesting alternative to estimate the soil water retention curve in engineering practice. This work is in progress and the predictions can be improved with the addition of new data. Know how to participate at the end of the paper.

Abstract Mining is an important economic activity in the modern world. However, despite the generated benefits, mining produces tremendous volumes of tailings, an environmental liability with numerous adverse effects. Researches about contaminant transport in tailings dam are important to assess the degree of contamination and to propose preventive or remedial measures. In geotechnical practice, the flow of solutes is generally characterized by numerical solution of the Richards equation to describe water movement followed by advection-dispersion equation to describe contaminant movement. This study aimed to model and simulate contaminant transport in a laboratory column test, using a new analytical formulation and mathematical codes, through tailings in transient unsaturated conditions. The analytical solution for the Richards equation was used to simulate the variation in the volumetric water content and to determine the transient contaminant plume using the advection-dispersion equation subsequently. The models were used to calibrate experimental data from hydraulic characterization and contamination tests. Finally, the normalized contaminant plume (cw/c0) was simulated as a function of time and space. Comparisons with experimental data showed that the analytical formulations adequately expressed the process of contaminant infiltration through the unsaturated porous medium. The formulations offered effectively and are configured as a new approach to solve various contamination problems in transient unsaturated conditions, providing insights into many complex processes that occur in the lab tests and requires far less computational effort compared with current programs to modeling the solute transport using numerical solutions, as the versatile commercial Software HYDRUS.

Abstract Allying technology, theory and engineering practice is one of the main challenges of modern foundation engineering. Current foundation and retaining walls designs may lead to oversizing or undersizing due to the spatial variability of the stratigraphic profile. As the design procedure of piled foundations involves defining the setting depth of the tip, sometimes the piles may not behave as expected, as the soil mass may change significantly even in a small region. In this paper, a study was conducted on the geoenergetic behavior of the soil mass and of the piles of a construction site located in Brasília, DF, Brazil. Previous studies showed that the energy needed to drill a continuous flight auger pile (CFAP) can be related to the strength of the drilled strata. Therefore, a methodological framework was built to further discuss how the geomechanical behavior of CFAPs foundations could be assessed by analyzing the energy needed to drill such piles. Statistical methods, in special the Bootstrap method, were used to assess the possible influences of construction procedures on pile behavior. It was studied how the execution energies of piles vary with initial depth and relative position in the terrain, as well as the influences that they suffer because of the order of execution within a same foundation group and due to the proximity to surrounding retaining walls. The proposed methodology can be used to improve the energy control procedure and performance evaluation of CFAPs, allowing a complementary reliability assessment for the foundation and retaining walls designs and implementations.

Abstract Several regions in Brazil and the world suffer from the presence of collapsible soils. The development of theories for understanding the phenomenon is significant because the increase of water content is associated with several reasons (e.g., precipitation, rupture of sewage, and water systems). Although some theories explain the behavior of various types of soils, they fail to explain collapsible and structured soils. In this research, an alternative interpretation of the consolidation theory is verified and calibrated for collapsible soil. The alternative model was applied to experimental data from a latosol from southeastern Brazil, and comparisons with the classical theory showed a difference in the saturated hydraulic conductivity of around 100 times. The observation showed promising results compared with the saturated hydraulic conductivity of the field (Guelph Permeameter). Furthermore, consolidation tests verified the collapse potential, the variation of consolidation coefficient and saturated hydraulic conductivity, and the total settlement prevision due to the presence of bleach and washing powder.

Abstract Mudflow is often associated with seismic activities. The present study applied a seismic based detection of the surface waves generated by the mudflow of Brumadinho dam collapse using records of Brazilian Seismographic Network. The signal envelope and time-frequency spectrograms of the mudflow signals were used in the analysis. As a result, the mudflow signals were successfully detected from the data recorded at a nearby seismic station. The findings of this study provide a good basis for future research to develop a flood early warning system based on cost-effective, remote and contentious seismic monitoring approaches.

RESUMO A implementação da Política Nacional de Resíduos Sólidos (Lei nº 12.305, de 2 de agosto de 2010) foi um marco para a disposição final e o tratamento de resíduos sólidos no país. A contaminação decorrente da negligência na disposição dos resíduos sólidos urbanos atinge sistemas naturais vitais para a existência humana. Torna-se, portanto, fundamental compreender os mecanismos que estão envolvidos no transporte de contaminantes e os dispositivos geotécnicos para mitigar e/ou remediar os impactos. Neste trabalho, é apresentada a utilização de modelagens matemáticas aplicadas aos resultados dos experimentos realizado por Ritter, em 1998, para determinar o transporte dos principais íons inorgânicos, encontrados no lixiviado do aterro Jardim Gramacho (K+, Cl-, Na+ e NH4 +), por difusão química e sorção. O Aterro de Resíduos Urbanos de Jardim Gramacho está localizado em Duque de Caxias, no estado do Rio de Janeiro, e operou por mais de 30 anos, de 1978 a 2012. Para a compreensão dos mecanismos de transporte, foi utilizada uma solução semi-analítica denominada de camada contaminada equivalente (CCE), proposta por Paz, em 2015, com o objetivo de traçar, no tempo e no espaço, o comportamento desses contaminantes ao longo da amostra de solo utilizada. A vantagem da utilização dessa solução analítica é que ela atende com maior rigor as condições de contorno dos experimentos analisados, quando comparadas com as soluções disponíveis na literatura. Os resultados mostram que os coeficientes de difusão efetivo determinados pela solução CCE apresentam-se dentro dos intervalos indicados na literatura.

ABSTRACT The implementation of the National Solid Waste Policy (Law No. 12.305, of August 2, 2010) was a milestone for the final disposal and treatment of solid waste in the country. The contamination due to negligence in the disposal of urban solid waste reaches natural resources and systems vital to human existence. It is, therefore, essential to understand the mechanisms involved in the transport of contaminants and the best geotechnical devices to mitigate and/or remediate impacts. This paper presents the use of mathematical models applied to the results of the experiments carried out by Ritter, in 1998, to determine the transport of the main inorganic ions found in the leachate of Jardim Gramacho landfill (K+, Cl-, Na+, and NH4 +), by chemical diffusion and sorption mechanisms. The Jardim Gramacho Urban Waste Landfill was located in Duque de Caxias, state of Rio de Janeiro, and operated for more than 30 years, from 1978 to 2012. In order to understand these transport mechanisms, a semi-analytical solution, denominated Equivalent Contaminated Layer (ECL) proposed by Paz, in 2015, was used to trace, in time and space, the behavior of these contaminants along the soil sample used. The advantage of using this analytical solution is that it meets more accurately the boundary conditions of the analyzed experiments, when compared with the solutions available in the literature. The results show that the effective diffusion coefficients determined by the ECL solution are within the ranges indicated in the literature.