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. analysis However methodologies nature consequently analyses controller roughness

ABSTRACT In this article, the effect on the resistance parameters of a stabilized SM soil with asphalt emulsion contents varying between 16% and 28% by mass was evaluated. The methodology consisted of collecting and characterizing the soil, mixing the materials and exposing them to air for 24 hours, compacting at the optimal level by Marshall energy (22%), and at levels above (28%) and below (16%) the optimum, and carrying out CIU triaxial compression tests under saturated conditions. The soil presented behavior typical of an elastic-plastic material with hardening, while the mixtures presented behavior similar to that of an elastic perfectly plastic material. As the emulsion content was increased, the friction angles were smaller and, for mixtures with 16% and 22% of content, the cohesive intercepts were higher. The mixture with 28% content of asphalt emulsion had a reduction in its cohesion, due to the excess of binder, which impaired the grain-to-grain contact. It was found that after a certain level of axial deformation, the mixtures obtained a slight gain in resistance, justified by the displacement of the asphalt film.

RESUMO Neste artigo avaliou-se o efeito nos parâmetros de resistência de um solo SM estabilizado com teores de emulsão asfáltica variando entre 16% e 28% em massa. A metodologia consistiu na coleta e caracterização do solo, mistura dos materiais e exposição ao ar por 24 horas, compactação no teor ótimo pela energia Marshall (22%), e em teores acima (28%) e abaixo (16%) do ótimo, e realização de ensaios de compressão triaxial CIU em condições saturadas. O solo apresentou comportamento típico ao de um material elastoplástico com endurecimento, enquanto que as misturas apresentaram comportamento semelhante ao de um material elástico perfeitamente plástico. À medida em que o teor de emulsão foi aumentado, menores foram os ângulos de atrito e, para as misturas com 16% e 22%, maiores foram os interceptos coesivos. A mistura 28% de emulsão teve uma redução em sua coesão, devido ao excesso de ligante, o que prejudicou o contato grão a grão. Constatou-se que após determinado nível de deformação axial as misturas obtiveram um leve ganho de resistência, justificado pelo deslocamento da película de asfalto.

Abstract There are an increasing number of studies that use the artificial neural networks (ANN) as a prediction tool in the field of foundations with satisfactory results. In this paper, multilayer perceptrons are used to develop prediction models for the shaft and tip bearing capacities of single piles based on a supervised training using the error back propagation algorithm. Results from static load tests carried out on 95 instrumented single piles executed in different regions of Brazil were used in the ANN modelling. The prediction models of shaft and tip bearing capacities of single piles were obtained portraying indicated in the validation phase determination coefficients equal to 95% and 99%, respectively. To demonstrate their applicability and efficiency, such models were used to estimate the bearing capacity of single piles unused in the models’ development, as well as groups of two and three piles. The results demonstrated that the neuron models were much closer to the values of the bearing capacities measured in single pile tests and groups of piles, than the estimated results using semi-empirical methods. As a result of overestimating the predicted bearing capacities in relation to the results of the load tests, it is recommended to use models applying reduction factors of 0.88 for single piles, and 0.75 for groups of up to three piles.

RESUMO A determinação da condutividade hidráulica em solos não saturados é essencial ao realizar análises de fluxo transiente nesses meios porosos. No entanto, a execução de ensaios de laboratório e de campo para a determinação dessa propriedade hidráulica não é prática corrente no âmbito da geotecnia, por se tratar de procedimentos demorados e dispendiosos. As redes neurais artificiais (RNA) têm sido bastante empregadas em Mecânica dos Solos, permitindo a estimativa de uma forma fácil e simples de fenômenos complexos e multivariados. Desse modo, este artigo tem como objetivo apresentar um modelo de estimativa da condutividade hidráulica em solos não saturados desenvolvido a partir de um tipo de RNA conhecido como perceptron multicamadas (MLP). As variáveis de entrada do modelo são: índice de vazios inicial, teor de umidade gravimétrico inicial, percentuais de areia, silte e argila, índice de plasticidade, coeficiente de permeabilidade saturado e sucção matricial. Durante a modelagem, um total de 275 exemplos foram utilizados, dos quais 85% foram empregados na fase de treinamento, e 15% na fase de teste. O modelo proposto possui uma arquitetura A: 8-4-2-1 e apresentou coeficiente de correlação de 0,97 após 500 mil iterações em ambas as fases de treinamento e de teste. Os resultados do modelo se ajustaram satisfatoriamente aos dados experimentais utilizados nas fases de treinamento e de teste, e a rede neural proposta foi capaz de representar a influência das variáveis de entrada no comportamento hidráulico de diferentes tipos de solo.

ABSTRACT The determination of hydraulic conductivity in unsaturated soils is essential when performing transient flow analysis in these porous media. However, the execution of laboratory and field tests to determine this hydraulic property is not a current practice in the scope of geotechnics, as these are time-consuming and expensive procedures. Artificial neural networks (ANN) have been widely used in Soil Mechanics, allowing the estimation of complex and multivariate phenomena in an easy and simple way. Thus, this article aims to present a model for estimating hydraulic conductivity in unsaturated soils developed from a type of ANN known as multilayer perceptron (MLP). The model’s input variables are the initial void ratio, initial gravimetric water content, sand content, silt content, clay content, plasticity index, saturated permeability coefficient and matric suction. During modeling, a total of 275 examples were used, of which 85% were used in the training phase, and 15% in the testing phase. The proposed model has an A: 8-4-2-1 architecture and presented a correlation coefficient of 0.97 after 500 thousand iterations in both training and testing phases. The results of the model adjusted satisfactorily to the experimental data used in the training and test phases, and the proposed neural network was able to represent the influence of the input variables on the hydraulic behavior of different types of soil.

RESUMO Neste artigo avaliou-se o efeito do processo de cura na resistência ao cisalhamento de um solo arenoso misturado com teores de emulsão superiores a 10% em massa. A metodologia consistiu na coleta e caracterização do solo, caracterização da emulsão, compactação das misturas, cura dos corpos de prova por exposição ao ar por 1, 7 e 28 dias, e realização de ensaios de compressão triaxial em condições saturadas e não saturadas. Evidenciou-se que o aumento do tempo de cura ocasionou uma diminuição da massa específica aparente dos corpos de prova em razão da diminuição do teor de umidade devido à evaporação da água de constituição da emulsão. Os resultados dos ensaios realizados em condições saturadas indicaram não haver influência do tempo de cura na resistência ao cisalhamento. Já nos corpos de prova sem saturação, o aumento do tempo de cura produziu um aumento no valor do intercepto coesivo das misturas, mais pelo incremento da sucção do que pelo aumento da capacidade de ligação entre os grãos minerais. Em todos os casos, a adição de altos teores de emulsão asfáltica provocou um aumento no intercepto coesivo e diminuição do ângulo de atrito nos corpos de prova ensaiados com e sem saturação.

ABSTRACT This paper aims to evaluate the effect of the curing process on the shear strength of mixtures of a sandy soil and high levels of emulsion (higher than 10% in weight). The adopted methodology consisted of collecting and characterizing the sandy soil, characterizing the asphaltic emulsion, compacting the mixtures, curing the specimens by exposure to air for 1, 7, and 28 days, and performing triaxial compression tests under saturated and unsaturated conditions. The results showed that the increase in the curing time caused a gradual decrease in the apparent specific gravity of the specimens due to the decrease in the moisture content caused by the evaporation of the water in the asphaltic emulsion. The results of tests carried out in saturated conditions indicated that there is no influence of the curing time of the specimens on their shear strength. In the specimens tested without saturation, the increase in the curing time produced a significant increase in the value of cohesive intercept of mixtures, more due to the increase in suction than to the increase in the bonding capacity between the soil grains. In all cases, the addition of asphalt emulsion contents higher than 10% caused an expressive increase in the cohesive intercept and a decrease in the friction angle in the specimens tested with and without saturation.

Abstract The purpose of this article is to present predictive models of dilation and shear stress of rock discontinuities by applying the neuro-fuzzy technique, which uses a) the high capacity of artificial neural networks (ANN) to understand and to model complex multivariate phenomena, and b) the concepts of fuzzy sets theory to consider the variability of the input parameters in the proposed models’ responses. To develop the proposed models, experimental results were obtained from large-scale direct shear tests performed on different types of rock discontinuities and boundary conditions. The input variables of the proposed neuro-fuzzy models are the normal boundary stiffness, the ratio of fill thickness to asperity height, the initial normal stress, the joint roughness coefficient, the uniaxial compressive strength of the intact rock, the basic friction angle of the intact rock, the friction angle of the infill, and the shear displacement. The proposed models for dilation and shear stress provided results that fitted satisfactorily the experimental data, and the analyses of their performances indicated that they can represent the influence of the input variables on the shear behavior parameters of the rock discontinuities. The results from the neuro-fuzzy systems developed are also closer to the experimental data than those estimated by using traditional analytical methodologies existing in Rock Mechanics. This occurs because once considering the uncertainty of the input data, a more representative shear behavior prediction can be made by the neuro-fuzzy models.

Abstract The purpose of this article is to evaluate the shear strength parameters of mixtures of sandy soil with high asphalt emulsion contents for their use in geotechnical structures, such as zoned earth dams, embankments, etc. The methodology adopted consisted of: collecting and characterizing samples of sandy soil to be laboratory tested; compacting the mixtures between soils and asphalt emulsion with contents varying between 13% and 28% in weight by using different compaction methodologies; and performing direct shear tests to evaluate the parameters governing the shear strength behavior of the manufactured mixtures. Results showed that the use of a high asphalt emulsion content contributed to greater homogeneity of the mixtures. It was also found that the presence of residual asphalt gave a bilinear behavior to the sandy soil for the failure envelopes obtained from direct shear tests. At normal stresses usually less than 100 kPa, the mixtures present a cohesive intercept due the existing residual binder, while for normal stresses higher than 200 kPa, the mixtures presented a friction angle equal to the matrix of sandy soil used.

Abstract It is well known that learning about the mechanical behavior of a fractured rock mass depends on the shear behavior of its discontinuities. Several studies have shown that the shear behavior of unfilled rock discontinuities depends on their boundary conditions, roughness characteristics and the properties of the joints walls. Currently, there are several analytical models that can be used to predict the shear behavior of clean rock joints. However, they are all purely deterministic in nature because their input variables are defined without considering the uncertainties inherent in the formative process of the rock mass and the discontinuity itself, i.e., they need an auxiliary tool to consider the variability of their parameters such as the Monte Carlo or Point Estimation Methods. Therefore, the purpose of this article is to present a model to predict the shear strength of clean rock joints incorporating uncertainties in the variables that govern their shear behavior with a zero-order Takagi-Sugeno fuzzy controller. The model is developed based on the results of 44 direct shear tests carried out on different joints. The model input variables are the normal boundary stiffness and initial normal stress acting on the joint, its roughness expressed by the JRC value, the uniaxial compressive strength and basic friction angle of the intact rock, as well as the shear displacement imposed on the joint. The results showed that the predicted shear strength of clean rock joints obtained by the fuzzy model fit the experimental data satisfactorily and helped define the shear behavior of the discontinuity.