Estimation of the soil strength parameters in Tertiary volcanic regolith (NE Turkey) using analytical hierarchy process

Abstract

Costly and time consuming testing techniques and the difficulties in providing undisturbed samples for these tests have led researchers to estimate strength parameters of soils with simple index tests. However, the paper focuses on estimation of strength parameters of soils as a function of the index properties. Analytical hierarchy process and multiple regression analysis based methodology were performed on datasets obtained from soil tests on 41 samples in Tertiary volcanic regolith. While the hierarchy model focused on determining the most important index properties affecting on strength parameters, regression analysis established meaningful relationships between strength parameters and index properties. The negative polynomial correlations between the friction angle and plasticity properties, and the positive exponential relations between the cohesion and plasticity properties were determined. These relations are characterized by a regression coefficient of 0.80. However, Terzaghi bearing capacity formulas were used to test the model. It is important to see whether there is any statistically significant relation between the calculated and the observed bearing capacity values for model testing. Based on the model, the positive linear correlation characterized by the regression coefficient of 0.86 were determined between bearing capacity values obtained by direct and indirect methods. the shearing strength is affected by the consistency of the materials, mineralogy, grain size distribution, shape of the particles, initial void ratio and features such as layers, joints, fissures and cementation (Poulos 1989). However, the consistency of soils is dependent on the weight of the water per unit weight of solid material. Because it is often highly dependent on the amount of soil water, consistency is an important property and is a useful measure for

Pedogenesis of Mt. Sumbing Volcanic Ash above The Alteration Clay Layer in The Formation of Landslide Susceptible Soils in Bompon Sub-Watershed

“…Reduction in soil volume was due to loading results in land subsidence (Handoko et al, 2015). Furthermore, a straight comparison of the liquid limit, plasticity limit, and plasticity index to clay was also observed in Turkey by Ersoy et al (2013) stating that the landslides potential was influenced by fine grain size, which had significant correlation as indicated by the clay value increasing linearly with the plasticity index. The higher the clay, the higher the aggregate and softening of the soil would be.…”

“…This was also supported by Handoko et al (2015) describing that the highest value of 54.47% was classified as finegrained soil with high plasticity index. Furthermore, it was also strengthened by Ersoy (2013), that the 50% value indicated significant correlation with the liquid limit, plasticity limit and plasticity index. The values were directly proportional to the level according to the theory which stated that the level determination was based on the Atterberg limits (Liu, 2016).…”

Estimation of Shear Strength Parameters of Lateritic Soils Using Artificial Neural Network

“…The understanding of the shear strength of a soil is important in the assessment of bearing capacities of foundations [2], slope stability [3], retaining structures, embankment dams [4], tunnel linings, pavement [5] and the resistance traction and tillage tools in agricultural applications [6].The shear strength of soils is generally represented by the Mohr-Coulomb theory. The theory, indicate that the shear strength of soils varies linearly with the applied stress through two shear strength factors; cohesion and angle of shearing resistance [7,8]. The tangent to the Mohr-Coulomb failure envelopes is defined by its slope and intercept.…”

“…The triaxial compression and direct shear tests are the most common tests for determining the cohesion and angle of friction values in the laboratory. Measurements of shear strength properties both at field and laboratory conditions are cumbersome, expensive, time-consuming and labourintensive [7,8,12]. In order to cope with the difficulty of experimental investigation, engineering design models are needed.…”

“…Among the various models developed are; Masada [15] for clay and silt embankments, Mofiz and Rahman [16] for Barind soils, Cola and Cortellazo [17] for peaty soils and Hajarwish and Shakor [18] for mudrock. Also, some models have been developed based on sustained hypothesis imposed by the researchers before estimation of the model parameters according to their assumptions concerning how the model parameters the dependent and explanatory variables are related, [7,8,[18][19][20][21]. Hence these various models may not have been the appropriate ones.…”