Stabilization of an Ore Pile by Drainage

Terzaghi, Karl; Peck, Ralph B.

doi:10.1061/jsfeaq.0000035

Cited by 105 publications

(170 citation statements)

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“…The cut-off points used for classifications are presented in Table 4. The consistency ranges recommended by Terzaghi et al (1996) andBS5930 (2015) were taken as the basis for determining the cut-off points. The Mamdani inference system was used because interpretability of the inference system is easier than Sugeno inference system.…”

Section: Fig 3 the Processing Diagram Of Fuzzy Logicmentioning

confidence: 99%

“…Liquid limit (𝐿𝐿) is defined as the minimum water content of the soil at which the soil behaves like a viscous fluid or in other words, it is the boundary limit water content value where the shear strength of soil is approximately zero. In the last five decades, several researchers (Wroth and Wood 1978;Whyte 1982;Federico 1983;Leroueil et al 1983;Locat and Demers 1988;Hirata et al 1990;Terzaghi et al 1996;Shimobe 2000;Yılmaz 2000;Koumoto and Houlsby 2001;NGI 2002;Hong et al 2003;Lee 2004;Trauner et al 2005;Yang et al 2006;Berilgen et al 2007;Edil et al 2009;Vinod et al 2013;Vardanega and Haigh 2014;Kayabalı et al 2015;Kang et al 2017;Kuriakose et al 2017;Spagnoli and Feinendegen 2017;Ullah et al 2017;Chacko and Jacob 2018;Sharma and Sridharan 2018;Karakan et al 2020;Budak et al 2022) have investigated the correlation of obtained undrained shear strength of the remolded soil with liquidity index (𝐿𝐼) (Eq. 1) or water content ratio (𝑊𝐶𝑅) (Eq.…”

Section: Introductionmentioning

confidence: 99%

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Prediction of the Undrained Shear Strength of the Remolded Soil with Non-Linear Regression, Fuzzy Logic and Artificial Neural Network

Yünkül

KARAÇOR

Gürbüz

et al. 2023

Preprint

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The aim of this study is to predict the undrained shear strength (Cu) of the remolded soil samples and for this purpose, non-linear regression (NLR) analyses, fuzzy logic (FL) and artificial neural network (ANN) modelling were used to assess. Total 1306 undrained shear strength results of soil types of CH, CL, MH and ML from 230 different remolded soil test settings on 21 publications were collected while six different measurement devices were used by researchers. Although water content, plastic limit and liquid limit were used as input parameters for FL and ANN modelling, liquidity index or water content ratio were considered as input parameter for NLR analyses. In NLR analyses, 12 different regression equations were derived for prediction of Cu. Feed-Forward backpropagation and TANSIG transfer function were used for ANN modelling while Mamdani inference system was preferred with trapezoidal and triangular membership function for FL modelling. The experimental results of 914 tests for training of the ANN models, 196 for validation and 196 for testing were used. It was observed that the accuracy of the ANN and FL modellings were higher than NRL analyses. Furthermore, the simple and reliable regression equation was proposed for assessments of Cu values having higher coefficient of determination values (R2).

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Section: Fig 3 the Processing Diagram Of Fuzzy Logicmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Prediction of the Undrained Shear Strength of the Remolded Soil with Non-Linear Regression, Fuzzy Logic and Artificial Neural Network

Yünkül

KARAÇOR

Gürbüz

et al. 2023

Preprint

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“…They have considered the plasticity of fines and integrated with PSD characteristics to build their fine-grained sediment classification. The degree of plasticity index (PI), representing the difference between the liquid limit ( LL ) and the plastic limit ( PL ) (Terzaghi et al 1996 ), implies a degree percentage of active (clay) minerals (i.e., the higher activity of clay minerals, the greater water capacity to be absorbed), whereas a low PI implies the converse. The liquid limits LL are lines delineated based on the predominant clay minerals even though this sediment has the same as the Particle Size Distribution curve.…”

Section: Sediment Structure Overviewmentioning

confidence: 99%

The use of particle size distribution integrated with consistency limits for experimentally simulating fine-grained sedimentary units

2021

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“…The properties that were measured are as follows: granulometry, characterised by the percentage of grains with size < 2 µm, (F 2 ≈ 63.2) , where, F2 is the proportion of clay % < 2 µm. The void ratios ( e 0 ) and water contents ( W 0 ) indicate a stiff clay [29], saturated but below their plasticity limit. Coefficient of permeability is K = 9.92 × 10 −8 m/s.…”

Section: Characterization Of the Soil Study And Organic Chemical Contaminantmentioning

confidence: 99%

Characterisation of the chemo-mechanical behaviour of clays polluted by BTEX: a case study of benzene

2021

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In chemo-mechanical coupling of clays, chemical phenomena are likely to have a stronger influence on the mechanical behaviour and mechanical actions can modify the chemical behaviour. The understanding of these different phenomena, taking into account the coupled mechanisms, is essential in the context of the problem of the durability of structures and works built on polluted sites. Thus, the laboratory characterisation of the chemo-mechanical behaviour of a clay contaminated by light hydrocarbon pollutant (BTEX: benzene) was carried out. First in the absence of pollutants, i.e., by the presence of water only, then under the influence of the pollutant, all in two stages: with no external stress, then under imposed external stress. This study presents an experimental protocol based on a series of uniaxial consolidation tests, specific oedometric tests and direct shear strength, this tests performed under controlled saturation conditions and in the presence of organic contamination by benzene. All results confirm the influence of pollutants in different concentrations on the mechanical behaviour of the soil. They show a strong increase in compressibility and a significant increase in swelling, the soil becomes more cohesive, low friction and less elastic. Furthermore, the results show that external load forces play a major role in modifying the behaviour of clay.

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Stabilization of an Ore Pile by Drainage

Cited by 105 publications

References 0 publications

Prediction of the Undrained Shear Strength of the Remolded Soil with Non-Linear Regression, Fuzzy Logic and Artificial Neural Network

Prediction of the Undrained Shear Strength of the Remolded Soil with Non-Linear Regression, Fuzzy Logic and Artificial Neural Network

The use of particle size distribution integrated with consistency limits for experimentally simulating fine-grained sedimentary units

Characterisation of the chemo-mechanical behaviour of clays polluted by BTEX: a case study of benzene

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