Métodos de obtenção da capacidade de suporte de carga de um argissolo cultivado

Rosa, David Peres da; Reichert, José Miguel; Mentges, Marcelo Ivan; Vieira, Davi Alexandre; Vogelman, Eduardo Saldanha; Rosa, Vanderleia Trevisan da; Reinert, Dalvan José

doi:10.1590/s0100-06832011000500010

Cited by 7 publications

(6 citation statements)

References 20 publications

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“…The regression method using 4 and 5 points was correlated with Casagrande, as well as the Pacheco method (Table 2). Similarity between Casagrande and Pacheco in terms of σ p also was found by Rosa et al (2011).…”

Section: Behavior Of the Methods Under Each Scenariosupporting

confidence: 69%

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Comparison of Methods for Determining Precompression Stress Based on Computational Simulation

Silva

Lima

2016

Rev. Bras. Ciênc. Solo

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There are many methods for determining precompression stress (σ p ), whose value is affected by the slope of the soil compression curve. This study was designed to evaluate the hypothesis that for a certain compression curve all methods used to determine σ p present the same value and accuracy. The aim of this study was to compare the accuracy and the relationship among seven of these methods by computational simulation of soil compression curves under nine scenarios. The following methods were used: Casagrande, Pacheco Silva, intersection of the initial void ratio with the virgin compression line (VCLzero), and the regression methods based on 2 (reg1), 3 (reg2), 4 (reg3), and 5 (reg4) points for modeling the elastic curve. Under each scenario, created by combining the swelling and the compression indices, 1,000 compression curves were computationally simulated via the Monte Carlo method. Subsequently, 95 % percentile confidence intervals were built using the 1,000 estimates of σ p from each method under each scenario. Most of the differences among the methods were detected under scenarios consisting of high swelling and low compression indices. In general, Casagrande, Pacheco Silva, and reg4 were strongly correlated and presented the highest values of σ p , as well as similar variability. The latter two can be considered as alternatives to the standard method of Casagrande, except for Pacheco Silva when the curve has a low compression index (≤0.2) and from medium to high swelling index (≥0.025), for which differences (p<0.05) were detected.

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Section: Behavior Of the Methods Under Each Scenariosupporting

confidence: 69%

“…When the variation among methods is analyzed under the same C s , differences mainly occur under low C c (Table 1). Variation among methods is largely influenced by the slope of VCL, C c (Rosa et al, 2011).…”

Section: Behavior Of the Methods Under Each Scenariomentioning

confidence: 99%

Comparison of Methods for Determining Precompression Stress Based on Computational Simulation

Silva

Lima

2016

Rev. Bras. Ciênc. Solo

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“…Consequently, the comparison of results of σp and Ic in several publications (GREGORY et al, 2006;CAVALIERI et al, 2008;KELLER et al, 2011;ROSA et al, 2011) is not suitable, because the differences in σp and Ic are partially caused by the soil property used and therefore may not accurately represent differences in the mechanical behavior of soils. Similarly, comparison of mathematical models that describe the compression curve based on ρ (DIAS JUNIOR & PIERCE, 1995;FRITTON, 2001;ASSOULINE et al, 2002) with those models that employ ε (GREGORY et al, 2006, CAVALIERI et al, 2008KELLER et al, 2011) may also contains such errors.…”

Section: Resultsmentioning

confidence: 99%

“…The mathematical procedure should be the same for the description of both curves, CC ε and CC ρ in order to avoid differences caused by the mathematical models themselves (GREGORY et al, 2006;CAVALIERI et al, 2008;ROSA et al, 2011).…”

Section: Theorymentioning

confidence: 99%

“…To quantify changes in soil structure with the CC, some researchers use bulk density (ρ), CC ρ , (DIAS JUNIOR & PIERCE, 1995;FRITTON., 2001;ASSOULINE et al, 2002) whereas others use the void ratio (ε), CCε, (GREGORY et al, 2006;CAVALIERI et al, 2008 ROSA et al, 2011). Experimentally it is observed that there are differences between the σp and Ic values in the same soil sample estimated with both curves, CC ρ and CC ε (MOSADDEGHI et al, 2003;RÜCKNAGEL et al, 2010).…”

Section: Introductionmentioning

confidence: 99%

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Precompression stress and compression index depend on the property used to represent the soil deformation in the compression curve

et al. 2015

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During linear deformation (h) in a soil sample, the variation of the void ratio with respect to deformation (dε/dh) and the respective variation of soil bulk density (dρ/dh) are identical only for a specific value of h. Consequently, if two compression curves are drawn for the same soil sample, one using ρ and the other using ε, there are differences in both the calculated precompression stress (σp) and compression index (Ic). In this study, we highlight the causes by a mathematical analysis and an experimental investigation, quantifying the differences in σp and Ic when using ε and ρ. σp and Ic were calculated for 103 compression curves of an ultisol and 193 of an oxisol. The σp (kPa) using ρ (σpρ) was greater than when using ε (σpε), and differences were rather independent of the soil type. The relations found by linear regression relating σpρ to σpε were σpρ=0.8186σpε+34.202 for the ultisol and σpρ=0.8878σpε+34.875 for the oxisol. In contrast, the used soil property (ρ or ε) as well as soil type affected Ic. Ic calculated using ρ was greater than when using ε in almost all (96%) of the cases for the ultisol, and in only 12% of the cases for the oxisol. For a wide range of ρ, evidence from this study indicated that the use of ρ overestimates σp when compared to the use of ε.

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soilphysics: An R package to determine soil preconsolidation pressure

Silva

Lima

2015

Computers & Geosciences

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Métodos de obtenção da capacidade de suporte de carga de um argissolo cultivado

Cited by 7 publications

References 20 publications

Comparison of Methods for Determining Precompression Stress Based on Computational Simulation

Comparison of Methods for Determining Precompression Stress Based on Computational Simulation

Precompression stress and compression index depend on the property used to represent the soil deformation in the compression curve

soilphysics: An R package to determine soil preconsolidation pressure

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