A method for predicting soil susceptibility to the compaction of surface layers as a function of water content and bulk density

Saffih-Hdadi, K.; Défossez, Pauline; Richard, Guy; Cui, Yu Jun; Tang, Anh Minh; Chaplain, Véronique

doi:10.1016/j.still.2009.05.012

Cited by 131 publications

(98 citation statements)

References 46 publications

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“…The curves simulated cover a wide range of soil compression curves, such as those obtained for soil samples in compression tests under different soil bulk densities, textures, and moisture contents (Arvidsson and Keller, 2004;Imhoff et al, 2004;Gregory et al, 2006;Cavalieri et al, 2008;Ajayi et al, 2009;Saffih-Hdadi et al, 2009;Ajayi et al, 2013;An et al, 2015).…”

Section: Simulated Soil Compression Curvesmentioning

confidence: 99%

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: Simulated Soil Compression Curvesmentioning

confidence: 99%

Comparison of Methods for Determining Precompression Stress Based on Computational Simulation

Silva

Lima

2016

Rev. Bras. Ciênc. Solo

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“…Continuous traffic of agricultural machines, especially at high soil moisture, can lead to excessive compaction in the soil surface and subsurface (Saffih-Hdadi et al, 2009). A very common way to assess the state of soil compaction is by means of soil penetration resistance (PR) with a cone penetrometer (Moraes et al, 2013(Moraes et al, , 2014a, due to its practicality, speed, and low cost.…”

Section: Introductionmentioning

confidence: 99%

“…However, the variation in PR according to change in bulk density (Bd) is influenced by soil water content, which can be a source of misinterpretation (Moraes et al, 2013(Moraes et al, , 2014a. Another method of assessing the state of soil compaction is by the compression curve, from which the preconsolidation pressure (σp) and compression index (CI) can be determined (Saffih-Hdadi et al, 2009;An et al, 2015). However, these mechanical parameters are also influenced by the water content and the initial state of soil compaction (Suzuki et al, 2008;Saffih-Hdadi et al, 2009).…”

Section: Introductionmentioning

confidence: 99%

“…Another method of assessing the state of soil compaction is by the compression curve, from which the preconsolidation pressure (σp) and compression index (CI) can be determined (Saffih-Hdadi et al, 2009;An et al, 2015). However, these mechanical parameters are also influenced by the water content and the initial state of soil compaction (Suzuki et al, 2008;Saffih-Hdadi et al, 2009). Therefore, the establishment of Bd correlations, of gravimetric water content in the soil (U), and of PR with CI and σp can more precisely indicate the degree of compaction of agricultural soils.…”

Section: Introductionmentioning

confidence: 99%

“…Avoiding pressures exceeding the load-bearing capacity, estimated by σp, constitutes the main strategy for prevention of soil compaction (Saffih-Hdadi et al, 2009). However, collection and analysis of soil samples to determine σp are expensive and timeconsuming procedures, difficult to carry out on a field scale (Dias Júnior et al, 2004).…”

Section: Introductionmentioning

confidence: 99%

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Modeling of Soil Load-Bearing Capacity as a Function of Soil Mechanical Resistance to Penetration

Ortigara

Moraes

Debiasi

et al. 2015

Rev. Bras. Ciênc. Solo

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estimation of soil load-bearing capacity from mathematical models that relate preconsolidation pressure (σp) to mechanical resistance to penetration (PR) and gravimetric soil water content (U) is important for defining strategies to prevent compaction of agricultural soils. Our objective was therefore to model the σp and compression index (CI) according to the PR (with an impact penetrometer in the field and a static penetrometer inserted at a constant rate in the laboratory) and U in a Rhodic Eutrudox. The experiment consisted of six treatments: no-tillage system (NT); NT with chiseling; and NT with additional compaction by combine traffic (passing 4, 8, 10, and 20 times). Soil bulk density, total porosity, PR (in field and laboratory measurements), U, σp, and CI values were determined in the 5.5-10.5 cm and 13.5-18.5 cm layers. Preconsolidation pressure (σp) and CI were modeled according to PR in different U. The σp increased and the CI decreased linearly with increases in the PR values. The correlations between σp and PR and PR and CI are influenced by U. From these correlations, the soil load-bearing capacity and compaction susceptibility can be estimated by pr readings evaluated in different u.

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Effects of dry bulk density and water content on compressive characteristics of wet clayey paddy soil

et al. 2022

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The application of soil compaction models is limited by the lack of soil compression properties and their variations as a function of different physical parameters. This study aimed to explore the effect of dry bulk density and water content on the characteristics of the soil compression curves and compression properties for wet clayey paddy soil. In order to investigate large‐scale soil initial conditions, uniaxial compression tests were conducted on a total of 25 soil states by controlling five soil water contents and five dry bulk densities. Soil compression curves were obtained from fitting uniaxial compression test results, and the swelling index, compression index, and precompression stress were measured. The swelling index of paddy soil ranged from 0.003 to 0.138 and showed a significant positive dependence on water content and a significant negative correlation with dry bulk density. The compression index ranged from 0.115 to 0.839. A quadratic polynomial function was established between water content and compression index, whereas the compression index showed a significant negative correlation with dry bulk density. The precompression stress ranged from 33 to 127 kPa. The precompression stress showed a prominent negative dependence on water content and a significant positive correlation with dry bulk density. The pedo‐transfer functions of the swelling index, compression index, and precompression stress could be used in soil compaction models as input parameters for risk evaluation of compaction damage of wet clayey paddy soil.

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A method for predicting soil susceptibility to the compaction of surface layers as a function of water content and bulk density

Cited by 131 publications

References 46 publications

Comparison of Methods for Determining Precompression Stress Based on Computational Simulation

Comparison of Methods for Determining Precompression Stress Based on Computational Simulation

Modeling of Soil Load-Bearing Capacity as a Function of Soil Mechanical Resistance to Penetration

Effects of dry bulk density and water content on compressive characteristics of wet clayey paddy soil

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