Analysis of soil compression curves from uniaxial confined compression tests

Keller, Thomas; Lamandé, Mathieu; Schjønning, Per; Dexter, A. R.

doi:10.1016/j.geoderma.2011.02.006

Cited by 109 publications

(94 citation statements)

References 53 publications

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“…The compressibility coefficient (C c ) was estimated as the slope of the linear regression fitted for VCL, determined as shown in equation 1, where e is the void ratio. The swelling index (C s ) was determined as the mean slope of the loading path up to 25 kPa (Equation 2), according to Keller et al (2011). The C c and C s indices are identified on the compression curve and graphically represented in figure 1.…”

Section: Methods For Determination and Calculation Of Indicesmentioning

confidence: 99%

“…We created scenarios based on the values of the swelling (recompression index) and compression indices (Keller et al, 2011). This allowed us to reproduce different compression curves, which are associated with the results of a soil compressibility test.…”

Section: Scenarios Of Simulationmentioning

confidence: 99%

“…Simulation was based on the result of a simple uniaxial compression test with loads of 1, 12.5, 25, 50, 100, 200, 400, 800, and 1,600 kPa. In this case, the loading of 1 kPa corresponds to the initial void ratio or bulk density, which was only to calculate the swelling line associated with the initial state of the soil sample (Keller et al, 2011;An et al, 2015). We combined three values of C c and three values of C s in order to create nine scenarios ( Figure 2).…”

Section: Scenarios Of Simulationmentioning

confidence: 99%

“…Compression is characterized by a mechanical process that describes the decrease in volume when soil is exposed to a mechanical load, which is defined by a soil compression curve. Three important parameters extracted from the soil compression curve were describe by Keller et al (2011): the swelling or recompression index (C s ), the compressibility coefficient (C c ), and the preconsolidation or precompression stress (σ p ), where C s is defined as the slope of the swelling line (SL) and C c is the slope of the Virgin Compression Line (VCL).…”

Section: Introductionmentioning

confidence: 99%

“…The second part is the VCL, for which plastic deformations are irreversible. This part can be verified by the C c value, not subject stress (Keller et al, 2011). Finally, σ p is mathematically defined as the point that divides the compression curve into the elastic and plastic parts of the soil compression curve (Casagrande, 1936).…”

Section: Introductionmentioning

confidence: 99%

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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: Methods For Determination and Calculation Of Indicesmentioning

confidence: 99%

Section: Scenarios Of Simulationmentioning

confidence: 99%

Section: Scenarios Of Simulationmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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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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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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Biological and physical controls of methane uptake in grassland soils across the US Great Plains

Koyama,

Johnson,

Brewer

et al. 2024

Ecosphere

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The grassland biome is an important sink for atmospheric methane (CH4), a major greenhouse gas. There is considerable uncertainty in the grassland CH4 sink capacity due to diverse environmental gradients in which grasslands occur, and many environmental conditions can affect abiotic (e.g., CH4 diffusivity into soils) and biotic (e.g., methanotrophy) factors that determine spatial and temporal CH4 dynamics. We investigated the relative importance of a soil's gas diffusivity versus net methanotroph activity in 22 field plots in seven sites distributed across the US Great Plains by making approximately biweekly measures during the growing seasons over 3 years. We quantified net methanotroph activity and diffusivity by using an approach combining a gas tracer, chamber headspace measurements, and a mathematical model. At each plot, we also measured environmental characteristics, including water‐filled pore space (WFPS), soil temperature, and inorganic nitrogen contents, and examined the relative importance of these for controlling diffusivity and net methanotroph activity. At most of the plots across the seven sites, CH4 uptake rates were consistently greatest when WFPS was intermediate at the plot level. Our results show that variation in net methanotroph activity was more important than diffusivity in explaining temporal variations in net CH4 uptake, but the two factors were equally important for driving spatial variation across the seven sites. WFPS was a significant predictor for diffusivity only in plots with sandy soils. WFPS was the most important control on net methanotroph activity, with net methanotroph activity showing a parabolic response to WFPS (concave down), and the shape of this response differed significantly among sites. Moreover, we found that the WFPS level at peak net methanotroph activity was strongly correlated with the mean annual precipitation of the site. These results suggest that the local precipitation regime determines unique sensitivity of CH4 uptake rates to soil moisture. Our findings indicate that grassland CH4 uptake may be predicted using local soil water conditions. More variable soil moisture, potentially induced through predicted future extremes of rainfall and drought, could reduce grassland CH4 sink capacity in the future.

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Analysis of soil compression curves from uniaxial confined compression tests

Cited by 109 publications

References 53 publications

Comparison of Methods for Determining Precompression Stress Based on Computational Simulation

Comparison of Methods for Determining Precompression Stress Based on Computational Simulation

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

Biological and physical controls of methane uptake in grassland soils across the US Great Plains

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