A simple technique for estimating the 1-D heave in expansive soils

Vanapalli, Sai K.; Lu, L; Oh, Won-Taek

doi:10.1201/b10526-187

Cited by 11 publications

(14 citation statements)

References 2 publications

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“…Both Vanapalli et al (2010) and Yilmaz (2006) model show increasing trend of % swell with the increase of plasticity index which is shown in FIG 4. However, the amount of swell from both model provide lower value for soil-1 and soil-2 and higher value for soil-3.…”

Section: Finite Element Model Predictionsmentioning

confidence: 81%

“…Considering the limitations of time-consuming laboratory tests involved in the previous two methods, a simplified method proposed by Vanapalli et al (2010) was selected. This method predicts soil swelling using both Fredlund (1983) and Hemberg & Nelson (1984) methods.…”

Section: Vanapalli Et Al (2010)mentioning

confidence: 99%

“…The change in void ratio with change in net normal stress was measured from 1-D consolidation test for calculation of saturated Young's modulus of elasticity(Esat) as per Zhang (2004). The parameters β and α are fitting parameters which were taken as 2 and 0.1 respectively and Poisson's ratio(µ) as 0.4 in accordance to Vanapalli and Oh (2010). These parameters were used to calculate Eunsat at the end of full swell.…”

Section: Swell Prediction Using Mebmmentioning

confidence: 99%

“…The values obtained are listed in Table 5. Model from Vanapalli et al (2010) is used to predict 1-D swell for given soil with their plasticity indices and variation of water content. All the soils have plasticity index more than 30, so that the empirical correlations are used to find the parameters for the model.…”

Section: Swell Prediction Using Mebmmentioning

confidence: 99%

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Evaluating the Ability of Swell Prediction Models to Predict the Swell Behavior of Excessively High Plastic Soils

Chittoori

Tamim

Gajurel

et al. 2018

PanAm Unsaturated Soils 2017

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Lightly loaded structures underneath expansive soils encounter severe damage due to the swell/shrink nature of expansive soils resulting from moisture variations. Billions of dollars are spent every year to repair the damages caused by these soils in the United States and worldwide. Designing structures to accommodate the swelling strains is a major challenge as predicting the swelling potential of these soils accurately is not easy. A wide variety of swell prediction models have been introduced by various researchers to predict the behavior of these often-problematic expansive soils. These models include various properties of soils such as, plasticity characteristics, compaction conditions, consolidation characteristics, moisture content variations, matric suction and clay mineralogical characteristics. However, these models are generally developed with typical moderate to high plastic soils in mind whose plasticity indices range from 25 to 45. Their applicability to soils that have liquid limits in the order of 200% is not well understood. In this paper, the ability of these models to predict the behavior of excessively high plastic soils with plasticity indices ranging from 45 to 85 were evaluated. For this purpose, four existing analytical prediction models that use combinations of abovementioned properties were selected and used to predict the one-dimensional and threedimensional swelling strains on three high swelling soils. These predictions were verified by conducting one-dimensional and three-dimensional swell tests on the three soil types. The swell tests were conducted at three different initial moisture contents to observe how well the models could predict different levels of moisture absorption. The ability of each of the four selected methods in predicting both 1-D and 3-D swell strains was discussed and their relative merits and demerits are highlighted. In addition, finite element modeling was performed to simulate onedimensional and three-dimensional swell tests by using material models that use volumetric and suction changes with moisture contents to simulate expansive soil behavior within the finite element model. The results indicated that while the analytical prediction models gave reasonable results the finite element analysis predicted results were closest to the laboratory measure soils in case both 1-D and 3-D analyses. Among other analytical models the ones that incorporated mineralogical and suction data exhibited better results.

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Section: Finite Element Model Predictionsmentioning

confidence: 81%

Section: Vanapalli Et Al (2010)mentioning

confidence: 99%

Section: Swell Prediction Using Mebmmentioning

confidence: 99%

Section: Swell Prediction Using Mebmmentioning

confidence: 99%

See 2 more Smart Citations

Evaluating the Ability of Swell Prediction Models to Predict the Swell Behavior of Excessively High Plastic Soils

Chittoori

Tamim

Gajurel

et al. 2018

PanAm Unsaturated Soils 2017

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show abstract

“…Corps of Engineers Model, termed in this paper the CE-Model. A list of other vertical swell-percentage models can be found in [1][2][3][4][5], among others. The outputs of the W-and CE-Models are compared in this paper with the predictive models developed in the present paper.…”

Section: Introduction and Objectivesmentioning

confidence: 99%

Prediction of the Vertical Swelling Percentage of Expansive Clays Using a Two-Stage Artificial Neural Networks Methodology

Bekhor

Livneh

2014

Journal of Testing and Evaluation

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Artificial Neural Networks (ANN), which are used in many different areas, have been applied to predict the vertical swelling percentage of expansive clays. In contrast to previous models that estimated ANN Models in a single phase, this paper proposes an alternative analysis in based on the following two-stage operation: (a) conducting an ANN analysis on the swelling-pressure test results (i.e., the ASTM 4546 Method C test results) to obtain the swelling-pressure model for any given clay characteristics; (b) performing an additional ANN analysis on the swelling-percentage test results (i.e., the ASTM 4546 Method B test results), including the former ones, with the given independent variables of the clay characteristics. This second stage includes a defined expression containing the given surcharge pressure and the predicted value of the swelling pressure as obtained from the model of the previous stage. Two final ANN Models, each with a different arrangement of the given independent variables, were derived from this two-stage procedure. Their statistical fit was clearly found to be superior in comparison to previous models estimated with the same data set. Furthermore, one of these two models exhibited the expected geophysical behavior. As this new ANN Model yields higher predicted swelling-percentage values, it can definitely be regarded as a preferable one in the sense of enlarging the safety margin in heave calculations.

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Characterization of an Expansive Soil in Southwest Brazilian Amazon—Behavior of an Expansive Subgrade in a Flexible Pavement

Barbosa

Marques

Guimarães

et al. 2021

Lecture Notes in Civil Engineering

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A simple technique for estimating the 1-D heave in expansive soils

Cited by 11 publications

References 2 publications

Evaluating the Ability of Swell Prediction Models to Predict the Swell Behavior of Excessively High Plastic Soils

Evaluating the Ability of Swell Prediction Models to Predict the Swell Behavior of Excessively High Plastic Soils

Prediction of the Vertical Swelling Percentage of Expansive Clays Using a Two-Stage Artificial Neural Networks Methodology

Characterization of an Expansive Soil in Southwest Brazilian Amazon—Behavior of an Expansive Subgrade in a Flexible Pavement

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