The Effect of Quicklime Stabilization on Soil Properties

Olinic, Tatiana; Olinic, Ernest

doi:10.1016/j.aaspro.2016.09.013

Cited by 13 publications

(7 citation statements)

References 5 publications

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“…Lime stabilization improves the geotechnical properties by changing the microstructure and fabric of expansive clays [112] through four important reactions [113], i.e., (1) cation exchange, (2) flocculation-agglomeration, (3) carbonation, and (4) pozzolanic reaction. It is mainly due to the flocculation-agglomeration reaction that the geotechnical properties of high plasticity clay soils are improved.…”

Section: Main Effect Of Lime Stabilizationmentioning

confidence: 99%

On the Recent Trends in Expansive Soil Stabilization Using Calcium‐Based Stabilizer Materials (CSMs): A Comprehensive Review

Jalal

Jamhiri

et al. 2020

Advances in Materials Science and Engineering

109

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Calcium-based stabilizer materials (CSMs) exhibit pozzolanic properties which improve the properties of clayey soils by hydration, cation exchange, flocculation, pozzolanic reaction, and carbonation. In this comprehensive review, comprising over past three decades from 1990 to 2019, a mechanistic literature of expansive soil stabilization by incorporating CSMs is presented by reviewing 183 published research articles. The advantages and disadvantages of CSMs as the ground stabilizing agent are succinctly presented, and the major outcomes of physicochemical effects on soil properties are discussed in detail. After blending with CSM, the main and interaction effects on soil properties with focus on chemical processes such as X-ray fluorescence, X-ray diffraction analyses, and microstructure interaction by using scanning electron microscopy and thermogravimetric analysis have been reviewed in light of findings of past researchers. This work will help geotechnical engineers to opt for suitable CSM in the field of geoenvironmental engineering in committing to sustainable construction of civil engineering structures over expansive soils.

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Section: Main Effect Of Lime Stabilizationmentioning

confidence: 99%

On the Recent Trends in Expansive Soil Stabilization Using Calcium‐Based Stabilizer Materials (CSMs): A Comprehensive Review

Jalal

Jamhiri

et al. 2020

Advances in Materials Science and Engineering

109

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“…Calcium enrichment in the northwestern part of the map might be due to the application of quicklime (Calcium oxide) to reduce soil acidity and its application in steel plants as basic oxygen in steel making process. On the other hand, other farmers prefer to use calcium hydroxide in acidic soil to neutralize the pH level, which also surges the calcium content of the soil 71 . Potassium exhibited hot spots in the northwestern part of the map and the eastern part as well.…”

Section: Resultsmentioning

confidence: 99%

Prediction of nickel concentration in peri-urban and urban soils using hybridized empirical bayesian kriging and support vector machine regression

Agyeman

Kebonye

John

et al. 2022

Sci Rep

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Soil pollution is a big issue caused by anthropogenic activities. The spatial distribution of potentially toxic elements (PTEs) varies in most urban and peri-urban areas. As a result, spatially predicting the PTEs content in such soil is difficult. A total number of 115 samples were obtained from Frydek Mistek in the Czech Republic. Calcium (Ca), magnesium (Mg), potassium (K), and nickel (Ni) concentrations were determined using Inductively Coupled Plasma Optical Emission Spectroscopy. The response variable was Ni, while the predictors were Ca, Mg, and K. The correlation matrix between the response variable and the predictors revealed a satisfactory correlation between the elements. The prediction results indicated that support vector machine regression (SVMR) performed well, although its estimated root mean square error (RMSE) (235.974 mg/kg) and mean absolute error (MAE) (166.946 mg/kg) were higher when compared with the other methods applied. The hybridized model of empirical bayesian kriging-multiple linear regression (EBK-MLR) performed poorly, as evidenced by a coefficient of determination value of less than 0.1. The empirical bayesian kriging-support vector machine regression (EBK-SVMR) model was the optimal model, with low RMSE (95.479 mg/kg) and MAE (77.368 mg/kg) values and a high coefficient of determination (R2 = 0.637). EBK-SVMR modelling technique output was visualized using a self-organizing map. The clustered neurons of the hybridized model CakMg-EBK-SVMR component plane showed a diverse colour pattern predicting the concentration of Ni in the urban and peri-urban soil. The results proved that combining EBK and SVMR is an effective technique for predicting Ni concentrations in urban and peri-urban soil.

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“…On the other hands, other farmers prefer to use calcium hydroxide in acidic soil to neutralize the pH level, which also surges the calcium content of the soil. 61 Potassium exhibited hot spots in the northwestern part of the map and eastern part as well. The Northwestern part is the predominantly agrarian community, and a moderate to a high pattern of K might be due to the application of NPK and muriate of potash.…”

Section: Spatial Distribution Of the Elementsmentioning

confidence: 98%

Prediction of Nickel Concentrations in Urban and Peri-Urban Soils: Application of a Hybridized Empirical Bayesian Kriging and Support Vector Machine Regression Approach

Kebonye

John

2021

Preprint

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Soil pollution is a big issue caused by anthropogenic activities. The spatial distribution of potentially toxic elements (PTEs) varies in most urban and peri-urban areas. As a result, spatially predicting the PTEs content in such soil is difficult. A total number of 115 samples were obtained from Frydek Mistek in the Czech Republic. Calcium(Ca), magnesium(Mg), potassium(K), and nickel (Ni) concentrations were determined using Inductively Coupled Plasma Optical Emission Spectroscopy. The correlation matrix between the response variable and the predictors revealed a satisfactory correlation between the elements. The prediction results indicated that support vector machine regression (SVMR) performed well although its estimated root mean square error (RMSE) (235.974) and mean absolute error (MAE) (166.946) were higher when compared with the other methods applied. Conversely, the hybridized model of empirical bayesian kriging -multiple linear regression (EBK-MLR) performed poorly as indicated by the measured coefficient of determination value below 0.1. The empirical bayesian kriging-support vector machine regression (EBK-SVMR) model was the best model, with low RMSE (95.479) and MAE (77.368) values and a high coefficient of determination (R2 = 0.637). EBK-SVMR modeling technique was visualized using self-organizing map. The clustered neurons of the hybridized model CakMg -EBK-SVMR component plane showed a diverse color pattern predicting the concentration of Ni in the urban and peri urban soil. The results proved that combining EBK and SVMR is an effective technique for predicting Ni concentrations in urban and peri-urban soil.

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The Effect of Quicklime Stabilization on Soil Properties

Cited by 13 publications

References 5 publications

On the Recent Trends in Expansive Soil Stabilization Using Calcium‐Based Stabilizer Materials (CSMs): A Comprehensive Review

On the Recent Trends in Expansive Soil Stabilization Using Calcium‐Based Stabilizer Materials (CSMs): A Comprehensive Review

Prediction of nickel concentration in peri-urban and urban soils using hybridized empirical bayesian kriging and support vector machine regression

Prediction of Nickel Concentrations in Urban and Peri-Urban Soils: Application of a Hybridized Empirical Bayesian Kriging and Support Vector Machine Regression Approach

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