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Investigating the Shear Strength of Granitic Gneiss Residual Soil Based on Response Surface Methodology
The shear strength of granitic gneiss residual soil (GGRS) determines the stability of colluvial landslides in the Huanggang area, China. It depends on several parameters that represent its structure and state as well as their interactions, and therefore requires accurate assessment. For an effectiv...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10181724/ https://www.ncbi.nlm.nih.gov/pubmed/37177512 http://dx.doi.org/10.3390/s23094308 |
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author | Zou, Hao Zhang, Shu Zhao, Jinqi Qin, Liuzhi Cheng, Hao |
author_facet | Zou, Hao Zhang, Shu Zhao, Jinqi Qin, Liuzhi Cheng, Hao |
author_sort | Zou, Hao |
collection | PubMed |
description | The shear strength of granitic gneiss residual soil (GGRS) determines the stability of colluvial landslides in the Huanggang area, China. It depends on several parameters that represent its structure and state as well as their interactions, and therefore requires accurate assessment. For an effective evaluation of shear strength parameters of GGRS based on these factors and their interactions, three parameters, namely, moisture content, bulk density, and fractal dimension of grain size, were selected as influencing factors in this study based on a thorough investigation of the survey data and physical property tests of landslides in the study area. The individual effects and interaction of the factors were then incorporated by implementing a series of direct shear tests employing the response surface methodology (RSM) into the regression model of the shear parameters. The results indicate that the factors affecting shear parameters in the order of greater to lower are bulk density, moisture content, and fractal dimension, and their interactions are insignificant. The proposed model was validated by applying it to soil specimens from other landslide sites with the same parent bedrock, showing the validity of the strength regression model. This study demonstrates that RSM can be applied for parameter estimation of soils and provide reliable performance, and is also significant for conducting landslide investigation, evaluation, and regional risk assessment. |
format | Online Article Text |
id | pubmed-10181724 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-101817242023-05-13 Investigating the Shear Strength of Granitic Gneiss Residual Soil Based on Response Surface Methodology Zou, Hao Zhang, Shu Zhao, Jinqi Qin, Liuzhi Cheng, Hao Sensors (Basel) Article The shear strength of granitic gneiss residual soil (GGRS) determines the stability of colluvial landslides in the Huanggang area, China. It depends on several parameters that represent its structure and state as well as their interactions, and therefore requires accurate assessment. For an effective evaluation of shear strength parameters of GGRS based on these factors and their interactions, three parameters, namely, moisture content, bulk density, and fractal dimension of grain size, were selected as influencing factors in this study based on a thorough investigation of the survey data and physical property tests of landslides in the study area. The individual effects and interaction of the factors were then incorporated by implementing a series of direct shear tests employing the response surface methodology (RSM) into the regression model of the shear parameters. The results indicate that the factors affecting shear parameters in the order of greater to lower are bulk density, moisture content, and fractal dimension, and their interactions are insignificant. The proposed model was validated by applying it to soil specimens from other landslide sites with the same parent bedrock, showing the validity of the strength regression model. This study demonstrates that RSM can be applied for parameter estimation of soils and provide reliable performance, and is also significant for conducting landslide investigation, evaluation, and regional risk assessment. MDPI 2023-04-26 /pmc/articles/PMC10181724/ /pubmed/37177512 http://dx.doi.org/10.3390/s23094308 Text en © 2023 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Article Zou, Hao Zhang, Shu Zhao, Jinqi Qin, Liuzhi Cheng, Hao Investigating the Shear Strength of Granitic Gneiss Residual Soil Based on Response Surface Methodology |
title | Investigating the Shear Strength of Granitic Gneiss Residual Soil Based on Response Surface Methodology |
title_full | Investigating the Shear Strength of Granitic Gneiss Residual Soil Based on Response Surface Methodology |
title_fullStr | Investigating the Shear Strength of Granitic Gneiss Residual Soil Based on Response Surface Methodology |
title_full_unstemmed | Investigating the Shear Strength of Granitic Gneiss Residual Soil Based on Response Surface Methodology |
title_short | Investigating the Shear Strength of Granitic Gneiss Residual Soil Based on Response Surface Methodology |
title_sort | investigating the shear strength of granitic gneiss residual soil based on response surface methodology |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10181724/ https://www.ncbi.nlm.nih.gov/pubmed/37177512 http://dx.doi.org/10.3390/s23094308 |
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