Prediction model of hydraulic conductivity for sedimentary residual soil mixed bentonite as compacted clay liner
This paper describes a development of regression model on predicting the hydraulic conductivity value for sedimentary residual soil mixed bentonite. The data for required parameter for model development was based on the laboratories testing such as compaction testing and hydraulic conductivity testi...
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Institute of Physics
2024
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2-s2.0-85201820657 Khalid N.; Mukri M.; Zain N.H.M.; Zainuddin A.N.; Kamarudin F. Prediction model of hydraulic conductivity for sedimentary residual soil mixed bentonite as compacted clay liner 2024 IOP Conference Series: Earth and Environmental Science 1347 1 10.1088/1755-1315/1347/1/012048 https://www.scopus.com/inward/record.uri?eid=2-s2.0-85201820657&doi=10.1088%2f1755-1315%2f1347%2f1%2f012048&partnerID=40&md5=80f40016007f37f13a89d06998be2aa9 This paper describes a development of regression model on predicting the hydraulic conductivity value for sedimentary residual soil mixed bentonite. The data for required parameter for model development was based on the laboratories testing such as compaction testing and hydraulic conductivity testing. The multiple linear regression model (MLR) was selected to develop a hydraulic conductivity model (k-model). The empirical model was developed based on the 45 datasets from experimental studies encompassing range of maximum dry density (MDD), optimum moisture content (OMC), effective stress and bentonite content. The model developed in this study has met the conditions and has been verified according to the statistical validity requirements. The result shows that the fitted regression model has the reasonably good regression model for R2 = 79%. Meanwhile, the validation shows the small deviation discrepancy from Mean Square Error (MSE), Mean Absolute Error (MAE), and Mean Absolute Percentage Error (MAPE) with a determination coefficient, R2 = 82%. In conclusion, the develop k-model in this study present a good prediction for hydraulic conductivity value. © 2024 Published under licence by IOP Publishing Ltd. Institute of Physics 17551307 English Conference paper |
author |
Khalid N.; Mukri M.; Zain N.H.M.; Zainuddin A.N.; Kamarudin F. |
spellingShingle |
Khalid N.; Mukri M.; Zain N.H.M.; Zainuddin A.N.; Kamarudin F. Prediction model of hydraulic conductivity for sedimentary residual soil mixed bentonite as compacted clay liner |
author_facet |
Khalid N.; Mukri M.; Zain N.H.M.; Zainuddin A.N.; Kamarudin F. |
author_sort |
Khalid N.; Mukri M.; Zain N.H.M.; Zainuddin A.N.; Kamarudin F. |
title |
Prediction model of hydraulic conductivity for sedimentary residual soil mixed bentonite as compacted clay liner |
title_short |
Prediction model of hydraulic conductivity for sedimentary residual soil mixed bentonite as compacted clay liner |
title_full |
Prediction model of hydraulic conductivity for sedimentary residual soil mixed bentonite as compacted clay liner |
title_fullStr |
Prediction model of hydraulic conductivity for sedimentary residual soil mixed bentonite as compacted clay liner |
title_full_unstemmed |
Prediction model of hydraulic conductivity for sedimentary residual soil mixed bentonite as compacted clay liner |
title_sort |
Prediction model of hydraulic conductivity for sedimentary residual soil mixed bentonite as compacted clay liner |
publishDate |
2024 |
container_title |
IOP Conference Series: Earth and Environmental Science |
container_volume |
1347 |
container_issue |
1 |
doi_str_mv |
10.1088/1755-1315/1347/1/012048 |
url |
https://www.scopus.com/inward/record.uri?eid=2-s2.0-85201820657&doi=10.1088%2f1755-1315%2f1347%2f1%2f012048&partnerID=40&md5=80f40016007f37f13a89d06998be2aa9 |
description |
This paper describes a development of regression model on predicting the hydraulic conductivity value for sedimentary residual soil mixed bentonite. The data for required parameter for model development was based on the laboratories testing such as compaction testing and hydraulic conductivity testing. The multiple linear regression model (MLR) was selected to develop a hydraulic conductivity model (k-model). The empirical model was developed based on the 45 datasets from experimental studies encompassing range of maximum dry density (MDD), optimum moisture content (OMC), effective stress and bentonite content. The model developed in this study has met the conditions and has been verified according to the statistical validity requirements. The result shows that the fitted regression model has the reasonably good regression model for R2 = 79%. Meanwhile, the validation shows the small deviation discrepancy from Mean Square Error (MSE), Mean Absolute Error (MAE), and Mean Absolute Percentage Error (MAPE) with a determination coefficient, R2 = 82%. In conclusion, the develop k-model in this study present a good prediction for hydraulic conductivity value. © 2024 Published under licence by IOP Publishing Ltd. |
publisher |
Institute of Physics |
issn |
17551307 |
language |
English |
format |
Conference paper |
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|
record_format |
scopus |
collection |
Scopus |
_version_ |
1812871796202930176 |