Assessment of leachate-contaminated clays using experimental and artificial methods
The investigation of leachate-contaminated clay (LCC) is essential for landfill engineering assessment and achievement of sustainable development goals. Several static and dynamic laboratory tests, including unconfined compressive strength (UCS), California bearing ratio (CBR), and cyclic simple she...
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| Format: | Article |
| Language: | English |
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Elsevier
2025-01-01
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| Series: | Journal of Rock Mechanics and Geotechnical Engineering |
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| Online Access: | http://www.sciencedirect.com/science/article/pii/S167477552400338X |
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| author | Hossein Moradi Moghaddam Ahmad Fahimifar Taghi Ebadi Mohsen Keramati Sumi Siddiqua |
| author_facet | Hossein Moradi Moghaddam Ahmad Fahimifar Taghi Ebadi Mohsen Keramati Sumi Siddiqua |
| author_sort | Hossein Moradi Moghaddam |
| collection | DOAJ |
| description | The investigation of leachate-contaminated clay (LCC) is essential for landfill engineering assessment and achievement of sustainable development goals. Several static and dynamic laboratory tests, including unconfined compressive strength (UCS), California bearing ratio (CBR), and cyclic simple shear, are conducted. Cyclic simple shear experiments on LCCs were performed to evaluate the damping and shear modulus. The investigated factors are vertical load (VL), leachate content (LC), frequency (F), and shear strain (ShS) for LCC. Forensic-based investigation optimization (FBIO) and equilibrium optimizer algorithm (EOA) were utilized in addition to multiple types of ensemble models, including adaptive boosting (ADB), gradient boosting regression tree (GBRT), extreme gradient boosting (XGB)) and random forest (RF). The comparison of the methods showed that GBRT-FBIO and XGB-EOA models outperformed other models for shear modulus and damping of LCC. The p-value less than 0.0001 shows the significance of the used models in the response surface methodology (RSM) method. |
| format | Article |
| id | doaj-art-fe03d6b26b2743979ca854b228a7025c |
| institution | Kabale University |
| issn | 1674-7755 |
| language | English |
| publishDate | 2025-01-01 |
| publisher | Elsevier |
| record_format | Article |
| series | Journal of Rock Mechanics and Geotechnical Engineering |
| spelling | doaj-art-fe03d6b26b2743979ca854b228a7025c2025-01-17T04:49:12ZengElsevierJournal of Rock Mechanics and Geotechnical Engineering1674-77552025-01-01171524538Assessment of leachate-contaminated clays using experimental and artificial methodsHossein Moradi Moghaddam0Ahmad Fahimifar1Taghi Ebadi2Mohsen Keramati3Sumi Siddiqua4Department of Civil & Environmental Engineering, Amirkabir University of Technology, Tehran, 1591634311, IranDepartment of Civil & Environmental Engineering, Amirkabir University of Technology, Tehran, 1591634311, Iran; Corresponding author.Department of Civil & Environmental Engineering, Amirkabir University of Technology, Tehran, 1591634311, IranFaculty of Civil Engineering, Shahrood University of Technology, Shahrood, 3619995161, IranSchool of Engineering, University of British Columbia, Kelowna, V6T 1Z4, CanadaThe investigation of leachate-contaminated clay (LCC) is essential for landfill engineering assessment and achievement of sustainable development goals. Several static and dynamic laboratory tests, including unconfined compressive strength (UCS), California bearing ratio (CBR), and cyclic simple shear, are conducted. Cyclic simple shear experiments on LCCs were performed to evaluate the damping and shear modulus. The investigated factors are vertical load (VL), leachate content (LC), frequency (F), and shear strain (ShS) for LCC. Forensic-based investigation optimization (FBIO) and equilibrium optimizer algorithm (EOA) were utilized in addition to multiple types of ensemble models, including adaptive boosting (ADB), gradient boosting regression tree (GBRT), extreme gradient boosting (XGB)) and random forest (RF). The comparison of the methods showed that GBRT-FBIO and XGB-EOA models outperformed other models for shear modulus and damping of LCC. The p-value less than 0.0001 shows the significance of the used models in the response surface methodology (RSM) method.http://www.sciencedirect.com/science/article/pii/S167477552400338XContaminated linerDynamic parameterResponse surface methodology (RSM)Python method |
| spellingShingle | Hossein Moradi Moghaddam Ahmad Fahimifar Taghi Ebadi Mohsen Keramati Sumi Siddiqua Assessment of leachate-contaminated clays using experimental and artificial methods Journal of Rock Mechanics and Geotechnical Engineering Contaminated liner Dynamic parameter Response surface methodology (RSM) Python method |
| title | Assessment of leachate-contaminated clays using experimental and artificial methods |
| title_full | Assessment of leachate-contaminated clays using experimental and artificial methods |
| title_fullStr | Assessment of leachate-contaminated clays using experimental and artificial methods |
| title_full_unstemmed | Assessment of leachate-contaminated clays using experimental and artificial methods |
| title_short | Assessment of leachate-contaminated clays using experimental and artificial methods |
| title_sort | assessment of leachate contaminated clays using experimental and artificial methods |
| topic | Contaminated liner Dynamic parameter Response surface methodology (RSM) Python method |
| url | http://www.sciencedirect.com/science/article/pii/S167477552400338X |
| work_keys_str_mv | AT hosseinmoradimoghaddam assessmentofleachatecontaminatedclaysusingexperimentalandartificialmethods AT ahmadfahimifar assessmentofleachatecontaminatedclaysusingexperimentalandartificialmethods AT taghiebadi assessmentofleachatecontaminatedclaysusingexperimentalandartificialmethods AT mohsenkeramati assessmentofleachatecontaminatedclaysusingexperimentalandartificialmethods AT sumisiddiqua assessmentofleachatecontaminatedclaysusingexperimentalandartificialmethods |