Analyzing surface settlement factors in single and twin tunnels : A review study
Surface settlement (SS) resulting from tunnel excavation operations is a critical concern in tunnel engineering due to its potential impact on adjacent structures. This review synthesizes current knowledge on factors influencing SS induced by tunneling activities, focusing on tunnel geometry, soil...
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2024
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Online Access: | http://ir.unimas.my/id/eprint/44867/2/Analyzing%20surface.pdf http://ir.unimas.my/id/eprint/44867/ https://www.sciencedirect.com/science/article/pii/S2307187724001226 https://doi.org/10.1016/j.jer.2024.05.009 |
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my.unimas.ir.448672024-05-27T03:59:40Z http://ir.unimas.my/id/eprint/44867/ Analyzing surface settlement factors in single and twin tunnels : A review study Huat, Chia Yu Danial Jahed, Armaghani Lai, Sai Hin Hossein, Motaghedi Panagiotis G., Asteris Pouyan, Fakharin TA Engineering (General). Civil engineering (General) Surface settlement (SS) resulting from tunnel excavation operations is a critical concern in tunnel engineering due to its potential impact on adjacent structures. This review synthesizes current knowledge on factors influencing SS induced by tunneling activities, focusing on tunnel geometry, soil properties, and operational parameters. Empirical formulas, numerical analyses, and machine learning (ML) techniques are examined for the effectiveness in predicting SS, highlighting the limitations and potential. Key findings underscore the significant influence of tunnel geometry, soil properties and tunnel operational parameters on SS outcomes. However, limitations exist in current studies, including the lack of consideration for diverse soil types and operational parameters like jack force thrust and penetration rate. The study underscores the importance of proper management of tunneling operations, including optimizing face pressure, to mitigate SS risks. Practical implications for practicing engineers include thorough site investigations, risk assessments and comprehensive monitoring programs. Leveraging historical data and ML algorithms can enhance SS prediction accuracy and aid in proactive risk management. Ultimately, mitigating SS risks is crucial for safeguarding existing infrastructure in congested urban areas. Elsevier Ltd. 2024 Article PeerReviewed text en http://ir.unimas.my/id/eprint/44867/2/Analyzing%20surface.pdf Huat, Chia Yu and Danial Jahed, Armaghani and Lai, Sai Hin and Hossein, Motaghedi and Panagiotis G., Asteris and Pouyan, Fakharin (2024) Analyzing surface settlement factors in single and twin tunnels : A review study. Journal of Engineering Research. pp. 1-13. ISSN 2307-1877 https://www.sciencedirect.com/science/article/pii/S2307187724001226 https://doi.org/10.1016/j.jer.2024.05.009 |
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TA Engineering (General). Civil engineering (General) Huat, Chia Yu Danial Jahed, Armaghani Lai, Sai Hin Hossein, Motaghedi Panagiotis G., Asteris Pouyan, Fakharin Analyzing surface settlement factors in single and twin tunnels : A review study |
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Surface settlement (SS) resulting from tunnel excavation operations is a critical concern in tunnel engineering
due to its potential impact on adjacent structures. This review synthesizes current knowledge on factors influencing SS induced by tunneling activities, focusing on tunnel geometry, soil properties, and operational parameters. Empirical formulas, numerical analyses, and machine learning (ML) techniques are examined for the effectiveness in predicting SS, highlighting the limitations and potential. Key findings underscore the significant influence of tunnel geometry, soil properties and tunnel operational parameters on SS outcomes. However, limitations exist in current studies, including the lack of consideration for diverse soil types and operational parameters like jack force thrust and penetration rate. The study underscores the importance of proper management of tunneling operations, including optimizing face pressure, to mitigate SS risks. Practical implications for practicing engineers include thorough site investigations, risk assessments and comprehensive monitoring programs. Leveraging historical data and ML algorithms can enhance SS prediction accuracy and aid in proactive risk management. Ultimately, mitigating SS risks is crucial for safeguarding existing infrastructure in congested urban areas. |
format |
Article |
author |
Huat, Chia Yu Danial Jahed, Armaghani Lai, Sai Hin Hossein, Motaghedi Panagiotis G., Asteris Pouyan, Fakharin |
author_facet |
Huat, Chia Yu Danial Jahed, Armaghani Lai, Sai Hin Hossein, Motaghedi Panagiotis G., Asteris Pouyan, Fakharin |
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Huat, Chia Yu |
title |
Analyzing surface settlement factors in single and twin tunnels : A review study |
title_short |
Analyzing surface settlement factors in single and twin tunnels : A review study |
title_full |
Analyzing surface settlement factors in single and twin tunnels : A review study |
title_fullStr |
Analyzing surface settlement factors in single and twin tunnels : A review study |
title_full_unstemmed |
Analyzing surface settlement factors in single and twin tunnels : A review study |
title_sort |
analyzing surface settlement factors in single and twin tunnels : a review study |
publisher |
Elsevier Ltd. |
publishDate |
2024 |
url |
http://ir.unimas.my/id/eprint/44867/2/Analyzing%20surface.pdf http://ir.unimas.my/id/eprint/44867/ https://www.sciencedirect.com/science/article/pii/S2307187724001226 https://doi.org/10.1016/j.jer.2024.05.009 |
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13.160551 |