Determination of earth pressure balance tunnel-related maximum surface settlement: a multivariate adaptive regression splines approach
A major consideration in urban tunnel design is to estimate the ground movements and surface settlements associated with the tunnelling operations. Excessive ground movements may result in damage to adjacent buildings and utilities. Numerous empirical and analytical solutions have been proposed to r...
| Main Authors: | , , , , |
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| Other Authors: | |
| Format: | Journal Article |
| Language: | English |
| Published: |
2016
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| Online Access: | https://hdl.handle.net/10356/84586 http://hdl.handle.net/10220/41886 |
| _version_ | 1811682778674102272 |
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| author | Goh, Anthony Teck Chee Zhang, Wengang Zhang, Yanmei Xiao, Yang Xiang, Yuzhou |
| author2 | School of Civil and Environmental Engineering |
| author_facet | School of Civil and Environmental Engineering Goh, Anthony Teck Chee Zhang, Wengang Zhang, Yanmei Xiao, Yang Xiang, Yuzhou |
| author_sort | Goh, Anthony Teck Chee |
| collection | NTU |
| description | A major consideration in urban tunnel design is to estimate the ground movements and surface settlements associated with the tunnelling operations. Excessive ground movements may result in damage to adjacent buildings and utilities. Numerous empirical and analytical solutions have been proposed to relate the shield tunnel characteristics and surface/subsurface deformation. Numerical analyses, either 2D or 3D, have also been applied to such tunnelling problems. However, substantially fewer approaches have been developed for earth pressure balance (EPB) tunnelling. Based on instrumented data on ground deformation and shield operation from three separate EPB tunnelling projects in Singapore, this paper utilizes a multivariate adaptive regression splines (MARS) approach to establish relationships between the maximum surface settlement and the major influencing factors, including the operation parameters, the cover depth and the ground conditions. Since the method has the ability to map input to output patterns, MARS enables one to map all influencing parameters to surface settlements. The main advantages of MARS over other soft computing techniques such as ANN, RVM, SVM and GP are its capacity to produce a simple, easy-to-interpret model, its ability to estimate the contributions of the input variables, and its computational efficiency. |
| first_indexed | 2024-10-01T04:02:15Z |
| format | Journal Article |
| id | ntu-10356/84586 |
| institution | Nanyang Technological University |
| language | English |
| last_indexed | 2024-10-01T04:02:15Z |
| publishDate | 2016 |
| record_format | dspace |
| spelling | ntu-10356/845862020-03-07T11:43:34Z Determination of earth pressure balance tunnel-related maximum surface settlement: a multivariate adaptive regression splines approach Goh, Anthony Teck Chee Zhang, Wengang Zhang, Yanmei Xiao, Yang Xiang, Yuzhou School of Civil and Environmental Engineering School of Mechanical and Aerospace Engineering Surface settlement EPB shield A major consideration in urban tunnel design is to estimate the ground movements and surface settlements associated with the tunnelling operations. Excessive ground movements may result in damage to adjacent buildings and utilities. Numerous empirical and analytical solutions have been proposed to relate the shield tunnel characteristics and surface/subsurface deformation. Numerical analyses, either 2D or 3D, have also been applied to such tunnelling problems. However, substantially fewer approaches have been developed for earth pressure balance (EPB) tunnelling. Based on instrumented data on ground deformation and shield operation from three separate EPB tunnelling projects in Singapore, this paper utilizes a multivariate adaptive regression splines (MARS) approach to establish relationships between the maximum surface settlement and the major influencing factors, including the operation parameters, the cover depth and the ground conditions. Since the method has the ability to map input to output patterns, MARS enables one to map all influencing parameters to surface settlements. The main advantages of MARS over other soft computing techniques such as ANN, RVM, SVM and GP are its capacity to produce a simple, easy-to-interpret model, its ability to estimate the contributions of the input variables, and its computational efficiency. Accepted version 2016-12-19T07:12:35Z 2019-12-06T15:47:47Z 2016-12-19T07:12:35Z 2019-12-06T15:47:47Z 2016 Journal Article Goh, A. T. C., Zhang, W., Zhang, Y., Xiao, Y., & Xiang, Y. (2016). Determination of earth pressure balance tunnel-related maximum surface settlement: a multivariate adaptive regression splines approach. Bulletin of Engineering Geology and the Environment, in press. 1435-9529 https://hdl.handle.net/10356/84586 http://hdl.handle.net/10220/41886 10.1007/s10064-016-0937-8 en Bulletin of Engineering Geology and the Environment © 2016 Springer-Verlag Berlin Heidelberg. This is the author created version of a work that has been peer reviewed and accepted for publication by Bulletin of Engineering Geology and the Environment, Springer Berlin Heidelberg. It incorporates referee’s comments but changes resulting from the publishing process, such as copyediting, structural formatting, may not be reflected in this document. The published version is available at: [http://dx.doi.org/10.1007/s10064-016-0937-8]. 32 p. application/pdf |
| spellingShingle | Surface settlement EPB shield Goh, Anthony Teck Chee Zhang, Wengang Zhang, Yanmei Xiao, Yang Xiang, Yuzhou Determination of earth pressure balance tunnel-related maximum surface settlement: a multivariate adaptive regression splines approach |
| title | Determination of earth pressure balance tunnel-related maximum surface settlement: a multivariate adaptive regression splines approach |
| title_full | Determination of earth pressure balance tunnel-related maximum surface settlement: a multivariate adaptive regression splines approach |
| title_fullStr | Determination of earth pressure balance tunnel-related maximum surface settlement: a multivariate adaptive regression splines approach |
| title_full_unstemmed | Determination of earth pressure balance tunnel-related maximum surface settlement: a multivariate adaptive regression splines approach |
| title_short | Determination of earth pressure balance tunnel-related maximum surface settlement: a multivariate adaptive regression splines approach |
| title_sort | determination of earth pressure balance tunnel related maximum surface settlement a multivariate adaptive regression splines approach |
| topic | Surface settlement EPB shield |
| url | https://hdl.handle.net/10356/84586 http://hdl.handle.net/10220/41886 |
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