Prediction of the tunnel displacement induced by laterally adjacent excavations using multivariate adaptive regression splines
Abstract Excavations may cause excessive ground movements, resulting in potential damage to laterally adjacent tunnels. The aim of this investigation is to present a simple assessment technique using a multivariate adaptive regression splines (MARS) model, which can map the nonlinear interactions be...
Ausführliche Beschreibung
Gespeichert in:
| Autor*in: |
Zheng, Gang [verfasserIn] He, Xiaopei [verfasserIn] Zhou, Haizuo [verfasserIn] Yang, Xinyu [verfasserIn] Yu, Xiaoxuan [verfasserIn] Zhao, Jiapeng [verfasserIn] |
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| Format: |
E-Artikel |
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| Sprache: |
Englisch |
| Erschienen: |
2020 |
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| Schlagwörter: |
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| Übergeordnetes Werk: |
Enthalten in: Acta geotechnica - Berlin : Springer, 2006, 15(2020), 8 vom: 08. Feb., Seite 2227-2237 |
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| Übergeordnetes Werk: |
volume:15 ; year:2020 ; number:8 ; day:08 ; month:02 ; pages:2227-2237 |
| Links: |
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| DOI / URN: |
10.1007/s11440-020-00916-w |
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| Katalog-ID: |
SPR040247546 |
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| 245 | 1 | 0 | |a Prediction of the tunnel displacement induced by laterally adjacent excavations using multivariate adaptive regression splines |
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| 520 | |a Abstract Excavations may cause excessive ground movements, resulting in potential damage to laterally adjacent tunnels. The aim of this investigation is to present a simple assessment technique using a multivariate adaptive regression splines (MARS) model, which can map the nonlinear interactions between the influencing factors and the maximum horizontal deformation of tunnels. A high-quality case history in Tianjin, China, is presented to illustrate the effect of excavation on the tunnel deformation and to validate the FEM. The hypothetical data produced by the FEM provide a basis for developing the proposed MARS model. Based on the proposed model, the independent and coupled effects of the input variables (i.e. the normalized buried depth of tunnels Ht/He, the normalized horizontal distance between tunnels and retaining structures Lt/He, and the maximum horizontal displacement of retaining structures, δRmax) on the tunnel response are analysed. The prediction precision and accuracy of the MARS model are validated via the artificial data and the collected case histories. | ||
| 650 | 4 | |a Case histories |7 (dpeaa)DE-He213 | |
| 650 | 4 | |a Excavation |7 (dpeaa)DE-He213 | |
| 650 | 4 | |a Multivariate adaptive regression splines |7 (dpeaa)DE-He213 | |
| 650 | 4 | |a Tunnel deformation |7 (dpeaa)DE-He213 | |
| 700 | 1 | |a He, Xiaopei |e verfasserin |4 aut | |
| 700 | 1 | |a Zhou, Haizuo |e verfasserin |4 aut | |
| 700 | 1 | |a Yang, Xinyu |e verfasserin |4 aut | |
| 700 | 1 | |a Yu, Xiaoxuan |e verfasserin |4 aut | |
| 700 | 1 | |a Zhao, Jiapeng |e verfasserin |4 aut | |
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10.1007/s11440-020-00916-w doi (DE-627)SPR040247546 (SPR)s11440-020-00916-w-e DE-627 ger DE-627 rakwb eng 550 ASE 56.20 bkl Zheng, Gang verfasserin aut Prediction of the tunnel displacement induced by laterally adjacent excavations using multivariate adaptive regression splines 2020 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Abstract Excavations may cause excessive ground movements, resulting in potential damage to laterally adjacent tunnels. The aim of this investigation is to present a simple assessment technique using a multivariate adaptive regression splines (MARS) model, which can map the nonlinear interactions between the influencing factors and the maximum horizontal deformation of tunnels. A high-quality case history in Tianjin, China, is presented to illustrate the effect of excavation on the tunnel deformation and to validate the FEM. The hypothetical data produced by the FEM provide a basis for developing the proposed MARS model. Based on the proposed model, the independent and coupled effects of the input variables (i.e. the normalized buried depth of tunnels Ht/He, the normalized horizontal distance between tunnels and retaining structures Lt/He, and the maximum horizontal displacement of retaining structures, δRmax) on the tunnel response are analysed. The prediction precision and accuracy of the MARS model are validated via the artificial data and the collected case histories. Case histories (dpeaa)DE-He213 Excavation (dpeaa)DE-He213 Multivariate adaptive regression splines (dpeaa)DE-He213 Tunnel deformation (dpeaa)DE-He213 He, Xiaopei verfasserin aut Zhou, Haizuo verfasserin aut Yang, Xinyu verfasserin aut Yu, Xiaoxuan verfasserin aut Zhao, Jiapeng verfasserin aut Enthalten in Acta geotechnica Berlin : Springer, 2006 15(2020), 8 vom: 08. Feb., Seite 2227-2237 (DE-627)513533192 (DE-600)2239453-9 1861-1133 nnns volume:15 year:2020 number:8 day:08 month:02 pages:2227-2237 https://dx.doi.org/10.1007/s11440-020-00916-w lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER SSG-OPC-GGO SSG-OPC-GEO SSG-OPC-ASE GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2118 GBV_ILN_2119 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4328 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 56.20 ASE AR 15 2020 8 08 02 2227-2237 |
| spelling |
10.1007/s11440-020-00916-w doi (DE-627)SPR040247546 (SPR)s11440-020-00916-w-e DE-627 ger DE-627 rakwb eng 550 ASE 56.20 bkl Zheng, Gang verfasserin aut Prediction of the tunnel displacement induced by laterally adjacent excavations using multivariate adaptive regression splines 2020 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Abstract Excavations may cause excessive ground movements, resulting in potential damage to laterally adjacent tunnels. The aim of this investigation is to present a simple assessment technique using a multivariate adaptive regression splines (MARS) model, which can map the nonlinear interactions between the influencing factors and the maximum horizontal deformation of tunnels. A high-quality case history in Tianjin, China, is presented to illustrate the effect of excavation on the tunnel deformation and to validate the FEM. The hypothetical data produced by the FEM provide a basis for developing the proposed MARS model. Based on the proposed model, the independent and coupled effects of the input variables (i.e. the normalized buried depth of tunnels Ht/He, the normalized horizontal distance between tunnels and retaining structures Lt/He, and the maximum horizontal displacement of retaining structures, δRmax) on the tunnel response are analysed. The prediction precision and accuracy of the MARS model are validated via the artificial data and the collected case histories. Case histories (dpeaa)DE-He213 Excavation (dpeaa)DE-He213 Multivariate adaptive regression splines (dpeaa)DE-He213 Tunnel deformation (dpeaa)DE-He213 He, Xiaopei verfasserin aut Zhou, Haizuo verfasserin aut Yang, Xinyu verfasserin aut Yu, Xiaoxuan verfasserin aut Zhao, Jiapeng verfasserin aut Enthalten in Acta geotechnica Berlin : Springer, 2006 15(2020), 8 vom: 08. Feb., Seite 2227-2237 (DE-627)513533192 (DE-600)2239453-9 1861-1133 nnns volume:15 year:2020 number:8 day:08 month:02 pages:2227-2237 https://dx.doi.org/10.1007/s11440-020-00916-w lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER SSG-OPC-GGO SSG-OPC-GEO SSG-OPC-ASE GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2118 GBV_ILN_2119 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4328 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 56.20 ASE AR 15 2020 8 08 02 2227-2237 |
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10.1007/s11440-020-00916-w doi (DE-627)SPR040247546 (SPR)s11440-020-00916-w-e DE-627 ger DE-627 rakwb eng 550 ASE 56.20 bkl Zheng, Gang verfasserin aut Prediction of the tunnel displacement induced by laterally adjacent excavations using multivariate adaptive regression splines 2020 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Abstract Excavations may cause excessive ground movements, resulting in potential damage to laterally adjacent tunnels. The aim of this investigation is to present a simple assessment technique using a multivariate adaptive regression splines (MARS) model, which can map the nonlinear interactions between the influencing factors and the maximum horizontal deformation of tunnels. A high-quality case history in Tianjin, China, is presented to illustrate the effect of excavation on the tunnel deformation and to validate the FEM. The hypothetical data produced by the FEM provide a basis for developing the proposed MARS model. Based on the proposed model, the independent and coupled effects of the input variables (i.e. the normalized buried depth of tunnels Ht/He, the normalized horizontal distance between tunnels and retaining structures Lt/He, and the maximum horizontal displacement of retaining structures, δRmax) on the tunnel response are analysed. The prediction precision and accuracy of the MARS model are validated via the artificial data and the collected case histories. Case histories (dpeaa)DE-He213 Excavation (dpeaa)DE-He213 Multivariate adaptive regression splines (dpeaa)DE-He213 Tunnel deformation (dpeaa)DE-He213 He, Xiaopei verfasserin aut Zhou, Haizuo verfasserin aut Yang, Xinyu verfasserin aut Yu, Xiaoxuan verfasserin aut Zhao, Jiapeng verfasserin aut Enthalten in Acta geotechnica Berlin : Springer, 2006 15(2020), 8 vom: 08. Feb., Seite 2227-2237 (DE-627)513533192 (DE-600)2239453-9 1861-1133 nnns volume:15 year:2020 number:8 day:08 month:02 pages:2227-2237 https://dx.doi.org/10.1007/s11440-020-00916-w lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER SSG-OPC-GGO SSG-OPC-GEO SSG-OPC-ASE GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2118 GBV_ILN_2119 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4328 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 56.20 ASE AR 15 2020 8 08 02 2227-2237 |
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10.1007/s11440-020-00916-w doi (DE-627)SPR040247546 (SPR)s11440-020-00916-w-e DE-627 ger DE-627 rakwb eng 550 ASE 56.20 bkl Zheng, Gang verfasserin aut Prediction of the tunnel displacement induced by laterally adjacent excavations using multivariate adaptive regression splines 2020 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Abstract Excavations may cause excessive ground movements, resulting in potential damage to laterally adjacent tunnels. The aim of this investigation is to present a simple assessment technique using a multivariate adaptive regression splines (MARS) model, which can map the nonlinear interactions between the influencing factors and the maximum horizontal deformation of tunnels. A high-quality case history in Tianjin, China, is presented to illustrate the effect of excavation on the tunnel deformation and to validate the FEM. The hypothetical data produced by the FEM provide a basis for developing the proposed MARS model. Based on the proposed model, the independent and coupled effects of the input variables (i.e. the normalized buried depth of tunnels Ht/He, the normalized horizontal distance between tunnels and retaining structures Lt/He, and the maximum horizontal displacement of retaining structures, δRmax) on the tunnel response are analysed. The prediction precision and accuracy of the MARS model are validated via the artificial data and the collected case histories. Case histories (dpeaa)DE-He213 Excavation (dpeaa)DE-He213 Multivariate adaptive regression splines (dpeaa)DE-He213 Tunnel deformation (dpeaa)DE-He213 He, Xiaopei verfasserin aut Zhou, Haizuo verfasserin aut Yang, Xinyu verfasserin aut Yu, Xiaoxuan verfasserin aut Zhao, Jiapeng verfasserin aut Enthalten in Acta geotechnica Berlin : Springer, 2006 15(2020), 8 vom: 08. Feb., Seite 2227-2237 (DE-627)513533192 (DE-600)2239453-9 1861-1133 nnns volume:15 year:2020 number:8 day:08 month:02 pages:2227-2237 https://dx.doi.org/10.1007/s11440-020-00916-w lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER SSG-OPC-GGO SSG-OPC-GEO SSG-OPC-ASE GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2118 GBV_ILN_2119 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4328 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 56.20 ASE AR 15 2020 8 08 02 2227-2237 |
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10.1007/s11440-020-00916-w doi (DE-627)SPR040247546 (SPR)s11440-020-00916-w-e DE-627 ger DE-627 rakwb eng 550 ASE 56.20 bkl Zheng, Gang verfasserin aut Prediction of the tunnel displacement induced by laterally adjacent excavations using multivariate adaptive regression splines 2020 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Abstract Excavations may cause excessive ground movements, resulting in potential damage to laterally adjacent tunnels. The aim of this investigation is to present a simple assessment technique using a multivariate adaptive regression splines (MARS) model, which can map the nonlinear interactions between the influencing factors and the maximum horizontal deformation of tunnels. A high-quality case history in Tianjin, China, is presented to illustrate the effect of excavation on the tunnel deformation and to validate the FEM. The hypothetical data produced by the FEM provide a basis for developing the proposed MARS model. Based on the proposed model, the independent and coupled effects of the input variables (i.e. the normalized buried depth of tunnels Ht/He, the normalized horizontal distance between tunnels and retaining structures Lt/He, and the maximum horizontal displacement of retaining structures, δRmax) on the tunnel response are analysed. The prediction precision and accuracy of the MARS model are validated via the artificial data and the collected case histories. Case histories (dpeaa)DE-He213 Excavation (dpeaa)DE-He213 Multivariate adaptive regression splines (dpeaa)DE-He213 Tunnel deformation (dpeaa)DE-He213 He, Xiaopei verfasserin aut Zhou, Haizuo verfasserin aut Yang, Xinyu verfasserin aut Yu, Xiaoxuan verfasserin aut Zhao, Jiapeng verfasserin aut Enthalten in Acta geotechnica Berlin : Springer, 2006 15(2020), 8 vom: 08. Feb., Seite 2227-2237 (DE-627)513533192 (DE-600)2239453-9 1861-1133 nnns volume:15 year:2020 number:8 day:08 month:02 pages:2227-2237 https://dx.doi.org/10.1007/s11440-020-00916-w lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER SSG-OPC-GGO SSG-OPC-GEO SSG-OPC-ASE GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2118 GBV_ILN_2119 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4328 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 56.20 ASE AR 15 2020 8 08 02 2227-2237 |
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Enthalten in Acta geotechnica 15(2020), 8 vom: 08. Feb., Seite 2227-2237 volume:15 year:2020 number:8 day:08 month:02 pages:2227-2237 |
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Case histories Excavation Multivariate adaptive regression splines Tunnel deformation |
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Acta geotechnica |
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Zheng, Gang @@aut@@ He, Xiaopei @@aut@@ Zhou, Haizuo @@aut@@ Yang, Xinyu @@aut@@ Yu, Xiaoxuan @@aut@@ Zhao, Jiapeng @@aut@@ |
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2020-02-08T00:00:00Z |
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<?xml version="1.0" encoding="UTF-8"?><collection xmlns="http://www.loc.gov/MARC21/slim"><record><leader>01000caa a22002652 4500</leader><controlfield tag="001">SPR040247546</controlfield><controlfield tag="003">DE-627</controlfield><controlfield tag="005">20220111071423.0</controlfield><controlfield tag="007">cr uuu---uuuuu</controlfield><controlfield tag="008">201007s2020 xx |||||o 00| ||eng c</controlfield><datafield tag="024" ind1="7" ind2=" "><subfield code="a">10.1007/s11440-020-00916-w</subfield><subfield code="2">doi</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(DE-627)SPR040247546</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(SPR)s11440-020-00916-w-e</subfield></datafield><datafield tag="040" ind1=" " ind2=" "><subfield code="a">DE-627</subfield><subfield code="b">ger</subfield><subfield code="c">DE-627</subfield><subfield code="e">rakwb</subfield></datafield><datafield tag="041" ind1=" " ind2=" "><subfield code="a">eng</subfield></datafield><datafield tag="082" ind1="0" ind2="4"><subfield code="a">550</subfield><subfield code="q">ASE</subfield></datafield><datafield tag="084" ind1=" " ind2=" "><subfield code="a">56.20</subfield><subfield code="2">bkl</subfield></datafield><datafield tag="100" ind1="1" ind2=" "><subfield code="a">Zheng, Gang</subfield><subfield code="e">verfasserin</subfield><subfield code="4">aut</subfield></datafield><datafield tag="245" ind1="1" ind2="0"><subfield code="a">Prediction of the tunnel displacement induced by laterally adjacent excavations using multivariate adaptive regression splines</subfield></datafield><datafield tag="264" ind1=" " ind2="1"><subfield code="c">2020</subfield></datafield><datafield tag="336" ind1=" " ind2=" "><subfield code="a">Text</subfield><subfield code="b">txt</subfield><subfield code="2">rdacontent</subfield></datafield><datafield tag="337" ind1=" " ind2=" "><subfield code="a">Computermedien</subfield><subfield code="b">c</subfield><subfield code="2">rdamedia</subfield></datafield><datafield tag="338" ind1=" " ind2=" "><subfield code="a">Online-Ressource</subfield><subfield code="b">cr</subfield><subfield code="2">rdacarrier</subfield></datafield><datafield tag="520" ind1=" " ind2=" "><subfield code="a">Abstract Excavations may cause excessive ground movements, resulting in potential damage to laterally adjacent tunnels. The aim of this investigation is to present a simple assessment technique using a multivariate adaptive regression splines (MARS) model, which can map the nonlinear interactions between the influencing factors and the maximum horizontal deformation of tunnels. A high-quality case history in Tianjin, China, is presented to illustrate the effect of excavation on the tunnel deformation and to validate the FEM. The hypothetical data produced by the FEM provide a basis for developing the proposed MARS model. Based on the proposed model, the independent and coupled effects of the input variables (i.e. the normalized buried depth of tunnels Ht/He, the normalized horizontal distance between tunnels and retaining structures Lt/He, and the maximum horizontal displacement of retaining structures, δRmax) on the tunnel response are analysed. 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Zheng, Gang |
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Zheng, Gang ddc 550 bkl 56.20 misc Case histories misc Excavation misc Multivariate adaptive regression splines misc Tunnel deformation Prediction of the tunnel displacement induced by laterally adjacent excavations using multivariate adaptive regression splines |
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550 ASE 56.20 bkl Prediction of the tunnel displacement induced by laterally adjacent excavations using multivariate adaptive regression splines Case histories (dpeaa)DE-He213 Excavation (dpeaa)DE-He213 Multivariate adaptive regression splines (dpeaa)DE-He213 Tunnel deformation (dpeaa)DE-He213 |
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ddc 550 bkl 56.20 misc Case histories misc Excavation misc Multivariate adaptive regression splines misc Tunnel deformation |
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ddc 550 bkl 56.20 misc Case histories misc Excavation misc Multivariate adaptive regression splines misc Tunnel deformation |
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Prediction of the tunnel displacement induced by laterally adjacent excavations using multivariate adaptive regression splines |
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Prediction of the tunnel displacement induced by laterally adjacent excavations using multivariate adaptive regression splines |
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Zheng, Gang He, Xiaopei Zhou, Haizuo Yang, Xinyu Yu, Xiaoxuan Zhao, Jiapeng |
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prediction of the tunnel displacement induced by laterally adjacent excavations using multivariate adaptive regression splines |
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Prediction of the tunnel displacement induced by laterally adjacent excavations using multivariate adaptive regression splines |
| abstract |
Abstract Excavations may cause excessive ground movements, resulting in potential damage to laterally adjacent tunnels. The aim of this investigation is to present a simple assessment technique using a multivariate adaptive regression splines (MARS) model, which can map the nonlinear interactions between the influencing factors and the maximum horizontal deformation of tunnels. A high-quality case history in Tianjin, China, is presented to illustrate the effect of excavation on the tunnel deformation and to validate the FEM. The hypothetical data produced by the FEM provide a basis for developing the proposed MARS model. Based on the proposed model, the independent and coupled effects of the input variables (i.e. the normalized buried depth of tunnels Ht/He, the normalized horizontal distance between tunnels and retaining structures Lt/He, and the maximum horizontal displacement of retaining structures, δRmax) on the tunnel response are analysed. The prediction precision and accuracy of the MARS model are validated via the artificial data and the collected case histories. |
| abstractGer |
Abstract Excavations may cause excessive ground movements, resulting in potential damage to laterally adjacent tunnels. The aim of this investigation is to present a simple assessment technique using a multivariate adaptive regression splines (MARS) model, which can map the nonlinear interactions between the influencing factors and the maximum horizontal deformation of tunnels. A high-quality case history in Tianjin, China, is presented to illustrate the effect of excavation on the tunnel deformation and to validate the FEM. The hypothetical data produced by the FEM provide a basis for developing the proposed MARS model. Based on the proposed model, the independent and coupled effects of the input variables (i.e. the normalized buried depth of tunnels Ht/He, the normalized horizontal distance between tunnels and retaining structures Lt/He, and the maximum horizontal displacement of retaining structures, δRmax) on the tunnel response are analysed. The prediction precision and accuracy of the MARS model are validated via the artificial data and the collected case histories. |
| abstract_unstemmed |
Abstract Excavations may cause excessive ground movements, resulting in potential damage to laterally adjacent tunnels. The aim of this investigation is to present a simple assessment technique using a multivariate adaptive regression splines (MARS) model, which can map the nonlinear interactions between the influencing factors and the maximum horizontal deformation of tunnels. A high-quality case history in Tianjin, China, is presented to illustrate the effect of excavation on the tunnel deformation and to validate the FEM. The hypothetical data produced by the FEM provide a basis for developing the proposed MARS model. Based on the proposed model, the independent and coupled effects of the input variables (i.e. the normalized buried depth of tunnels Ht/He, the normalized horizontal distance between tunnels and retaining structures Lt/He, and the maximum horizontal displacement of retaining structures, δRmax) on the tunnel response are analysed. The prediction precision and accuracy of the MARS model are validated via the artificial data and the collected case histories. |
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8 |
| title_short |
Prediction of the tunnel displacement induced by laterally adjacent excavations using multivariate adaptive regression splines |
| url |
https://dx.doi.org/10.1007/s11440-020-00916-w |
| remote_bool |
true |
| author2 |
He, Xiaopei Zhou, Haizuo Yang, Xinyu Yu, Xiaoxuan Zhao, Jiapeng |
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He, Xiaopei Zhou, Haizuo Yang, Xinyu Yu, Xiaoxuan Zhao, Jiapeng |
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| doi_str |
10.1007/s11440-020-00916-w |
| up_date |
2024-07-03T14:44:56.852Z |
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1803569486212628480 |
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| score |
7.400298 |