Effects of Soil Test Variability in the Bearing Capacity of Shallow Foundations
Abstract This study presents the influence of variability for geotechnical parameters on the bearing capacity of shallow foundations. This was made from the ground variability and variability of the geotechnical tests. Finite element models of a continuous footing were used with an elastoplastic mod...
Ausführliche Beschreibung
Gespeichert in:
| Autor*in: |
Bolaños, Cristhian Camilo Mendoza [verfasserIn] |
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| Format: |
E-Artikel |
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| Sprache: |
Englisch |
| Erschienen: |
2021 |
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| Schlagwörter: |
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| Anmerkung: |
© The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2021 |
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| Übergeordnetes Werk: |
Enthalten in: Transportation infrastructure geotechnology - New York, NY : Springer US, 2014, 9(2021), 6 vom: 01. Okt., Seite 854-873 |
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| Übergeordnetes Werk: |
volume:9 ; year:2021 ; number:6 ; day:01 ; month:10 ; pages:854-873 |
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| DOI / URN: |
10.1007/s40515-021-00201-7 |
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| Katalog-ID: |
SPR048647993 |
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| 100 | 1 | |a Bolaños, Cristhian Camilo Mendoza |e verfasserin |4 aut | |
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| 520 | |a Abstract This study presents the influence of variability for geotechnical parameters on the bearing capacity of shallow foundations. This was made from the ground variability and variability of the geotechnical tests. Finite element models of a continuous footing were used with an elastoplastic model with the soil geological history. Then, random parameters were generated from the selected model. The parameters were generated in two ways. Firstly, when the parameters are not correlated. This is done with the variability coefficients (COV) recorded by different researchers for each parameter. Secondly, the parameters are considered statistically correlated because they come from the same test. This case used the same COV for the parameters from the same test. The division of the parameters was for the soil shear strength parameters and the soil compression parameters. Subsequently, with the generated parameters, Monte Carlo simulations were performed. The above was possible by integrating these parameters in the finite element models. The results explain the influence of geotechnical parameters on the bearing capacity of a shallow foundation. In addition, the weight of different geotechnical parameters was shown in the quality function with which the tests were made. Regarding the tests, it shows which tests are more important for the bearing capacity. Then, it can be concluded which parameters and tests should be obtained more carefully because they have greater weight in the behavior of a shallow foundation. In addition, an analysis of the exceedance probability of the load capacity was performed. | ||
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| 650 | 4 | |a Shallow foundations |7 (dpeaa)DE-He213 | |
| 650 | 4 | |a Elastoplastic model |7 (dpeaa)DE-He213 | |
| 650 | 4 | |a Variability in geotechnical tests |7 (dpeaa)DE-He213 | |
| 700 | 1 | |a Hurtado, Jorge E. |4 aut | |
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10.1007/s40515-021-00201-7 doi (DE-627)SPR048647993 (SPR)s40515-021-00201-7-e DE-627 ger DE-627 rakwb eng Bolaños, Cristhian Camilo Mendoza verfasserin aut Effects of Soil Test Variability in the Bearing Capacity of Shallow Foundations 2021 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2021 Abstract This study presents the influence of variability for geotechnical parameters on the bearing capacity of shallow foundations. This was made from the ground variability and variability of the geotechnical tests. Finite element models of a continuous footing were used with an elastoplastic model with the soil geological history. Then, random parameters were generated from the selected model. The parameters were generated in two ways. Firstly, when the parameters are not correlated. This is done with the variability coefficients (COV) recorded by different researchers for each parameter. Secondly, the parameters are considered statistically correlated because they come from the same test. This case used the same COV for the parameters from the same test. The division of the parameters was for the soil shear strength parameters and the soil compression parameters. Subsequently, with the generated parameters, Monte Carlo simulations were performed. The above was possible by integrating these parameters in the finite element models. The results explain the influence of geotechnical parameters on the bearing capacity of a shallow foundation. In addition, the weight of different geotechnical parameters was shown in the quality function with which the tests were made. Regarding the tests, it shows which tests are more important for the bearing capacity. Then, it can be concluded which parameters and tests should be obtained more carefully because they have greater weight in the behavior of a shallow foundation. In addition, an analysis of the exceedance probability of the load capacity was performed. Geotechnical parameters (dpeaa)DE-He213 Finite elements with random parameters (dpeaa)DE-He213 Shallow foundations (dpeaa)DE-He213 Elastoplastic model (dpeaa)DE-He213 Variability in geotechnical tests (dpeaa)DE-He213 Hurtado, Jorge E. aut Enthalten in Transportation infrastructure geotechnology New York, NY : Springer US, 2014 9(2021), 6 vom: 01. Okt., Seite 854-873 (DE-627)780378830 (DE-600)2760372-6 2196-7210 nnns volume:9 year:2021 number:6 day:01 month:10 pages:854-873 https://dx.doi.org/10.1007/s40515-021-00201-7 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER 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_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 AR 9 2021 6 01 10 854-873 |
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10.1007/s40515-021-00201-7 doi (DE-627)SPR048647993 (SPR)s40515-021-00201-7-e DE-627 ger DE-627 rakwb eng Bolaños, Cristhian Camilo Mendoza verfasserin aut Effects of Soil Test Variability in the Bearing Capacity of Shallow Foundations 2021 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2021 Abstract This study presents the influence of variability for geotechnical parameters on the bearing capacity of shallow foundations. This was made from the ground variability and variability of the geotechnical tests. Finite element models of a continuous footing were used with an elastoplastic model with the soil geological history. Then, random parameters were generated from the selected model. The parameters were generated in two ways. Firstly, when the parameters are not correlated. This is done with the variability coefficients (COV) recorded by different researchers for each parameter. Secondly, the parameters are considered statistically correlated because they come from the same test. This case used the same COV for the parameters from the same test. The division of the parameters was for the soil shear strength parameters and the soil compression parameters. Subsequently, with the generated parameters, Monte Carlo simulations were performed. The above was possible by integrating these parameters in the finite element models. The results explain the influence of geotechnical parameters on the bearing capacity of a shallow foundation. In addition, the weight of different geotechnical parameters was shown in the quality function with which the tests were made. Regarding the tests, it shows which tests are more important for the bearing capacity. Then, it can be concluded which parameters and tests should be obtained more carefully because they have greater weight in the behavior of a shallow foundation. In addition, an analysis of the exceedance probability of the load capacity was performed. Geotechnical parameters (dpeaa)DE-He213 Finite elements with random parameters (dpeaa)DE-He213 Shallow foundations (dpeaa)DE-He213 Elastoplastic model (dpeaa)DE-He213 Variability in geotechnical tests (dpeaa)DE-He213 Hurtado, Jorge E. aut Enthalten in Transportation infrastructure geotechnology New York, NY : Springer US, 2014 9(2021), 6 vom: 01. Okt., Seite 854-873 (DE-627)780378830 (DE-600)2760372-6 2196-7210 nnns volume:9 year:2021 number:6 day:01 month:10 pages:854-873 https://dx.doi.org/10.1007/s40515-021-00201-7 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER 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_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 AR 9 2021 6 01 10 854-873 |
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10.1007/s40515-021-00201-7 doi (DE-627)SPR048647993 (SPR)s40515-021-00201-7-e DE-627 ger DE-627 rakwb eng Bolaños, Cristhian Camilo Mendoza verfasserin aut Effects of Soil Test Variability in the Bearing Capacity of Shallow Foundations 2021 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2021 Abstract This study presents the influence of variability for geotechnical parameters on the bearing capacity of shallow foundations. This was made from the ground variability and variability of the geotechnical tests. Finite element models of a continuous footing were used with an elastoplastic model with the soil geological history. Then, random parameters were generated from the selected model. The parameters were generated in two ways. Firstly, when the parameters are not correlated. This is done with the variability coefficients (COV) recorded by different researchers for each parameter. Secondly, the parameters are considered statistically correlated because they come from the same test. This case used the same COV for the parameters from the same test. The division of the parameters was for the soil shear strength parameters and the soil compression parameters. Subsequently, with the generated parameters, Monte Carlo simulations were performed. The above was possible by integrating these parameters in the finite element models. The results explain the influence of geotechnical parameters on the bearing capacity of a shallow foundation. In addition, the weight of different geotechnical parameters was shown in the quality function with which the tests were made. Regarding the tests, it shows which tests are more important for the bearing capacity. Then, it can be concluded which parameters and tests should be obtained more carefully because they have greater weight in the behavior of a shallow foundation. In addition, an analysis of the exceedance probability of the load capacity was performed. Geotechnical parameters (dpeaa)DE-He213 Finite elements with random parameters (dpeaa)DE-He213 Shallow foundations (dpeaa)DE-He213 Elastoplastic model (dpeaa)DE-He213 Variability in geotechnical tests (dpeaa)DE-He213 Hurtado, Jorge E. aut Enthalten in Transportation infrastructure geotechnology New York, NY : Springer US, 2014 9(2021), 6 vom: 01. Okt., Seite 854-873 (DE-627)780378830 (DE-600)2760372-6 2196-7210 nnns volume:9 year:2021 number:6 day:01 month:10 pages:854-873 https://dx.doi.org/10.1007/s40515-021-00201-7 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER 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_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 AR 9 2021 6 01 10 854-873 |
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10.1007/s40515-021-00201-7 doi (DE-627)SPR048647993 (SPR)s40515-021-00201-7-e DE-627 ger DE-627 rakwb eng Bolaños, Cristhian Camilo Mendoza verfasserin aut Effects of Soil Test Variability in the Bearing Capacity of Shallow Foundations 2021 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2021 Abstract This study presents the influence of variability for geotechnical parameters on the bearing capacity of shallow foundations. This was made from the ground variability and variability of the geotechnical tests. Finite element models of a continuous footing were used with an elastoplastic model with the soil geological history. Then, random parameters were generated from the selected model. The parameters were generated in two ways. Firstly, when the parameters are not correlated. This is done with the variability coefficients (COV) recorded by different researchers for each parameter. Secondly, the parameters are considered statistically correlated because they come from the same test. This case used the same COV for the parameters from the same test. The division of the parameters was for the soil shear strength parameters and the soil compression parameters. Subsequently, with the generated parameters, Monte Carlo simulations were performed. The above was possible by integrating these parameters in the finite element models. The results explain the influence of geotechnical parameters on the bearing capacity of a shallow foundation. In addition, the weight of different geotechnical parameters was shown in the quality function with which the tests were made. Regarding the tests, it shows which tests are more important for the bearing capacity. Then, it can be concluded which parameters and tests should be obtained more carefully because they have greater weight in the behavior of a shallow foundation. In addition, an analysis of the exceedance probability of the load capacity was performed. Geotechnical parameters (dpeaa)DE-He213 Finite elements with random parameters (dpeaa)DE-He213 Shallow foundations (dpeaa)DE-He213 Elastoplastic model (dpeaa)DE-He213 Variability in geotechnical tests (dpeaa)DE-He213 Hurtado, Jorge E. aut Enthalten in Transportation infrastructure geotechnology New York, NY : Springer US, 2014 9(2021), 6 vom: 01. Okt., Seite 854-873 (DE-627)780378830 (DE-600)2760372-6 2196-7210 nnns volume:9 year:2021 number:6 day:01 month:10 pages:854-873 https://dx.doi.org/10.1007/s40515-021-00201-7 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER 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_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 AR 9 2021 6 01 10 854-873 |
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10.1007/s40515-021-00201-7 doi (DE-627)SPR048647993 (SPR)s40515-021-00201-7-e DE-627 ger DE-627 rakwb eng Bolaños, Cristhian Camilo Mendoza verfasserin aut Effects of Soil Test Variability in the Bearing Capacity of Shallow Foundations 2021 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2021 Abstract This study presents the influence of variability for geotechnical parameters on the bearing capacity of shallow foundations. This was made from the ground variability and variability of the geotechnical tests. Finite element models of a continuous footing were used with an elastoplastic model with the soil geological history. Then, random parameters were generated from the selected model. The parameters were generated in two ways. Firstly, when the parameters are not correlated. This is done with the variability coefficients (COV) recorded by different researchers for each parameter. Secondly, the parameters are considered statistically correlated because they come from the same test. This case used the same COV for the parameters from the same test. The division of the parameters was for the soil shear strength parameters and the soil compression parameters. Subsequently, with the generated parameters, Monte Carlo simulations were performed. The above was possible by integrating these parameters in the finite element models. The results explain the influence of geotechnical parameters on the bearing capacity of a shallow foundation. In addition, the weight of different geotechnical parameters was shown in the quality function with which the tests were made. Regarding the tests, it shows which tests are more important for the bearing capacity. Then, it can be concluded which parameters and tests should be obtained more carefully because they have greater weight in the behavior of a shallow foundation. In addition, an analysis of the exceedance probability of the load capacity was performed. Geotechnical parameters (dpeaa)DE-He213 Finite elements with random parameters (dpeaa)DE-He213 Shallow foundations (dpeaa)DE-He213 Elastoplastic model (dpeaa)DE-He213 Variability in geotechnical tests (dpeaa)DE-He213 Hurtado, Jorge E. aut Enthalten in Transportation infrastructure geotechnology New York, NY : Springer US, 2014 9(2021), 6 vom: 01. Okt., Seite 854-873 (DE-627)780378830 (DE-600)2760372-6 2196-7210 nnns volume:9 year:2021 number:6 day:01 month:10 pages:854-873 https://dx.doi.org/10.1007/s40515-021-00201-7 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER 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_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 AR 9 2021 6 01 10 854-873 |
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Enthalten in Transportation infrastructure geotechnology 9(2021), 6 vom: 01. Okt., Seite 854-873 volume:9 year:2021 number:6 day:01 month:10 pages:854-873 |
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Geotechnical parameters Finite elements with random parameters Shallow foundations Elastoplastic model Variability in geotechnical tests |
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Bolaños, Cristhian Camilo Mendoza @@aut@@ Hurtado, Jorge E. @@aut@@ |
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This was made from the ground variability and variability of the geotechnical tests. Finite element models of a continuous footing were used with an elastoplastic model with the soil geological history. Then, random parameters were generated from the selected model. The parameters were generated in two ways. Firstly, when the parameters are not correlated. This is done with the variability coefficients (COV) recorded by different researchers for each parameter. Secondly, the parameters are considered statistically correlated because they come from the same test. This case used the same COV for the parameters from the same test. The division of the parameters was for the soil shear strength parameters and the soil compression parameters. Subsequently, with the generated parameters, Monte Carlo simulations were performed. The above was possible by integrating these parameters in the finite element models. 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Bolaños, Cristhian Camilo Mendoza |
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Bolaños, Cristhian Camilo Mendoza misc Geotechnical parameters misc Finite elements with random parameters misc Shallow foundations misc Elastoplastic model misc Variability in geotechnical tests Effects of Soil Test Variability in the Bearing Capacity of Shallow Foundations |
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Effects of Soil Test Variability in the Bearing Capacity of Shallow Foundations Geotechnical parameters (dpeaa)DE-He213 Finite elements with random parameters (dpeaa)DE-He213 Shallow foundations (dpeaa)DE-He213 Elastoplastic model (dpeaa)DE-He213 Variability in geotechnical tests (dpeaa)DE-He213 |
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Effects of Soil Test Variability in the Bearing Capacity of Shallow Foundations |
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Effects of Soil Test Variability in the Bearing Capacity of Shallow Foundations |
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effects of soil test variability in the bearing capacity of shallow foundations |
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Effects of Soil Test Variability in the Bearing Capacity of Shallow Foundations |
| abstract |
Abstract This study presents the influence of variability for geotechnical parameters on the bearing capacity of shallow foundations. This was made from the ground variability and variability of the geotechnical tests. Finite element models of a continuous footing were used with an elastoplastic model with the soil geological history. Then, random parameters were generated from the selected model. The parameters were generated in two ways. Firstly, when the parameters are not correlated. This is done with the variability coefficients (COV) recorded by different researchers for each parameter. Secondly, the parameters are considered statistically correlated because they come from the same test. This case used the same COV for the parameters from the same test. The division of the parameters was for the soil shear strength parameters and the soil compression parameters. Subsequently, with the generated parameters, Monte Carlo simulations were performed. The above was possible by integrating these parameters in the finite element models. The results explain the influence of geotechnical parameters on the bearing capacity of a shallow foundation. In addition, the weight of different geotechnical parameters was shown in the quality function with which the tests were made. Regarding the tests, it shows which tests are more important for the bearing capacity. Then, it can be concluded which parameters and tests should be obtained more carefully because they have greater weight in the behavior of a shallow foundation. In addition, an analysis of the exceedance probability of the load capacity was performed. © The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2021 |
| abstractGer |
Abstract This study presents the influence of variability for geotechnical parameters on the bearing capacity of shallow foundations. This was made from the ground variability and variability of the geotechnical tests. Finite element models of a continuous footing were used with an elastoplastic model with the soil geological history. Then, random parameters were generated from the selected model. The parameters were generated in two ways. Firstly, when the parameters are not correlated. This is done with the variability coefficients (COV) recorded by different researchers for each parameter. Secondly, the parameters are considered statistically correlated because they come from the same test. This case used the same COV for the parameters from the same test. The division of the parameters was for the soil shear strength parameters and the soil compression parameters. Subsequently, with the generated parameters, Monte Carlo simulations were performed. The above was possible by integrating these parameters in the finite element models. The results explain the influence of geotechnical parameters on the bearing capacity of a shallow foundation. In addition, the weight of different geotechnical parameters was shown in the quality function with which the tests were made. Regarding the tests, it shows which tests are more important for the bearing capacity. Then, it can be concluded which parameters and tests should be obtained more carefully because they have greater weight in the behavior of a shallow foundation. In addition, an analysis of the exceedance probability of the load capacity was performed. © The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2021 |
| abstract_unstemmed |
Abstract This study presents the influence of variability for geotechnical parameters on the bearing capacity of shallow foundations. This was made from the ground variability and variability of the geotechnical tests. Finite element models of a continuous footing were used with an elastoplastic model with the soil geological history. Then, random parameters were generated from the selected model. The parameters were generated in two ways. Firstly, when the parameters are not correlated. This is done with the variability coefficients (COV) recorded by different researchers for each parameter. Secondly, the parameters are considered statistically correlated because they come from the same test. This case used the same COV for the parameters from the same test. The division of the parameters was for the soil shear strength parameters and the soil compression parameters. Subsequently, with the generated parameters, Monte Carlo simulations were performed. The above was possible by integrating these parameters in the finite element models. The results explain the influence of geotechnical parameters on the bearing capacity of a shallow foundation. In addition, the weight of different geotechnical parameters was shown in the quality function with which the tests were made. Regarding the tests, it shows which tests are more important for the bearing capacity. Then, it can be concluded which parameters and tests should be obtained more carefully because they have greater weight in the behavior of a shallow foundation. In addition, an analysis of the exceedance probability of the load capacity was performed. © The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2021 |
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Effects of Soil Test Variability in the Bearing Capacity of Shallow Foundations |
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https://dx.doi.org/10.1007/s40515-021-00201-7 |
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Hurtado, Jorge E. |
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10.1007/s40515-021-00201-7 |
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| score |
7.4023256 |