Documents disponibles écrits par cet auteur

Learning of dnamic soil behavior from downhole arrays / Chi-Chin Tsai in Journal of geotechnical and geoenvironmental engineering, Vol. 135 N° 6 (Juin 2009) 

Public ISBD [article]  in Journal of geotechnical and geoenvironmental engineering > Vol. 135 N° 6 (Juin 2009) . - pp. 745–757 Titre : Learning of dnamic soil behavior from downhole arrays Type de document : texte imprimé Auteurs : Chi-Chin Tsai, Auteur ; Youssef M. Hashash, Auteur Année de publication : 2009 Article en page(s) : pp. 745–757 Note générale : Geotechnical and geoenvironmental engineering Langues : Anglais (eng) Mots-clés : Dynamic  properties  Neural  networks  Shear  modulus  Shear  strain Résumé : An increasing number of downhole arrays are deployed to measure motions at the ground surface and within the soil profile. Measurements from these arrays provide an opportunity to improve site response models and to better understand underlying dynamic soil behavior. Parametric inverse analysis approaches have been used to identify constitutive model parameters to achieve a better match with field observations. However, they are limited by the selected material model. Nonparametric inverse analysis approaches identify averaged soil behavior between measurement locations. A novel inverse analysis framework, self-learning simulations (SelfSim), is employed to reproduce the measured downhole array response while extracting the underlying soil behavior of individual soil layers unconstrained by prior assumptions of soil behavior. SelfSim is successfully applied to recordings from Lotung and La Cienega. The extracted soil behavior from few events can be used to reliably predict the measured response for other events. The field extracted soil behavior shows dependencies of shear modulus and damping on cyclic shear strain level, number of loading cycles, and strain rate that are similar qualitatively to those reported from laboratory studies but differ quantitatively. En ligne : http://ascelibrary.org/doi/abs/10.1061/%28ASCE%29GT.1943-5606.0000050 [article] Learning of dnamic soil behavior from downhole arrays [texte imprimé] / Chi-Chin Tsai, Auteur ; Youssef M. Hashash, Auteur . - 2009 . - pp. 745–757. Geotechnical and geoenvironmental engineering Langues : Anglais (eng) in Journal of geotechnical and geoenvironmental engineering > Vol. 135 N° 6 (Juin 2009) . - pp. 745–757 Mots-clés : Dynamic  properties  Neural  networks  Shear  modulus  Shear  strain Résumé : An increasing number of downhole arrays are deployed to measure motions at the ground surface and within the soil profile. Measurements from these arrays provide an opportunity to improve site response models and to better understand underlying dynamic soil behavior. Parametric inverse analysis approaches have been used to identify constitutive model parameters to achieve a better match with field observations. However, they are limited by the selected material model. Nonparametric inverse analysis approaches identify averaged soil behavior between measurement locations. A novel inverse analysis framework, self-learning simulations (SelfSim), is employed to reproduce the measured downhole array response while extracting the underlying soil behavior of individual soil layers unconstrained by prior assumptions of soil behavior. SelfSim is successfully applied to recordings from Lotung and La Cienega. The extracted soil behavior from few events can be used to reliably predict the measured response for other events. The field extracted soil behavior shows dependencies of shear modulus and damping on cyclic shear strain level, number of loading cycles, and strain rate that are similar qualitatively to those reported from laboratory studies but differ quantitatively. En ligne : http://ascelibrary.org/doi/abs/10.1061/%28ASCE%29GT.1943-5606.0000050

Probabilistic seismic hazard analysis for maximum seismic shear stresses in soils using improved ground-motion parameters / Tadahiro Kishida in Journal of geotechnical and geoenvironmental engineering, Vol. 139 N° 2 (Février 2013) 

Public ISBD [article]  in Journal of geotechnical and geoenvironmental engineering > Vol. 139 N° 2 (Février 2013) . - pp. 288-297 Titre : Probabilistic seismic hazard analysis for maximum seismic shear stresses in soils using improved ground-motion parameters Type de document : texte imprimé Auteurs : Tadahiro Kishida, Auteur ; Chi-Chin Tsai, Auteur Année de publication : 2013 Article en page(s) : pp. 288-297 Note générale : geotechnique Langues : Anglais (eng) Mots-clés : seismic  design;  shear  stress;  ground  motion;  probability;  hazards;  soil  strength Résumé : Maximum seismic shear stresses (τmax) have been recognized as one of the important parameters in design practice. This study develops ground-motion parameters for τmax and implements these in probabilistic seismic hazard analysis to provide the τmax distribution of deep soil layers for design purposes. The application of improved ground-motion parameters for τmax is demonstrated at the Oakland International Airport, where a thick Young Bay Mud deposit exists under the artificial fill. Model biases in the predictive equations of seismic shear-stress reduction coefficients (rd) are evaluated by comparison with the site response analyses performed with a wide range of input ground motions. Based on these results, we introduce improved ground-motion parameters for τmax (Itau) as a linear combination of spectral accelerations, implemented in probabilistic seismic hazard analysis to calculate seismic hazard curves. Conditional mean spectra are calculated, given Itau at 10% in 50 years to illustrate the variations in frequency contents with depth compared with the uniform hazard spectra. Finally, τmax is calculated with depth by using hazard values of Itau and compared with the peak-ground-acceleration-based and uniform-hazard-spectra-based calculations. Analysis results show that τmax will be underestimated for deep soil layers by peak-ground-acceleration-based calculation if the median value of rd is used in design practice. En ligne : http://ascelibrary.org/doi/abs/10.1061/%28ASCE%29GT.1943-5606.0000740 [article] Probabilistic seismic hazard analysis for maximum seismic shear stresses in soils using improved ground-motion parameters [texte imprimé] / Tadahiro Kishida, Auteur ; Chi-Chin Tsai, Auteur . - 2013 . - pp. 288-297. geotechnique Langues : Anglais (eng) in Journal of geotechnical and geoenvironmental engineering > Vol. 139 N° 2 (Février 2013) . - pp. 288-297 Mots-clés : seismic  design;  shear  stress;  ground  motion;  probability;  hazards;  soil  strength Résumé : Maximum seismic shear stresses (τmax) have been recognized as one of the important parameters in design practice. This study develops ground-motion parameters for τmax and implements these in probabilistic seismic hazard analysis to provide the τmax distribution of deep soil layers for design purposes. The application of improved ground-motion parameters for τmax is demonstrated at the Oakland International Airport, where a thick Young Bay Mud deposit exists under the artificial fill. Model biases in the predictive equations of seismic shear-stress reduction coefficients (rd) are evaluated by comparison with the site response analyses performed with a wide range of input ground motions. Based on these results, we introduce improved ground-motion parameters for τmax (Itau) as a linear combination of spectral accelerations, implemented in probabilistic seismic hazard analysis to calculate seismic hazard curves. Conditional mean spectra are calculated, given Itau at 10% in 50 years to illustrate the variations in frequency contents with depth compared with the uniform hazard spectra. Finally, τmax is calculated with depth by using hazard values of Itau and compared with the peak-ground-acceleration-based and uniform-hazard-spectra-based calculations. Analysis results show that τmax will be underestimated for deep soil layers by peak-ground-acceleration-based calculation if the median value of rd is used in design practice. En ligne : http://ascelibrary.org/doi/abs/10.1061/%28ASCE%29GT.1943-5606.0000740