Documents disponibles écrits par cet auteur

Characterization of model uncertainty in the static pile design formula / M. Dithinde in Journal of geotechnical and geoenvironmental engineering, Vol. 137 N° 1 (Janvier 2011) 

Public ISBD [article]  in Journal of geotechnical and geoenvironmental engineering > Vol. 137 N° 1 (Janvier 2011) . - pp. 70-85 Titre : Characterization of model uncertainty in the static pile design formula Type de document : texte imprimé Auteurs : M. Dithinde, Auteur ; K. K. Phoon, Auteur ; M. de Wet, Auteur Année de publication : 2011 Article en page(s) : pp. 70-85 Note générale : Géotechnique Langues : Anglais (eng) Mots-clés : Pile  load  test  Reliability-based  design  Model  uncertainty  Ultimate  limit  state  Serviceability  limit  state  Capacity  model  factor  Hyperbolic  curve-fitting  parameters  Lognormal  distribution Index. décimale : 624.1 Infrastructures.Ouvrages en terre. Fondations. Tunnels Résumé : Level 1 reliability methods have been internationally accepted as the basis for development of the new generation of geotechnical design codes. A key requirement of this design approach is the identification and quantification of uncertainties associated with the geotechnical design under consideration. This paper presents four load test databases from South Africa for driven piles in noncohesive soils (29 tests), bored piles in noncohesive soils (33 tests), driven piles in cohesive soils (59 tests), and bored piles in cohesive soils (53 tests). The capacity model factor is defined as the ratio of the interpreted capacity (Chin-Davisson approach) and the predicted capacity (static pile design formula). The uncertainty in the capacity model factor is modeled as a lognormal random variable. The model factor statistics reported in this study are required for reliability-based ultimate limit state design. The uncertainty in the load-settlement behavior is characterized by fitting measured load-settlement data to a hyperbolic equation and then normalizing the hyperbolic curve with the interpreted capacity. The resulting exercise reduces uncertainties in a set of nonlinear continuous curves to uncertainties in two hyperbolic curve-fitting parameters. This approach is practical and grounded realistically on the load test database with minimal assumptions. The hyperbolic parameter statistics reported in this study are required for reliability-based serviceability limit state design. DEWEY : 624.1 ISSN : 1090-0241 En ligne : http://ascelibrary.org/gto/resource/1/jggefk/v137/i1/p70_s1?isAuthorized=no [article] Characterization of model uncertainty in the static pile design formula [texte imprimé] / M. Dithinde, Auteur ; K. K. Phoon, Auteur ; M. de Wet, Auteur . - 2011 . - pp. 70-85. Géotechnique Langues : Anglais (eng) in Journal of geotechnical and geoenvironmental engineering > Vol. 137 N° 1 (Janvier 2011) . - pp. 70-85 Mots-clés : Pile  load  test  Reliability-based  design  Model  uncertainty  Ultimate  limit  state  Serviceability  limit  state  Capacity  model  factor  Hyperbolic  curve-fitting  parameters  Lognormal  distribution Index. décimale : 624.1 Infrastructures.Ouvrages en terre. Fondations. Tunnels Résumé : Level 1 reliability methods have been internationally accepted as the basis for development of the new generation of geotechnical design codes. A key requirement of this design approach is the identification and quantification of uncertainties associated with the geotechnical design under consideration. This paper presents four load test databases from South Africa for driven piles in noncohesive soils (29 tests), bored piles in noncohesive soils (33 tests), driven piles in cohesive soils (59 tests), and bored piles in cohesive soils (53 tests). The capacity model factor is defined as the ratio of the interpreted capacity (Chin-Davisson approach) and the predicted capacity (static pile design formula). The uncertainty in the capacity model factor is modeled as a lognormal random variable. The model factor statistics reported in this study are required for reliability-based ultimate limit state design. The uncertainty in the load-settlement behavior is characterized by fitting measured load-settlement data to a hyperbolic equation and then normalizing the hyperbolic curve with the interpreted capacity. The resulting exercise reduces uncertainties in a set of nonlinear continuous curves to uncertainties in two hyperbolic curve-fitting parameters. This approach is practical and grounded realistically on the load test database with minimal assumptions. The hyperbolic parameter statistics reported in this study are required for reliability-based serviceability limit state design. DEWEY : 624.1 ISSN : 1090-0241 En ligne : http://ascelibrary.org/gto/resource/1/jggefk/v137/i1/p70_s1?isAuthorized=no

Reliability analysis of partial safety factor design method for cantilever retaining walls in granular soils / A. T. Goh in Journal of geotechnical and geoenvironmental engineering, Vol. 135 N° 5 (Mai 2009) 

Public ISBD [article]  in Journal of geotechnical and geoenvironmental engineering > Vol. 135 N° 5 (Mai 2009) . - pp. 616–622 Titre : Reliability analysis of partial safety factor design method for cantilever retaining walls in granular soils Type de document : texte imprimé Auteurs : A. T. Goh, Auteur ; K. K. Phoon, Auteur ; F. H. Kulhawy, Auteur Année de publication : 2009 Article en page(s) : pp. 616–622 Note générale : Geotechnical and geoenvironmental engineering Langues : Anglais (eng) Mots-clés : Safety  Failures  Reliability  Retaining  walls  Sand Résumé : Uncertainties in the geotechnical design variables and design equations have a significant impact on the safety of cantilever retaining walls. Traditionally, uncertainties in the geotechnical design are addressed by incorporating a conservative factor of safety in the analytical model. In this paper, a risk-based approach is adopted to assess the influence of the geotechnical variable and design equation uncertainties on the design of cantilever retaining walls in sand using the “partial factor of safety on shear strength” approach. A random model factor based on large-scale laboratory test data from the literature has been incorporated into the reliability analyses to quantify the uncertainty in the geotechnical calculation model. Analyses conducted using Monte Carlo simulation show that the same partial factor can have very different levels of risk depending on the degree of uncertainty of the mean value of the soil friction angle. Calibration studies show the partial factor necessary to achieve target probability values of 1 and 0.1%. En ligne : http://ascelibrary.org/doi/abs/10.1061/%28ASCE%29GT.1943-5606.0000061 [article] Reliability analysis of partial safety factor design method for cantilever retaining walls in granular soils [texte imprimé] / A. T. Goh, Auteur ; K. K. Phoon, Auteur ; F. H. Kulhawy, Auteur . - 2009 . - pp. 616–622. Geotechnical and geoenvironmental engineering Langues : Anglais (eng) in Journal of geotechnical and geoenvironmental engineering > Vol. 135 N° 5 (Mai 2009) . - pp. 616–622 Mots-clés : Safety  Failures  Reliability  Retaining  walls  Sand Résumé : Uncertainties in the geotechnical design variables and design equations have a significant impact on the safety of cantilever retaining walls. Traditionally, uncertainties in the geotechnical design are addressed by incorporating a conservative factor of safety in the analytical model. In this paper, a risk-based approach is adopted to assess the influence of the geotechnical variable and design equation uncertainties on the design of cantilever retaining walls in sand using the “partial factor of safety on shear strength” approach. A random model factor based on large-scale laboratory test data from the literature has been incorporated into the reliability analyses to quantify the uncertainty in the geotechnical calculation model. Analyses conducted using Monte Carlo simulation show that the same partial factor can have very different levels of risk depending on the degree of uncertainty of the mean value of the soil friction angle. Calibration studies show the partial factor necessary to achieve target probability values of 1 and 0.1%. En ligne : http://ascelibrary.org/doi/abs/10.1061/%28ASCE%29GT.1943-5606.0000061