Serviceability limit state CPT-based design for vertically loaded shallow footings on sand

Uzielli, Marco; Mayne, Paul W.

doi:10.1080/17486025.2010.531146

Cited by 38 publications

(25 citation statements)

References 18 publications

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“…The ratio of Q STC,n to Q app,n represents a lumped load-and resistance factor, ψ Q , equivalent to a single deterministic global safety factor, and ensures that p f is equal to p T (Phoon 2006 Uzielli and Mayne 2011;Stuedlein and Reddy 2013;Stuedlein and Uzielli 2014). The probability of failure is then calculated as:…”

Section: Serviceability Limit State Designmentioning

confidence: 99%

“…First-Order Second Moment [FOSM], First-Order Reliability Method [FORM]), Monte Carlo simulations (MCS) were used herein because these simulations are not restricted to certain types of distributions (e.g. normal, lognormal), and are generally considered more appropriate for nonlinear limit state functions (Allen et al 2005;Uzielli and Mayne 2011). Two main sources of uncertainty are addressed in this approach: the parameter uncertainty associated with each random variable in the performance function, and the transformation uncertainty resulting from the imperfect fit between the observed load-displacement curves and the hyperbolic model.…”

Section: Monte Carlo Simulations For Reliability Analysesmentioning

confidence: 99%

“…Ideally each Q a would be associated with an invariant allowable displacement and vice versa; however, significant uncertainty between these performance measures exists and therefore its characterization is D r a f t Page 6 of 32 critical for appropriate RBD. A performance function, P, is used to assess the probability of exceeding the SLS (Phoon and Kulhawy 2008;Uzielli and Mayne 2011;Stuedlein and Reddy 2013):…”

Section: Serviceability Limit State Designmentioning

confidence: 99%

“…At present, the ULS has received considerably more attention in reliability-based design (RBD); however, the SLS is often the governing criterion for many foundation alternatives (Becker 1996;Wang and Kulhawy 2008;Zhang et al 2008;Uzielli and Mayne 2011). Phoon and Kulhawy (2008) incorporated the accuracy and uncertainty of the Meyerhof (1976) method for estimating shaft resistance of drilled shafts to make assessments of reliability at the SLS for augered cast-in-place (ACIP) piles.…”

Section: Introductionmentioning

confidence: 99%

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Serviceability limit state reliability-based design of augered cast-in-place piles in granular soils

Reddy¹,

Stuedlein

2017

Can. Geotech. J.

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This study proposes a reliability-based design (RBD) procedure to evaluate the allowable load for augered cast-in-place (ACIP) piles installed in predominately granular soils based on a prescribed level of reliability at the serviceability limit state (SLS). The ultimate limit state (ULS) ACIP pile-specific design model proposed in the companion paper is incorporated into a bivariate hyperbolic load-displacement model capable of describing the variability in the loaddisplacement relationship for a wide range of pile displacements. Following the approach outlined in the companion paper, distributions with truncated lower-bound capacities were incorporated into the reliability analyses. A lumped load-and resistance factor is calibrated using a suitable performance function and Monte Carlo simulations. The average and conservative 95 percent lower-bound prediction intervals for the calibrated load-and resistance factor resulting from the simulations are provided. Although unaccounted for in past studies, the slenderness ratio was shown to have significant influence on foundation reliability. Because of the low uncertainty in the proposed ULS pile capacity prediction model, the use of a truncated distribution had moderate influence on foundation reliability.Author Keywords: ACIP piles; Reliability; Serviceability limit state; Statistics; Design INTRODUCTIONA suitable foundation design will satisfy the strength limit or ultimate limit state (ULS) as well as the serviceability limit state (SLS), which is often associated with the allowable displacement or angular distortion of a structure. At present, the ULS has received considerably more attention in reliability-based design (RBD); however, the SLS is often the governing criterion for many foundation alternatives (Becker 1996;Wang and Kulhawy 2008; Zhang et al. 2008;Uzielli and Mayne 2011). Phoon and Kulhawy (2008) incorporated the accuracy and uncertainty of the Meyerhof (1976) method for estimating shaft resistance of drilled shafts to make assessments of reliability at the SLS for augered cast-in-place (ACIP) piles. However, the Meyerhof method was originally developed to predict the capacity of driven displacement piles and then modified for use with drilled shafts, which are constructed differently than ACIP piles.Additionally, Phoon and Kulhawy (2008) neglected toe bearing resistance when estimating ACIP pile capacity, resulting in a biased and considerably variable model (Phoon et al. 2006). Phoon et al. (2006) noted that models specific to ACIP piles needed to be developed (Phoon et al. 2006).The goal of this study is to use the ACIP pile-specific ULS design models presented in the companion paper (Reddy and Stuedlein 2016) to investigate reliability-based SLS design of ACIP piles installed in predominately granular soils. Those case histories described in the companion paper characterized with high quality load-displacement (Q-δ) curves were used to investigate foundation reliability at the SLS. First, an approach to link the ULS capacity models ...

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Section: Serviceability Limit State Designmentioning

confidence: 99%

Section: Monte Carlo Simulations For Reliability Analysesmentioning

confidence: 99%

Section: Serviceability Limit State Designmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Serviceability limit state reliability-based design of augered cast-in-place piles in granular soils

Reddy¹,

Stuedlein

2017

Can. Geotech. J.

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“…However, transformation uncertainty has not been investigated as extensively as other components of geotechnical uncertainty. Recent contributions to the quantitative characterization of transformation uncertainty include Phoon & Kulhawy (2005, 2008, Uzielli & Mayne (2011) and Zhang et al (2012).…”

Section: Introductionmentioning

confidence: 99%

Bayesian Characterization of Transformation Uncertainty for Strength and Stiffness of Sands

Uzielli¹,

Mayne²

2013

Foundation Engineering in the Face of Uncertainty

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This paper focuses on the Bayesian probabilistic modelling of uncertainty in the evaluation of drained sand strength (i.e., friction angle) and stiffness of natural sands in-situ, as evaluated using the cone penetration test (CPT), and on the probabilistic prediction of loadinginduced settlements. For the sand strength, two special datasets are compiled from undisturbed (frozen) sands that were tested in triaxial compression following thawing. For stiffness, equivalent Young's moduli were back-calculated from full-scale footing load tests on sands via elastic continuum theory. Transformation uncertainty is parameterized by means of model factors, which can be directly implemented in geotechnical limit state design for any user-defined target reliability level.

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Reliability-Based Serviceability Limit State Design of Driven Piles in Glacial Deposits

Jesswein

Liu

2022

Geotech Geol Eng

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Serviceability limit state CPT-based design for vertically loaded shallow footings on sand

Cited by 38 publications

References 18 publications

Serviceability limit state reliability-based design of augered cast-in-place piles in granular soils

Serviceability limit state reliability-based design of augered cast-in-place piles in granular soils

Bayesian Characterization of Transformation Uncertainty for Strength and Stiffness of Sands

Reliability-Based Serviceability Limit State Design of Driven Piles in Glacial Deposits

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