Load and resistance factor design of shallow foundations against bearing failure

2008 ◽  
Vol 45 (11) ◽  
pp. 1556-1571 ◽  
Author(s):  
Gordon A. Fenton ◽  
D. V. Griffiths ◽  
Xianyue Zhang
Keyword(s):  
Bearing Capacity ◽  
Limit State ◽  
Resistance Factor ◽  
Shallow Foundation ◽  
Ultimate Limit State ◽  
Full Potential ◽  
Design Codes ◽  
Reliability Based Design ◽  
Factor Design ◽  
Load And Resistance Factor

Shallow foundation designs are typically governed either by settlement, a serviceability limit state, or by bearing capacity, an ultimate limit state. While geotechnical engineers have been designing against these limit states for over half a century, it is only recently that they have begun to migrate towards reliability-based designs. At the moment, reliability-based design codes are generally derived through calibration with traditional working stress designs. To take advantage of the full potential of reliability-based design the profession must go beyond calibration and take geotechnical uncertainties into account in a rational fashion. This paper proposes a load and resistance factor design (LRFD) approach for the bearing capacity design of a strip footing, using load factors as specified by structural codes. The resistance factors required to achieve an acceptable failure probability are estimated as a function of the spatial variability of the soil and by the level of “understanding” of the soil properties in the vicinity of the foundation. The analytical results, validated by simulation, are primarily intended to aid in the development of the next generation of reliability-based geotechnical design codes, but can also be used to assess the reliability of current designs.

Consequence factors in the ultimate limit state design of shallow foundations

2011 ◽  
Vol 48 (2) ◽  
pp. 265-279 ◽  
Author(s):  
Gordon A. Fenton ◽  
D. V. Griffiths ◽  
Olaide O. Ojomo
Keyword(s):  
Limit State ◽  
Shallow Foundations ◽  
Resistance Factor ◽  
Shallow Foundation ◽  
Ultimate Limit State ◽  
Resistance Factors ◽  
Limit State Design ◽  
Reliability Based Design ◽  
Load And Resistance Factors ◽  
Load And Resistance Factor

The reliability-based design of shallow foundations is generally implemented via a load and resistance factor design methodology embedded in a limit state design framework. For any particular limit state, the design proceeds by ensuring that the factored resistance equals or exceeds the factored load effects. Load and resistance factors are determined to ensure that the resulting design is sufficiently safe. Load factors are typically prescribed in structural codes and take into account load uncertainty. Factors applied to resistance depend on both uncertainty in the resistance (accounted for by a resistance factor) and desired target reliability (accounted for by a newly introduced consequence factor). This paper concentrates on how the consequence factor can be defined and specified to adjust the target reliability of a shallow foundation designed to resist bearing capacity failure.

Reliability Based Design Criteria for Installation of Pipelines in the Bay of Campeche, Mexico: Part 2

2002 ◽  
Author(s):  
Robert Bea ◽  
Tao Xu ◽  
Ernesto Heredia-Zavoni ◽  
Leonel Lara ◽  
Rommel Burbano
Keyword(s):  
Limit State ◽  
Companion Paper ◽  
Design Criteria ◽  
Ultimate Limit State ◽  
Large Database ◽  
Reliability Based Design ◽  
Working Stress ◽  
Factor Design ◽  
Load And Resistance Factor ◽  
Ultimate Limit

Studies have been performed to propose reliability based design criteria for the installation of pipelines in the Bay of Campeche, Mexico. This paper summarizes formulations that were used to characterize the important Ultimate Limit State capacities of the pipelines during the installation period (collapse, bending, tension, combined, and propagating buckling). A large database of laboratory and numerical analysis ‘tests’ (more than 2,000 results) to determine pipeline capacities was assembled to help evaluate the Biases (ratio of measured/predicted capacities) in the analytical methods used to determine pipeline capacities. Given the formulations, target reliabilities, and installation demand characterizations summarized in a companion paper (Part 1), installation design criteria were developed for both Working Stress Design and Load and Resistance Factor Design formats.

Reliability Based Design Criteria for Installation of Pipelines in the Bay of Campeche, Mexico: Part 1

2002 ◽  
Author(s):  
Robert Bea ◽  
Tao Xu ◽  
Ernesto Heredia-Zavoni ◽  
Leonel Lara ◽  
Rommel Burbano
Keyword(s):  
Limit State ◽  
Companion Paper ◽  
Design Guidelines ◽  
Design Criteria ◽  
Ultimate Limit State ◽  
Reliability Based Design ◽  
Factor Design ◽  
Load And Resistance Factor ◽  
Ultimate Limit ◽  
Allowable Stress Design

Studies have been performed to propose reliability based design criteria for the installation of pipelines in the Bay of Campeche, Mexico. This paper summarizes the reliability formulations that were used to develop Allowable Stress Design and Load and Resistance Factor Design guidelines for Ultimate Limit State conditions, background on the target reliabilities that were used in the development, and the methods that were used to characterize the demands (loads, displacements) induced in pipelines during their installation. This paper summarizes data that was gathered during the installation of pipelines in the Bay of Campeche to help define the Biases (actual stresses/calculated stresses) associated with the analytical model used to predict installation demands. These results are compared with those published previously based on other field and laboratory tests. A companion paper details the analyses of pipeline Ultimate Limit State capacities and the Biases associated with these capacities.

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

2017 ◽  
Vol 54 (12) ◽  
pp. 1704-1715 ◽  
Author(s):  
Seth C. Reddy ◽  
Armin W. Stuedlein
Keyword(s):  
Lower Bound ◽  
Limit State ◽  
Companion Paper ◽  
Resistance Factor ◽  
Granular Soils ◽  
Serviceability Limit State ◽  
Reliability Based Design ◽  
Wide Range ◽  
Load Displacement ◽  
Load And Resistance Factor

This study proposes a reliability-based design 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. 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 load–displacement relationship for a wide range of pile displacements. Following the approach outlined in the companion paper, distributions with truncated lower-bound capacities are 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% 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 is 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 has moderate influence on foundation reliability.

scholarly journals Ultimate limit state reliability-based design of augered cast-in-place piles considering lower-bound capacities

2017 ◽  
Vol 54 (12) ◽  
pp. 1693-1703 ◽  
Author(s):  
Seth C. Reddy ◽  
Armin W. Stuedlein
Keyword(s):  
Lower Bound ◽  
Limit State ◽  
Resistance Factor ◽  
Reasonable Assumption ◽  
Ultimate Limit State ◽  
Design Models ◽  
Resistance Factors ◽  
Reliability Based Design ◽  
The Impact ◽  
Ultimate Limit

The use of augered cast-in-place (ACIP) piles for transportation infrastructure requires an appropriate reliability-based design (RBD) procedure. In an effort to improve the accuracy of an existing design model and calibrate appropriate resistance factors, this study presents a significantly revised RBD methodology for estimating the shaft and toe bearing capacity of ACIP piles using a large database consisting of static loading tests in predominately granular soils. The proposed design models are unbiased, as opposed to those currently recommended. Based on the reasonable assumption that a finite lower-bound resistance limit exists, lower-bound design lines are developed for shaft and toe bearing resistance by applying a constant ratio to the proposed design models. Resistance factors are calibrated at the strength or ultimate limit state (ULS) for ACIP piles loaded in compression and tension for two commonly used target probabilities of failure with and without lower-bound limits. For piles loaded in compression, separate resistance factors are calibrated for the proposed shaft and toe bearing resistance models. The inclusion of a lower-bound limit for piles loaded in tension results in a 24%–50% increase in the calibrated resistance factor. For piles loaded in compression, the application of a lower-bound limit results in a 20%–150% increase in the calibrated resistance factor, and represents a significant increase in useable pile capacity. Although the impact of a lower-bound limit on resistance factor calibration is directly dependent on the degree of uncertainty in the distribution of resistance, this effect is outweighed by the type of distribution selected (i.e., normal, lognormal) at more stringent target probabilities of failure due to differences in distribution shape at the location of the lower-bound limit. A companion paper explores the use of the revised ULS model in a reliability-based serviceability limit state design framework.

Reliability Design of Footings in Cohesionless Soils using Soft Computing Metamodelings

2016 ◽  
pp. 442-464
Author(s):  
Anthony T. C. Goh ◽  
Wengang Zhang
Keyword(s):  
Bearing Capacity ◽  
Soft Computing ◽  
Model Building ◽  
Limit State ◽  
Multivariate Adaptive Regression Splines ◽  
Ultimate Limit State ◽  
Cohesionless Soils ◽  
Reliability Design ◽  
Reliability Based Design ◽  
Adaptive Regression Splines

An extensive database of full-scale field load tests was used to build predictive models to determine the bearing capacity of footings under axial compression in cohesionless soils. Based on this database, soft computing techniques, i.e., the multivariate adaptive regression splines (MARS) and artificial neural networks (ANN) are adopted for comparison for surrogate model building on bearing capacity. The performances of the two computing techniques are compared. A reliability-based design of footings was then presented. It allows one to obtain the probability that the ultimate limit state was exceeded for a given soil variability.

Calibration concepts for load and resistance factor design (LRFD) of reinforced soil walls

2008 ◽  
Vol 45 (10) ◽  
pp. 1377-1392 ◽  
Author(s):  
Richard J. Bathurst ◽  
Tony M. Allen ◽  
Andrzej S. Nowak
Keyword(s):  
Limit State ◽  
Reinforced Soil ◽  
Resistance Factor ◽  
Resistance Factors ◽  
Soil Walls ◽  
Calibration Methods ◽  
Load And Resistance Factors ◽  
Factor Design ◽  
Load And Resistance Factor ◽  
Reinforced Soil Walls

Reliability-based design concepts and their application to load and resistance factor design (LRFD or limit states design (LSD) in Canada) are well known, and their adoption in geotechnical engineering design is now recommended for many soil–structure interaction problems. Two important challenges for acceptance of LRFD for the design of reinforced soil walls are (i) a proper understanding of the calibration methods used to arrive at load and resistance factors, and (ii) the proper interpretation of the data required to carry out this process. This paper presents LRFD calibration principles and traces the steps required to arrive at load and resistance factors using closed-form solutions for one typical limit state, namely pullout of steel reinforcement elements in the anchorage zone of a reinforced soil wall. A unique feature of this paper is that measured load and resistance values from a database of case histories are used to develop the statistical parameters in the examples. The paper also addresses issues related to the influence of outliers in the datasets and possible dependencies between variables that can have an important influence on the results of calibration.

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