Multiple Resistance Factor Methodology for Service Limit State Design of Deep Foundations using a ''t-z'' Model Approach

Author(s):  
Lance A. Roberts ◽  
Bradley S. Gardner ◽  
Anil Misra
2018 ◽  
Author(s):  
◽  
Minh Dinh Uong

Since 2007, the American Association of State Highway Administration Officials (AASHTO) has made utilization of Load and Resistance Factor Design (LRFD) mandatory on all federally-funded new bridge projects (AASHTO, 2007). However, currently, there are no guidelines implementing LRFD techniques for design of drilled shaft subjected to lateral loads using reliability-based analysis. On a national level, the AASHTO LRFD Bridge Design Specifications (AASHTO, 2012) specify that a resistance factor of 1.0 be used for design of drilled shafts subjected to lateral loading at service limit state, which means reliability-based analyses for calibration of resistance factors have not been performed. Therefore, there is a need to create a LRFD procedure for drilled shafts subjected to lateral loading at service limit state that has reliability-based calibrated resistance factors applicable for future projects. The research focuses on the reliability-based analysis of drilled shaft subjected to lateral loading, characterize lateral load transfer model of drilled shafts in shale, probabilistic calibrate resistance factor and contribute to the development of design procedure using LRFD. The objective of this work is to improve the design of drilled shaft subjected to lateral loading using LRFD at service limit state by providing a more reliable design procedure than the current AASHTO LRFD procedure for drilled shafts subjected to lateral loading at service limit state.


Géotechnique ◽  
2014 ◽  
Vol 64 (10) ◽  
pp. 787-799 ◽  
Author(s):  
F. NAGHIBI ◽  
G.A. FENTON ◽  
D.V. GRIFFITHS

2011 ◽  
Vol 48 (2) ◽  
pp. 265-279 ◽  
Author(s):  
Gordon A. Fenton ◽  
D. V. Griffiths ◽  
Olaide O. Ojomo

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.


2011 ◽  
Vol 48 (11) ◽  
pp. 1729-1741 ◽  
Author(s):  
Mehrangiz Naghibi ◽  
Gordon A. Fenton

This paper investigates the ultimate limit state load and resistance factor design (LRFD) of deep foundations founded within purely cohesive soils. The geotechnical resistance factors required to produce deep foundation designs having a maximum acceptable failure probability are estimated as a function of site understanding and failure consequence. The probability theory developed in this paper, used to determine the resistance factors, is verified by a two-dimensional random field Monte Carlo simulation of a spatially variable cohesive soil. The agreement between theory and simulation is found to be very good, and the theory is then used to derive the required geotechnical resistance factors. The results presented in this paper can be used to complement current ultimate limit state design code calibration efforts for deep foundations in cohesive soils.


2009 ◽  
Vol 46 (2) ◽  
pp. 168-176 ◽  
Author(s):  
Lance A. Roberts ◽  
Anil Misra

Load–displacement analysis of a single deep foundation element can be accomplished by utilizing a soil–structure interaction model, such as the “t–z” model. By combining the soil–structure interaction model with a probabilistic analysis technique, such as Monte Carlo simulation, methods to rationally incorporate variability in the model parameters can be developed. As a result, the service limit state load capacity of a single deep foundation element can be computed for an allowable total head displacement. However, in design, differential settlement between individual foundation elements is often the event of interest. This paper develops a reliability-based design methodology for deep foundations based on a differential settlement design criterion. The design methodology is developed for various levels of uncertainty in the model parameters. The results are presented in the form of cumulative distribution functions that, combined with the calculated service limit state load capacity, form the basis for serviceability design of deep foundations based on a differential settlement criterion.


2011 ◽  
Vol 48 (11) ◽  
pp. 1742-1756 ◽  
Author(s):  
Gordon A. Fenton ◽  
Mehrangiz Naghibi

This paper investigates the probabilistic nature of ultimate limit state failures of deep foundations in purely frictional soils (e.g., sands). In so doing, the theory required to predict both the probability of ultimate limit state failure and the resistance factors needed to avoid this limit state are proposed. The proposed resistance factors are functions of site understanding and failure consequence, and the theory leading to these resistance factors is validated via Monte Carlo simulation of a two-dimensional spatially variable random field. In both the theory and the simulation, a pile is assumed to be placed vertically at a certain position in the soil mass, and the soil is sampled at various distances from the pile to come up with characteristic soil properties (namely friction angle) for use in the pile design. Agreement between theory and simulation is found to be very good. The theoretical model is then employed to determine upper bound geotechnical resistance factors, which can be used to complement current ultimate limit state design code calibration efforts. An example of such a calibration is presented.


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