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The paper demonstrates load and resistance factor design (LRFD) calibration for tensile strength and pullout strength limit states for steel strip mechanically stabilized earth (MSE) walls using a reliability theory-based approach. The analyses adopt load models found in current North American LRFD specifications in combination with a coupled mechanical-corrosion model for the reinforcement tensile strength and pullout models found in design guidelines and in the research literature. Resistance factors for prescribed load factors and different load and resistance model combinations are compiled in tables. The limitations of the LRFD approach to generate resistance factors that are judged to be acceptable based on current practice are demonstrated. The challenges to generate consistent design outcomes with the same margin of safety expressed probabilistically are identified, and the link to reliability-based design is described. Example designs are provided to show the impact on steel reinforcement quantities and length when using different models in combination with proposed and current specified load and resistance factors. The calibration outcomes will be of value to code writers in Canada and the US for MSE wall design sections in the next editions of national geotechnical foundation LRFD codes. [ABSTRACT FROM AUTHOR]

The results of load and resistance factor design (LRFD) calibration are reported for the pullout limit state in geogrid reinforced soil walls under self-weight loading and permanent uniform surcharge. Bias statistics are used to account for the prediction accuracy of the underlying deterministic models for load and pullout capacity and the random variability in the input parameters. The paper shows that the current AASHTO simplified method to calculate reinforcement loads under operational conditions is overly conservative leading to poor prediction accuracy of the underlying deterministic model used in LRFD calibration. Refinements to the load and default pullout capacity models in the AASHTO and Federal Highway Administration guidance documents are proposed. These models generate reasonable resistance factors using a load factor of 1.35 and give a consistent probability of pullout failure of 1%. A comparison with the allowable stress design (ASD) past practice shows that the operational factors of safety using a reliability-based LRFD approach give factors of safety greater than 1.5. Regardless of the design approach (ASD or LRFD), the analysis results demonstrate that the current empirical minimum reinforcement length criteria will likely control the design for pullout. [ABSTRACT FROM AUTHOR]

The paper reports the results of load and resistance factor design (LRFD) calibration for pullout and yield limit states for steel strip reinforced soil walls under self-weight loading. An important feature of the calibration method is the use of bias statistics to account for prediction accuracy of the underlying deterministic models for reinforcement load, pullout capacity and yield strength of the steel strips, and random variability in input parameters. To improve the accuracy of reinforcement load predictions, small adjustments to current semiempirical American Association of State Highway and Transportation Officials (AASHTO) load design charts are proposed. Similarly, current empirical-based design charts found in AASHTO and Federal Highway Administration (FHWA) guidance documents for the estimation of the pullout resistance factor for smooth and ribbed steel strips are adjusted to improve the accuracy of pullout capacity predictions. The results of calibration lead to a load factor of 1.35 that is consistent with current practice and resistance factors that together give a consistent probability of failure of 1% for all three limit states considered. Furthermore, comparison with allowable stress design (ASD) past practice (AASHTO simplified method) shows that the operational factors of safety using a rigorous LRFD approach give the same or higher factors of safety and lower probabilities of failure. In this study, data for steel strip reinforced soil walls are used as an example to illustrate rigorous reliability theory-based LRFD calibration concepts. However, the general approach is applicable to other reinforced soil wall technologies and calibration outcomes can be updated as more data become available. [ABSTRACT FROM AUTHOR]

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A rigorous probabilistic-based approach for load and resistance factor design (LRFD) calibration of internal stability tensile rupture and pullout limit states for geogrid reinforced mechanically stabilized earth (MSE) walls is presented. Load and resistance factors are provided for different combinations of the load model with pullout model and the tensile strength model used in current practice. The load models are the AASHTO Simplified Method and the Simplified Stiffness Method. Resistance factors are tabulated for use in LRFD foundation practice in Canada which rewards designers with larger resistance factors for greater project level of understanding. Resistance factors are also provided that are amenable to US practice where the notion of level of understanding is not explicitly considered in LRFD practice. The paper demonstrates the application of the load and resistance factors for tensile rupture and pullout internal stability limit states using a design example and shows the reduction in required reinforcement strength using the Simplified Stiffness Method. The paper is of value to practitioners and LRFD code writers in the United States and Canada for future revisions of design specifications in their jurisdictions. [ABSTRACT FROM AUTHOR]

Abstract: North American design codes are now committed to the development of load and resistance factor design (LRFD) for reinforced soil structures including internal stability limit states. Reliability-based analysis is required to carry out these calibrations. A framework for LRFD calibration has been proposed by the writers that requires bias statistics for load and resistance terms for each limit state function. In this paper the formulation of the limit state for reinforcement tensile rupture is developed and the component strength-reduction bias statistics identified. The paper describes how to compute bias statistics from project-specific installation damage trials for use in reliability-based design for the reinforcement rupture limit state or using data from multiple sources for LRFD calibration. A database of results from field installation damage trials on 103 different geosynthetic products was collected from 20 different sources. A total of 799 and 2248 in-air tensile test results were reviewed for undamaged and damaged geosynthetic specimens, respectively. This database is used to compute installation damage bias statistics for six different categories of geosynthetic and four categories of backfill soils classified according to the D 50 particle size. A practical outcome is that for analysis purposes, bias statistics can be grouped into two ranges for each geosynthetic type based on D 50 of the soil greater than or less than 19 mm. The paper shows how bias statistics together with load and resistance factors for the geosynthetic rupture limit state function recommended by can be used to calculate probability of failure using Monte Carlo simulation and demonstrates the sensitivity of probability of failure to magnitude of installation damage bias statistics. The installation damage data is valuable for future LRFD calibration to select resistance factors for use in design codes for the geosynthetic rupture limit state in reinforced soil structures. [Copyright &y& Elsevier]