A new working stress method for prediction of reinforcement loads in geosynthetic walls

2003 ◽  
Vol 40 (5) ◽  
pp. 976-994 ◽  
Author(s):  
T M Allen ◽  
Richard J Bathurst ◽  
Robert D Holtz ◽  
D Walters ◽  
Wei F Lee

Proper estimation of soil reinforcement loads and strains is key to accurate internal stability design of reinforced soil structures. Current design methodologies use limit equilibrium concepts to estimate reinforcement loads for internal stability design of geosynthetic and steel reinforced soil walls. For geosynthetic walls, however, it appears that these methods are excessively conservative based on the performance of geosynthetic walls to date. This paper presents a new method, called the K-stiffness method, that is shown to give more accurate estimates of reinforcement loads, thereby reducing reinforcement quantities and improving the economy of geosynthetic walls. The paper is focused on the new method as it applies to geosynthetic walls constructed with granular (noncohesive, relatively low silt content) backfill soils. A database of 11 full-scale geosynthetic walls was used to develop the new design methodology based on working stress principles. The method considers the stiffness of the various wall components and their influence on reinforcement loads. Results of simple statistical analyses show that the current American Association of State Highway and Transportation Officials (AASHTO) Simplified Method results in an average ratio of measured to predicted loads (bias) of 0.45, with a coefficient of variation (COV) of 91%, whereas the proposed method results in an average bias of 0.99 and a COV of 36%. A principle objective of the method is to design the wall reinforcement so that the soil within the wall backfill is prevented from reaching a state of failure, consistent with the notion of working stress conditions. This concept represents a new approach for internal stability design of geosynthetic-reinforced soil walls because prevention of soil failure as a limit state is considered in addition to the current practice of preventing reinforcement rupture.Key words: geosynthetics, reinforcement, walls, loads, strains, design, K-stiffness method.

1992 ◽  
Vol 29 (5) ◽  
pp. 832-842 ◽  
Author(s):  
S-C. R. Lo ◽  
D-W. Xu

A new design methodology was developed to predict the collapse of reinforced soil walls or slopes caused by failure of the reinforcing elements. The rupture surface was modelled by a generalized log spiral selected by numerical optimization, and the conventional assumption of rigid–plastic deformation at wall collapse was not made. The limit equilibrium equations were established by examining the equilibrium of slices of soil parallel to the reinforcing elements. A strain-based criterion was used to model the initiation of wall collapse by breakage of reinforcement. The tensile forces in the reinforcing elements were determined based on, approximately, strain compatibility along the rupture surface. The proposed method can model reinforcement with nonlinear load extension response that depends on embedment, non-uniform distribution of reinforcement, and dilatancy of soil. An expedient numerical scheme for performing the analysis is presented to enable the routine use of the analysis in a design office. The proposed method was validated by comparing the predictions with published observations and finite element simulation of a reinforced soil wall. Key words : collapse, kinematics, limit equilibrium, numerical optimization, reinforced soil, strain.


2010 ◽  
Vol 47 (8) ◽  
pp. 885-904 ◽  
Author(s):  
Bingquan Huang ◽  
Richard J. Bathurst ◽  
Kianoosh Hatami ◽  
Tony M. Allen

A verified fast Lagrangian analysis of continua (FLAC) numerical model is used to investigate the influence of horizontal toe stiffness on the performance of reinforced soil segmental retaining walls under working stress (operational) conditions. Results of full-scale shear testing of the interface between the bottom of a typical modular block and concrete or crushed stone levelling pads are used to back-calculate toe stiffness values. The results of numerical simulations demonstrate that toe resistance at the base of a reinforced soil segmental retaining wall can generate a significant portion of the resistance to horizontal earth loads in these systems. This partially explains why reinforcement loads under working stress conditions are typically overestimated using current limit equilibrium-based design methods. Other parameters investigated are wall height, interface shear stiffness between blocks, wall facing batter, reinforcement stiffness, and reinforcement spacing. Computed reinforcement loads are compared with predicted loads using the empirical-based K-stiffness method. The K-stiffness method predictions are shown to better capture the qualitative trends in numerical results and be quantitatively more accurate compared with the AASHTO simplified method.


2008 ◽  
Vol 45 (10) ◽  
pp. 1377-1392 ◽  
Author(s):  
Richard J. Bathurst ◽  
Tony M. Allen ◽  
Andrzej S. Nowak

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.


Sign in / Sign up

Export Citation Format

Share Document