Numerical analysis of the behaviour of mechanically stabilized earth walls reinforced with different types of strips

A mechanically stabilized earth (MSE) wall behaves as a flexible coherent block able to sustain significant loading and deformation due to the interaction between the backfill material and the reinforcement elements. The internal behaviour of a reinforced soil mass depends on a number of factors, including the soil, the reinforcement and the soil/structure interaction and represents a complex interaction sol/structure problem. The use of parameters determined from experimental studies should allow more accurate modelling of the behaviour of the MSE structures.In this article, a reference MSE wall is modelled from two points of view: serviceability limit state “SLS” and ultimate limit state “ULS”. The construction of the wall is simulated in several stages and the soil/interface parameters are back analysed from pullout tests. An extensive parametric study is set up and permits to highlight the influence of the soil, the reinforcement and the soil/structure parameters. The behaviour of MSE walls with several geosynthetic straps is compared with the metallic one. Several constitutive models with an increasing complexity have been used and compared.The results obtained from stress-deformation analyses are presented and compared. The use of geosynthetic straps induces more deformation of the wall but a higher safety factor. To design theses walls the important parameters are: the soil friction, the cohesion, the interface shear stiffness and the strip elastic modulus.It is shown that for wall construction that involves static loading conditions, the modified Duncan-Chang model is a good compromise but induces slightly lower strip tensile forces due to the fact that it do not take into account of dilatancy before failure.     

Geosynthetic reinforcement stiffness for analytical and numerical modelling of reinforced soil structures

Many analytical and numerical analysis and design methods for geosynthetic-reinforced soil structures require a single-value (constant) estimate of reinforcement stiffness. However, geosynthetic reinforcement products are rate-dependent polymeric materials meaning that they exhibit time and strain-dependent behaviour under load. Hence, the appropriate selection of a constant (elastic) stiffness value requires careful consideration. A simple hyperbolic stiffness model is shown to be a useful approximation to the constant-load isochronous creep-strain behaviour of these materials at low load levels applicable to operational (serviceability) conditions of geosynthetic-reinforced soil structures. A large database of 606 creep tests on 89 different geosynthetic reinforcement products falling within seven different product categories was collected. From these data, isochronous stiffness values were determined for different combinations of duration of loading and strain level. Data from products falling within the same category were collected together to provide approximations linking the isochronous load-strain (creep) stiffness to the ultimate tensile strength of the material. These approximations are useful for analytical and numerical modelling particularly when parametric studies are undertaken to identify the sensitivity of model outcomes to reinforcement stiffness. Finally, three different geosynthetic-reinforced soil application examples are provided to demonstrate the important role of tensile stiffness on analysis and design outcomes.     

Deterministic and probabilistic assessment of margins of safety for internal stability of as-built PET strap reinforced soil walls

The paper demonstrates deterministic and reliability-based assessment of strength limit states (tensile resistance and pullout) and the service limit state for soil failure for mechanically stabilized earth (MSE) walls constructed with polyester (PET) strap reinforcement. The general approach considers the accuracy of the load and resistance models that appear in each limit state equation plus uncertainty in the estimate of nominal load and resistance values at time of design. Reliability index is computed using a closed-form solution that is easily implemented in a spreadsheet. Three PET strap MSE wall case studies are used to demonstrate the reliability-based assessment approach and to compare margins of safety using different load and resistance model combinations. In some walls using the Coherent Gravity Method to compute loads, the recommended nominal factors of safety for tensile strength and pullout limit states were not satisfied. However, reliability analyses showed that the walls satisfy recommended minimum target reliability index values for the limit states investigated, usually by large amounts. The most critical limit state is the soil failure limit state which is used in the Simplified Stiffness Method to keep the reinforced soil zone at working stress conditions assumed for geosynthetic MSE walls under operational conditions.     

微型桩–加筋土挡墙的模型试验和数值模拟分析

微型桩–加筋土挡墙是一种适用于山区陡坡地带公路工程的新型路基支挡结构,为了初步检验其工作机制和效果,通过模型试验,并结合有限元模拟,对微型桩加固前后的斜坡加筋土挡墙在多级附加荷载下的静力响应进行对比研究。结果表明:数值计算手段能够较好地再现模型试验结果;在2~10 kPa附加荷载下,实测微型桩–加筋土挡墙的沉降比加固前减小11%~40%,面板侧向位移减小50%~66%,且附加荷载越大,减小的比例越大;同时,基底压力和侧向土压力也比加固前明显降低;倾斜桩对挡土墙变形的限制发挥着更为重要的作用,实测2~10 kPa附加荷载导致的倾斜桩身弯矩比竖直桩高出25.9%~40.3%,因而有必要采用较高强度的微型桩作为倾斜方向的加固构件。研究结论初步验证了微型桩–加筋土挡墙的有效性,可为其在实际工程中的应用提供指导。     

Auto machine learning-based modelling and prediction of excavation-induced tunnel displacement

The influence of a deep excavation on existing shield tunnels nearby is a vital issue in tunnelling engineering. Whereas, there lacks robust methods to predict excavation-induced tunnel displacements. In this study, an auto machine learning(Auto ML)-based approach is proposed to precisely solve the issue.Seven input parameters are considered in the database covering two physical aspects, namely soil property, and spatial characteristics of the deep excavation. The 10-fold cross-validation method...     

Use of artificial neural networks to predict 3-D elastic settlement of foundations on soils with inclined bedrock

The application of the theory of elasticity for the calculation of foundation settlements has yielded equations that are well-established and consolidated in geotechnical standards and/or that are recommended for use. These equations are corrected by an influence factor in order to increase their precision and to encompass the existing complex geotechnical casuistry. The study presented herein utilizes neural networks to improve the determination of the influence factor (I_α), which considers the effect of a finite elastic half-space limited by the inclined bedrock under a foundation. The results obtained through the utilization of artificial neural networks (ANNs) demonstrate a notable improvement in the predicted values for the influence factor in comparison with those of existing analytical equations.