Railway ballast anisotropy testing via true triaxial apparatus

This paper aims to demonstrate the anisotropic behaviour of railway ballast via true-triaxial tests. To do so, a novel, large-scale, true-triaxial testing apparatus (GeoTT) is designed and constructed. It consists of six hydraulic actuators, designed to apply a distributed stress to large granular cubic test specimens with dimensions: 500 mm × 500 m × 500 mm. To show the capability of the new facility, crushed granite railway ballast with d50 = 43 mm is tested. Three different confining stresses are applied to determine the Poisson’s ratio and modulus in three dimensions. Anisotropic behaviour is clearly evident, with horizontal directions showing a lower modulus compared to the vertical direction. It is also found that confining stress has an important effect on both Poisson’s ratio and modulus when the primary loading is applied in three orthogonal directions. These results are useful for understanding the behaviour of railway ballast and for the calibration of railroad numerical models

Discreet element modeling of under sleeper pads using a box test

It has recently been reported that under sleeper pads (USPs) could improve ballasted rail track by decreasing the sleeper settlement and reducing particle breakage. In order to find out what happens at the particle-pad interface, discrete element modelling (DEM) is used to provide micro mechanical insight. The same positive effects of USP are found in the DEM simulations. The evidence provided by DEM shows that application of a USP allows more particles to be in contact with the pad, and causes these particles to transfer a larger lateral load to the adjacent ballast but a smaller vertical load beneath the sleeper. This could be used to explain why the USP helps to reduce the track settlement. In terms of particle breakage, it is found that most breakage occurs at the particle-sleeper interface and along the main contact force chains between particles under the sleeper. The use of USPs could effectively reduce particle abrasion that occurs in both of these regions

Combined Discrete-Continuum Analysis for Ballasted Rail Tracks

A study on the load-deformation behaviour of railway ballast aggregates subjected to cyclic loadings using a combined discrete-continuum modelling approach is presented. Discrete ballast particles are simulated in the DEM and the continuum-based subgrade is simulated by the FDM. Interface elements are generated to transmit contact forces and displacements between the two domains (i.e. discrete and continuum) whereby the DEM exchanges contact forces to the FDM, and then the FDM transfers the displacement back to the DEM. Distributions of contact forces, coordination number, stress contours on the subgrade and corresponding number of broken bonds (representing ballast breakage) are analysed

Nondestructive flexible pavement evaluation using ILLI-PAVE based artificial neural network models

Artificial neural networks (ANNs) were used in this paper to develop an improved and more accurate approach for backcalculating pavement layer moduli from Falling Weight Deflectometer (FWD) test data collected in the field. For this purpose, critical pavement responses were computed by the ILLI-PAVE finite element program widely used and proven to be effective for the analysis of flexible pavement systems with the considerations of the nonlinear aggregate base and subgrade soil behavior. The ANN models were then trained to map the nonlinear functional relationships between the FWD deflections, layer properties, and the critical pavement responses

Performance Assessment of Geocell-Reinforced Subballast: Modeling and Design Implications

This paper presents a study of the load-deformation behavior of geocell-stabilised subballast subjected to cyclic loads using a large-scale track process simulation apparatus and numerical modelling. The tests and numerical simulations were conducted to mimic the actual track conditions. Subjected to a given frequency and cyclic loads the predicted load-deformation behavior of the subballast with and without geocell inclusions match reasonably with those measured in the laboratory, and show that geocell could effectively decrease the lateral and axial deformations of the reinforced subballast. The results also provide an insight to design of rail tracks capturing the roles of geocell in decreasing lateral deformation of subballast. Additionally, the numerical modelling carried out in this study can be applied in the preliminary design of track substructure where a wide range of subballast aggregates and geocell mattresses with varying strengths and stiffness can be considered

Quantifying effects of lime stabilized subgrade on conventional flexible pavement responses

Lime stabilization is commonly used to improve weak natural subgrade in Illinois. ILLI-PAVE nonlinear finite element (FE) program was utilized in this study as an advanced pavement structural analysis tool to quantify the improvement from the lime stabilized soil layer in conventional flexible pavements. Using ILLI-PAVE, many combinations of typical Illinois highway pavement layer thicknesses and material properties were analyzed to establish a database of surface deflections and critical pavement responses. Using this database, Artificial Neural Network (ANN) structural models were trained successfully as forward analysis tools, surrogate to ILLI-PAVE, to be used in the backcalculation of the Falling Weight Deflectometer data. The ANN model predictions were on the average within 1% of the ILLI-PAVE FE results. The developed ANN models were therefore quite accurate for the rapid analyses of conventional flexible pavements built on lime stabilized soils replicating the ILLI-PAVE results

Analyzing pavements on lime-stabilized soils with artificial neural networks

Lime stabilization has been used as an improvement technique in the soft ground for many years. Pavements with lime-stabilized subgrades result in reduced deflections and improved critical pavement responses under applied wheel loading. ILLI-PAVE, a nonlinear finite element program for Advanced pavement analysis, was utilized in this study to model pavements on lime-stabilized soils and show benefits of lime stabilization. A wide range of material model parameters and pavement geometries was studied to obtain corresponding deflections and critical pavement responses. The results were used to create a database for developing artificial neural network (ANN) models and capturing the nonlinear relationship by means of the backpropagation algorithm. The developed ANN models worked as highly Effective and robust ILLI-PAVE surrogate solutions to investigate the effects of lime stabilization on deflection profiles and critical responses. Significant differences were found between responses of full depth pavements on unmodified subgrade and lime-stabilized subgrade