Thermal stress and fracture temperature prediction for flexible pavement

Analytical solutions of thermal stresses in multilayered elastic system whose materials characteristics are dependent on temperature are derived by a transfer matrix and integral transformation method.The resulting formulation is used to calculate thermal stresses in the low temperature cracking problem of asphalt pavement.Numerical simulations and analyses are performed using different structural combinations and material characteristics of base course.And fracture temperatures are predicted for a given flexible pavement constructed with three types of asphalt mixtures based on the calculated results and experimental data.This approach serves as a better model for real pavement structure as it takes into account the relationships between the material characteristics and temperature in the pavement system.

Review on dynamic analysis of road pavements under moving vehicles and plane strain conditions

This paper reviews works on the dynamic analysis of flexible and rigid pavements under moving vehicles on the basis of continuum-based plane strain models and linear theories.The purpose of this review is to provide in-formation about the existing works on the subject,critically discuss them and make suggestions for further research.The reviewed papers are presented on the basis of the various models for pavement-vehicle systems and the various methods for dynamically analyzing these systems.Flexible pavements are modeled by a homogeneous or layered half-plane with isotropic or anisotropic and linear elastic,viscoelastic or poroelastic material behavior.Rigid pavements are modeled by a beam or plate on a homogeneous or layered half-plane with material properties like the ones for flexible pavements.The vehicles are modeled as concentrated or distributed over a finite area loads moving with constant or time dependent speed.The above pavement-vehicle models are dynamically analyzed by analytical,analytical/numerical or purely numerical methods working in the time or frequency domain.Representative examples are presented to illustrate the models and methods of analysis,demonstrate their merits and assess the effects of the various parameters on pavement response.The paper closes with con-clusions and suggestions for further research in the area.The significance of this research effort has to do with the presentation of the existing literature on the subject in a critical and easy to understand way with the aid of representative examples and the identification of new research areas.

Estimation of flexible pavement structural capacity using machine learning techniques

The most common index for representing structural condition of the pavement is the structural number.The current procedure for determining structural numbers involves utilizing falling weight deflectometer and ground-penetrating radar tests,recording pavement surface deflections,and analyzing recorded deflections by back-calculation manners.This procedure has two drawbacks:falling weight deflectometer and ground-penetrating radar are expensive tests;back-calculation ways has some inherent shortcomings compared to exact methods as they adopt a trial and error approach.In this study,three machine learning methods entitled Gaussian process regression,M5P model tree,and random forest used for the prediction of structural numbers in flexible pavements.Dataset of this paper is related to 759 flexible pavement sections at Semnan and Khuzestan provinces in Iran and includes“structural number”as output and“surface deflections and surface temperature”as inputs.The accuracy of results was examined based on three criteria of R,MAE,and RMSE.Among the methods employed in this paper,random forest is the most accurate as it yields the best values for above criteria(R=0.841,MAE=0.592,and RMSE=0.760).The proposed method does not require to use ground penetrating radar test,which in turn reduce costs and work difficulty.Using machine learning methods instead of back-calculation improves the calculation process quality and accuracy.

Using Sorghum Stalk as a Partial Replacement of Lime in the Stabilization of Red Clay Soil for Road Sub-Grade Construction

This research aimed at testing the viability of using Sorghum Stalk Ash (SSA) as a partial replacement of lime in the stabilization of red clay soils for road subgrade construction. Red clay soils have been identified as highly expansive soils, which are affected by both climatic conditions and loading patterns. The consideration of both traffic loading patterns and climatic effects on these soils has been taken into account. A penetration test of 2.5 mm has been used on both pure red soils and stabilized soils at 10% and 15% partial replacement of lime with SSA and showed an improvement in the CBR of stabilized red clay soils up to 11.6%. Again, the PI of stabilized soils at 15% partial replacement of lime reduced up to 11.2%. The results obtained on both CBR and PI of these red clay soils are within the recommended values for the effective subgrade required for laying both permanent and flexible pavements. As a result, a recommendation of making use of SSA to lower the quantities of lime and its costs used in the stabilization of highly expansive soils have been tested through this research. However, further research on a more percentage partial replacement of lime to improve the PI of these soils to below 10% while keeping the CBR levels within the road construction regulations is welcomed.

Pavement sustainability index for highway infrastructures： A case study of Maryland

Pavement deterioration creates conditions that undermine their performances, which gives rise to the need for maintenance and rehabilitation. This paper develops a mathematical multi-linear regression analysis （MLRA） model to determine a pavement sustainability index （PSTI） as dependent variable for flexible pavements in Maryland. Four categories of pavement performance evaluation indicators are subdivided into seven pavement condition indices and analyzed as independent variables for each section of pavement. Data are collected from five different roadways using field evaluations and existing database. Results indicate that coefficient of determination （R^2） is correlated and significant, R^2 = 0.959. Of the seven independent variables, present serviceability index （PSI） is the most significant with a coefficient value of 0.032, present serviceability rating （PSR） coefficient value=0.028, and international roughness index （IRI） coefficient value = -0.001. Increasing each unit value of coefficients for PSI and PSR would increase the value of PSTI; thereby providing a more sustainable pavement infrastructure; which explains the significance of the model and why IR/ will most likely impact environmental, economic and social values.

A review of top-down cracking in asphalt pavements:Causes, models, experimental tools and future challenges

In the last decades,a new type of distress has been observed more and more frequently on asphalt pavements.This distress,ascribable to fatigue failure,has been named top-down cracking(TDC) because it consists in longitudinal cracks that initiate on the pavement surface and then propagate downwards.A series of surveys recently carried out on Italian motorways highlighted that TDC can affect up to 20%-30% of the slow traffic lane.Therefore,in order to achieve a better understanding of such distress,this paper reviews causes,models and experimental tools and highlights future challenges for TDC.The literature review indicates that TDC can evolve on the pavement surface in three stages(i.e.,single crack,sister cracks,alligator cracking) and,below a certain depth,the cracks can form angles of 20°-40° with respect to the vertical plane.Even though multiple factors contribute to TDC development,thick pavements are more likely to fail due to TDC induced by tire-pavement contact stresses,especially in the presence of open-graded friction courses(OGFCs).Moreover,in literature there are several TDC models based on mechanics(e.g.,fracture mechanics or continuum damage mechanics) which allow a rigorous study of crack initiation and propagation.Future challenges include the identification of a reliable and feasible test method,among those proposed in literature,to study the TDC performance of asphalt mixtures and the implementation of TDC in pavement management systems(PMSs) through the definition of criteria for TDC recognition in the field as well as for the rehabilitation depth evaluation.Finally,more research is needed for open-graded asphalt mixtures,which present critical drawbacks in terms of TDC.

Dynamic analysis of falling weight deflectometer

Falling weight deflectometer （FWD） testing has been used to evaluate structural condition of pavements to predict the layer moduli using backcalculation process. However, the predicted pavement layer moduli sometimes may not be accurate even if computed and measured deflection basin has fulfilled the standard and is in concurrence with certain tolerable limits. The characteristics of pavement structure, including pavement layer thickness condition and temperature variation, affect the predicted pavement structural capacity and back calculated layer modulus. The main objective of this study is to analyze the FVc＇D test results of flexible pavement in Western Australia to predict the pavement structural capacity. Collected data includes, in addition to FWD measurements, core data and pavement distress surveys. Results showed that the dynamic analysis of falling weight deflectometer test and prediction for the strength of character of flexible pavement layer moduli have been achieved, and algorithms for interpretation of the deflection basin have been improved. The variations of moduli of all layers along the length of sections for majority of the projects are accurate and consistent with measured and computed pre- diction. However, some of the projects had some inconsistent with modulus values along the length of the sections. Results are reasonable but consideration should be taken to fix varied pavement layers moduli sections.