Methodology for Pavement Design Reliability and Back Analysis Using Markov Chain Monte Carlo Simulation

Given the increasing cost of designing and building new highway pavements, reliability analysis has become vital to ensure that a given pavement performs as expected in the field. Recognizing the importance of failure analysis to safety, reliability, performance, and economy, back analysis has been employed in various engineering applications to evaluate the inherent uncertainties of the design and analysis. The probabilistic back analysis method formulated on Bayes' theorem and solved using the Markov chain Monte Carlo simulation method with a Metropolis-Hastings algorithm has proved to be highly efficient to address this issue. It is also quite flexible and is applicable to any type of prior information. In this paper, this method has been used to back-analyze the parameters that influence the pavement life and to consider the uncertainty of the mechanistic-empirical pavement design model. The load-induced pavement structural responses (e.g., stresses, strains, and deflections) used to predict the pavement life are estimated using the response surface methodology model developed based on the results of linear elastic analysis. The failure criteria adopted for the analysis were based on the factor of safety (FOS), and the study was carried out for different sample sizes and jumping distributions to estimate the most robust posterior statistics. From the posterior statistics of the case considered, it was observed that after approximately 150 million standard axle load repetitions, the mean values of the pavement properties decrease as expected, with a significant decrease in the values of the elastic moduli of the expected layers. An analysis of the posterior statistics indicated that the parameters that contribute significantly to the pavement failure were the moduli of the base and surface layer, which is consistent with the findings from other studies. After the back analysis, the base modulus parameters show a significant decrease of 15.8% and the surface layer modulus a decrease of 3.12% in the mean value. The usefulness of the back analysis methodology is further highlighted by estimating the design parameters for specified values of the factor of safety. The analysis revealed that for the pavement section considered, a reliability of 89% and 94% can be achieved by adopting FOS values of 1.5 and 2, respectively. The methodology proposed can therefore be effectively used to identify the parameters that are critical to pavement failure in the design of pavements for specified levels of reliability. DOI: 10.1061/(ASCE)TE.1943-5436.0000455. (C) 2013 American Society of Civil Engineers.

Effect of Input Source Energy on SASW Evaluation of Cement Concrete Pavement

A series of spectral analyses of surface waves (SASW) tests were conducted on a cement concrete pavement by dropping steel balls of four different values of diameter (D) varying between 25.4 and 76.2 mm. These tests were performed (1) by using different combinations of source to nearest receiver distance (S) and receiver spacing (X), and (2) for two different heights (H) of fall, namely, 0.25 and 0.50 m. The values of the maximum wavelength (lambda(max)) and minimum wavelength (lambda(min)) associated with the combined dispersion curve, corresponding to a particular combination of D and H, were noted to increase almost linearly with an increase in the magnitude of the input source energy (E). A continuous increase in strength and duration of the signals was noted to occur with an increase in the magnitude of D. Based on statistical analysis, two regression equations have been proposed to determine lambda(max) and lambda(min) for different values of source energy. It is concluded that the SASW technique is capable of producing nearly a unique dispersion curve irrespective of (1) diameters and heights of fall of the dropping masses used for producing the vibration, and (2) the spacing between different receivers. The results presented in this paper can be used to provide guidelines for deciding about the input source energy based on the required exploration zone of the pavement. (C) 2014 American Society of Civil Engineers.

Influence of Spatial Variability on Pavement Responses Using Latin Hypercube Sampling on Two-Dimensional Random Fields

Although uncertainties in material properties have been addressed in the design of flexible pavements, most current modeling techniques assume that pavement layers are homogeneous. The paper addresses the influence of the spatial variability of the resilient moduli of pavement layers by evaluating the effect of the variance and correlation length on the pavement responses to loading. The integration of the spatially varying log-normal random field with the finite-difference method has been achieved through an exponential autocorrelation function. The variation in the correlation length was found to have a marginal effect on the mean values of the critical strains and a noticeable effect on the standard deviation which decreases with decreases in correlation length. This reduction in the variance arises because of the spatial averaging phenomenon over the softer and stiffer zones generated because of spatial variability. The increase in the mean value of critical strains with decreasing correlation length, although minor, illustrates that pavement performance is adversely affected by the presence of spatially varying layers. The study also confirmed that the higher the variability in the pavement layer moduli, introduced through a higher value of coefficient of variation (COV), the higher the variability in the pavement response. The study concludes that ignoring spatial variability by modeling the pavement layers as homogeneous that have very short correlation lengths can result in the underestimation of the critical strains and thus an inaccurate assessment of the pavement performance. (C) 2014 American Society of Civil Engineers.

Influence of Anisotropy on Pavement Responses Using Adaptive Sparse Polynomial Chaos Expansion

Modeling the spatial variability that exists in pavement systems can be conveniently represented by means of random fields; in this study, a probabilistic analysis that considers the spatial variability, including the anisotropic nature of the pavement layer properties, is presented. The integration of the spatially varying log-normal random fields into a linear-elastic finite difference analysis has been achieved through the expansion optimal linear estimation method. For the estimation of the critical pavement responses, metamodels based on polynomial chaos expansion (PCE) are developed to replace the computationally expensive finite-difference model. The sparse polynomial chaos expansion based on an adaptive regression-based algorithm, and enhanced by the combined use of the global sensitivity analysis (GSA) is used, with significant savings in computational effort. The effect of anisotropy in each layer on the pavement responses was studied separately, and an effort is made to identify the pavement layer wherein the introduction of anisotropic characteristics results in the most significant impact on the critical strains. It is observed that the anisotropy in the base layer has a significant but diverse effect on both critical strains. While the compressive strain tends to be considerably higher than that observed for the isotropic section, the tensile strains show a decrease in the mean value with the introduction of base-layer anisotropy. Furthermore, asphalt-layer anisotropy also tends to decrease the critical tensile strain while having little effect on the critical compressive strain. (C) 2015 American Society of Civil Engineers.

Recommendations for driver licensing and traffic law enforcement in India aiming to improve road safety

During the last decade, developing countries such as India have been exhibiting rapid increase in human population and vehicles, and increase in road accidents. Inappropriate driving behaviour is considered one of the major causes of road accidents in India as compared to defective geometric design of pavement or mechanical defects in vehicles. It can result in conditions such as lack of lane discipline, disregard to traffic laws, frequent traffic violations, increase in crashes due to self-centred driving, etc. It also demotivates educated drivers from following good driving practices. Hence, improved driver behaviour can be an effective countermeasure to reduce the vulnerability of road users and inhibit crash risks. This article highlights improved driver behaviour through better driver education, driver training and licensing procedures along with good on-road enforcement; as an effective countermeasure to ensure road safety in India. Based on the review and analysis, the article also recommends certain measures pertaining to driver licensing and traffic law enforcement in India aimed at improving road safety.

On the height of fall of dropping mass in SASW measurements for asphaltic road pavements

A number of spectral analysis of surface waves (SASW) tests were performed on asphaltic road pavements by dropping a metallic 6.5 kg sphere, from a height (H) ranging from 1 to 3 m. Various combinations of source to first receiver distance (S) and receiver spacing (X) were employed. By increasing the height of the fall of the dropping mass, the maximum wavelength (lambda(max)), up to which the shear wave velocity profile can be predicted with the usage of the SASW measurements, was found to increase continuously. The height of fall of the dropping mass also seems to affect the admissible range of the wavelength for given combinations of X and S. Irrespective of different chosen combinations of S, X and H, a unique combined dispersion curve was generated in all the cases for a given pavement site as long as the threshold minimum value of the coherence function is greater than 0.90.

SASW evaluation of asphaltic and cement concrete pavements using different heights of fall for a spherical mass

A number of spectral analysis of surface wave tests were performed on asphaltic and cement concrete pavements by dropping freely a 6.5kg spherical mass, having a radius of 5.82cm, from a height (h) of 0.51.5m. The maximum wavelength ((max)), up to which the shear wave velocity profile can be detected with the usage of surface wave measurements, increases continuously with an increase in h. As compared to the asphaltic pavement, the values of (max) and (min) become greater for the chosen cement concrete pavement, where (min) refers to the minimum wavelength. With h=0.5m, a good assessment of the top layers of both the present chosen asphaltic and the cement concrete pavements, including soil subgrade, can be made. For a given h, as compared to the selected asphaltic pavement, the first receiver in case of the chosen cement concrete pavement needs to be placed at a greater distance from the source. Inverse analysis has also been performed to characterise the shear wave velocity profile of different layers of the pavements.

System Reliability Analysis of Flexible Pavements

The uncertainty in material properties and traffic characterization in the design of flexible pavements has led to significant efforts in recent years to incorporate reliability methods and probabilistic design procedures for the design, rehabilitation, and maintenance of pavements. In the mechanistic-empirical (ME) design of pavements, despite the fact that there are multiple failure modes, the design criteria applied in the majority of analytical pavement design methods guard only against fatigue cracking and subgrade rutting, which are usually considered as independent failure events. This study carries out the reliability analysis for a flexible pavement section for these failure criteria based on the first-order reliability method (FORM) and the second-order reliability method (SORM) techniques and the crude Monte Carlo simulation. Through a sensitivity analysis, the most critical parameter affecting the design reliability for both fatigue and rutting failure criteria was identified as the surface layer thickness. However, reliability analysis in pavement design is most useful if it can be efficiently and accurately applied to components of pavement design and the combination of these components in an overall system analysis. The study shows that for the pavement section considered, there is a high degree of dependence between the two failure modes, and demonstrates that the probability of simultaneous occurrence of failures can be almost as high as the probability of component failures. Thus, the need to consider the system reliability in the pavement analysis is highlighted, and the study indicates that the improvement of pavement performance should be tackled in the light of reducing this undesirable event of simultaneous failure and not merely the consideration of the more critical failure mode. Furthermore, this probability of simultaneous occurrence of failures is seen to increase considerably with small increments in the mean traffic loads, which also results in wider system reliability bounds. The study also advocates the use of narrow bounds to the probability of failure, which provides a better estimate of the probability of failure, as validated from the results obtained from Monte Carlo simulation (MCS).

AN APPROACH FOR EVALUATION OF USE OF GEOCELLS IN FLEXIBLE PAVEMENTS

The design methodology for flexible pavements needs to address the mechanisms of pavement failure, loading intensities and also develop suitable approaches for evaluation of pavement performance. In the recent years, the use of geocells to improve pavement performance has been receiving considerable attention. This paper studies the influence of geocells on the required thickness of pavements by placing it below the granular layers (base and sub-base) and above the subgrade. The reduction in thickness here refers to the reduction in the thickness of the GSB (Granular Sub-base) layer, with a possibility of altogether getting rid of it. To facilitate the analysis, a simple linear elastic approach is used, considering six of the sections as given in the Indian Roads Congress (IRC) code. All the analysis was done using the pavement analysis package KENPAVE. The results show that the use of geocells enables a reduction in pavement thickness.

Experimental and numerical studies on protection of buried pipelines and underground utilities using geocells

This paper presents the results of the laboratory model tests and the numerical studies conducted on small diameter PVC pipes, buried in geocell reinforced sand beds. The aim of the study was to evaluate the suitability of the geocell reinforcement in protecting the underground utilities and buried pipelines. In addition to geocells, the efficacy of only geogrid and geocell with additional basal geogrid cases were also studied. A PVC (Poly Vinyl Chloride) pipe with external diameter 75 mm and thickness 1.4 mm was used in the experiments. The vehicle tire contact pressure was simulated by applying the pressure on the top of the bed with the help of a steel plate. Results suggest that the use of geocells with additional basal geogrid considerably reduces the deformation of the pipe as compared to other types of reinforcements. Further, the depth of placement of pipe was also varied between 1B to 2B (B is the width of loading plate) below the plate in the presence of geocell with additional basal geogrid. More than 50% reduction in the pressure and more than 40% reduction in the strain values were observed in the presence of reinforcements at different depths as compared to the unreinforced beds. Conversely, the performance of the subgrade soil was also found to be marginally influenced by the position of the pipe, even in the presence of the relatively stiff reinforcement system. Further, experimental results were validated with 3-dimensional numerical studies using FLAC(3D) (Fast Lagrangian Analysis of Continua in 3D). A good agreement in the measured pipe stain values were observed between the experimental and numerical studies. Numerical studies revealed that the geocells distribute the stresses in the lateral direction and thus reduce the pressure on the pipe. In addition, the results of the 1-g model tests were scaled up to the prototype case of the shallow buried pipeline below the pavement using the appropriate scaling laws. (C) 2015 Elsevier Ltd. All rights reserved.