A. Burak Göktepe

Advances in backcalculating the mechanical properties of flexible pavements

In current practice, the evaluation of the performance of existing road pavements has become a priority issue for many highway engineers. To make appropriate rehabilitation and management decisions the engineer must rely on an efficient method for determining the structural conditions of pavements. Nondestructive testing (NDT) reveals the stress-strain properties of pavement layers at relatively low strain levels. Since the theoretical approaches used to determine the stress-strain relationships in pavement layers calculate the deflections for given mechanical properties, it is necessary to make an inversion using a backcalculation tool. Several methods have been developed to backcalculate the mechanical properties of flexible pavement; these methods vary in analysis type, material model, and optimization algorithm. This study is designed to explain these methods and to compare and contrast them in terms of modeling precision, computational expense, and calculation details. Consequently, innovations and advances in backcalculating flexible pavements are considered in this paper.

Backcalculation of Flexible Pavements Using Soft Computing

Analysis of the mechanical properties of existing road pavements is crucial for pavement rehabilitation and management problems. Numerous studies have focused on developing an efficient method for determining the structural conditions of pavements. Non-destructive testing (NDT) methods can characterize stress-strain behavior of pavement layers at relatively low strain levels. However, the majority of NDT techniques are based on measuring the deflections caused by an applied load to determine the stress-strain behavior. Structural analysis techniques can also calculate deflections using material and loading properties where it is commonly necessary to make an inversion between measured deflections and mechanical properties using a back-calculation tool. Soft computing techniques, i.e. neural networks, fuzzy logic, genetic algorithms, and hybrid systems, have successfully been used to perform efficient and precise back-calculation analyses. This chapter explains the advances in pavement back-calculation methodologies based on soft computing approaches by presenting the concepts behind them and the fundamental advantages of each. An alternative utilization of soft computing techniques for pavement engineering is also presented.

The Effects of Orthotropic Materials on the Vibration Characteristics of Structural Systems

Abstract The rapid growth in anisotropic material (such as composite materials) usage marks a new era in material science. Obviously, in order to understand the physical behavior of structural systems constituted by composite materials, several parameters, such as natural frequencies, mode shapes, and transmissiblities, must be incorporated into anisotropic elastic analyses. Orthotropy, as a special case of anisotropy, is common in almost all fields of civil and mechanical engineering. The objective of this effort is to investigate the effect of orthotropy on the behavior of vibrating plate systems near degenerate modes. A degenerate plate may be lack of geometric stability since the plate may exhibit a qualitatively different behavior under an arbitrarily small change in special parameters. The special parameters considered in this study are orthotropy and the location of additional mass, which have the effect of removing the system symmetry. The method, which depends on a variational procedure in conjunction with a finite difference method, is employed to examine free vibration characteristics as well as to characterize steady state response to a sinusoidally varying force applied to orthotrophic elastic rectangular plate. The problem is reduced to the solution of a system consisting of algebraic equations by using the variational difference method (VDM). In order to sort the effect of orthotropy on the vibration behavior from other factors, locations of external force, and mass are treated as additional parameters in the analyses. Furthermore, supports are constituted as elastic so as to be able to obtain force transmissibility curves. Finally, plate systems having two different boundary conditions, namely elastically supported and elastically point supported, are utilized to observe the generalization of the outcomes. Results reveal that in case of material orthotropy existence in a plate system, there are several keynote issues that must be taken into account in vibration analyses, which are not important under isotropic conditions. Obviously, these effects are of theoretical importance and should be considered in practical applications.

EFFECT OF FRACTAL DIMENSION ON THE STRAIN BEHAVIOR OF PARTICULATE MEDIA

In this study, the influence of several fractal identifiers of granular materials on dynamic behavior of a flexible pavement structure as a particulate stratum is considered. Using experimental results and numerical methods as well, 15 different grain-shaped sands obtained from 5 different sources were analyzed as pavement base course materials. Image analyses were carried out by use of a stereomicroscope on 15 different samples to obtain quantitative particle shape information. Furthermore, triaxial compression tests were conducted to determine stress–strain and shear strength parameters of sands. Additionally, the dynamic response of the particulate media to standard traffic loads was computed using finite element modeling (FEM) technique. Using area-perimeter, line divider and box counting methods, over a hundred grains for each sand type were subjected to fractal analysis. Relationships among fractal dimension descriptors and dynamic strain levels were established for assessment of importance of shape descriptors of sands at various scales on the dynamic behavior. In this context, the advantage of fractal geometry concept to describe irregular and fractured shapes was used to characterize the sands used as base course materials. Results indicated that fractal identifiers can be preferred to analyze the effect of shape properties of sands on dynamic behavior of pavement base layers.

Evaluation and use of clustering algorithms for standard penetration test data classification

Abstract The standard penetration test (SPT) is the most common test conducted in the field, and it is used to determine in situ properties of different soils. Although it is a matter of debate, these tests are also used for the determination of the consistency of fine-grained soils, whereby the test results can also be utilized to establish numerous empirical correlations to predict the strength of soils in the field. In this study, unsupervised clustering algorithms were employed to classify the SPT standard penetration resistance value (SPT-N) in the field. In this scope, shear strength and liquidity index parameters were used to classify the SPT-N values by taking the classification system of Terzaghi and Peck (1967) into consideration. The results showed that the input parameters were successful for classifying the SPT-N value to an acceptable degree of strength attribute. Therefore, in cases where the SPT tests are unreliable or could not be performed, laboratory tests on undisturbed specimens can give valuable information regarding the consistency and SPT-N value of the soil specimen under investigation. Data in this study is based on several tests that were conducted in a region; nevertheless, it is advised that the results of this study should be evaluated using global data.