Murat Guler

Distribution of Strains Within Hot-Mix Asphalt Binders: Applying Imaging and Finite-Element Techniques

Because of several orders of magnitude difference between the stiffness of aggregate and binder and the randomness of the binder domain boundaries, the induced deformation under loading can result in a wide distribution of stresses and strains within each of the components. It is expected that although aggregates undergo small strains, most of the strain will accumulate within the binder. Although studies have covered the micromechanics of hot-mix asphalt (HMA), information about the actual typical distribution of asphalt binder domains in HMA and the resulting distribution of stresses and strains is scarce. In this study, advances in imaging techniques are applied to understand the distribution of binder and air voids in selected HMAs. The objective is to determine the strain distribution within the binder using digitized images analyzed with finite-element procedures. This approach captures the image of the specimen cross section and converts the image into finite-element mesh after image processing. The images are converted to finite-element mesh and the finite-element program ABAQUS provides numerical solutions to relate bulk stresses or strains applied to the asphalt mixture to stresses and strains within the binder domains. The results are presented including a summary of the distribution of directional binder film thickness and maximum strains in the mastic domain. Also included is a discussion of the effect of air voids and mineral fillers.

DEVICE FOR MEASURING SHEAR RESISTANCE OF HOT-MIX ASPHALT IN GYRATORY COMPACTOR

The development of a gyratory load-cell and plate assembly (GLPA) to measure the shear resistance of hot-mix asphalt mixtures is described. The GLPA is a simple tool that allows the measurement of the eccentricity of the resultant load applied by the gyratory compactor in real time during compaction. The GLPA is inserted on top of the mixture specimen in the compaction mold, requiring no changes in the compaction procedure. The results from the GLPA give a continuous measure of the resistance of asphalt mixtures to shearing under gyratory loading at a fixed angle. On the basis of a simplified analysis, it is hypothesized that the bulk shear resistance estimated from the GLPA is a good indicator of the compactibility of asphalt mixtures and their potential resistance to rutting under traffic. The shear resistance and volumetric characteristics of a number of trial mixtures fabricated in the laboratory were tested to show the utility of the GLPA. The results show that the shear resistance is highly sensitive to gradation, asphalt content, and temperature. They also indicate that there are interactive effects of these factors that are independent of the volumetric properties. Although the relationship between the results of the GLPA and the field performance of mixtures is yet to be determined, this device has the potential to be a low-cost and effective tool to complement the current volumetric mixture design procedure. It provides a tool to measure an important mechanical property that is a good indicator of bulk shear resistance of asphalt mixtures.

Prediction of Subgrade Resilient Modulus Using Genetic Algorithm and Curve-Shifting Methodology: Alternative to Nonlinear Constitutive Models

This paper demonstrates the applicability of the genetic algorithm and curve-shifting methodology to the estimation of the resilient modulus at various stress states for subgrade soils by using the results of triaxial resilient modulus tests. This innovative methodology is proposed as an alternative to conventional nonlinear constitutive relationships. With the genetic algorithm, laboratory curves for different deviator stress levels at different confining pressures are horizontally shifted to form a final gamma distribution curve that can represent the stress–strain behavior of subgrade soils with the corresponding predicted shift factors. Resilient modulus values for a given stress state can be estimated on the basis of this curve and another gamma function that represents the variation of the shift values for different confining stresses. To compare the effectiveness of these two approaches, coefficients for the Uzan constitutive model were also determined for each laboratory test and compared with those determined by the approach described in this paper. Predicted resilient modulus values from each approach are separately compared with artificial neural network (ANN) model predictions to evaluate their efficiency and reliability for resilient response prediction. The results of the analysis indicated that the curve-shifting methodology gave superior estimates and a coefficient of determination 14% higher than the Uzan model predictions when the results were evaluated with the ANN model outputs. Thus, although it is not a constitutive model, use of the genetic algorithm and curve-shifting methodology is proposed as a promising technique for the evaluation of the stress–strain dependency of subgrade soils.

A Porous Elasto-Plastic Compaction Model for Asphalt Mixtures with Parameter Estimation Algorithm

Estimation of field compaction requirements to achieve a target density is important for predicting construction costs of asphalt concrete pavements. A model to predict the effects of mixture volumetric properties on compaction efficiency is desirable to optimize the design of asphalt mixtures. A compaction model is developed to predict laboratory compaction by the Superpave gyratory compactor. The presented work represents only a preliminary evaluation of the model to extend it to field compaction conditions. A pressure dependent porous material with elastoplastic matrix is assumed to contract under a prescribed compaction pressure induced by the Superpave gyratory compactor to a 6 in. cylindrical sample. Plastic strains are integrated from an incremental elastoplastie constitutive equation by forward difference method. Three model constants, ql, q2 and %, are calibrated to determine measured deflections from the gyratory compactor by means of Levenberg-Marquardt nonlinear parameter estimation algorithm. A statistical correlation between estimated parameters and volumetric components are constructed to evaluate the effects of mixture properties on the estimated model constants. The proposed constitutive model accurately predicts the volume change behavior of mixture specimens undergoing gyratory compaction. Mixture volumetric properties also show correlations with the estimated model constants. 1 Visiting Assistant Professor, Bucknell University, Dept. of Civil and Environmental Eng., Lewisburg, PA 17837, E-mail: mguler@bueknell.edu 2 Professor, University of Wisconsin-Madison, Dept. of Civil and Environmental Eng., Madison, WI 53706, E-mail: bosscher@engr.wisc.edu 3 Professor, University of Wisconsin-Madison, Dept. of Engineering Physics, Madison, WI 53706, E-mail: plesha@engr.wise.edu

Evaluation of strain distribution in geotextiles using image analysis

Localized strains due to production defects, seams and punctured zones significantly affect mechanical performance of geosynthetic materials. Accurate determination of localized strains becomes particularly important for QC/QA evaluation of these materials and plays a critical role in design problems. A number of geosynthetic specimens were tested in an accredited laboratory to determine strain distributions under wide-with tensile loading using image analysis techniques. Specimens were tested using both roller and pneumatic grips to identify the effects of clamping. The tensile load, cross head extensions and image frames at a specified rate were recorded during testing. The testing plan included nonwoven, low strength and high strength woven geotextiles each sewn with flat, butterfly and J-type seam to determine the effect of seaming on strain distributions. Punctured specimens were also used to simulate localized failures in field applications. Average strains were calculated at peak strength values to compare the performance of different geosynthetic specimens. The results indicated that digital image analysis is highly effective in determining the localized strains and their distributions within specimens tested with two different grips. Furthermore, the image-based strains can clearly identify the performance of different seam types and effect of puncture on specimen performance. Introduction Geosynthetics are polymeric materials and have been widely used in various aspects of civil engineering applications and areas involving environmental design problems. In the design process, geosynthetic materials are expected to offer certain mechanical properties that will provide satisfactory performance when exposed to field conditions. Among various mechanical performance tests, the wide-width tensile test is the most common and important one being widely used in design applications (Koerner 1997). Primarily, the stress-strain behavior and strength properties determined from this test are defined at a particular strain or elongation level and strains are usually calculated on average basis for the entire specimen. However, the accurate determination of localized strains and their respective zones becomes particularly critical for design purposes in the presence of seams, punctured zones or possible defects occurred during production. Due to limitations in the current test methodologies, these zones usually remain undetected in the wide-with tensile testing which results in incomplete characterization of mechanical performance which may eventually lead to either an unconservative design or possible catastrophic failures during service conditions. Even though there are various methods used to measure strains, i.e., extensometers, strain gages, laser beam and infrared sensors, they have certain shortcomings to accurately define complete strain fields. Extensometers and strain gages impose additional strains by disrupting individual filaments or yarns and consequently shadowing possible causes of 1 Assistant Professor, Middle East Technical University, Ankara, Turkey, E-mail: gmurat@metu.edu.tr 2 Graduate Research Assistant, and Assistant Professor, respectively, University of Maryland, 1163 Glenn Martin Hall, College Park, Maryland, 20742. E-mail: aydilek@eng.umd.edu

Characterization of Homogeneity of Asphalt Concrete Using 2D Cross-Sectional Images

Asphalt concrete is fabricated from a three-phase mixture consisting of aggregate, asphalt binder, and air voids. Homogeneity of asphalt mixtures affects performance characteristics of asphalt concrete pavements. In this study, homogeneity is determined from 2D vertical section images of gyratory compacted specimens. Because the aggregate structure dominates the performance of asphalt concrete, the mixture homogeneity is determined via statistical distribution of aggregate particles. The cross-sectional images are obtained using a flatbed scanner and then processed to detect various particle shape parameters and locations. Aggregate shape parameters are used for the purpose of determining aggregate gradation curves based on 2D cross-section images of asphalt concrete specimens. An algorithm is developed to detect all the particles in the cross-sections, and then the detected aggregates are redistributed at random orientations and locations to create synthetic images of the same cross-sections. In this way, a large number of sectional images representing the distribution of the same aggregate size fractions are generated. Statistical analyses are performed on four different mixture specimens to determine the range of particle size distributions functions. Results show that the particle distribution of the specimens fall within the range of distribution functions for homogenous mixtures.