Mehran Mazari

How to Estimate Resilient Modulus for Unbound Aggregate Materials: A Theoretical Explanation of an Empirical Formula

To ensure the quality of pavement, it is important to make sure that the resilient moduli—that describe the stiffness of all the pavement layers—exceed a certain threshold. From the mechanical viewpoint, pavement is a non-linear medium. Several empirical formulas have been proposed to describe this non-linearity. In this paper, we describe a theoretical explanation for the most accurate of these empirical formulas.

Simulation of lightweight deflectometer measurements considering nonlinear behavior of geomaterials

Lightweight deflectometers (LWDs) are being used more often for modulus-based quality control of earthwork. One of the practical concerns about implementation of LWDs is that the equation used to estimate the LWD modulus is based on elastic half-space theory and does not account for the nonlinear behavior of soil and soil–impact plate interaction. The finite element method can be used to study the effects of nonlinear behaviors of geomaterials and the soil–plate interaction on the measured deflections. This study provides a means for accounting for the impact of these parameters on the measured responses and the depths of influence. A dynamic finite element model that considers the nonlinear behavior of geomaterials was developed to simulate the LWD on a pavement structure. A comprehensive range of single-layer and two-layer systems with a wide range of properties and thicknesses was considered. Transfer functions were developed to adjust the surface deformations and moduli from the responses obtained from a simple layered elastic static model. The study provides practical relationships that minimize the additional effort in implementing time-consuming dynamic finite element methods. The relationships proposed in this study can be used to estimate more representative target LWD modulus values.

Effects of Moisture Variation on Resilient and Seismic Moduli of Unbound Fine-Grained Materials

Moisture variation in a pavement structure due to the environment has a large impact on the moduli of unbounded layers. The moisture variation can affect the performance of the pavement as documented in a number of laboratory and field studies. As such, it is desirable to account for this behavior in the design or evaluation of a pavement. In this study, the effects of moisture variation and compaction effort were investigated through a series of well-controlled laboratory tests on different fine-grained geomaterials. Different sources of fine-grained materials were selected to prepare the laboratory specimens for both resilient and seismic modulus tests. The existing modulus-moisture models were evaluated during the moisture conditioning cycles for the specimens prepared and compacted at different moisture levels. Furthermore, the normalized difference of moisture content at the time of compaction and optimum moisture content was used to explain the trends. A model is proposed to improve the prediction of changes in resilient modulus based upon moisture content. The proposed model showed reasonable agreement with the experimental data.

Correlating the resilient modulus and seismic modulus of subgrade materials incorporating moisture and density variations

Resilient modulus tests are commonly used to determine the representative modulus of geomaterials as well as to establish their nonlinear behaviors. Such tests are complex and time consuming and therefore only performed during high priority construction projects. In comparison, seismic modulus tests are rapid, nondestructive and provide low-strain linear elastic moduli. Although, seismic moduli are measured at lower strains than those imparted to pavements by vehicular traffic, it is desirable to relate the moduli from these two tests since the seismic modulus tests lend themselves to a convenient tool for quality management of compacted geomaterials. Several geomaterials were comprehensively tested with the resilient modulus and seismic modulus devices at different moisture contents. The laboratory seismic moduli were several times greater than the corresponding representative resilient moduli. However, a reasonably well-correlated relationship was observed between them. This relationship was further improved and strengthened by incorporating moisture-density parameters of the materials.

Mechanistic Estimation of Lightweight Deflectometer Target Field Modulus for Construction Quality Control

The lightweight deflectometer (LWD) is an emerging device for evaluating the quality of compacted layers. Establishing the proper field target modulus for the LWD is crucial for judging the quality of the compacted unbound layers. A rigorous numerical approach to determine the project-specific field target values for a LWD device during the pavement design process is presented in this study. The input parameters to the model include the thickness of the layers, as well as the nonlinear stiffness parameters of each layer estimated from the resilient modulus tests. Simple relationships are proposed to estimate the target modulus when the earthwork can be approximated as a single layer. A parametric study was performed to quantify the impact of the input parameters on the estimated target modulus. The applied load and the plate diameter of the LWD along with some of the nonlinear soil parameters significantly affect the target modulus. The processes of the development and validation of these models are presented in this paper. Furthermore, the impact of moisture variation on estimated target LWD modulus is discussed.

Evaluating Influence Depth of Light Weight Deflectometer through Finite Element Modeling

The light-weight deflectometer (LWD), which is the portable version of the common falling weight deflectometer (FWD), has been gaining popularity due to the ease of use and familiarity of pavement community to the deflection-based concepts. LWD imparts a pulse load to the surface of a soil layer through a circular plate to measure the soil surface deflection and to estimate the effective modulus of the underlying system. An extensive finite element modeling was performed to study the mechanism of two common types of LWDs during quality control of unbound pavement materials. The performance of the LWDs was evaluated under various loading conditions, different plate sizes and a diverse range of geomaterial properties. The influence depth was studied using both stress and strain criteria. The nonlinear constitutive model parameters seem to have significant influence on the measured influence depth of both devices. However, different functional properties of each device found to be the source of variations in the results.

Impact of Geospatial Classification Method on Interpretation of Intelligent Compaction Data

Intelligent compaction is an emerging technology in the management of pavement layers, more specifically, of unbound geomaterial layers. Different types of intelligent compaction measurement values (ICMVs) are available on the basis of the configuration of the roller, vibration mechanism, and data collection and reduction algorithms. The spatial distribution of the estimated ICMVs is usually displayed as a color-coded map, with the ICMVs categorized into a number of classes with specific color codes. The number of classes, as well as the values of the breaks between classes, significantly affect the perception of compaction quality during the quality management process. In this study, three sets of ICMV data collected as a part of a field investigation were subjected to geostatistical analyses to evaluate different classification scenarios and their impact on the interpretation of the data. The classification techniques were evaluated on the basis of the information theory concept of minimizing the information loss ratio. The effect of the ICMV distribution on the selection of the classification method was also studied. An optimization technique was developed to find the optimal class breaks that minimize the information loss ratio. The optimization algorithm returned the best results, followed by the natural breaks and quantile methods, which are suited to the skewness of the ICMV distribution. The identification of less-stiff areas by using the methods presented will assist highway agencies to improve process control approaches and further evaluate construction quality criteria. Although the concepts discussed can apply to any compacted geomaterial layer, the conclusions apply to the type of compacted soil in this particular test section.

Compaction Quality Monitoring of Lime-Stabilized Clayey Subgrade Using Intelligent Compaction Technology

This study presents the evaluation of the compaction process on a lime-stabilized clayey subgrade soil using the intelligent compaction (IC) technology. Two test beds with similar clayey subgrade soil were constructed with and without in-situ lime stabilization. These test beds were evaluated using several in situ nondestructive testing devices and an IC-equipped vibratory roller. The results from the study showed significant spatial variability in the in-situ test results and the roller measurements. In comparison to the untreated subgrade, the lime-stabilized test sections demonstrated a reduction in the variability of the roller measurements. The roller measurements on the stabilized section were influenced by the testing time and the underlying support conditions. The laboratory results and the field measurements using the roller and in-situ devices pointed to the improvement in the soil properties after stabilization. The moduli of the stabilized subgrade soil increased by almost two times. Statistical analyses demonstrated the influence of the underlying support condition, the moisture content and the lift thickness variations on the roller measurements.

Evaluation and Harmonization of Intelligent Compaction Systems

Intelligent compaction (IC) is an emerging technology for quality management of compacted pavement layers. Data collected by a vibration sensor and translated to a stiffness-based parameter is usually called the IC measurement value (ICMV). The ICMVs are coordinated with the global positioning system (GPS) data to assess the geospatial distribution of compacted layer properties. The IC rollers can be equipped with the original equipment manufacturer (OEM) systems that are provided by the vendors. However, with the recent introduction of the after-market or retrofit IC kits, it is possible to collect IC data with most regular vibratory rollers. Even though the use of the IC retrofit kits has been gaining popularity, its performance during the field operation has not been documented extensively. In this study, two dynamic vibratory rollers equipped with the OEM IC systems were employed along a test section. A retrofit kit was also installed on one of the rollers to collect the IC data during the same field operation simultaneously with the OEM system. The geospatial distribution of the ICMVs between the two types of systems for the most part was comparable. However, the magnitudes of the ICMVs among rollers and IC systems were somewhat different. These differences in the ICMVs were attributed to the differences in the vibration sensors and their installation as well as the data reduction algorithms among different systems. The reliability of the results from the OEM systems and retrofit kits seemed to be dependent on the proper installation of the vibration sensors as well as the accurate calibration of the GPS unit prior to the field data collection. A validation system and a standard protocol are needed to harmonize the performance of the IC rollers.

Modeling the Effect of Filler Materials on Performance of Hot Mix Asphalt Using Genetic Programming

This study aims to address the effect of filler materials (passing no. 200 sieve) on performance of hot mix asphalt mixtures. The Marshall mix design procedure was followed to prepare laboratory specimens using various types of filler materials to determine the optimum asphalt content. Furthermore, three different gradations with various amount of filler contents were selected to estimate the performance of asphalt mixture in laboratory conditions in terms of Marshall stability and flow. It was observed that more filler content increases the plasticity of the mix and thus the permanent deformation. Moreover, adding the hydrated lime as filler improves the functional properties of the asphalt mixtures. A nonlinear genetic programming algorithm was developed to predict and formulize the Marshall stability results using material characteristics. The prediction power of the employed soft computing technique is deemed satisfactory as compared to the experimental results.