Laboratory Resilient Modulus Research Articles

Evaluation of Gradation and Stress State Effects on the Resilient Modulus of Crushed Aggregate Materials

Resilient modulus is a key mechanical parameter for unbound granular base materials. To evaluate gradation effects on the resilient modulus of crushed aggregate materials, the present study conducted laboratory resilient modulus tests on two categories of crushed aggregate materials with seven different gradations. A multi-factor sensitivity analysis was performed on test results and found that the confining pressure and axial stress yield a more significant impact on resilient modulus than the gradation. Different material gradations can yield an average impact of 8%, with a maximum of 21%, and show increased sensitivity with aggregate gradation becoming finer.

Stress-Dependent Behavior of Lightly Stabilized Industrial Waste Subbase Using Falling Weight Deflectometer

Abstract Pavement layers exhibit stress-dependent behavior, characterized by using a laboratory resilient modulus (Mr) test. However, the field behavior of such materials seldom matches with the laboratory because of changes in the state of stress, material matrix, and loading patterns. In this study, the nonlinear behaviors of three innovative fly ash-based lightly stabilized industrial waste mixes that are proposed to replace the granular subbase of flexible pavement are characterized and compared in the laboratory and field for the first time. Nine full-scale pavement test sections were constructed with three varying thicknesses of waste mix subbase layers, namely, fly ash + 5 % lime (FAL), 70 % copper slag + 30 % fly ash (CFA) and 80 % fly ash + 20 % granulated blast furnace slag (FAG). Repeated load triaxial tests on lab samples and multiload falling weight deflectometer (FWD) tests (40 kN, 55 kN and 70 kN) on test sections conducted for three years post-construction were used to extract the nonlinear behavior of Mr and the FWD backcalculated modulus (EFWD) of subbase layers. Effects of curing and traffic damage on the nonlinear parameters of EFWD were investigated. Stress-dependent conversion factors based on two different constitutive models were established to convert Mr to EFWD at different points of the subbase service life. Stabilized waste mixes exhibited stress hardening with increasing bulk and deviatoric stresses both in the field and laboratory. Curing increased EFWD and reduced the effect of stresses on the EFWD. In contrast, traffic damage imparted the opposite effect, as the stabilized waste mixes transformed into a cracked and blocky mass. The results of this study will allow practitioners to predict the field performance of waste mix subbase with great accuracy, resulting in a reliable design and possible cost savings.

Selection of suitable backcalculation technique and prediction of laboratory resilient modulus from NDT devices

ABSTRACT This study aims to analyse the backcalculated cohesive subgrade moduli using various backcalculation approaches. A series of in situ and laboratory investigations have been carried out on 190 test locations from 30 pavement sections of cohesive soils using Falling Weight Deflectometer (FWD), Light Weight Deflectometer (LWD), and Repeated Load Triaxial to determine backcalculated resilient moduli (MR_back), composite resilient moduli (MR_comp), and laboratory resilient modulus (MR_lab). The comparative analysis was performed for MR_back by LWD (MR_back_LWD), MR_comp by LWD on subgrade (MR_comp_LWD), and MR_back by FWD (MR_back_FWD) with MR_lab values to assess the level of agreement. MR_back_FWD and MR_back_LWD values of different soils by using Artificial Neural Network and Support Vector Machine techniques have shown the mean percentage variation (1.16–59.63%), correlation in terms of R2 value (0.628–0.824), and RMSE value (0.51–20.49%) with MR_lab values. In contrast, MR_comp_LWD values have shown good agreement with MR_lab values among MR_back_LWD and MR_comp_LWD. This study also suggested adjustment factors (0.308–0.974) for predicting MR_lab values from MR_back_FWD and MR_back_LWD for cohesive soils. Thus, this study recommends an appropriate backcalculation technique and suggests adjustment factors to the cohesive type of soils for realistic prediction of resilient characteristics of subgrade.

A Machine-Learning Approach for Extracting Modulus of Compacted Unbound Aggregate Base and Subgrade Materials Using Intelligent Compaction Technology

This study presents a rigorous approach for the extraction of the modulus of soil and unbound aggregate base materials for quality management using intelligent compaction (IC) technology. The proposed approach makes use of machine-learning methods in tandem with IC technology and modulus-based spot testing as a local calibration process to estimate the mechanical properties of compacted geomaterials. A calibrated three-dimensional finite element (FE) model that simulates the proof-mapping process of compacted geomaterials was used to develop a comprehensive database of responses of a wide range of single and two-layered geosystems. The database was then used to develop different inverse solvers using artificial neural networks for the estimation of the modulus from the characteristics of the roller and information about the geomaterials. Several instrumented test sites were used for the evaluation and validation of the inverse solvers. The proposed approach was found promising for the extraction of the modulus of compacted geomaterials using IC. The accuracy of the inverse solvers is enhanced if a local calibration process is incorporated as part of a quality management program that includes the use of in situ measurements using modulus-based test devices and laboratory resilient modulus testing. Moreover, compaction uniformity plays a key role in the retrieval of the modulus of geomaterials with certainty. The proposed approach fuses artificial intelligence with mechanistic solutions to position IC as a technology that is well suited for the quality management of compacted materials.

Considerations for laboratory resilient modulus testing of unbound pavement base materials

This paper explains equipment related considerations on differences between the lab and field conditions that can lead to variations in resilient modulus (Mr) values of unbound materials as determined in accordance with AASHTO T307 standard. Three different granular materials and an elastic polyurethane (control) sample were tested using commercially available laboratory test equipment. A field test bed was also constructed to measure vehicle (Class 3) induced loading conditions at the bottom of an unbound granular layer underlying new hot-mix asphalt pavement to determine stress pulse duration as a function of vehicle speed. Various interpretation issues were identified within the framework of the testing methods and equipment including: (1) insufficient laboratory sensor sampling rate (per standard); (2) the laboratory specified 0.1 s load-pulse duration and haversine shape are not matching the field stress pulse duration and shape; (3) the need for careful tuning of the load system gain settings; (4) the number of LVDTs used in the vertical strain calculation; (5) limiting quality control and quality assurance to deformation ratio values in the preconditioning sequence; and (6) limiting the load step calculations to the last 5 of 100 load cycles. The goal of this paper is to provide equipment users and specification developers with user knowledge concerning laboratory resilient modulus determination.

Resilient modulus prediction of soft low-plasticity Piedmont residual soil using dynamic cone penetrometer

Dynamic cone penetrometer (DCP) has been used for decades to estimate the shear strength and stiffness properties of the subgrade soils. There are several empirical correlations in the literature to predict the resilient modulus values at only a specific stress state from DCP data, corresponding to the predefined thicknesses of pavement layers (a 50 mm asphalt wearing course, a 100 mm asphalt binder course and a 200 mm aggregate base course). In this study, field-measured DCP data were utilized to estimate the resilient modulus of low-plasticity subgrade Piedmont residual soil. Piedmont residual soils are in-place weathered soils from igneous and metamorphic rocks, as opposed to transported or compacted soils. Hence the existing empirical correlations might not be applicable for these soils. An experimental program was conducted incorporating field DCP and laboratory resilient modulus tests on “undisturbed” soil specimens. The DCP tests were carried out at various locations in four test sections to evaluate subgrade stiffness variation laterally and with depth. Laboratory resilient modulus test results were analyzed in the context of the mechanistic-empirical pavement design guide (MEPDG) recommended universal constitutive model. A new approach for predicting the resilient modulus from DCP by estimating MEPDG constitutive model coefficients (k1, k2 and k3) was developed through statistical analyses. The new model is capable of not only taking into account the in situ soil condition on the basis of field measurements, but also representing the resilient modulus at any stress state which addresses a limitation with existing empirical DCP models and its applicability for a specific case. Validation of the model is demonstrated by using data that were not used for model development, as well as data reported in the literature.

Comparative mechanistic-empirical analysis for design of alternative cold recycled asphalt technologies with conventional pavement

It is essential to carry out a detailed study on the mechanical behaviour of materials so as to evaluate the distress parameters of flexible pavements. This study can be performed through finite element simulations like ANSYS, KENPAVE, IITPAVE, etc. However, this study was mainly carried out using the pavement designing tool ANSYS to study and compare the mechanical behaviour of a typical conventional pavement with hot bituminous surfacing, with cold recycled emulsified and foamed base pavements with fresh overlay. Further, the results obtained from this ANSYS were compared with other simulations like KENPAVE and IITPAVE. Optimum design thickness of the pavement was determined based upon the predicted tensile and compressive strain from laboratory resilient modulus values. The analytical results showed that, linear elastic analysis in both KENPAVE and IITPAVE match well, but a slight lesser tensile strain and vertical displacement values are observed in ANSYS. Also, the study was extended towards the comparative cost benefit analysis of both recycled and conventional mixes. Through this study, it was observed that recycled mix is economical when compared to conventional mixes.

Investigating Stress Dependency of Unbound Layers Using Falling-Weight Deflectometer and Resilient Modulus Tests

Unbound layer materials, such as base and subgrade, exhibit stress-hardening and/or -softening, which can be determined from their resilient modulus values. However, unavailability of required amount of material and compaction variability between field and laboratory necessitate a need to predict stress dependency of the unbound layers by field tests. This study evaluates stress dependency of unbound layers using a falling-weight deflectometer (FWD) test. The FWD tests were conducted at multi-load levels on several pavement sections. The FWD back-calculated layer moduli are then used to determine bulk and octahedral shear stresses using the layered elastic analysis technique. Next, the regression analysis is performed to interpret the stress-dependent parameters, i.e., regression coefficients of pavement ME's resilient modulus model of nonlinear unbound material. It is observed that stress-hardening is dominant in the case of the base layer, whereas subgrade exhibits both stress-hardening and -softening. This was also confirmed by laboratory resilient modulus tests on both base and subgrade materials in this study. Therefore, it is recommended not to ignore either stress-hardening or -softening during nonlinear modeling of the unbound layers. In addition, in this study, empirical relationships are developed to perform inter-conversion of laboratory resilient and FWD back-calculated modulus incorporating the field state of stresses in base and subgrade.

Systematic back-calculation protocol and prediction of resilient modulus for MEPDG

A research focusing on the characterisation of representative local material properties was conducted to facilitate the full implementation of the Mechanistic-Empirical Pavement Design Guide for roadway designs in Wyoming. As part of the test program, falling weight deflectometer deflection data were collected from 25 test sites in Wyoming for back-calculation of subgrade resilient modulus. Also, subgrade materials from these test sites were sampled for laboratory resilient modulus measurement in accordance with the AASHTO T 307. The back-calculation is a user-dependent procedure and produces a non-unique resilient modulus estimation. To alleviate this limitation, this paper focuses on the recent development of a systematic back-calculation protocol for subgrade resilient modulus using MODCOMP6 software. The protocol is intended for use on a flexible pavement with a crushed base. The proposed procedure discusses pre-analysis checks, seed modulus adjustment, pavement structure adjustment and program termination criteria. A correlation study was conducted to correct back-calculated resilient modulus to laboratory-equivalent values. The results conclude that a non-zero intercept linear regression model provides a better correlation than the widely used zero intercept linear regression model. Furthermore, better correlations are achieved when the back-calculated resilient modulus of a lower subgrade layer and resilient modulus measured at higher laboratory test sequences Nos. 11 to 15 are considered. The non-zero model based on Mr test sequence No. 14 and lower subgrade layer yields the best correlation. For the zero model, a C-factor of 0.645 based on Mr test sequence No. 15 and lower subgrade layer yields the best correlation.

Modeling of unsaturated granular materials in flexible pavements

The unsaturated granular material (UGM) is found to exhibit the moisture-sensitive and stress-dependent nonlinear cross-anisotropic behaviour in flexible pavements. This paper aims at developing a finite element (FE) model for pavement structure, which takes into account this behaviour of UGM. First, the Lytton model is employed to characterize the moisture-sensitive and stress-dependent behaviour of UGM, which incorporated a matric suction term to the existing stress-dependent constitutive model. The Lytton model is validated by the laboratory resilient modulus tests on the selected UGMs at different moisture contents. Second, the nonlinear cross-anisotropic constitutive equation of UGM is derived from the generalized Hooke’s Law. The coefficients of the constitutive model are determined by the rapid triaxial test. Third, a User-Defined Material (UMAT) subroutine is developed to characterize this constitutive behaviour in the FE software ABAQUS. The UMAT subroutine adopts the secant stiffness approach with multiple damping factors. The UMAT subroutine is then implemented in the FE model of flexible pavement structures. The FE simulation results indicate the nonlinear cross-anisotropic model predicts greater pavement responses than the isotropic model. When the UGM is suction sensitive, it is found that the moisture content of UGM significantly affects the moduli distribution of base layer and the critical strains (i.e., tensile strain at the bottom of asphalt concrete, and compressive strains in base and subgrade layers) of pavement structures.

Field and Laboratory Determination of Subgrade Resilient Modulus and its Application in Pavement Design

This paper presents a comparison study of the experimental results from the falling weight deflectometer (FWD) test and laboratory resilient modulus test on granular subgrade materials and its application in flexible pavement design. Field and laboratory testing programs were conducted to develop a practical methodology for estimating resilient modulus (Mr) values of subgrade soils for use in the design of pavement structures. Soil characterization database was established for lab testing. A multiple regression model can be used to predict Mr value using several factors including soil properties, soil type and state of stresses for three popular American Association of State Highway and Transportation Officials (AASHTO) soil types (A-4, A-6, and A-7-6) in Indiana, and these prediction models developed were verified compared with laboratory Mr tests with high R2 value. In situ Mr seasonal variation based on abundant FWD test data in five field testing sites spread in Indiana was conducted in order to find the correlation between resilient modulus, temperature, and precipitation for the period from 2006 to 2012. The proposed method can accurately predict subgrade Mr of lab testing. However results from lab testing are significantly lower than recommended range by mechanistic-empirical pavement design guide (MEPDG) and backcalculation one using an adjust factor of 3. The design examples showed that the seasonal variation of temperature and precipitation as well as traffic can affect the design thickness by as much as 15 to 20 % in general. The findings of this study are expected to be helpful in the implementation of the pavement design in Indiana and elsewhere.

Method to determine height and water content of highway subgrade filled with fine grained soil materials

In this paper, a new method of determining height and water content of subgrade filled with fine grained soil materials is proposed in view of deformation control. Firstly, a fine grained clay soil is considered as reference material, and the laboratory resilient modulus experiments are conducted to derive the relationship among the compactness, water content and resilient modulus of the samples. Then, the allowable deformation value of the subgrade filled with fine grained soil is obtained based on the dynamic response solutions for subgrade and the condition of deformation compatibility between pavement and subgrade. Moreover, by combing the experimental results and the allowable deformation value of the subgrade, a reasonable method is presented to determine the critical height, compactness and the water content of highway subgrade filled with such materials. Finally, a typical road structure is introduced to derive numerical example and taken for illustration using this method.

Estimating the coefficient of at-rest earth pressure in granular pavement layers

Compaction of pavement layers composed of unbound granular materials increases the at-rest earth pressure coefficients. These coefficients influence the stress-state in the material and are therefore important for modeling pavement behavior; they may also serve as indicators, alongside densities, of compaction quality. Given the inability of geotechnical tools to directly measure the coefficient of at-rest earth pressure in granular pavement layers the paper offers an estimation approach that is computational in nature. The scheme is based on solving a multi-objective inverse problem and requires a pavement instrumented with implanted sensors, preferably monitoring a wide variety of response types. It also requires laboratory resilient modulus information of granular specimens compacted to in situ densities. In order to demonstrate the computations, a simplified version of the method is applied to an airport pavement system tested in an accelerated loading facility. Post-construction at-rest earth pressure coefficients of the base and subbase layers are quantified and evaluated for reasonableness. It is concluded that the approach, even in its simplified form, is capable of producing realistic estimates.

Evaluation of Resilient Modulus of Subgrade and Base Materials in Indiana and Its Implementation in MEPDG

In order to implement MEPDG hierarchical inputs for unbound and subgrade soil, a database containing subgrade M R, index properties, standard proctor, and laboratory M R for 140 undisturbed roadbed soil samples from six different districts in Indiana was created. The M R data were categorized in accordance with the AASHTO soil classifications and divided into several groups. Based on each group, this study develops statistical analysis and evaluation datasets to validate these models. Stress-based regression models were evaluated using a statistical tool (analysis of variance (ANOVA)) and Z-test, and pertinent material constants (k 1, k 2 and k 3) were determined for different soil types. The reasonably good correlations of material constants along with M R with routine soil properties were established. Furthermore, FWD tests were conducted on several Indiana highways in different seasons, and laboratory resilient modulus tests were performed on the subgrade soils that were collected from the falling weight deflectometer (FWD) test sites. A comparison was made of the resilient moduli obtained from the laboratory resilient modulus tests with those from the FWD tests. Correlations between the laboratory resilient modulus and the FWD modulus were developed and are discussed in this paper.

Comparison of resilient modulus values for Florida flexible mechanistic-empirical pavement design

The primary objective of this study is to recommend correction factors (CFs) for determining equivalent laboratory resilient modulus (M R) values, given the corresponding unbound granular layer moduli from in situ pavement testing to support the flexible pavement design based on mechanistic-empirical pavement design guide (M-EPDG). To evaluate CFs for limerock base, mechanically stabilised subgrade, and embankment materials used on Florida flexible pavements, the authors conducted field and laboratory test programmes along with reviewing available data. The authors compared field modulus determined from backcalculation of falling weight deflectometer (FWD) data and laboratory determined modulus that considers in situ moisture content condition based on soil–water characteristic curve. To the end, a series of charts were established showing correlation between FWD modulus and CF for each material for the purpose of determining equivalent laboratory M R with the given FWD backcalculated modulus to provide input for M-EPDG-based pavement design.

Feasibility Study on Building-Derived Concrete Debris for Use in Highway Construction

Abstract The current American Association of State Highway and Transportation Officials standard on crushed concrete in base applications (M 319-02) allows up to 5 % brick by mass, and more with the approval of the engineer; however, in some regions the brick content may be greater than 10 %. More than 41 states allow the use of crushed concrete in highway applications, but only a handful allow the use of building derived concrete (BDC) or mixed stream crushed concrete. Barriers to increasing the appropriate use of BDC in highway applications include a lack of data comparing BDC properties and performance to natural aggregates, as well as data that pavement engineers can use for design. This research has focused on characterizing BDC that was screened to meet New Hampshire Department of Transportation specifications. The gradation, optimum water content, unit weight, and resilient modulus were measured for the BDC and for the control materials, which were a crushed stone and a sand. The resilient modulus was measured using both a laboratory triaxial cell, and a light falling weight deflectometer (LWD) in a test pit. The resilient modulus of the BDC exceeded that of the control materials as measured in the laboratory and using the LWD. In addition, the laboratory resilient modulus showed good correlation with the LWD stiffness. These results suggest that BDC would perform as well as natural aggregates in base course applications.

In situ mechanistic characterisations of granular pavement foundation layers

This paper presents experimental test results comparing in situ point test measurements using falling weight deflectometer (FWD), light weight deflectometer (LWD), dynamic cone penetrometer and static piezocone, and near continuous roller-integrated continuous compaction control measurements on a granular pavement foundation embankment. Piezoelectric earth pressure cells buried in the pavement foundation layers were used to compare vertical and horizontal stresses during vibratory roller compaction, and LWD and FWD impulse loading. The resulting total stress paths are compared with standard laboratory resilient modulus stress paths. Insights into differences in measurement influence depths and comparison of vertical stress profiles for the different measurements are discussed and relationships between the various measurements in terms of elastic modulus are presented. Some practical considerations for interpreting the relationships and implementation are discussed.

Developing Correlation Relationship between Modulus of Subgrade Reaction and Resilient Modulus for Florida Subgrade Soils

The resilient modulus of pavement subgrade is an essential parameter for mechanistically based pavement design procedures; the modulus of subgrade reaction (k) is used as a primary parameter for rigid pavement design. The AASHTO pavement design guide (1986, 1993) suggested a theoretical relationship between modulus of subgrade reaction and resilient modulus of subgrade based on the assumption that the subgrade material is linear elastic. This paper presents an experimental study to evaluate the load–deformation and resilient modulus characteristics of the granular subgrade soils with the use of field and laboratory tests. An extensive field static plate bearing load testing program was conducted to evaluate the in situ bearing characteristics of typical Florida pavement subgrade soils. A full-scale laboratory evaluation of the subgrade performance was conducted in a test-pit facility that simulated the actual field conditions. A laboratory triaxial test was performed to evaluate the resilient modulus characteristics of the subgrade materials. Comparative studies were conducted to evaluate the resilient modulus from laboratory triaxial tests and field experimental studies. Correlation relationships were developed between the measured resilient modulus in the laboratory and the resilient modulus measured with the use of a test-pit facility and between the subgrade soil resilient modulus and the modulus of subgrade reaction. The calibrated relationship based on the experimental studies was close to the AASHTO theoretical relationship. The calibrated relationship could be used in the Florida pavement design guide to obtain realistic subgrade resilient modulus values from laboratory resilient modulus measurements.

Comparison of Stress States and Paths

Vibratory roller-based measurement of soil stiffness during intelligent compaction and continuous compaction control can be used for performance-based quality assurance of unbound materials. To realize this potential, the relationship between the roller-measured soil stiffness and the soil modulus, particularly resilient modulus, must be understood. The in situ stress states and paths experienced by soil beneath a vibratory roller were compared with stress states and paths during laboratory resilient modulus testing. Observed stress fields within the 1-m depth of influence varied considerably for both vertically homogeneous embankment soil and layered base over subgrade conditions. During low excitation force vibration, roller-induced levels of deviator stress were notably greater than those used during laboratory resilient modulus testing, whereas levels of mean stress were less. Predicted modulus variation with depth was strongly influenced by modulus function parameters. With typical granular soil parameters, modulus was found to be constant with depth for the embankment conditions. With modulus parameters of more fine-grained behavior, modulus increased considerably with depth.

Neural network model for resilient modulus of emulsified asphalt mixtures

This paper explores the potential use of neural networks (NNs) in the field of emulsified asphalt mixtures. A neural network model is developed for predicting, with sufficient approximation, relationship between the factors affecting resilient modulus (inputs: curing time, cement addition level, and residual asphalt content) and the resilient modulus (output) of emulsified asphalt mixture. A backpropagation neural network of three layers is employed. First resilient modulus data are obtained by conducting laboratory resilient modulus tests on emulsified asphalt samples, and then the results are used to train the neural network. The effectiveness of different neural network configurations is investigated. Effect of parameters such as curing time, cement addition level and residual asphalt content that influence the resilient modulus is also explored. Results indicate that NN predicts the resilient modulus with high accuracy. It is also demonstrated that NN is an excellent method that can reduce the time consumed and can be used as an important tool in evaluating the factors affecting resilient modulus of emulsified asphalt mixture at the design stage.