Laboratory Repeated Load Triaxial Tests Research Articles

Prediction of resilient modulus and critical dynamic stress of recycled aggregates: Experimental study and machine learning methods

This paper aimed to investigate the feasibility of partially or completely replacing natural aggregates with recycled aggregates from construction and demolition wastes for low-carbon-emission use as coarse-grained embankment fill materials. The laboratory specimens were prepared by blending natural and recycled aggregates at varying proportions, and a series of laboratory repeated load triaxial compression tests were carried out to study the effects of material index properties and dynamic stress states on the resilient modulus and permanent strain characteristics. Based on the experimental results and by considering the main influencing parameters of the resilient modulus and permanent deformation, an artificial neural network (ANN) prediction model with optimal architecture was developed and optimized by the particle swarm optimization (PSO) algorithm, and its performance and accuracy were verified by supplementary analyses. A shakedown state classification method was proposed based on the unsupervised clustering algorithm, and a prediction model of critical dynamic stress was established based on the machine learning (ML) method and the shakedown state classification results. The research results indicate that the stress state has a greater influence on the resilient modulus and permanent deformation characteristics than other factors, and the shear stress ratio has a significant effect on the shakedown state. The resilient modulus and critical dynamic stress of such specimens vary linearly with confining pressure. The improved PSO-ANN prediction model exhibits high prediction accuracy and robustness, superior to several other commonly used ML regression prediction algorithms. The resilient modulus and critical dynamic stress prediction methods based on ML algorithms can provide technical guidance and theoretical basis for the design and in-service maintenance of similar unbound granular materials.

Using Repeated Light-Weight Deflectometer Test Data to Predict Flexible Pavement Responses Based on the Mechanistic–Empirical Design Method

This study investigated the potential of lightweight deflectometer (LWD) data in predicting layer moduli and response measurements within the Mechanistic–Empirical Pavement Design Guide. To achieve this goal, field repeated LWD tests and laboratory repeated load triaxial tests were carried out on granular base material compacted at 3% and 6% water content, sandy subgrade soil compacted at 3%, 4% and 9% water content and silty sand subgrade soil compacted at 8% and 10% water content. The results revealed that substituting traditional repeated load triaxial (RLT) data with LWD data for predicting these parameters was notably effective for cohesionless materials, especially for unbound granular materials (UGMs) compacted at optimum water content. The accuracy and reliability of predictions were remarkably high, showcasing the potential of LWD to enhance efficiency and precision in pavement design within this context. Conversely, for cohesive road materials, the study emphasized the importance of considering specific material properties and water content when integrating LWD into the Mechanistic–Empirical Pavement Design Guide. The distinctive characteristics and behaviors of cohesive materials necessitate a nuanced approach. This understanding is critical to ensuring the accuracy and reliability of pavement design and assessment across diverse conditions. In summary, the study presents a promising avenue for utilizing LWD data in cohesionless road materials, offering potential cost and time-saving advantages. Additionally, it underscores the necessity of tailored approaches when considering material properties and moisture content for cohesive materials, thereby advancing the field of pavement engineering by providing insights for improved practices and adaptable frameworks.

Evaluation of Airport Pavement Base Layer Stiffness Characteristics via Embedded Field Sensors

Real-time stiffness monitoring of unbound aggregate layers using embedded field sensors is crucial for advanced airport pavement design and management. This paper describes research findings on monitoring base layer stiffness characteristics for airport pavements using an embedded bender element (BE) field sensor, inductive coil sensors, and pressure cells. A full-scale pavement test section was constructed at the Federal Aviation Administration (FAA)’s National Airport Pavement Test Facility (NAPTF). A BE field sensor, inductive coil sensor pairs, and pressure cells were installed in the unbound aggregate base to evaluate the layer stiffness, applied load stress, and deformation characteristics. A triple dual tandem gear loading module applied 58,000 lb per wheel to the tested section with a wander pattern consisting of 66 passes arranged in nine lateral wander positions. Dynamic responses of coil sensors and pressure cells were collected during the traffic test, whereas BE signals were collected after completing each wander pattern. Laboratory repeated load triaxial tests with BE instrumentation were also conducted to establish a correlation for converting BE field sensor readings to layer modulus properties. The in situ modulus characteristics of the aggregate base layer were evaluated during full-scale testing using two methods: shear wave velocities from a BE field sensor, and strain and stress measurements from coil sensors and pressure cells. The moduli estimated using both approaches fell into typical ranges of crushed aggregate bases and were highly comparable. The moduli from the dynamic sensor measurements clearly showed the effect of vehicle wander on aggregate base layer measured responses.

Development of Artificial-Neural-Network-Based Permanent Deformation Prediction Model of Unbound Granular Materials Subjected to Moving Wheel Loading.

The majority of existing regression models for unbound granular materials (UGMs) consider only the effects of the number of loading cycles and stress levels on the permanent deformation characteristics and are thus unable to account for the complexity of plastic deformation accumulation behavior influenced by other factors, such as dry density, moisture content and gradation. In this study, research efforts were made to develop artificial-neural-network (ANN)-based prediction models for the permanent deformation of UGMs. A series of laboratory repeated load triaxial tests were conducted on UGM specimens with varying gradations to simulate realistic stress paths exerted by moving wheel loads and study permanent deformation characteristics. On the basis of the laboratory testing database, the ANN prediction models were established. Parametric sensitivity analyses were then performed to evaluate and rank the relative importance of each factor on permanent deformation behavior. The results indicated that the developed ANN prediction model is more accurate and reliable as compared to previously published regression models. The two major factors influencing the magnitude of accumulated plastic deformation of UGMs are the shear stress ratio (SSR) and the number of loading cycles, of which the calculated influence coefficients are 38% and 41%, respectively, while the degree of influence of gradation is twice that of the confining pressure.

Resilient Modulus Behavior and Prediction Models of Unbound Permeable Aggregate Base Materials Derived from Tunneling Rock Wastes.

Tunneling rock wastes (TRWs), which are often open- or gap-graded in nature, have been increasingly recycled and reused for sustainable construction of unbound permeable aggregate base (UPAB) courses with high porosity and desired drainability. However, there is still a lack of sufficient understanding of long-term mechanical stability of such TRW materials subjected to repeated applications of moving wheel loads. This paper aimed to characterize and predict resilient modulus (Mr) behavior of the TRW materials used in unbound permeable aggregate base applications. To achieve this goal, five different UPAB gradations were designed based on the gravel-to-sand ratio (G/S) concept. In order to study their Mr behavior, the laboratory repeated load triaxial tests were conducted under different combinations of confining pressure and deviator stress as controlled by the levels of the shear stress ratio (SSR). The prediction accuracy of fourteen classical Mr prediction models was comparatively analyzed, from which the improved Mr prediction model incorporating gradation and stress variables was proposed for TRW-derived UPAB materials and further validated by external database accordingly. The results show that under the same G/S value and confining pressure level, the higher the SSR is, the greater the final Mr values are, and the more significant the effect of G/S on Mr is. Under the same SSR level, the increase of confining pressure alleviates the effect of G/S on Mr. There appears to exist an optimal G/S value of around 1.6–1.8 that yields the best Mr behavior of the TRW-derived UPAB materials studied. The improved Mr prediction model was verified extensively to be universally applicable. It can potentially contribute to balancing long-term mechanical stability and drainability of TRW-derived UPAB materials through gradation optimization. The findings could provide a theoretical basis and technical reference for cost-effective and sustainable applications of UPAB materials derived from TRWs.

Resilient Modulus—Physical Parameters Relationship of Improved Red Clay by Dynamic Tri-Axial Test

As one of the important parameters used in the analysis and design of subgrade, resilient modulus is directly related to the safety, economic and life time of subgrade structure. In this paper, the characteristics of resilient modulus of improved red clay at different additive content were studied through conducting laboratory repeated load tri-axial tests. The influence of stress state, moisture content, compactness, additive types, and content on resilient modulus were analyzed. In addition, the regression analysis of resilient modulus, was carried out referencing three existing prediction models. The results showed that the Andrei model can better fit the resilient modulus of red clay and have a higher determination coefficient. However, the Andrei model and other existing prediction models, reflect only the influence of stress state on resilient modulus, without considering the influence of moisture content, compactness and additive content. Therefore, based on the Andrei model, a comprehensive prediction model, which can reflect the influence of compactness, moisture content, additive content, and stress state on resilient modulus was introduced. Good agreement between the regression results and the measured ones demonstrated the integrative ability of the introduced model.

The Effect of Cyclic Load Characteristics on Unbound Granular Materials

Vertical load characteristics used in laboratory repeated load triaxial tests (RLTT) have a significant impact on evaluating unbound granular materials (UGMs) for the flexible road pavements. Many studies and standard testing protocols suggest a diverse range of these characteristics (i.e. stress magnitude, pulse shape type, loading period and rest period). Several studies have been conducted to identify the factors that affect the permanent deformation (PD) and resilient modulus (Mr) of UGMs. However, the effect of the pulse shape types has not yet been investigated. The aim of this study is to experimentally investigate the effect of vertical stress pulse shape type on the PD and Mr behaviour of the UGMs using RLTT. For further assessment, a parametric analysis was also conducted using eight existing PD and Mr constitutive models. Three typical vertical stress pulse shape types were investigated, namely trapezoidal, haversine and triangular, as suggested by several international testing protocols. The results show that tested UGMs, using trapezoidal stress pulse, produced higher PD and lower Mr than haversine and triangular pulses under controlled experimental conditions. As the loading span of the pulse increased, the amount of PD also increased, and Mr decreased. Some of the regression parameters of the investigated constitutive models for both PD and Mr showed correlations with the type of applied stress pulses. Moreover, it was found that the PD and Mr models were material dependent, as a better statistical fit was achieved for the granite than the basalt samples. It is recommended to take extra precautions while adopting a particular type of vertical stress pulse shape as the results may vary widely.

The effect of instrumentation on the determination of the resilient modulus of unbound granular materials using advanced repeated load triaxial testing

Unbound Granular Materials (UGMs) are used in the base/subbase layers of flexible pavement structures for the vast majority of the main roads around the world. The resilient modulus of UGMs is a key input parameter for the design and analysis of flexible pavement structures. In the present study, four road base UGMs with a range of moisture contents are used to evaluate each material’s resilient deformation behaviour using laboratory repeated load triaxial tests. The triaxial system for the tests is instrumented with four axial deformation gauges: an on-specimen axial Hall-Effect transducer, an internal Linear Variable Differential Transformer (LVDT), an external LVDT, and the actuator LVDT. The application of a Hall-Effect transducer directly mounted on the specimen and the three LVDTs permits the comparative study of alternative deformation measurements for the determination of an accurate and reliable resilient modulus value. By comparing tests results obtained with each transducer, the relative capability of each measurement is determined and a reference transducer for deformation measurement is identified. A constitutive model is then used to carry out a regression analysis and to predict the resilient modulus of the four tested materials.

Elastic Nonlinear Finite Element Analysis of a Flexible Pavement Subjected to Varying Falling Weight Deflectometer Loads

A nonlinear finite element method (FEM) model has been developed to model thin-surfaced, unbound granular pavements. The FEM model incorporates a nonlinear anisotropic material model for the granular material and a nonlinear material model for the subgrade. The coefficients for the material models were determined from laboratory repeated load triaxial tests. A test pavement at the Canterbury Accelerated Pavement Testing Indoor Facility (CAPTIF) was instrumented with an inductive coil soil strain system to measure vertical compressive strains and pressure cells to measure the vertical compressive stresses. The test pavement was subjected to loading by a falling weight deflectometer (FWD) device at four different load levels. The initial FEM model configuration was undertaken at one load level using the surface deflection measurements from the FWD; however, there were significant differences between the computed and measured stress and strain values. The scalar coefficients for the granular and subgrade materials were adjusted so that the measured and computed stress and strain values matched within a reasonable tolerance (10%). After the calibration process was finished, it was found that the computed and measured surface deflections also matched. The model was rerun with the three remaining load cases; the computed and measured stress, strain, and surface deflection values were in close agreement. The range of computed stiffness values varied with both the pavement and load level. The results from this analysis showed the need to use a full nonlinear model to obtain realistic results when FWD data are modeled.

Determination of Elastic and Plastic Subgrade Soil Parameters for Asphalt Cracking and Rutting Prediction

A preliminary step in the prediction of rutting and cracking in a number of accelerated loading facility trials in Australia is presented. The results of laboratory repeated load triaxial tests were used to characterize the residual and resilient deformation of a silty clay subgrade material. The analysis of permanent deformation indicated that the well-known model Ep, = INSc can be used to estimate the accumulated strain at any number of loading cycles. The parameter S (the slope of the line in a plot of log Ep-log N) was found to be independent of stress and density, but very small increases were observed as moisture content increased. The parameter I (the intercept in a plot of log Ep-log N) was found to be most sensitive to deviator stress. The test results also indicated that I increased with increasing moisture content and decreased as dry density increased. The analysis revealed that an exponential relationship existed between I and deviator stress. This relationship was used to develop a constitut...

Determination of Elastic and Plastic Subgrade Soil Parameters for Asphalt Cracking and Rutting Prediction

A preliminary step in the prediction of rutting and cracking in a number of accelerated loading facility trials in Australia is presented. The results of laboratory repeated load triaxial tests were used to characterize the residual and resilient deformation of a silty clay subgrade material. The analysis of permanent deformation indicated that the well-known model ∈p= INScan be used to estimate the accumulated strain at any number of loading cycles. The parameter S (the slope of the line in a plot of log ∈p–log N) was found to be independent of stress and density, but very small increases were observed as moisture content increased. The parameter I (the intercept in a plot of log ∈p–log N) was found to be most sensitive to deviator stress. The test results also indicated that I increased with increasing moisture content and decreased as dry density increased. The analysis revealed that an exponential relationship existed between I and deviator stress. This relationship was used to develop a constitutive model for silty clay based on the previously mentioned well-known model. The constitutive model obtained would be able to predict the plastic strain under any number of loads at any specified stress level. Resilient deformation analysis has shown that resilient modulus initially decreased rapidly with increasing deviator stress and then increased slightly or was nearly constant. The elastic and plastic parameters will be used as input for performance predictors such as VESYS and Mechano-Lattice.

Deformation analyses of Florida highway subgrade sand subjected to repeated load triaxial tests: Pumphrey, N D; Lentz, R W Trans Res RecN1089, 1986, P49–56

Laboratory repeated load triaxial tests are conducted to estimate the effects of highway traffic on the permanent and resilient deformation of a subgrade sand commonly used as a foundation for a flexible highway pavement structure in Florida. Combinations of confining stress and cyclic principal stress difference (test variables) and of dry unit weight and moisture content (sample variables) are used for each sample and loaded to 10,000 cycles. Confining stress, cyclic principal stress difference, and dry unit weight are correlated with permanent strain and resilient modulus and thus affect deformation properties of these soils. However, moisture content correlates with neither permanent strain nor resilient modulus. Static tests are conducted on various samples similar to those used in the cyclic tests. These results are used to normalize cyclic stress and strain at 10,000 cycles. A regression model is developed for predicting cyclic strain in the sand from satic tests by using a technique previously developed by Lenz. The model is compared to one for Michigan highway subgrade sand. Using a general linear test at a level of significance of 0.05, it is found that the data sets from each sand cannot be pooled to form one reression model. Values of resilient modulus after 10,000 loading cycles for the Florida sand ranged from 16,000 psi (110 240 kPa) at 5 psi (34.5 kPa) confining stress to 56,000 psi (385 840 kPa) at 50 psi (344.5 kPa) confining stress.