Top-down Cracking Research Articles

Development of an Artificial Neural Network-Based k-Value Prediction Model to Improve the Sensitivity of Base Layer on Rigid Pavement Performance

The performance of rigid pavement is greatly affected by the properties of the base/subbase and subgrade layer. However, the performance predicted by the AASHTOWare Pavement Mechanistic-Empirical (ME) Design shows low sensitivity to the properties of base and subgrade layers. In this study, a new set of modified models, that is, resilient modulus ( MR) and modulus of subgrade reaction ( k-value) are adopted to better reflect these layers’ influence on the overall performance. An artificial neural network (ANN) model is developed to predict the modified k-value based on finite element (FE) analysis. The training and validation data sets in the ANN model consist of 27,000 simulation cases with different combinations of pavement layer thickness, layer modulus, and slab-base interface bond ratio. Eight pavement section data are collected from the long-term pavement performance (LTPP) database and modeled using the FE software ISLAB2000 to evaluate the sensitivity of the modified MR model and k-values to pavement performance. The computational results indicate that the modified MR values have a higher sensitivity to water content in the base layer on fatigue cracking (bottom-up and top-down cracking) and the faulting performance of rigid pavements compared with the results using the Pavement ME design model. It is also observed that the k-values using the ANN model have a greater sensitivity to cracking and faulting performance as a result of changes in any bonded conditions (fully bonded, partially bonded, zero bonded), whereas the Pavement ME design model can only calculate at two extreme bonding conditions (i.e., fully bonded and zero bonded).

A prediction model for top-down cracking in asphalt pavements with open-graded friction course

Thick asphalt pavements with open-graded friction course (OGFC) are subjected to top-down cracking (TDC), a distress consisting of cracks that initiate on the pavement surface close to the wheelpath and propagate downwards. However, road agencies do not yet have adequate tools to predict TDC. The objective of this study was to develop a practical and reliable model to predict TDC depth evolution in such pavements. The proposed model provides a maximum TDC depth that can potentially occur in a pavement characterized by certain mechanical properties and traffic at the time of interest. The model was calibrated and validated considering several Italian motorway pavements affected by TDC based on limited data, therefore more data should be collected in the future. This model can be used in a pavement management system (PMS) to plan timely surface maintenance against TDC.

Prediction of top-down crack resistance in semi-flexible pavements under coupling effect of rutted surface and temperature gradient

ABSTRACT Top-down cracking (TDC) as a severe type of cracking has been widely reported in pavements with heavy traffic loads and mixtures sensitive to rutting damages. Since the likelihood of TDC increases as a result of weak mastic, semi-flexible pavements (SFPs) grouted with cement asphalt emulsion pastes (CAEPs) were introduced in this study to evaluate its performance in prevalence or mitigation of this problem. Using laboratory tests, the material properties and rutting resistance of SFP with CAEPs were compared to the conventional asphalt mixture. Then comprehensive finite element (FE) models were employed to investigate the influence of rutting damage severity on non-uniform contact stresses and critical TDC responses. Considering various degrees of rutted surface, the critical locations of TDC were predicted based on maximum transverse and shear strain responses. The results demonstrated that the presence of a rutted surface induced the near-surface responses significantly, and the more severe rutting, the higher propensity for TDC. Besides, the location of TDC initiation was greatly influenced by the severity of the rutted surface. Finally, based on SFP performance in the surface layer, CAEP40 was recommended as the best grouting material to reduce the likelihood of TDC and rutting damage development.

The influence of truck speed on pavement defects

ABSTRACT The response of asphalt material depends on the rate of loading and varies from elastic to plastic. Therefore, the behaviour of flexible pavement would also be different along the entire length of a road because of truck speed changes due to the existence of police checkpoints, bus stations, speed bumps, intersections, horizontal and vertical curves, and climbing lanes. The objective of this study is to investigate the effect of truck speed on the performance of flexible pavement. Thus, analyses were conducted for various truck speeds (1–75 km/hr) on three different pavement structures and three traffic levels using AASHTOWare Pavement ME Design 2.5.5 for the local conditions of Izmir, Turkey. The analysis results of the study manifested that a reduction in traffic speed (75–1 km/hr) on a road resulted in higher pavement distress. According to the results, reducing truck speed from 25 to 1 km/hr resulted in a rapid increase in AC rutting, alligator cracking and top-down cracking by 13.3 mm, 10.6% and 1473.8 m/km, respectively. It is expected that the outcomes of this study would promote the local calibration of the mechanistic-empirical pavement design guide (MEPDG) and pavement design in Turkey and the region.

Investigation on Top-Down Cracking on Two-Lift Concrete Pavement under Freeze–Thaw Environment

Investigation on Top-Down Cracking on Two-Lift Concrete Pavement under Freeze–Thaw Environment

Effect of various interface bonding conditions on critical response characteristics for cracking potential of asphalt pavements

Interface bonding conditions are important to ensure the desired performance of multi-layered asphalt pavements. Most previous studies only investigated the sole effect of the interface at a specific location, although the most extreme case is when poor bonding occurred at multiple locations simultaneously. Also, the sensitivity of bonding effects to structural parameters is unclear. Therefore, this study investigated the effects of multiple bonding scenarios and structural parameters on critical responses, the 3-D viscoelastic finite element model. The results indicated that critical locations for cracking potential depend on bonding scenarios. Interface bonding between asphalt and aggregate base layers mainly contributed to bottom-up cracking, while the interface between asphalt layers was more associated with top-down and near-surface cracking. In addition, the use of a thicker asphalt layer was more effective than the use of a strong base layer to mitigate the negative effects of poor bonding conditions.

Asphalt Layer Cracking Behavior and Thickness Control of Continuously Reinforced Concrete and Asphalt Concrete Composite Pavement

Based on thermal–mechanical coupling simulation analysis and physical engineering tracking observation, the mechanical behavior and response of a continuously reinforced concrete and asphalt concrete (CRC + AC) composite pavement layer were analyzed, and the causes of cracking on the surface and bottom of the asphalt layer were revealed. Studies have shown that under normal driving conditions, the AC layer, which is usually in the position of the wheel load gap and wheel load side, more easily generates a longitudinal “corresponding crack”. Compared to normal driving, longitudinal cracks are generated more easily inside of the curve, and transverse cracks occur more easily on poor stadia curves. When the AC layer thickness is less than 8 cm, the AC layer is more prone to bottom-up cracking, and it is more prone to top-down cracking when it is more than 8 cm thick. Comprehensively considering the tensile stress, shear stress, and the thickness of the AC layer, it is recommended that the suitable thickness range of the AC layer is 8 cm~14 cm. The calculated results show good agreement with the physical engineering investigation. The research results can provide a theoretical and scientific basis for cracking control and the rational design of a CRC + AC composite pavement layer.

Inspection and depth sizing of surface-initiated cracking for preventive maintenance of asphalt pavements

ABSTRACT Adequate monitoring and timely treatment of partial-depth, surface-initiated cracks are essential in order to prolong the life cycle of pavement structures. Therefore, methodologies to precisely identify and assess the progression of top-down cracking (TDC) depth are fundamental. For this purpose, a calibrated model for ultrasound inspection of various types of bituminous mixtures for paving (semi-dense asphalt concrete AC-S, stone mastic asphalt SMA, and porous asphalt PA) is proposed to assess the depth and extent of top-down propagated macro-cracks in asphalt pavements. Extensive laboratory measurements were recorded on specimens of the different materials, thicknesses, temperatures and distances between sensors, with varying crack depths. The laboratory results were compared with in situ tests and with the theoretical approach. The application of the calibrated model allowed an appraisal of the depth of TDC with sufficient precision for a routine practical application regarding pavement maintenance. This non-destructive, inexpensive and easy-to-implement methodology for on-site identification and evaluation of TDC depth in asphalt pavements ensures straightforward implementation on non-prepared surfaces and provides sufficient reliability in the laboratory and on in-service pavements.

Numerical Analysis of Top-Down Crack in AC Layer of Continuous Reinforced Composite Pavement under Multifactor Coupling

Numerical Analysis of Top-Down Crack in AC Layer of Continuous Reinforced Composite Pavement under Multifactor Coupling

Optimization of Rigid Pavement

Abstract: The construction of national highways nowadays is preferred by using rigid pavements as they are durable, have the high flexural strength, can withstand different heavy axle loads, higher design span and moreover they can sustain adverse environmental conditions more efficiently with better ease. Considering their remarkable qualities, the national highways should be constructed by providing the tied shoulders and dowel bars in the transverse joints because they can better resist the fatigue accumulations on the slab with minimum safe thickness which ultimately leads to reduction in the cost of making the road efficiently. In this chapter, for the two different CBR conditions (CBR-9 & CBR-10) and three concrete mix design grades namely (M40, M45, M50) along with different shoulders and dowel bars conditions, the trial methods were carried on the IRC58 Software for bottom-up cracking fatigue analysis for single and tandem axle for day-time (6 hour) traffic and positive temperature differential and top-down cracking fatigue analysis for single, tandem and tridem axle for day-time (6 hour) traffic and negative temperature differential for evaluating the flexural stresses and cumulative fatigue damage values for the slab having dimensions of (3.5m x 4.5m). For determining the safe design, different trails on the thickness parameter of the slab were being adopted so as to get the cumulative fatigue values of BUC and TDC for single, tandem and tridem axles less than one. The results obtained showed that for which grade and CBR condition, the values of flexural stresses and cumulative fatigue damage determined is maximum. It was concluded that the rigid pavements should be constructed by using higher grades like M45 and M50 as the fatigue stresses and cumulative fatigue damage values due to variable single, tandem and tridem axle load repetitions obtained are less as compared to M40 grade. Keywords: California Bearing Ratio (CBR); Bottom Up Cracking (BUC); Top Down Cracking (TDC); Mix Design Grade Value (M), Indian Road Congress (IRC); Flexural Stresses; Cumulative Fatigue Damage(CFD)

Structural and Fatigue Analysis of Jointed Plain Concrete Pavement Top-Down and Bottom-Up Transverse Cracking Subjected to Superloads

Superheavy vehicles, also called superloads, have non-standardized loading configurations as well as high gross vehicle weights (GVW) and axle loadings, all of which may cause unexpectedly greater distresses on jointed plain concrete pavements (JPCP) than those caused by conventional vehicle class types categorized by the Federal Highway Administration (FHWA). In general, superloads include “Implements of Husbandry” and “Superheavy Loads”, both known to be the main types of heavy transport vehicles in the Midwestern region of the United States. To characterize non-standardized loading configurations of superloads, a mechanistic analysis approach is needed for predicting potential damage to JPCPs. In this paper, critical loading locations are determined and categorized according to the superload loading configuration for each superload generating critical pavement responses for both bottom-up transverse cracking and top-down transverse cracking. Critical pavement responses of JPCPs under critical loading conditions for each superload are calculated by performing finite element analysis and are then converted to damage ratios by comparing them with critical pavement responses resulting from FHWA class 9 truck loading using various available transfer functions based on concrete fatigue test results. The resulting critical loading location for each superload category can then be derived easily and the potential for damage to the JPCP pavement systems by each superload can be determined by comparing fatigue damage ratios.

Investigation of Tri-Axial Stress Sensing and Measuring Technology for Tire-Pavement Contact Surface

A tri-axial stress sensor was designed to measure contact stresses in the tire–pavement contact patch. The shape and size of the sensor surface were designed considering both the asphalt pavement texture and the tire pattern. The top-down cracking mechanism was also taken into account, and the sensor was placed at the vertical crack depth. Temperature drifts and zero drifts were compensated for. The sensor had high structural strength and met the sensing requirements of specialized heavy vehicles. In a preliminary study, three sensors were fabricated and calibrated in three directions. Simulated measurements were performed using a tire–pavement surface contact test bench. Signals from the L-shaped sensor region were obtained for the upper, middle, and lower parts of the tire, and preliminary stress distributions were determined at different positions on the contact surface. This study has laid a foundation for the design and construction of a more precise test system in the future.

A semi-empirical model for top-down cracking depth evolution in thick asphalt pavements with open-graded friction courses

Thick asphalt pavements with open-graded friction course (OGFC) are exposed to top-down cracking (TDC), a distress consisting of longitudinal cracks that initiate on the pavement surface close to the wheel path and propagate downwards. The main objective of this study is to develop a semi-empirical model for the prediction of TDC depth evolution for such pavements. For this purpose, a series of cores were taken from different Italian motorway pavements affected by TDC and analyzed in the laboratory. Cracked cores taken from the wheel path area were analyzed to determine TDC depth, whereas intact cores taken from the middle of the lane (not affected by traffic loadings) were tested to obtain the volumetric and mechanical properties of the OGFC mixture. The proposed model, developed on the basis of the results already available in literature and on the findings of the laboratory investigation, predicts the evolution of TDC depth as a function of the applied traffic loadings (in terms of 12-ton fatigue equivalent single axle loads, i.e., ESALs). The model is sigmoidal with a maximum TDC depth assumed equal to 150 mm. The shape parameter of the sigmoidal function depends on the indirect tensile strength (ITS) of the OGFC mixtures (which takes into account indirectly also the volumetrics and stiffness of the OGFC), whereas the evolutive translation factor depends on the age of the OGFC mixture. After excluding some outliers, the model was able to predict the measured TDC depth very well. Moreover, in-situ observations allowed a preliminary validation of the proposed model. This model can be used in pavement management systems (PMSs) to plan surface repairs due to TDC in a timely manner, thus minimizing pavement damage and maintenance costs. • The semi-empirical model predicts TDC depth as a function of the traffic loads. • The model is sigmoidal with a maximum TDC depth assumed equal to 150 mm. • The model parameters depend on the properties and the age of the OGFC. • In-situ observations provide a preliminary validation of the model. • The model can be used in a PMS to identify pavement areas where TDC is critical.

A mass specific volume-based viscoelastic damage model to characterize fatigue damage in asphalt mixtures

Fatigue cracking is one of the most common distresses in flexible pavements, and many damage models have been proposed to predict fatigue cracking, but in these models, the evaluation of damage is related to the choice of the reference configuration, whose subjectivity may lead to subjective evaluation of damage. To describe micro-cracking in asphalt concrete under loading, this paper proposes a new viscoelastic damage model, where damage evolution is connected with the mass specific volume, which is independent of the reference configuration, and the resistance to damage is also represented as an exponential function of mass specific volume to show its decrease under destructive loading. To determine material parameters in the model, nondestructive creep test data are used to obtain the relaxation modulus, and by determining the initial resistance to damage of asphalt concrete with different air voids, the evolution of resistance to damage can be obtained. The rest material parameters can be determined by fitting the destructive test data. To verify the validity of the proposed model, the material behavior under controlled-strain repeated direct tension (RDT) is predicted and the model predictions are compared with test data. It shows and the damage increment in the first loading cycle is largest and the rate of damage increases first and then decreases in each cyclic loading period. In addition, the behavior of the pavement structure under traffic loading is simulated, and fatigue cracking in the asphalt concrete layer of the pavement can be captured by the proposed model. It shows that in thick flexible pavements, both top-down cracking and bottom-up cracking occurs, but top-down cracking is dominant.

Prediction of interlayer shear strength of double-layer asphalt using novel hybrid artificial intelligence models of ANFIS and metaheuristic optimizations

The pavement damages such as slipping, rutting, top-down cracking of flexible pavement are very common during the operation process. These damages are mainly caused by interlayer shear stress acting between the asphalt layers during traffic movement. This is one of the main reasons for reduced pavement service life and increased maintenance costs. Therefore, the Interlayer Shear Strength (ISS) parameter needs to be evaluated and accurately predicted. Generally, ISS of double–layer asphalt concrete is measured directly in the field or on the samples in the laboratory, which involves much time and cost. Therefore, in this study, we have estimated ISS of asphalt pavement based on three input parameters: temperature, normal pressure and aggregate diameter using novel hybrid machine learning models namely Culture Algorithm based Adaptive Neuro Fuzzy Inference System (ANFIS-CA), Differential Evolution based Adaptive Neuro Fuzzy Inference System (ANFIS-DE) and Invasive Weed Optimization based Adaptive Neuro Fuzzy Inference System (ANFIS-IWO). Estimated shear strength was compared with the direct measured shear strength for the validation of model’s performance. In this study results of 180 double-layer asphalt samples which were fabricated by three different mixtures of Dmax 12.5, Dmax 19 and Dmax 25 and tested by shear device in the laboratory with five levels of normal pressure (0, 0.14, 0.2, 0.4, 0.6 MPa) at three temperature levels (25, 40 and 60 °C) were considered. Standard statistical measures namely Mean Absolute Error (MAE), Root-Mean-Square Error (RMSE), and Correlation Coefficient (R) were used to assess the models’ prediction capabilities. The results exhibit that all the suggested models have high accuracy of prediction, but performance of ANFIS-IWO (MSE = 0.02, MAE = 0.024, RMSE = 0.047, and R = 0.953) is slightly better than ANFIS-CA (MSE = 0.04, MAE = 0.031, RMSE = 0.047, and R = 0.966) and ANFIS-DE (MSE = 0.03, MAE = 0.034, RMSE = 0.057, and R = 0.953). Therefore, all the proposed models are suitable and powerful potential tools for the accurate prediction of the ISS for the proper consideration of pre-construction and post-construction pavement asphalt mixture design but the ANFIS-IWO model is the best.

Mesoscopic asphalt pavement response analysis using a random aggregate generation-based concurrent multiscale method

Asphalt concrete (AC) layers in asphalt pavements are heterogeneous, but they are generally deemed as homogeneous in engineering practice, which cannot realistically reflect the complex mechanical behavior of asphalt pavement, particularly at finer scales. To resolve this problem, the present study developed a random aggregate generation-based concurrent multiscale method to simulate the mechanical response of asphalt pavement using ABAQUS software. In this method, the mesoscopic structure of AC with a 60 cm length was simulated in the vicinity of tire loading by a random aggregate generation method and embedded into a macroscale pavement model. To account for the effects of pavement structure and environmental factors, three thicknesses of AC layer (10 cm, 15 cm and 20 cm), two types of pavement structures respectively with a cement-treated base (CTB) and a granular base (GB), and two pavement temperatures (5 and 35℃) were adopted in the simulation. The maximum principal stress (MPS) values of fine aggregate matrix (FAM) within the region of interest were sorted and the values at the percentiles of 10%, 20%, …, 90%, 100% were extracted. Besides, the number of the elements with top 1% MPS values were evaluated. Specific statistical analysis was performed on these values to investigate potential damage behavior of the AC layer. The results showed that the MPS at the percentile of 100% is at least three times that at the percentile of 90%, which indicates considerable stress concentrations at the narrow gaps between coarse aggregates. Top-down cracking could be the main cracking pattern for the CTB and GB pavement at low temperatures, and bottom-up cracking may be the main damage mode for the GB pavement at high temperatures. Increasing the thickness of the AC layer may effectively reduce the stress level at top of the AC layer for the CTB pavement at low temperatures.

Rutting and surface-initiated cracking mechanisms of semi-flexible pavements with cement asphalt emulsion pastes

ABSTRACT The semi-flexible pavement (SFP) has been used as a promising wearing course in heavy traffic roads. It is crucial to investigate the main failure mechanisms caused by different influencing factors on SFPs at medium and high temperatures. In this research, utilising a three-dimensional (3D) finite-element model (FEM), the performance of SFP and conventional pavement under realistic tire–pavement contact stresses was compared by computing the critical responses associated with rutting and top-down cracking (TDC). Besides, experimental studies were conducted on typical asphalt concrete (AC16) and four types of SFP mixtures grouted with cement paste and cement asphalt emulsion pastes (CAEPs) to evaluate their rutting resistance and fatigue cracking potential at medium and high temperatures. The numerical analysis results indicated that SFP mixtures with lower asphalt emulsion (AE) content enhanced rutting resistance significantly while TDC potential was reduced at higher percentages of AE. Compared to dual-tire assembly, the wide-base tire led to less TDC damage and asphalt layer (primary) rutting, but more subgrade (secondary) rutting once carrying the same load. Moreover, based on the findings of laboratory evaluation, SFP with CAEP presented the best performance in terms of fatigue life and permanent deformation when AE to cement by weight (AE/C) was no more than 0.4.

Research progress in the mechanism and treatment of asphalt pavement cracking

Cracking defect is one of the diseases of asphalt pavement to be solved urgently, in recent years, with the continuous improvement of pavement custody requirements, maintenance of new materials, new technology, new technology constantly emerging, based on the asphalt pavement engineering of the typical Top-Down cracking and reflection cracking, both at home and abroad were reviewed on the analysis of its mechanism and treatment measures, It can provide a reference for pavement engineering maintenance researchers and technicians.

Calibration of mechanics-based pavement predictive framework for top-down cracking performance of flexible pavement considering wheel wander effect

This study presents a pavement analysis framework for top-down cracking (TDC) for flexible pavements with considerations of the effects of lateral wheel wander on the long-term pavement performance. A mechanics-based pavement analysis framework developed for predicting TDC is adopted and extended to account for the influence of lateral wheel wander on long-term pavement performance. The mechanics-based pavement analysis model was developed based on the HMA Fracture Mechanics with thresholds introduced to capture the changes in the asphalt concrete mixture resistances to damage and fracture. The fracture resistance and healing propensity of mixture are correlated to mixture morphology to account for the contribution of mixture morphology to these key mixture properties. A failure-curve calibration methodology is developed and implemented using pavement sections with well-documented performance histories from Florida. By accounting for a more realistic representation of the traffic conditions, the calibrated framework delivered accurate predictions of the long-term top-down cracking performance of the pavement sections considered in the study. The TDC performance of pavement for non-wheel wander scenario is evaluated to simulate the loading characteristic of autonomous trucks. A comparative evaluation of the pavement performance for traffic conditions with lateral wheel wander, and the non-wheel wander case was performed. As expected, the results indicate a higher level of accumulated damage in the non-wheel wonder case. The crack initiation time (i.e., the number of years to initiation of cracks) of all pavement sections for non-wheel wander cases is earlier than those with lateral wheel wander. The results show that the non-wheel wander case (autonomous truck scenario) can account for about a 20% reduction in pavement life depending on the traffic volume, pavement structure, materials, and climatic conditions. In addition, the results further exhibit that pavement sections with different traffic volumes exhibited a varying degree of sensitivity to the effect of wheel wander on the long-term performance.

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This study presents a pavement analysis framework for top-down cracking (TDC) for flexible pavements with considerations of the effects of lateral wheel wander on the long-term pavement performance. A mechanics-based pavement analysis framework developed for predicting TDC is adopted and extended to account for the influence of lateral wheel wander on long-term pavement performance. The mechanics-based pavement analysis model was developed based on the HMA Fracture Mechanics with thresholds introduced to capture the changes in the asphalt concrete mixture resistances to damage and fracture. The fracture resistance and healing propensity of mixture are correlated to mixture morphology to account for the contribution of mixture morphology to these key mixture properties. A failure-curve calibration methodology is developed and implemented using pavement sections with well-documented performance histories from Florida. By accounting for a more realistic representation of the traffic conditions, the calibrated framework delivered accurate predictions of the long-term top-down cracking performance of the pavement sections considered in the study. The TDC performance of pavement for non-wheel wander scenario is evaluated to simulate the loading characteristic of autonomous trucks. A comparative evaluation of the pavement performance for traffic conditions with lateral wheel wander, and the non-wheel wander case was performed. As expected, the results indicate a higher level of accumulated damage in the non-wheel wonder case. The crack initiation time (i.e., the number of years to initiation of cracks) of all pavement sections for non-wheel wander cases is earlier than those with lateral wheel wander. The results show that the non-wheel wander case (autonomous truck scenario) can account for about a 20% reduction in pavement life depending on the traffic volume, pavement structure, materials, and climatic conditions. In addition, the results further exhibit that pavement sections with different traffic volumes exhibited a varying degree of sensitivity to the effect of wheel wander on the long-term performance.