Pavement Parameters Research Articles

Development and Validation of Asphalt Pavement Rutting Prediction Model with Transient Temperature Field Considered

This study developed a transient rutting analysis program based on the principles of heat transfer and the viscoelastic–viscoplastic theory of asphalt mixtures. Using the finite element model (FEM) model corresponding to the multi-layer pavement structure and the subprogram interface of ABAQUS software, along with Python programming, the program was designed to estimate rutting under transient temperature field conditions with climate conditions, traffic flow, and structure layer constitutive parameters of pavement considered. Subsequently, the program was used to validate the efficiency of the solution and analyze the influencing factors of internal temperature field and rutting depth within the asphalt pavement structure. Results showed that, based on meteorological data and recommended values of material thermal properties, the FEM of transient temperature field can accurately simulate the temperature field distribution of pavement structure. Based on loading information and dynamic modulus test, the transient temperature variable rutting with FEM proposed in this paper can simulate and calculate the rutting of pavement structure layer with some errors for different pavement conditions from 5% to 40%. Through parametric analysis of the influence factors of temperature field and rutting, the modified transient temperature field rutting prediction program can effectively simulate rutting of pavement structure, and the minor errors were less than 20%.

An efficient analysis method for system reliability of semi-rigid base asphalt pavement structure based on direct probability integral method

The structural design parameters of asphalt pavement inherently possess randomness. Reliability theory aids in considering the stochastic nature of these parameters in asphalt pavement design. However, as the number of considered random factors increases, the complexity of reliability calculation models and the consumption of computational resources also significantly escalate. To analyze the structural reliability of semi-rigid base asphalt pavements more efficiently and accurately, a method combining Weighted Kernel Density Estimation (Weighted-KDE) with Direct Probability Integration Method (DPIM) using sampling strategies was employed. Furthermore, integrating the equivalent extreme value principle, an asphalt pavement structural system reliability analysis method was proposed, considering multiple failure mode correlations. The numerical solution steps of this method are also outlined. Based on the typical semi-rigid asphalt pavement structure in China, this study utilized the elastic layer system method (the program Apbi) and a computational program developed in MATLAB to compare the efficiency and accuracy of calculating reliability between DPIM and the Monte Carlo Simulations (MCS). The computational outcomes indicate that, under the premise of selecting 18 random parameters, DPIM can achieve the required accuracy in assessing the reliability of asphalt pavement structure and system reliability. Analyzing how the number of samples affects the computational results reveals that using weighted-KDE and DPIM only needs a few hundred sample points to limit the relative error within 4 %, compared to the results obtained from 105 samples in MCS. The research findings demonstrate that DPIM incorporating the principle of equivalent extreme value events can serve as an efficient analytical approach for assessing the system reliability of asphalt pavement structures characterized by more complex failure modes.

Safety impact of highway geometrics and pavement parameters on crashes along mountainous roads

Having the capability of estimating both the number of crashes and their severity levels, crash prediction models are a precious tool in highway safety. However, there hasn't been any research on predicting traffic crashes on Indian mountainous rural highways. The primary objective of this research is to develop safety performance functions (SPFs) for traffic crashes occurring on rural roads located in the mountainous region of Uttarakhand, India.For analysis, the study utilized five years of crash data collected from different types of rural roads. The road network was divided into constant segments of 500m each, and separate models were developed for single (TSVC) and multi-vehicle (TMVC) crashes using the negative binomial regression approach. These SPFs highlight important significant variables in terms of positive and negative association and a potential change in subject crash frequencies. The results concluded that different types of risk factors impact both types of crashes, with horizontal (HC) and vertical curves (VC) in common. For instance, spot speed increases TSVC crashes by 3.87 %, whereas HC and VC tend to increase subject crashes by 8.32 % and 29.95 %, respectively.Similarly, TMVC is influenced by carriageway (CW) and shoulder width (SW). The result proposed that an increase in CW and SW can decrease frequencies by 0.668 times and 0.819, respectively. Additionally, the model highlighted the importance of rut-depth and the presence of pavement markings in the road safety analysis. At last, further research scope is suggested based on the limitations of this study.

Reliability of depleted cement–ground slab with waste granodiorite dust admixture on semi-saturated substrate

There are many types of pavements for roads. For technical roads, one of the most effective and economically advantageous pavement types is chemically stabilized soil pavement. When designing a pavement made of soil admixed with binders, it is necessary to meet the load-bearing conditions while considering the effects of environmental factors. The aims of this study were to optimize the strength parameters of pavement, minimize negative environmental effects, minimize the carbon footprint, and simultaneously dispose of mineral waste materials from the production of asphalt mixes for roads. After testing the strengths of samples admixed with cement or with reduced cement content and the addition of dust, questions arose as to how both materials affect the reliability of the pavement structure. Samples of soil doped with cement and dust were subjected to reliability analyses. Abaqus software with a three-dimensional subgrade model was used for a comparative analysis. The substrates under soil stabilization slabs were subjected to varying saturation states, which affected their vulnerability. In this study, the changes in the saturation characteristics of the subsoils associated with different types of climatic interactions were simulated. The Darcy–Buckingham law was used to describe the flow of liquids through the subsoil. Pavement reliability calculations were performed for a multidimensional space of random variables. The results served as an interesting starting point for recommendations to decrease the use of energy-intensive materials, increase the reuse of waste, and reduce the effects of the strengthening process on the environment.

Prediction model of asphalt pavement functional and structural performance using PSO-BPNN algorithm

The rapid expansion of expressway mileage has resulted in a significant maintenance workload. Accurately predicting pavement performance is an effective approach to cost-saving, maintaining the pavement in optimal condition, and prolonging its service life. However, the current asphalt pavement performance prediction model demonstrates low accuracy and fails to fully capture the actual changes in pavement performance under varying traffic and environmental conditions. In this study, we propose an enhanced back propagation neural network (BPNN) prediction model based on the particle swarm optimization (PSO) algorithm for predicting six performance parameters of asphalt pavement, encompassing both functional and structural aspects. The influential factors considered as inputs for our model include surface layer thickness, traffic load, and climate conditions, while the output is represented by specific pavement performance indices. To evaluate the effectiveness of our proposed model, three performance indices - root mean square error (RMSE), mean absolute percentage error (MAPE), and R-squared (R2) - were employed, leading us to obtain an optimized PSO-BPNN prediction model structure. We validated our results using road surface detection data from a Chinese highway spanning from 2016 to 2020, thereby demonstrating the feasibility of our PSO-BPNN prediction model. Our case study reveals that compared to the pre-optimized BPNN model as a whole, the optimized BPNN model achieved a higher R2 value by 17.43%, with an average R2 value exceeding 0.878 across all performance indices, additionally maintaining MAPE within 5%. These findings indicate that our optimized model exhibits faster convergence speed along with improved predictive capability and generalization effect. Consequently, this developed model can be effectively integrated into a pavement management system for generating accurate and timely maintenance plans.

An Improved Crack Identification Method for Asphalt Concrete Pavement

The results of high-precision asphalt concrete pavement crack identification can provide help for pavement maintenance. Therefore, methods of image feature enhancement and crack identification of asphalt concrete pavement cracks are proposed. First of all, we used an industrial CCD camera mounted on a vehicle to collect an asphalt concrete pavement crack image. Then, after using the NeighShrink algorithm to denoise the acquired image, a fractional differential image enhancement algorithm was designed based on image feature blocks to enhance the image features. On this basis, crack characteristics were segmented and processed by watershed algorithm. Through crack direction identification and crack parameter extraction, crack distribution direction, crack length and width and other parameters of asphalt concrete pavement were obtained in order to achieve accurate identification of asphalt concrete pavement cracks. The experiment found that this method can effectively remove noise information from asphalt concrete crack images; after applying this method, the image entropy value of each image was improved, with a minimum improvement of 0.38 and a maximum improvement of 1.98. The time consumed by this method in identifying cracks in asphalt concrete pavement varied between 1.4 s and 2.4 s. When identifying the length of cracks in asphalt concrete pavement, the maximum deviation value was only 0.47 mm; when identifying the width of cracks in asphalt concrete pavement, the maximum deviation value was only 0.31 mm. The above results indicate that by enhancing the image features of asphalt concrete cracks, this method achieves more accurate identification results for crack distribution direction, length and width values, with high identification efficiency and good application effect.

International Roughness Index Prediction for Jointed Plain Concrete Pavements Using Regression and Machine Learning Techniques

Rigid pavements are recently gaining vast interest for their durability and large traffic volume endurance. This raises the need for a robust method to predict their long-term performance to support decisions on their future maintenance and rehabilitation requirements. One of the most descriptive parameters of pavement ride quality is the International Roughness Index (IRI). IRI can be used as a performance indicator for the level of serviceability of rigid pavement. This study presents the evaluation of 21 variables covering climate, traffic, and structural parameters in predicting IRI for jointed plain concrete pavement (JPCP) sections using 1,414 data points acquired from the Long-Term Pavement Performance (LTPP) database. It was found that only 10 variables are significant in the IRI prediction for JPCP. Moreover, four modeling techniques were applied, namely, linear regression, multivariate adaptive regression splines, Gaussian process regression, and artificial neural network. It was found that a deep ANN model with a structure of one input layer, three hidden layers, and one output layer [10-36-18-9-1] gives the highest IRI prediction accuracy with root mean square error and coefficient of determination (R2) of 0.117 and 0.92, respectively. Finally, a sensitivity analysis was performed to evaluate the impact of each input variable on the accuracy of IRI prediction for JPCP sections, and it was found that the most influential variables are initial IRI, pavement age, mean and standard deviation of humidity, standard deviation of evaporation, mean and standard deviation of freezing index, pavement compressive strength, ratio between pavement and base layers thickness, and finally an estimated parameter called site factor which is a function of (age, freezing index and soil percentage passing sieve no. 200).

Experimental and Numerical Study on Response Characteristics of Airport Pavement Subjected to Wetting in Silt Subgrade

Silt is often selected as the filling soil in Northwest and North China. “Pot cover effect” or rainfall infiltration are easily to cause localized wetting during the service period of airport. The response characteristics of pavement derived from aircraft loading under wetting condition are the basis to explore the evolution law of pavement damage. To investigate this response characteristics for different parameters of pavement under wetting condition, a self-developed model test system was developed, and the verified numerical model was then established. The interaction mechanisms of pavement slabs, and the influence of wetting on mechanical response in loading area of pavement under different pavement parameters were analyzed. The results showed that the increased vertical deformation depends on water-holding capacity of silt, and the vertical deformation under loading is little affected by pavement parameters. The peak shear stress and the increased peak shear stress derived from wetting at the bottom of pavement layers are largely influenced by elastic modulus of base course. For cement concrete pavement, the increase in load transfer capacity of joints cannot decrease the increase of peak stress, including horizontal stress and shear stress, derived from wetting. The increase in load transfer capacity of joints can decrease the stress concentration in surface layer, while the elastic modulus of surface layer has little influence. For bituminous pavement, optimal parameters of base course can be obtained to decrease the peak stress and the increase of peak stress derived from wetting in subgrade. The research can provide technical basis for the structure design, optimization, and disease treatment of pavement in airport engineering.

Three-dimensional finite element analysis for structural parameters of asphalt pavement: A combined laboratory and field accelerated testing approach

To solve the issues that material parameters measured under specific laboratory conditions are extremely different from the actual pavement, a method of structural parameters correction in semi-rigid base asphalt pavement combining numerical simulations, laboratory tests, and accelerated pavement testing (APT) was proposed. The dynamic modulus and the uniaxial static compression creep tests were conducted to explore the effect of temperature, size, and fatigue. Then, these factors were coupled to the modified Burgers model that can reflect the creep law of the whole process. A constitutive model reflecting the real parameters of the pavement was subsequently constructed with the ABAQUS user-defined material (UMAT) subroutine. Experimental results illustrated it was verified that the modified subroutine has good feasibility both in single-layer and multi-layer materials from the actual pavement. Furthermore, simulated results also showed excellent agreement with field-tested findings. Finally, the rutting deformation curves and the demarcation points of each stage were obtained, which could guide the rutting prediction and maintenance decision of semi-rigid asphalt pavement.

Indices relation and statistical probability analysis of physical and mechanical performance of asphalt mixtures

Rutting deformation is one of the most prominent diseases in asphalt pavement’s early damage. In this paper, it analyzes the relation and their distribution law between Marshall stability and the physical and mechanical indices of asphalt mixtures based upon a correlation analysis and statistical principles, which is to find the reasonable range of rutting performance design parameters of asphalt pavement. The results showed that the asphalt mixture’s stability increased with the increase in bulk volume relative density and asphalt saturation, but decreased with the increase in the percent of air-voids and the voids in the mineral aggregate. The optimal fitting function of bulk volume relative density and asphalt saturation for AC-13 asphalt mixture follows a Weibull distribution, that of Marshall stability and air-voids follows a Gamma distribution, and that of percent voids in the mineral aggregate and flow value follows a Lognormal distribution. For a GAM-16 asphalt mixture, the optimal fitting function of bulk volume relative density and Marshall stability follows the Weibull distribution, the optimal fitting function of air-voids follows a Gamma distribution, that of flow value and percent voids in the mineral aggregate follows a Lognormal distribution, and asphalt saturation follows a Normal distribution. It is recommended that AC-13 asphalt mixtures’bulk volume relative density ranges from 2.27～2.38 g·cm3, the air-voids ranges from 3.4～6.0%, and GAM-16 asphalt mixtures’bulk volume relative density ranges from 2.29～2.37 g·cm3, the voids in mineral aggregate ranges from 17～18.17%, the asphalt saturation ranges from 75～82.13%, which can provide a reference for in-depth understanding of the deformation characteristics and construction of highways’ pavement in similar areas.

FEM based parametric analysis for investigating effect of wheel base characteristics and axle configurations on flexural stresses in rigid pavements

The main advantages of rigid pavements are their durability and ability to hold their shapes when subject to heavy traffic and extreme weather conditions. Different vehicles have different wheel base characteristics and axle load configurations, due to which the above conditions structurally affect the performance of the rigid pavements in different ways. One of the main causes of critical defects in the rigid pavement is the development of flexural stress exceeding the critical level under different conditions. In rigid pavements the critical stresses are generated with the combination of wheel load stresses and curling stresses. In this paper, the investigation of the variation of flexural stress developed in jointed plain concrete pavements under different axle load configuration and wheelbase characteristics was done using FEM (Finite Element Method). In this paper, the modelling of the rigid pavement was carried out using KENPAVE software. In modelling, effect of both axle load and temperature difference is considered. For loading effect, axle configuration of SASW (Single Axle Single Wheel), SADW (Single Axle Dual Wheel), Tandem and Tridem axle was considered in modelling. To include the combined effect of base and subgrade an equivalent modulus of subgrade reaction was considered as per the IRC-58 code provisions. Parameters related to rigid pavement were taken according to the provisions of IRC code for modelling of base case. Parameters of pavement like thickness of pavement slab, equivalent modulus of subgrade reaction, temperature difference, modulus of elasticity and location of wheel load were changed from the base case and maximum tensile stress was calculated for each axle configurations. Based on the analysis of results for different thickness of pavement slab, equivalent modulus of subgrade reaction, temperature difference, modulus of elasticity and location of wheel load, the variation of magnitude and location of maximum tensile stress was reported for given properties of subgrade, base and axle configuration.

Dynamic response analysis of vehicle and asphalt pavement coupled system with the excitation of road surface unevenness

This study aims to solve the dynamic responses of the vehicle and asphalt pavement coupled system while considering road surface unevenness and deformation. First, an advanced solving procedure is proposed by decoupling the vehicle-pavement coupled system into two subsystems (i.e., quarter vehicle model with two degrees of freedom, and viscoelastic multilayered asphalt pavement) and solving them independently until the surface deformation has converged through an iterative scheme. During the solving procedure, the finite difference method and integral transform techniques are respectively conducted to compute the dynamic responses of vehicle and pavement. Then, the solutions for the dynamic responses of the pavement are verified through finite element simulation, which highlights the accuracy and efficiency of the proposed solution. The convergence study for the iterative procedure of vehicle-pavement coupled system is conducted, and the coupling effect on pavement and vehicle displacements is investigated. Finally, the effects of the vehicle and pavement parameters (i.e., suspension stiffness and damping, tire stiffness and damping, road surface unevenness, and pavement temperature and vehicle speed related to the viscoelasticity of asphalt material) on the pavement dynamic responses and damages are discussed comprehensively. These numerical investigations could prove that the solutions for the dynamic responses of the vehicle-pavement coupled system has the potential to guide road-friendly vehicle design and pavement service life evaluation.

Economic Impact Analysis of the Application of Different Pavement Performance Models on First-Class Roads with Selected Repair Technology

Mathematical expression of the deterioration of individual pavement parameters is, from the point of optimal repair and maintenance strategy decision-making process, an important part of the application of any pavement management system (PMS). The reliability of individual PMS depends on the quality of the inputs and the reliability of its internal sub-systems; thus, deterioration equations derived from high-quality input data play pivotal roles in a system for the prediction of the pavement life cycle. This paper describes the application of pavement performance models within pavement life cycle analysis (LCA) with the use of the integrated system of economic evaluation (ISEH), which is a calculation tool used for first-class roads with a standardized pavement composition of asphalt binders, where changes in operational capability parameters are modeled using individual model simulations. The simulations presented in this paper demonstrate changes in main economic indicators (net present value and internal rate of return) on two different pavement performance models. Both simulations share the same input parameters (traffic intensity, construction intervention, maintenance costs, discount rate) but differ in deterioration evaluation, all of which were applied to each model (a total of five models).

Optimizing the Texturing Parameters of Concrete Pavement by Balancing Skid-Resistance Performance and Driving Stability.

Curved texturing is an effective technique to improve the skid-resistance performance of concrete pavements, which relies on the suitable combination of the groove parameters. This study aims to optimize these parameters with the consideration of skid-resistance performance and driving stability. A pressure film was adopted to obtain the contact stress distribution at the tire–pavement interface. The evaluated indicator of the stress concentration coefficient was established, and the calculation method for the stationary steering resistance torque was optimized based on actual tire–pavement contact characteristics. Test samples with various groove parameters were prepared use self-design molds to evaluate the influence degree of each groove parameter at different levels on the skid-resistance performance through orthogonal and abrasion resistance tests. The results showed that the groove depth and groove spacing had the most significant influence on the stress concentration coefficient and stationary steering resistance torque, respectively, with the groove depth having the most significant influence on the texture depth. Moreover, the driving stability and durability of the skid-resistance performance could be balanced by optimizing the width of the groove group. After analyzing and comprehensively comparing the influences of various parameters, it was found the parameter combination with width, depth, spacing, and the groove group width, respectively, in 8 mm, 3 mm, 15 mm, and 50 mm can balance the skid-resistance performance and driving stability. The actual engineering results showed that the R2 of the fitting between the stress concentration coefficient and SFC (measured at 60 km/h) was 0.871, which proved the effectiveness of the evaluation index proposed in this paper.

Particle Parameters of Asphalt Pavement Milling Recycling Material

Based on laboratory data and literature data, this paper has carried out a study on the particle parameters of asphalt pavement milling recycled materials. From the two indicators of the characteristic particle size and uniformity of the aggregate, the difference between the particle characteristics of the new aggregate and the recycled material, the changes in the composition of the macroscopic particles after the recycled material are extracted in advance and the attenuation law of the asphalt mixture gradation during the service time of the road surface was studied in this paper. The results show that based on the RRS equation, the particle distribution simulation of aggregates, RAP materials and mixtures can be simulated, and two characterization parameters of characteristic particle size and uniformity coefficient can be obtained. Under the condition of the same particle size range, the characteristic particle size of RAP material is smaller than that of the new aggregate, the uniformity improved, and the particle size distribution range becomes narrow. There is a good mathematical relationship between the characteristic particle size and uniformity coefficient of the RAP material after extraction. The characteristic particle size of the RAP material after extraction reduces, while the uniformity coefficient gets further reduced. With the extension of the age, the characteristic particle size and uniformity coefficient of the mixture have shown a significant linear attenuation. In order to ensure the quality stability of recycled mixtures, the classification and management of RAP materials should be strengthened in the actual recycling design and application process.

Eliciting a mathematical model from the traffic safety index to estimate the number of road traffic accidents

Traffic accidents have become one of the most important problems experienced by countries, leading to the death or injury of many people and the waste of money, which is supposed to be spent on developmental and economic projects that benefit the entire society. In Iraq with the absence of suitable recording system of (Iraqi Roads Traffic Accident Data) and the lack in the measure of highway safety. Thus, lead to error in the analysis of traffic accidents. The aim of this study is to estimate Road Safety Index value and developing a model related it with Road Traffic Accident. To reach the research aim, parameters of Roadway, traffic, Roadside, Pavement and Miscellaneous, characteristics of ten cities in central and southern Iraq (Baghdad, Babylon, Karbala, Najaf, Qadissiya, Muthanna, Dhi Qar, Wasit, Maysan and Basra) were studied. The results show that the extra increase of Road Traffic Accident can be represented by negative exponential trend in relation with Road Safety Index, at 0.05 level of significance 87.6% of variation in Road Safety Index can be accounted for by exponential relationship with Road Traffic Accident.

Nondestructive quality testing of concrete and asphalt concrete pavements

The technical level of the applied methods and controls has an impact on the result of construction and installation works. One of the main tasks of contractors in the process of paving is to quickly determine the parameters of asphalt pavement. The quality of the asphalt pavement device allows you to increase the service life and reduce the cost of repairing road surfaces. A number of methods and means of nondestructive quality testing of concrete and asphalt concrete pavements are considered. Some characteristics of defects of concrete and asphalt concrete pavements are given. The main attention is paid to ground-penetrating radar methods, eddy-current, radiation and acoustic, also the devices implementing these methods are considered.

Precast prestressed concrete pavement (PPCP): Effect of thermal gradient on curling deflection and stress

In this study, a three-dimensional (3-D) finite element (FE) model was developed and validated to evaluate the effect of thermal gradient on behavior of Precast Prestressed Concrete Pavement (PPCP) system. The FE model developed was then utilized to perform a numerical analysis for determination of the curling deflections and curling stresses by changing the important pavement parameters (i.e., prestress forces, concrete property, and subgrade stiffness). Results indicated that the 3-D FE model developed for PPCP system was capable of providing reliable predictions in consideration of the effect of thermal gradient on change in curling deflection and stress.

Mechanistic Responses of Asphalt Concrete Overlay Over Jointed Plain Concrete Pavement Using Finite Element Method

This study focused on the development of a three-dimensional Finite Element Model of an asphalt concrete overlaid on a jointed plain concrete pavement to assess the mechanical behaviour of the pavement under traffic load. The objective of this study was to determine the influence of different asphalt concrete thickness, asphalt concrete modulus, the interface bond between the asphalt concrete and the Portland cement concrete layer, Portland cement concrete modulus, and joint width on the tensile strain at the bottom of the asphalt overlay. The results showed that changes in the pavement parameters result in a large range of variations on the magnitude of pavement responses. The magnitude of the longitudinal tensile strain at the bottom of the overlay varied between 25 με and 460 με. Asphalt concrete thickness, interface contact condition, and asphalt concrete modulus parameters had the most influence on the pavement responses. The interface bonding condition was significant, regardless of the thickness of the surface layer.

Time-Delay Estimation by a Modified Orthogonal Matching Pursuit Method for Rough Pavement

Pavement survey is one of the most important applications for ground penetrating radar (GPR) in civil engineering. In the case of centimeter scale of GPR waves, the influence of interface roughness cannot be neglected and should be taken into account in the radar data model. The objective of this article is to estimate the time-delay in the presence of interface roughness by GPR. Using the property of noncircular signals, we propose a modified orthogonal matching pursuit method to estimate the pavement parameters for both overlapped and nonoverlapped echoes. Compared with subspace-based methods in coherent scenarios, the proposed method can estimate the time delays of backscattered echoes without applying the cumbersome interpolation and spatial smoothing procedures, which are more practical in real applications. The performance of the proposed method is tested on both simulated and experimental data. The estimation results show the good performance of the proposed method.