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The mounting impacts of climate change on infrastructure demand proactive adaptation strategies to ensure long-term resilience. This study investigates the effects of predicted future global warming on asphalt binder performance grade (PG) selection in the United States using a time series method. Leveraging Long-Term Pavement Performance (LTPP) data and Superpave protocol model, the research forecasts temperature changes for the period up to 2060 and calculates the corresponding PG values for different states. The results reveal significant temperature increases across the majority of states, necessitating adjustments in PG selection to accommodate changing climate conditions. The findings indicate significant increases in average 7-day maximum temperatures across the United States by 2060, with 38 out of 50 states likely to experience rising trends. Oregon, Utah, and Idaho are anticipated to face the largest temperature increases. Concurrently, the low air temperature has risen in 33 states, with notable increases in Maine, North Carolina, and Virginia. The widening gap predicted between required high and low PG poses challenges, as some necessary binders cannot be produced or substituted with other grades. The study highlights the challenge of meeting future PG requirements with available binders, emphasizing the need to consider energy consumption and CO2 emissions when using modifiers to achieve the desired PG properties. [ABSTRACT FROM AUTHOR]

The long-term aging of bitumens and its effect on low-temperature performance is a detrimental phenomenon. In order to investigate the effects of the aging phenomenon on the low-temperature performance of bitumens, it is very important to accurately simulate the behavior of bitumens in repeated aging cycles and to investigate related viscoelastic, chemical, and microstructural changes. In this research, three types of bitumen with penetration grades of 40/50 , 60/70 , and 85/100 were subjected to one to three cycles of pressure aging vessel (PAV) aging. Comprehensive data on the bitumen's behavior were obtained by conducting bending beam rheometer, Fourier transform infrared spectroscopy, and atomic force microscopy tests. Using the results of the conducted tests, an attempt was made to find precise relationships between different indicators of bitumen aging in terms of chemistry and viscoelasticity. The results revealed a linear correlation between the aging index and the ΔTc and dissipated energy ratio (DER) values, as well as the aging index and the vertical shift factor of the stiffness-time curve. The fitting coefficients of these linear relationships were R2=0.8 and above, indicating a strong linear relationship between these parameters. Furthermore, the viscoelastic indices DER and the derivation of creep compliance (J′) exhibited a fairly good linear relationship. [ABSTRACT FROM AUTHOR]

This paper evaluated the effect of a biobased polyurethane modifier on the moisture resistance of asphalt binder. Biomodifiers with high acid values have been implicated in moisture damage to asphalt. Here, castor oil with a relatively high acid value of 190 mg KOH·g−1 was used to produce biobased polyurethane. Biobased polyurethane was produced by combining castor oil, toluene diisocyanate (TDI), and diethylene glycol (DEG) at a molar ratio of 1∶2∶1. Asphalt binder was modified with 3%, 6%, or 9% of the biobased polyurethane (by weight of asphalt binder), and the moisture susceptibility of the modified asphalt was evaluated with a comprehensive laboratory experiment plan using the boiling water test, the indirect tensile strength test, the bitumen bond strength test, the water contact-angle moisture-susceptibility test, and the moisture-induced shear-thinning index test. Study results showed that the introduction of biobased polyurethane enhanced the bond between the aggregate and asphalt, thereby increasing the asphalt mixture's resistance to moisture damage. Consequently, the resistance of asphalt binders to cohesive failure and adhesive failure was enhanced in biobased polyurethane, as evidenced by respective increases of 19%, 40%, and 49% in tensile strength ratio for dosages of 3%, 6%, and 9% biobased polyurethane. Compared with neat asphalt, the asphalt blend containing 9% polyurethane had the highest bond-strength increases, 55.73% and 37.93%, for dry and wet conditions, respectively. This improvement is attributable to the phenol and amide components in biobased polyurethane, which increase the polarity of asphalt binder and increase the affinity of asphalt binder to siliceous aggregate. In addition, the moisture-induced shear-thinning index and the contact-angle moisture-susceptibility index showed that increased doses of biobased polyurethane resulted in increased resistance of asphalt to moisture damage. The study outcomes promote the sustainability of asphalt construction by introducing biobased polyurethane as a sustainable modifier for asphalt. [ABSTRACT FROM AUTHOR]

Predicting faulting failure is useful in the optimal concrete pavement design. In this study, artificial neural networks and the random forest method have been used to predict the amount of this failure. The general prediction model was created by inserting 32 available input variables into artificial neural networks. An integer two objectives optimisation problem was designed to select features that significantly affect the faulting. After applying this method, 19 important variables were identified and used to develop two simplified models based on artificial neural networks and the random forest method. It is shown that the simplified model developed by artificial neural networks is the best model to accurately predict the faulting considering the number of input variables. The cumulative number of days when the precipitation is more than 12.7 mm, the elastic modulus of concrete slab, the number of days passed since the pavement was built, base thickness, the cumulative ESALs in the traffic lane, and the annual average number of days when the temperature is more than 32°C were identified as the most important parameters in predicting faulting using the random forest method. A Sensitivity analysis has been then performed on these variables and optimal values were determined. [ABSTRACT FROM AUTHOR]

Acid sludge is an environmental pollutant that is produced daily in large amounts in used engine oil refineries. Recycling this waste is the primary goal of this paper. This study used 'washing with water' and 'neutralization with quicklime' methods to prepare acid sludge for use in bituminous materials as huge potential disposal. The neutralised sludge by the 'washing with water' method was added to bitumen in the wet blending process at 10, 20, and 30 wt%. This product is brittle without proper adhesion and cohesion and cannot meet the standard limits as an acceptable binder. It performs like long-term aged bitumen, reducing penetration and ductility and increasing the aging potential and viscosity. In another method, the neutralised sludge by adding quicklime was added to the asphalt mixture to replace fine aggregates in 50, 75, and 100 wt%. Using this product decreases the aging potential and moisture susceptibility up to 36.4, and increases rutting resistance up to 34.7%, indirect tensile strength up to 17.3%, and resilient modulus up to 17.3%. Despite the presence of large amounts of heavy metals in acid sludge, using this product in asphalt mixtures is an economical and completely hygienic solution for disposing of acid sludge. [ABSTRACT FROM AUTHOR]

The objective of this study is to create explicit prediction models for the complex shear modulus (G*) and phase angle (δ) of bitumen mastic fabricated using an evolutionary machine learning approach. The dynamic shear rheometer (DSR) test in frequency sweep mode at seven test temperatures was performed to measure G* and δ. In order to create specific prediction models for each modifier, multigene genetic programming (MGGP) was employed. These models took into account various factors including the dosage of the additive, filler volume filling rate, loading frequency, temperature, as well as the G* and δ values of the neat bitumen. In general, six explicit prediction models are presented for different additives with R-squared values of more than 0.9. The results showed that the hybrid machine learning approach can effectively develop precise, meaningful, and yet simple formulas for calculating G* and δ of the bitumen mastic. To gain a deeper understanding of the developed models, a comprehensive parametric study and sensitivity analysis were carried out. [ABSTRACT FROM AUTHOR]

The effect of different volume filling ratios (VFR) of filler on the flexural creep stiffness and complex shear modulus of bituminous composites can be identified using BBR and DSR test setups. This research compares the findings of extensive experimental studies with the biphasic heterogeneous micromechanical finite element (FE) models to introduce the Effective Volume Filling Ratio (EVFR). The different VFRs from 10 to 40% were selected to fabricate asphalt mastic samples. The effects of loading regime, temperature, loading frequency, and VFR on the mechanical behavior of asphalt mastic were investigated, and practical formulations were proposed to determine the EVFR for both shear and bending stiffening. It was found that for VFR ≤ 20%, the differences between the FE and test results are negligible under both loading schemes. However, higher VFRs cause a further increase in the stiffening and percolation effects which produce more differences between the experimental and FE results. [ABSTRACT FROM AUTHOR]

In this study, the mutual effect of polyphosphoric acid (PPA) and ethylene bis(stearamide) (EBS) modification was examined on the high and low service temperatures and viscosity of a performance grade (PG) 58-22 asphalt binder as a conventional neat bitumen widely used for paving applications. Three different dosages of PPA, including 0.5%, 1.0%, and 1.5% were used to modify the neat asphalt binder, and 3% of EBS as a selected percentage was added to PPA-modified samples. The dynamic shear rheometer was used to evaluate the high-temperature properties of the neat and modified bitumens based on standard Superpave protocol parameter (G*/sinδ) and multiple stress creep and recovery test. The low service temperatures of the samples were determined using the bending beam rheometer test. Also, the high-temperature ranges viscosities of the samples were evaluated using a series of rotational viscometer tests. The results have shown that increasing the PPA dosage up to 1.5% enhances the high service temperature of the neat asphalt binder 20.4°C and 14.7°C based on Superpave protocol and multiple stress creep and recovery test, respectively. However, it deteriorates the low-temperature performance of modified binders from −24.3°C to −16.9°C. The EBS can significantly compensate for the negative effect of PPA modification on the low-temperature behavior of modified bitumens. The optimum combination was 1% PPA+3% EBS as it provides a similar low-temperature grade to the neat asphalt binder having a significant two grades enhancement of high service temperature. Modifying a PPA-modified asphalt binder with EBS can reduce its viscosity at high temperatures, leading to saving energy of mixing and compaction. [ABSTRACT FROM AUTHOR]

Three-dimensional numerical finite element (FE) biphasic models verified against the experimental data were developed aiming to study the accuracy of FE modelling in the prediction of viscoelastic properties of crumb rubber-modified asphalt binders. In the numerical models, crumb rubber-modified asphalt binders are considered as a heterogeneous composite material consisting of the original asphalt binder and rubber particles which respectively have viscoelastic and hyperelastic behaviours. Three different dosages of crumb rubber including 10, 15 and 20 wt% of the original asphalt are added. To capture rubber particles distribution within the bituminous matrix, a random generation method by using the MOA software (French acronym for random object modeller) was implemented based on rubber's minimum and maximum particle sizes. In order to determine the viscoelastic properties of the original asphalt binder as well as the crumb rubber-modified ones, the dynamic shear rheometer (DSR) was used. The excellent agreement between the numerical FE modelling and experimental results witnessed the capability of biphasic finite element models to predict the visco-hyperelastic behaviour of crumb rubber-modified asphalt binders having an error lower than 9%. [ABSTRACT FROM AUTHOR]

This study investigated the effect of waste toner as a cost-effective enhancement modifier on short-term aging and moisture resistance of asphalt binders and mixtures. Moreover, the mechanism of asphalt binder aging and moisture resistance was reviewed, aiming to provide promising evaluation methods for assessing short-term aging resistance of asphalt binders as well as moisture resistance of asphalt binders and mixtures. First, the aging resistance of neat and toner-modified asphalt (TMA) binders was evaluated using three approaches: rheological aging index (RAI), viscosity aging index (VAI), and chemical functional group indices based on data obtained from Fourier transform infrared spectroscopy (FTIR) analysis. To measure viscoelastic and viscosity characteristics of neat and TMA binders, a dynamic shear rheometer (DSR) and a viscometer were employed, respectively. Second, the moisture resistance of asphalt binders and mixtures were investigated based on analyzing the infrared spectrum and tensile strength ratio (TSR), respectively. The findings indicated that modifying binder with low percentages of waste toner enhanced the short-term aging resistance. Also, TMA binders containing 12% of waste toner presented a significant improvement in moisture resistance of asphalt binders and mixtures. [ABSTRACT FROM AUTHOR]

Moisture damage is a major concern for evaluating the performance of asphalt mixtures. There are different types of experimental methods to determine the effect of moisture on mechanical and durability characteristics of asphalt mixtures. In this study, three different experimental approaches were implemented, including the boiling water test, the indirect tensile test, and the resilient modulus test, as well as the fracture energy analysis to evaluate moisture susceptibility of asphalt mixtures fabricated with different types of fillers including portland cement, limestone powder, and recycled concrete aggregates. Replacing the control filler material with these fillers resulted in improved fracture energy, which shows the stripping rate becomes slower by using them as fine aggregate. The fracture energy ratio of the asphalt mixture containing portland cement has the lowest rate of decrease for freeze-thaw cycles. Also, by applying a two-dimensional registration image-processing method as a low-cost soft-computing technique, an adhesion–cohesion index is introduced for determining the effect of moisture on adhesion between asphalt binder and aggregates as well as cohesion within asphalt mastic. Results have shown that there is a meaningful correlation between adhesion–cohesion index and number of freeze-thaw cycles, tensile strength ratio, resilient modulus ratio, and fracture energy ratio. To predict the adhesion–cohesion index of asphalt mixtures as an output of the image-processing method based on experimental results, a regression model was developed and verified in terms of the aforementioned parameters with an average prediction error of 4.46%. [ABSTRACT FROM AUTHOR]

This work focuses on the use of a heterogeneous generation method in order to develop a micromechanical model of Hot Mix Asphalt (HMA) that takes into account the effects of characteristics at the interfacial zone (IZ), where aggregate surfaces come into contact with the mortar matrix. Numerical calculations are conducted to investigate the effect of IZ mechanical characteristics on both the overall viscoelastic response of HMA and the local scale behavior. First of all, the HMA is treated as a biphasic material composed of mortar and granular inclusions. Next, a third phase is added between these two at each point of aggregate/mortar contact. Elastic and viscoelastic behaviors are assigned to the aggregates and mortar, respectively. The mechanical behavior of IZ varies between that of the inclusions and the matrix. At the global scale, these numerical results demonstrate that the use of triphasic micromechanical models improves the predictive accuracy of the dynamic modulus. At the local scale, a significant strain variation was found in each model. These results justify our triphasic modeling approach whenever local zone characteristics are the subject of interest. [ABSTRACT FROM AUTHOR]

In this research, the effect of adding SBS and vacuum bottoms residue on 60/70 neat asphalt binder have been carried out using classic and superpave testing methods. Adding SBS led to increase of softening point, elastic recovery and viscosity of asphalt binder. Besides, SBS reduced the penetration and ductility of specimens. Results of dynamic shear rheometer indicated that G and G sinδ reduced by adding the SBS content before and after aging while δ and G /sinδ parameters increased. Therefore, adding SBS improves the permanent deformation and fatigue resistance of neat asphalt binder. [ABSTRACT FROM AUTHOR]

Low-temperature cracking in pavement is a common distress in cold regions especially in North America; such distresses are shown to be highly related to binder low-temperature properties. To reduce the low-temperature cracking, several state departments of transportation are requiring the use of polymer-modified asphalt. However, polymer modification tends to be costly and in some cases led to phase separation in asphalt. Therefore, the current paper implements a fractional viscoelastic approach to study the effectiveness of several bio-based modifiers on improving asphalt binder's low-temperature characteristics. As such, implementing the bending beam rheometer (BBR) test, low-temperature rheological characteristics of asphalt binders, which are modified by four different bio-oils including biobinder from swine manure, corn stover, wood pellet, and miscanthus pellet are investigated. For this purpose, the BBR test was performed on asphalt binder samples containing 10% modifier at three temperatures of -12, -18, and -24°C. In order to analyze results of the BBR test, a fractional viscoelastic model is used to describe the relation of creep compliance and time. Utilizing the simple fractional model, relaxation modulus, storage modulus, and loss modulus are derived. In addition to the Superpave performance grading (PG) protocol, parameters of the simple fractional viscoelastic model are used to evaluate the performance of asphalt binders at low service temperatures through damping ratio and dissipated energy ratio. While biobinder from swine manure has the best performance by Superpave PG protocol analysis, corn stover shows the highest values for damping ratio and dissipated energy ratio among all modified asphalt samples. [ABSTRACT FROM AUTHOR]

Physiochemical and rheological properties of asphalt binder are known to directly relate to asphalt pavement performance as it relates to fatigue and low temperature cracking. While other performance criteria such as rutting is also affected by binder properties, the latter is known to be also very sensitive to aggregate skeleton and mixture gradation. To enhance pavement performance, asphalt industry has commonly used various modifiers to improve binder rheological properties both before and after it is exposed to oxidative aging. Among those additives are polymers, ground tire rubber, as well as several organic and inorganic fillers. Inorganic fillers such as nano-clay and silica fume showed to be promising candidates to enhance asphalt rheology and aging behavior. Such enhancements are typically attributed to the presence of silicate platelet and silica particles. Accordingly, this paper investigates the merits of application of mesoporous silica nanoparticles in this paper referred to as nano-silica as an asphalt binder additive to enhance binder rheological properties and oxidative aging resistance. To do so, different percentages of nano-silica were added to neat asphalt binder. Asphalt binder was then exposed to short-term oxidative aging using a rolling thin film oven (RTFO). To study the distribution of nano-silica in binder as well as the change in the chemical, rheological, and morphological properties of asphalt binders due to the addition of nano-silica, the scanning electron microscopy (SEM), Superpave tests, and Fourier transform infrared spectroscopy (FTIR) were conducted. It was found that introduction of nano-silica to asphalt binder can improve the rheological properties and oxidative aging resistance of asphalt binder. [ABSTRACT FROM AUTHOR]

This paper examines effects of a new biobased modifier, 'biobinder,' on low-temperature properties of asphalt binder and compares the results with those of conventional modifiers: crumb rubber, Gilsonite, styrene-butadiene-styrene (SBS), and polyphosphoric acid (PPA). Low-temperature characteristics of modified and nonmodified asphalts were studied using experimental and modeling approaches. A three-point bending beam rheometer was used to measure the stress-strain response of each specimen. A theoretical approach was used to determine stiffness and stress release rate; in addition, the Burgers model was implemented to predict the stored and dissipated energy ratio and quantity of derivation of creep compliance in each of modified and nonmodified asphalt specimens. Effects of various modifications were compared based on both the calculated stored and dissipated energy ratio and quantity of derivation of creep compliance. The proposed biobinder is produced from the thermochemical conversion of biomass (including animal waste, switch grass, and woody biomass). Biobinder is then blended with virgin binder to produce biomodified binder (BMB). This paper argues that the improved low-temperature rheological properties in biomodified binder is reflected in the enhancement in energy dissipation ratio and quantity of derivation of creep compliance. [ABSTRACT FROM AUTHOR]

This study exploits silica and polyphosphoric acid (PPA) synergistic effects to produce air-blown bitumen with desired stiffness and reduced carbon footprint. This in turn enhances the durability of the resulting air-blown bitumen while reducing gaseous emissions associated with its production. Here, we hypothesize that PPA-grafted silica made by adsorption of polyphosphoric acid to pristine silica nanoparticles promotes intermolecular interactions in vacuum bottom (VB), facilitating the production of air-blown bitumen. To test this hypothesis, laboratory experiments and modeling were used to determine the underlying molecular interactions determining PPA-grafted silica's role in facilitating the production of air-blown bitumen. Our molecular modeling showed PPA promotes the interaction between VB molecules by up to 10.28%; this combined with the increased polarity of VB molecules during the air-blowing process, leads to a significant increase in intermolecular interactions accelerating VB's stiffening. The latter was evidenced in our experiments showing that the required air-blowing time to reach desired stiffness measured by penetration and softening point was reduced up to 25% (time to reach required stiffness was reduced from 120 min to 90 min when silica-grafted polyphosphoric acid was used). Reduction of manufacturing time reduces VB's exposure to heat which leads to the formation of secondary organic aerosols. This promotes the economic and environmental sustainability aspects of the air-blowing process and contributes to resource conservation. [Display omitted] [ABSTRACT FROM AUTHOR]

[Display omitted] • Three types of additives were used at three different dosages: crumb rubber, SBS, and PPA to modify bitumen. • Genetic programming based closed-form equations are developed for G* and δ of modified bitumens. • G* and δ of original bitumen, test temperature and frequency were considered as model inputs. • The performance of models were successfully verified using statistical indices and external data validation. The objective of this research was to develop prediction models for complex shear modulus (G*) and phase angle (δ) of bitumens modified with crumb rubber, styrene-butadiene styrene, and polyphosphoric acid at low and moderate temperatures. The experiments consisted of three different dosages of each modifier added to the original bitumen followed by measurement of G* and δ of the original and modified bitumen using the dynamic shear rheometer (DSR) test in frequency sweep mode (21 loading frequencies from 0.1 to 100 Hz) at seven test temperatures: −22, −16, −10, 0, 10, 16 and 22 °C. Having the experimental database, a robust genetic programming (GP) method was used to develop an individual prediction model for each modifier based on temperature, loading frequency, the G* and δ of the original bitumen, and the dosage of the modifier. Results showed that GP successfully developed accurate and meaningful expressions for calculating G* and δ of the modified bitumen as two main constitutive components of the viscoelastic behavior of bituminous composites. Then, a parametric study and sensitivity analysis were performed on the developed models to better understand the effect of variables on the trend of the models. The modifier dosage is the most effective input variable of the model and the amount of G* and δ of the original bitumen accurately reflect the effect of temperature and loading frequency on viscoelastic behavior of the modified bitumen, as they behave linearly at the considered test temperatures. [ABSTRACT FROM AUTHOR]

• A biphasic random generated model was introduced to simulate microstructure of modified bitumen. • Using 2D or 3D heterogeneous viscoelastic FE models of the BBR test resulted in identical outputs. • Addition of crumb rubber having lower modulus than bitumen improved critical cracking temperature. This paper uses a heterogeneous micromechanical model to evaluate the resistance to thermal cracking in bituminous composites containing granular particulates. Thermal cracking is mainly caused by temperature fluctuations leading to accumulated stress that exceeds the strength of the materials. The presence of various granular particulates significantly affects a material's strength and capacity to release stress. Here, we use a two-dimensional heterogeneous numerical finite element model to evaluate and predict the thermal cracking characteristics of bitumen containing granular particulates such as crumb rubber and taconite. To develop the model, randomly distributed polygons using the Delaunay triangulation method were used to represent taconite and crumb rubber inside a bitumen matrix. The elastic properties of taconite and crumb rubber were assigned to the particulates, and the viscoelastic properties of the bitumen were modeled using a Prony series by implementing a simple fractional viscoelastic model. The study results showed that the flexural creep stiffness and creep rate calculated by the model were in good agreement with the measurements of experiments: the maximum errors were 6.15% for bitumen containing crumb rubber and 13.72% for bitumen containing taconite. Considering that flexural creep stiffness and creep rate are commonly used as indicators of thermal cracking resistance, the newly developed heterogeneous micromechanical model can be used to evaluate the thermal cracking resistance of bituminous matrices containing granular particulates. The model was further used to study the effects of temperature, elasticity, and concentration of particulates on the cracking resistance of the bituminous matrix. For instance, it was found that introducing 16% particulates with an elasticity of 1.02 MPa (representing crumb rubber) to bitumen improves its critical cracking temperature from −25 °C to −29.3 °C. This model provides insights to help the design of bituminous composites with desired cracking resistance properties by incorporating the proper particulates. [ABSTRACT FROM AUTHOR]

Asphalt binder resistance to permanent deformation at intermediate temperature significantly affects overall pavement resistance to rutting. To enhance asphalt resistance to permanent deformation, researchers have used various modifiers and additives such as styrene butadiene styrene (SBS) block copolymer, ethylene vinyl acetate (EVA), polyvinyl acetate (PVA), styrene butadiene rubber (SBR), and natural rubber latex. In this paper, the effectiveness of modification of asphalt binder by styrene-ethylene/propylene-styrene (SEPS) in order to enhance asphalt binder's resistance to permanent deformation has been investigated using two different evaluation methods: the Superpave specification parameter, , and the cross model for calculating zero shear viscosity (ZSV). The experiments were conducted using dynamic shear rheometer (DSR) frequency sweep test performed on both the neat sample and modified ones at 40, 50, and 60°C. Utilizing these two approaches, rutting resistance of modified asphalt binders are determined and then normalized using the rutting resistance of the neat asphalt binder as the control data in order to calculate the rutting resistance improvement ratio. The research results showed that regardless of the evaluation method, SEPS can significantly improve anti-rutting performance of asphalt binder. However, it was found that ranking of modified asphalt binders according to the two approaches is different. [ABSTRACT FROM AUTHOR]

• MOEA/D method has the best performance to select 17 features affecting faulting. • ANN- SAA with R2 value of 0.976 has been the best model for predicting faulting. • Pavement age, cumulative average precipitation, and elasticity modulus of concrete slab are the most important variables. This study aims to predict faulting failure of jointed plain concrete pavement (JPCP) using different variables. For this purpose, four feature selection methods were developed by combining the artificial neural networks (ANN) and four multi-objective metaheuristic optimization algorithms, namely, the Pareto envelope-based selection algorithm II (PESA-2), the strength Pareto evolutionary algorithm 2 (SPEA-2), multi-objective particle swarm optimization (MPSO), and multi-objective evolutionary algorithm based on decomposition (MOEA/D). The MOEA/D showed better performance compared to the other models, which identified 17 input variables affecting faulting failure. In the next step, the classic back-propagation (BP), Biogeography-based optimization (BBO), invasive weed optimization (IWO), and simulated annealing algorithm (SAA) were combined with the ANN to develop three prediction models for faulting failure. Modeling with metaheuristic optimization algorithms showed better performance than the ordinary ANN. The pavement age, cumulative average precipitation, and elasticity modulus of the concrete slab have the most significant impact on the formation and increase of faulting. [ABSTRACT FROM AUTHOR]