Search Results (106)

This research aimed to evaluate the impact of using brick waste powder (BWP) and varying lengths of polyester fibers (PFs) on the performance properties of asphalt concrete (AC) mixtures. BWP was utilized as a replacement for traditional limestone powder (LS) filler, while PFs of three lengths (3 mm, 8 mm, and 15 mm) were introduced. The study employed the response surface methodology (RSM) for experimental design and analysis of variance (ANOVA) to identify the influence of BWP and PF on the selected performance indicators. These indicators included bulk density, air voids, voids in the mineral aggregate, voids filled with asphalt, Marshall stability, Marshall flow, Marshall quotient, indirect tensile strength, wet tensile strength, and the tensile strength ratio. The findings demonstrated that BWP improved moisture resistance and the mechanical performance of AC mixes. Moreover, incorporating PF alongside BWP further enhanced these properties, resulting in superior overall performance. Using multi-objective optimization through RSM-based empirical models, the study identified the optimal PF length of 5 mm in combination with BWP for achieving the best AC properties. Validation experiments confirmed the accuracy of the predicted results, with an error margin of less than 8%. The study emphasizes the intriguing prospect of BWP and PF as sustainable alternatives for improving the durability, mechanical characteristics, and cost-efficiency of asphalt pavements. Full article

In this study, the feasibility of using three-dimensional (3D) printing technology to investigate the impact of macrotexture and microtexture on the skid resistance of asphalt pavement was verified. The macrotexture characteristics of the five types of real asphalt mixtures were captured, reconstructed, and printed. The comparison analysis of the skid resistance between the pavement and printed specimens was conducted, and the correlations and contribution proportions of the macrotexture and microtexture on skid resistance were also calculated. Results show that five printed asphalt mixtures present good consistency in the microtexture with a roughness of about 100 nm. The impact of thin water film on the skid resistance is insignificant for real asphalt mixtures, while it is significant for printed mixtures. The printed specimens under dry conditions show a similar British pendulum number (BPN) with the real pavement specimens under wet conditions, while the BPN under wet conditions for printed specimens are much smaller than the real ones but follows a similar variation trend. Mean profile depth (MPD) values of four printed asphalt concrete (AC) mixtures are well linearly correlated with their BPN under dry and wet conditions, especially for wet conditions with the R² of 0.91. The contribution proportion of macrotexture to the skid resistance is nearly 90% for the dry condition and about 50% for the wet condition. Full article

The skid resistance of asphalt pavement is vital for traffic safety and reducing accidents. Existing research using only wavelet transforms or fractal theory to study the pavement surface texture-skid resistance relationship has limitations. This paper integrates a wavelet transform and fractal theory to extract the multi-scale fractal features of pavement texture. It proposes an interpretable machine learning model for skid resistance assessments of sand-accumulated pavements. The three-dimensional (3D) texture of asphalt pavements is decomposed at multiple scales, and fractal and multifractal features are extracted to build a dataset. The performance of mainstream machine learning models is compared, and the eXtreme Gradient Boosting (XGBoost) model is optimized using the Covariance Matrix Adaptation Evolution Strategy (CMA-ES) algorithm. The SHapley Additive exPlanations (SHAP) method is used to analyze the optimal model’s interpretability. The results show that asphalt concrete with a maximum nominal particle size of 13 mm (AC-13) has the most concentrated fractal dimension, followed by open-graded friction course with a maximum nominal particle size of 9.5 mm (OGFC-10), with stone matrix asphalt with a maximum nominal particle size of 16 mm (SMA-16) being the most dispersed. The singular intensity difference of the multifractal (Δα) changes oppositely to the fractal dimension (D), and the fractal dimension difference of the multifractal (Δf) decreases with the number of wavelet decomposition layers. The CMA-ES-XGBoost model improves R² by 27.1%, 9%, and 3.4% over Linear Regression, Light Gradient Boosting Machine (LightGBM), and XGBoost, respectively. The 0.4–0.8 mm range fractal dimension most significantly impacts the model output, with complex interactions between features at different scales. Full article

Aggregates are the main material forming the skeleton structure of asphalt mixtures and are of great importance to resist external load for asphalt pavement. This study analyzed the packing characteristics and mechanical performance of aggregate blend to provide a reference for improving the bearing capacity of asphalt mixtures. The single-size, two-size, and multi-size aggregate blends were chosen to conduct the laboratory packing and California bearing ratio (CBR) tests. Six particle sizes were selected to design the single-size aggregate blends. Six size combinations were included and various mass ratios were considered for each size combination in the two-size aggregate blends. The multi-size aggregate blends were designed through the gradually filling method according to stone matrix asphalt with a nominal maximum particle size (NMPS) of 16 mm (SMA16) and dense asphalt concrete with an NMPS of 26.5 mm (AC25). The packing characteristics of the blends were quantified by the air voids and the percentage of contribution to the packing volume (PCPV). The mechanical performance of the blends was analyzed by the CBR value. The relationship between packing characteristics and mechanical performance was explored by data fitting. The results showed that the particle size and the size ratio have an effect on the packing characteristics and mechanical performance of aggregate blend. The smaller the particle size, the larger the air void of the blend. The blends composed of larger particles have better load bearing capacity than those composed of smaller particles. The larger the particle size ratio, the greater the air void of the blend and the weaker the load bearing capacity. The particles smaller than 1.18 mm and those smaller than 0.3 mm in AC25 mainly play a role in filling the voids and have little contribution to the load bearing. There is a certain correlation between the packing characteristics and mechanical performance of aggregate blend. Full article

The semi-circular bending method (SCB) is a useful test for evaluating the cracking resistance of asphalt mixtures with added reclaimed asphalt shingles. A mixture of the asphalt concrete AC 16 with 50/70 paving bitumen was used for the binder course test as a reference mix. The purpose of the paper is to evaluate two aging conditions (short-term and long-term) of the above-mentioned asphalt mixtures in relation to their fracture properties. Laboratory experiments are enhanced with the application of image processing techniques (digital image correlation and image segmentation) that account for the asphalt mixture heterogeneity. Consequently, they can provide a more detailed description of the specimen performance. Statistical analyses of the laboratory results indicate that the best sensitivity in terms of differentiating the tested mixtures, especially taking into account the aging conditions of the mixtures, was observed for the post-peak parameters such as the flexibility index (FI), toughness index (TI), and, above all, cracking resistance index (CRI), for which the average coefficient of the result variability is approximately 10%, while for the FI and TI parameters it is approximately 30%. Digital image correlation analyses provided a confirmative illustration of the aforementioned observation. Full article

This study investigates the potential use of tire-derived carbon black “N-330” as a sustainable waste binder in asphalt concrete mixtures, combined with resin as an alternative to the usual binding material in asphalt mixtures, “bitumen”. With the increasing demand for environmentally friendly construction materials, this research aims to assess the feasibility of incorporating resin tire carbon black N-330 “RTCB N-330” into asphalt as a full replacement for conventional binders. A comprehensive experimental program has been designed to evaluate the mechanical and performance properties of asphalt mixtures containing varying proportions of RTCB N-330, ranging from 2% to 10% by weight of the binder. The impact of replacing bitumen with resin that contains TCB N-330 on the physical, rheological, and thermal characteristics of RTCB N-330 as a modified asphalt binder is assessed in this study. To assess the binders, a number of tests were carried out, including standard tests for ductility, the softening point, and penetration. DTG (Derivative Thermogravimetric Analysis) and testing the thermal susceptibility index were performed. A higher percentage of TCB N-330 reduced the penetration while increasing both the softening point and ductility. Resin with 8% of TCB N-330 was the optimum percentage, which was compared with bitumen as a new environmentally friendly binder. The testing program involved the preparation of asphalt concrete specimens using a Marshall mix design, followed by a Marshall Stability test to evaluate the deformation resistance of the modified mixtures. The results were anticipated to demonstrate that incorporating N-330 into asphalt mixtures can enhance stability. The Marshall test results indicated that samples with 6% resin tire carbon black as the binder percentage “AC-RTCB6” demonstrated the highest stability among all RTCB samples. Moreover, these samples outperformed asphalt mixtures using bitumen as the binder in terms of stability. Also, the AC-B mixes exhibited lower flow values compared to the AC-RTCB mixes. The higher flow observed in the AC-RTCB specimens suggests that the addition of 1.5% xylene as a solvent to the resin was effective and positively influenced the flow characteristics. Full article

This paper discusses the properties of OMV Starfalt^® PmB 45/80 RC bituminous binder developed by the Austrian oil company OMV Downstream GmbH (OMV, Vienna, Austria), intended to be used for the recycling of reclaimed asphalt mixtures (RAP). The binder is characterized by various adjusted properties like higher needle penetration, higher softening point and higher elastic recovery (close to 95–100%), with the aim to compensate for the properties of the aged binder contained in the reclaimed asphalt. Three experimental sections were laid in the Czech Republic. Monitoring was performed on these sections (cores were taken after 0, 6, 12, 24, 44 and 93 months) with a consecutive analysis of the properties of the used binder—the binder was extracted from the cores and tested for penetration, softening point, critical temperature at bending beam rheometer (BBR), complex modulus and phase angle using a dynamic shear rheometer (DSR). The previously described binder was used during the construction of trial sections in the villages Domasov and Lednice and near the city Opava. In the first case, a surface course mixture of asphalt concrete type (AC surf 11+) contained 18% of RAP, whereas in the second and third case, a binder course mixture of asphalt concrete type (AC bin 22 S) comprised 23% and 39% of RAP, respectively. After approx. 8 years (Domasov and Lednice) and 3.5 years (Opava) in service, no failures or defects were recorded at any of the sections. This paper gives an update of the research work carried out in 2019 with the latest results from 2023. Full article

This study articulates findings from research pertaining to the utilisation of recycled geogrid in asphalt concrete. The issue of contamination of reclaimed waste with geosynthetic materials persists as a significant concern that warrants attention. In Poland, the allowable quantity of geogrid contaminants within the mineral–asphalt composition is 0.1% w/w. The preliminary evaluation of the validity of the research topic was conducted based on an analysis of correspondence and survey outcomes. The fundamental material research was executed employing elements of experimental design theory. The experimental domain considered two qualitative factors: the type of bituminous mixture for the binding layer (AC16W and AC22W) and the type of geogrid material (glass, carbon), in addition to two quantitative factors: the length of the recycled geogrid fibres ranging from 1 cm to 5 cm, and the quantity of recycled geogrid fibres varying from 0.2% to 1%. A generalised linear model was employed for the analysis, enabling the consideration of dependent qualitative factors in forecasting characteristics. The qualitative evaluation of the resultant solution was conducted using multi-criteria optimisation via the Harrington function. Consequently, recycled carbon mesh fibres demonstrated a notably positive impact, enhancing the material’s quality by 22%. Regarding glass mesh, the fibre content should not exceed 0.2% in the AC22W mixture, whereas it can be increased to 1% in the AC16W mixture. Comparing all evaluated mixtures, it was ascertained that surpassing the allowable contamination limit of 0.1% in geogrid form does not result in a significant reduction in the quality of asphalt concrete compared to the reference mix. Full article

In this study, the practical application of self-healing asphalt mixtures incorporating steel wool fibers and induction heating was investigated, expanding upon previous research that primarily assessed the self-healing properties rather than optimizing the heating process. Specifically, the aim was to enhance the induction heating methodology for a semi-dense asphalt concrete mixture (AC 16 Surf 35/50 S). In this research, the induction heating parameters were refined to improve the self-healing capabilities, focusing on the following three key aspects: (i) energy consumption, (ii) heating rate, and (iii) heating homogeneity. The findings reveal that the current intensity, the percentage of ferromagnetic additives, and coil shape are critical for achieving optimal heating conditions. Higher current intensity and additive percentage correlate with improved heating speed and reduced energy consumption. Additionally, variations in coil shape significantly influence the heating uniformity. Although asphalt mixtures with steel slag coarse aggregates exhibit slightly higher specific heat, this aggregate type is preferable for sustainability, as it allows for the recycling of industrial waste. The optimized mixtures can rapidly reach high temperatures, facilitating effective crack repair. This innovation offers a durable, environmentally friendly, and cost-effective solution for road maintenance, thereby enhancing the longevity and performance of asphalt pavements. Full article

The mechanical performance of Masterbatch Natural Rubber (MNR)-modified asphalt concrete (MNR-AC) was investigated and is presented in this paper. When compared to conventional asphalt concrete (AC), MNR-AC exhibits significantly superior performance across key mechanical parameters, including Marshall stability, indirect tensile strength (ITS), resilient modulus (IT Mr), indirect tensile fatigue life (ITFL), and rutting resistance. The most pronounced enhancements are observed at the optimal dry rubber to asphalt cement (r/b) ratio of 3%, at which MNR-AC demonstrates peak performance in all evaluated tests. The fatigue distress models for MNR-AC and AC reveal distinct logarithmic relationships, with an intersection point occurring at an r/b ratio of approximately 3%. This suggests that MNR-AC with an r/b ratio of 3% or less exhibits a markedly superior fatigue life compared to conventional AC under equivalent applied-stress conditions. MNR offers significant practical advantages over liquid natural rubber, including more consistent mixing, and simplified storage and transportation, positioning it as a promising and sustainable advancement in pavement material technology. Full article

Pavement skid resistance is significant for driving safety. British Pendulum Number (BPN) is commonly used as a low-speed skid resistance indicator, whereas sometimes it is impractical for data collection on roads in service. Since skid resistance is greatly affected by pavement surface texture, this research aims to evaluate pavement surface texture comprehensively and estimate the low-speed friction BPN from road surface texture on macro- and micro- scale. Asphalt Concrete (AC) and Stone Mastic Asphalt (SMA) were included. Road surface texture was evaluated from four aspects, texture depth, amplitude-related Root Means Square (RMS), elevation variances corresponding to different wavebands and texture spectral analysis. Texture depth indicators include Mean Texture Depth (MTD) and Mean Profile Depth (MPD). Elevation variances with three wavebands, from 5 mm to 50 mm, from 0.5 mm to 5 mm and from 0.024 mm to 0.5 mm respectively, were obtained. The results show that MPD is well correlated with MTD. Elevation variances with different wavebands demonstrates that the elevation variance of macro-texture with long wavelengths from 5 mm to 50 mm dominates the total variance. Spectral analysis shows that texture level is larger when the wavelength is beyond 4 mm, which is consistent with elevation variances. A linear regression between BPN and single texture index, as well as multiple linear regression analysis were conducted. The former regression result indicates that it is not feasible to estimate BPN using single index due to low correlation coefficient R². The latter shows that the BPN can be estimated from texture levels corresponding to 64 mm and 2 mm, and the micro-texture. The R² can be up to 0.684. This research will contribute to fast acquisition of BPN from pavement surface texture, thus improving skid resistance. Full article

Trail pavement roughness significantly impacts user experience and safety. Measuring roughness over large areas using traditional equipment is challenging and expensive. The utilization of smartphones and bicycles offers a more feasible approach to measuring trail roughness, but the current methods to capture data using these have accuracy limitations. While machine learning has the potential to improve accuracy, there have been few applications of real-time roughness evaluation. This study proposes a hybrid ensemble machine learning model that combines sequence-based modeling with support vector regression (SVR) to estimate trail roughness using smartphone sensor data mounted on bicycles. The hybrid model outperformed traditional methods like double integration and whole-body vibration in roughness estimation. For the 0.031 mi (50 m) segments, it reduced RMSE by 54–74% for asphalt concrete (AC) trails and 50–59% for Portland cement concrete (PCC) trails. For the 0.31 mi (499 m) segments, RMSE reductions of 37–60% and 49–56% for AC and PCC trails were achieved, respectively. Additionally, the hybrid model outperformed the base random forest model by 17%, highlighting the effectiveness of combining ensemble learning with sequence modeling and SVR. These results demonstrate that the hybrid model provides a cost-effective, scalable, and highly accurate alternative for large-scale trail roughness monitoring and assessment. Full article

Moisture-induced damage is a serious problem that severely impairs asphaltic pavement and affects road serviceability. This study examined numerous variables in asphalt concrete mixtures to assess their impact on moisture damage resistance. Mix design parameters such as the asphalt content (AC) and aggregate passing sieve No. 4 (PNo. 4) were considered as variables during this study. Additionally, hydrated lime (HL) was utilized as a partial substitute for limestone dust (LS) filler at 1.5% by weight of the aggregate in asphalt concrete mixtures for the surface layer. This study also investigated the potential enhancement of traditional asphalt binders and mixtures by adding nano-additives, specifically nano-silica oxide (NS) and nano-titanium dioxide (NT), at rates ranging from 0% to 6% by weight of the asphalt binder. To quantify the moisture damage resistance of the asphalt concrete mixes, two types of laboratory tests were employed: the tensile strength ratio (TSR) and the index of retained strength (IRS). The former characterizes moisture damage using tensile strength, whereas the latter uses compression strength. The physical properties of the asphalt binder, such as its penetration, softening point, and ductility, were also evaluated to identify the effects of the nanomaterials. The results indicated that variations in the mix design variables significantly affected the moisture damage resistance of the asphalt concrete mixtures. The maximum improvement values were obtained at the optimum asphalt content (OAC) and PNo. 4 (mid-range + 6%) with TSR values of 80.45 and 82.46 and IRS values of 74.39 and 77.14, respectively. Modifying asphalt concrete mixtures with 1.5% HL resulted in improved moisture resistance compared with mixtures without HL (0% HL) at each PNo. 4 level, reaching superior performance at PNo. 4 (mid-range + 6%) by 4.58% and 3.96% in the TSR and IRS tests, respectively. Additionally, both NS and NT enhanced the physical properties of the asphalt binder, leading to substantial enhancements in asphalt concrete mixture performance against moisture damage. A 6% dosage of NS and NT showed the best performance, with NS performing slightly better than NT. TSR was increased by 14.72 and 11.55 and IRS by 15.60 and 12.75, respectively, with 6% NS and NT compared with mixtures without nanomaterials (0% NM). Full article

The temperature estimation within asphalt concrete (AC) overlaid on cement-stabilized bases (CSB) is necessary for pavement analysis and design. However, the impact of different CSB gradations and rubberized CSB on AC temperature has not been thoroughly investigated. This study aims to clarify this effect by examining two types of CSB with nominal particle aggregate sizes of 25 mm and 31.5 mm, as well as the substitution of 5%, 10%, and 20% graded aggregates with rubber aggregates (RA) in CSB Dmax 25 using Ansys-based numerical simulations. The modelling also investigated 11 scenarios with different AC thicknesses (h_AC) ranging from 6 to 26 cm. The results indicated that CSB Dmax 31.5 reduced the daily maximum temperature fluctuation at the bottom of the AC (∆T_bottomAC) by approximately 8% compared to CSB Dmax 25. The inclusion of 5% RA in CSB Dmax 25 decreased ∆T_bottomAC by up to 20%. Additionally, the rubberized CSB increased the maximum temperature gradient between the top and bottom of the AC (ΔT_maxAC) by 9.5% with 5% RA and a 6 cm AC thickness; however, this increase was insignificant when h_AC exceeded 12 cm. This study also proposed the use of artificial neural network (ANN) models to predict the AC’s temperature distribution based on depth, the time of day, surface paving temperatures, and h_AC. The proposed ANN model demonstrated high accuracy (R² = 0.996 and MSE = 0.000685),which was confirmed by the numerical simulations, with an acceptable RMSE ranging from 0.28 °C to 0.67 °C. Full article

Currently, there are limitations in the research on the use of carbon fiber geogrids to prevent low-temperature cracking in asphalt pavements. This study aims to comparatively investigate the effects of carbon fiber-based geogrid type and dense-graded asphalt concrete mixture (AC) surface combined body (SCB) type on the low-temperature cracking resistance of reinforced asphalt pavement through low-temperature bending damage tests. Two geogrid types were prepared: a carbon fiber geogrid (CCF) and a glass/carbon fiber composite qualified geogrid (GCF). Two SCB types were studied: AC-13/AC-20 and AC-20/AC-25. The results show that the improvement in the flexural tensile strength of CCF is similar to that for GCF. Moreover, under reinforced conditions, the improvement in the low-temperature cracking resistance of AC-20/AC-25 is better than that for AC-13/AC-20 by 16.26–24.57%. Based on the analysis, the reasonable ratio range of the aperture sizes to the major particle sizes in the dense gradation can achieve a more effective interlocking effect. This can improve the low-temperature cracking resistance of carbon fiber-based geogrid-reinforced samples. Then, increasing the bending absorption energy is a key way of improving the low-temperature cracking resistance of carbon fiber-based geogrid reinforcements. Eventually, the fracture type of carbon fiber-based geogrid-reinforced samples is a mixed plastic–brittle fracture. These results can provide a reference for the road failure analysis of geogrid-reinforced asphalt pavement. Full article