Asphalt Concrete Research Articles

Improved fracture toughness evaluation for fiber-reinforced asphalt concrete through double-parameter theory

Fracture toughness serves as a key parameter in the design and durability assessment of asphalt concrete. Quantifying the fracture toughness for fiber-reinforced asphalt concrete (FRAC), remains challenging due to the incorporation of fibers. This study proposes an improved method for evaluating the fracture toughness of FRAC, based on the double-parameter theory derived from the theoretical concepts of stress intensity factor K and energy release rate (double-K and double-G fracture models). Using Digital Image Correlation (DIC) technology, crack propagation during three-point bending beam tests on FRAC beams was measured, refining the calculation of critical crack length ac in the double-K fracture parameters. Additionally, a method is introduced to calculate the improved solution of double-G fracture parameters by monitoring crack propagation in real-time to determine the effective crack length a, and simultaneously computing the energy absorbed per unit crack extension, thereby constructing the J-R curve during stable crack growth phases. The fracture toughness of FRAC is evaluated by the improved method obtained double-G fracture parameters were used in Virtual Crack Closure Technique (VCCT) simulations to achieve virtual modeling of FRAC. The results demonstrate that the improved method provides accurate fracture performance indicators for FRAC. Moreover, the study establishes modified calculation formulas for (GICu) and (KICu) at unstable fracture toughness for FRAC at different temperatures, considering various fiber types and contents, thereby enhancing computational efficiency for practical applications. This research contributes to more accurate and effective methods for testing and evaluating the fracture performance of FRAC

Sustainable application of recycled plastics in asphalt pavement: Case study of a trial in Newtonville, Ontario, Canada

Global research on using plastic waste in asphalt roads highlights its benefits: recycling waste, reducing greenhouse gas emissions, and providing an alternative to non-renewable asphalt binders. This study aims to bridge the gap between laboratory results and field performance of recycled plastic-modified asphalt in cold regions, promoting broader adoption. Laboratory analysis of core samples was performed as part of a quality assurance program. High-temperature rutting resistance was evaluated using the Hamburg wheel tracking test, while low-temperature cracking resistance was assessed through semi-circular bending testing. Results show that the impact of recycled plastics and fibers on rutting resistance varies with temperature, with the greatest benefit at the highest temperatures. For low-temperature cracking resistance, polyethylene terephthalate (PET) fibers outperform mixed plastics by delaying crack propagation. Low-temperature conditioning can induce thermal shrinkage in the asphalt mixture, slightly moderating the effects of recycled plastics and fibers.

Assessment of moisture susceptibility and stripping effect in wax based warm mix asphalt

Assessment of moisture susceptibility and stripping effect in wax based warm mix asphalt

Evaluation of Mechanical Properties of Warm-Mix Asphalt Mixtures Prepared with Sasobit and Zeolite Additives

This study aimed to evaluate the impact of different additive percentages on the mechanical properties and durability of warm-mix asphalt. Two types of additives, Sasobit as an organic additive and Zeolite as a water-based additive, along with bituminous foam, were used at 2%, 4%, and 6% levels in modified asphalt mixes. Rutting resistance, moisture susceptibility, and cracking resistance were assessed using semi-circular bending tests, dynamic creep tests, and indirect tensile strength tests, respectively. Additionally, a two-dimensional performance interaction diagram was developed. The results indicated that incorporating different percentages of Sasobit and Zeolite additives improved rutting and cracking resistance, respectively. Zeolite showed a positive impact on enhancing the resistance of the asphalt mixture against moisture susceptibility, while Sasobit had a negative effect. Moreover, the influence of these additives on mechanical performance intensified with increasing percentages. Notably, the mixture containing 6% Zeolite demonstrated the highest resistance to moisture susceptibility, while the mixture with 6% Sasobit showed the lowest. Furthermore, the performance interaction diagram results suggested that using 4% and 6% Zeolite along with 4% Sasobit is optimal for rutting and cracking resistance. Considering the degradation mechanisms of moisture susceptibility, rutting, and cracking, mixtures with 6% Zeolite and 4% Zeolite exhibited satisfactory performance against these factors.

Investigating the Influence of Steel Fibre on Self-Healing in Stone Mastic Asphalt Mixtures Using the Indirect Tensile Strength Test: A Case Study Aligned with the Sustainable Development Goal (SDG) 9

Investigating the Influence of Steel Fibre on Self-Healing in Stone Mastic Asphalt Mixtures Using the Indirect Tensile Strength Test: A Case Study Aligned with the Sustainable Development Goal (SDG) 9

Exploring Cool Pavement Technologies: A Lab-Based Experimental Analysis of Temperature and Reflectivity

Urban heat islands (UHI) have become an increasingly pressing issue owing to the global warming trend and a steady growth of urban areas. Revegetation, shading, or the reduction of sealed surfaces is not always possible in cities. Therefore, one way to fight UHIs is through adapting currently used pavements. This study assesses the thermal behavior of 12 different pavement materials in a custom-made test stand. The materials include mastic asphalt ( MA 8, MA 8 white), porous asphalt ( PA 4, PA 4 abraded, PA 4 white, PA 8, PA 8 abraded, PA 8 white), asphalt concrete ( AC 11 transparent, AC 8 yellow), and semi-flexible pavements ( SFP 8, SFP 8 zeolite). The albedo was assessed using pyranometer. Sensors and thermal imaging were used to measure temperatures during two simulated heat cycles. Both the temperatures underneath the test specimens and at the surface were considered, as well as the cooling times of the materials. The results showed high maximum temperatures for PA and MA, as well as low maxima for the white painted materials, with differences in maxima of up to 15°C. Porous asphalt, like PA 8, cools faster than MA 8 from roughly 47°C to 28°C, taking 3.7 h compared with MA 8’s 5.1 h. This highlights the importance of considering cooling times and regional solar phases in experimental setups. Through the wide range of tested materials, a significant linear correlation between the measured albedo and surface temperature was proven. Ultimately, a foundation for thermal comparability between these materials was established.

Coal gangue based geopolymer as an additive of warm mix asphalt: Preparation and properties

Coal gangue based geopolymer as an additive of warm mix asphalt: Preparation and properties

Masterbatch Natural Rubber—Innovative Asphalt Cement Additive for Sustainable Flexural Pavements

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.

Meadows or asphalt road – Does momentary affective well-being vary with immediate physical environment? Results from a geographic ecological momentary assessment study in three metropolitan areas in Germany

We investigated the association between the immediate physical environment of individuals and individual fluctuations of momentary affective well-being in everyday life with a focus on medium sized metropolitan areas in Europe representing a typical living environment of a large proportion of the world’s population. The sample comprised 365 individuals (54.8 % female) with participants ranging from 14.08 to 88.27 years of age (M = 43.9, SD = 20.9). In an geographic ecological momentary assessment (GEMA), participants were prompted six times a day on at least 9 days over the course of 3 weeks, covering a total of six weekdays and three weekend days on mobile phones to report their momentary affective well-being. Urban land use categories (forest, water, urban green) were assessed with GPS-localization as environmental variables. Additionally, sunshine, rainfall, whether participants were inside or outside as well as whether they were alone or had company were included into the analyses.We used dynamic structural equation modelling to model the inter- and intraindividual differences as well as fluctuations and assess potential covariates while acknowledging the autoregressive nature of affect.The results showed that on individual level, fluctuations of momentary affective well-being were associated with sunshine, having company and travelling. No significant association emerged for urban green, forest, and water neither within individuals nor between. Methodological as well as conceptual implications are discussed and an interpretation of the present findings are provided.

Study on rutting performance of synthetic zeolite based warm mix asphalt using railway carriage workshop incineration ash as filler

Study on rutting performance of synthetic zeolite based warm mix asphalt using railway carriage workshop incineration ash as filler

Study of the Performance of Warm-Mix Asphalt Containing Recycled Concrete as a Coarse Aggregate in Egypt and the Middle East

Study of the Performance of Warm-Mix Asphalt Containing Recycled Concrete as a Coarse Aggregate in Egypt and the Middle East

Study of the Fatigue Damage Characteristics of Emulsified Asphalt Mastics

Study of the Fatigue Damage Characteristics of Emulsified Asphalt Mastics

Influence of direct coal liquefaction residue (DCLR) on the rutting behavior of asphalt mixture with the discrete element method

The research explores the influence of direct coal liquefaction residue (DCLR) as a fine aggregate on the rutting behavior of asphalt mixtures (AMs). Four AMs were prepared and modeled, namely AM (AM-0), AM with 2.36 mm DCLR (AM-2.36), AM with 1.18 mm DCLR (AM-1.18), and AM with 0.6 mm DCLR (AM-0.6). Firstly, the rutting depth and uplift height of AMs were analyzed. Results indicated that the rutting depth and uplift height of AMs increased with rising temperatures and loads. The order of rutting depth and uplift height of AMs at different temperatures and loads was: AM-0＞AM-2.36＞AM-1.18＞AM-0.6. This suggests that DCLR replacing fine aggregates improved the high-temperature performance of AMs, and DCLR replacing 0.6 mm fine aggregate was the best alternative. Moreover, the influence mechanism of DCLR on the rutting behavior was investigated by the force chain distribution and particle movement. The results showed that the rutting deformation was caused by the movement of 0.6–2.36 mm particles. Compared with AM-0, the chain distribution of AM-2.36 was uniform and sparse, and the movement of 0.6–2.36 mm particles in AM-2.36 was small. This was due to the composite modification effect of DCLR within the AM, which increased the bonding degree of asphalt mastics. This enhancement improved connectivity between aggregates, strengthened their load transfer capacity, and raised the AM's overall self-organizing adaptability. Finally, it was also found that DCLR as fine aggregates served dual roles within the AM, acting both as a skeleton and a filler.

Image-driven prediction system: Automatic extraction of aggregate gradation of pavement core samples integrating deep learning and interactive image processing framework

Aggregate gradation plays a crucial role in determining the asphalt pavement performance, necessitating assessment post-construction. Additionally, efficient gradation measurement is vital for the design and construction of reclaimed pavement. This study proposes a methodology for predicting gradation based on imagery. Initially, a scanning device is devised to capture unfolded side surface images of pavement core samples. Subsequently, an interactive software named PyImageJ is developed for image post-processing and acquiring aggregate feature information. A morphological model is then introduced to determine the mass ratios among various grading levels of coarse aggregates with nominal particle sizes greater than 2.36 mm. Finally, sequence prediction models are established to forecast the mass ratios among different grading levels of fine aggregates with nominal particle sizes smaller than 2.36 mm. Simple conversion of the mass ratios can yield the gradation. Experimental results indicate that the Long Short-Term Memory (LSTM) network offers more accurate predictions for the mass ratios of fine aggregates in stone mastic asphalt (SMA-13), with an R-squared value of 0.8985. Conversely, one-dimensional convolutional neural networks (1D CNN) are better suited for predicting the fine aggregate mass ratios in asphalt concrete (AC-20 and AC-25), with R-squared values of 0.9010 and 0.8824, respectively. Visualization results demonstrate that the predicted complete gradation closely aligns with the actual values (R-squared > 0.99), opening a new avenue for evaluating pavement quality.

Temporal Homogenization Modeling of Viscoelastic Asphalt Concretes and Pavement Structures under Large Numbers of Load Cycles

Temporal Homogenization Modeling of Viscoelastic Asphalt Concretes and Pavement Structures under Large Numbers of Load Cycles

Monte Carlo simulations of the fracture resistance of an asphalt pavement layer

The purpose of the proposed numerical model is to analyze the cracking of the wearing course in a pavement overlay, assuming a pre-existing crack that passes through the binding layer and base. The computations employed the author's simulation-based Monte Carlo material model, which describes the failure process of a Semi-Circular Bend (SCB) specimen during standard laboratory testing of asphalt concrete. A key feature of this model is the incorporation of the random nature of material parameters, allowing for the simulation of result dispersion when analyzing a sufficiently large population of samples. The proposed FEM model and obtained material data were directly applied to the numerical analysis of the pavement structure. The comprehensive computational algorithm allows for a random description of the load that induces crack propagation in the pavement wearing course, leading to the creation of a histogram that defines the range of failure load dispersion. Such supporting calculations can assist in optimizing asphalt mix design and, in the future, may allow for the estimation of pavement structure reliability.

Laboratory and Field Evaluation of Asphalt Concrete Modulus &Critical Strain Inputs for M-E Flexible Pavement Design in the State of Illinois

This study aims to update the current algorithm for modulus prediction of hot mix asphalt in the state of Illinois-USA. Numerically, laboratory, and field-obtained modulus and strain levels were connected to advances in asphalt materials and current design criteria. Four mix designs were selected and combined with seven different binders for modulus measurements. The reference experimental results were compared to: the current Illinois Department of Transportation (IDOT) modulus algorithm, traditional regression models, a Bayesian Neural Network (BNN) model, and field measurements obtained using the Traffic Speed Deflectometer. Results showed that the current IDOT algorithm under-predicts modulus and BNN (840 data points, R^2 = 0.986) outperformed the Witczak and Hirsch models. Field modulus and critical strains were sensitive to temperature and showed considerable variability, but confirmed that HMA in perpetual pavement sections performs under low strain levels. These findings guided considerations for an updated design method: realistic modulus prediction can be achieved using data-driven methods and less conservative strain criterion might be considered.

A Cold Winter Day.

Description I am a post-anesthesia care unit nurse who works in a busy ambulatory surgery center, and I consider myself a closet photographer. I love taking photographs of nature. It helps me relax and focus after a busy day. This photograph was taken on my way home on a very cold and snowy day. I found the trees stunning with their white snowy branches contrasting the black asphalt road. Such a peaceful view of nature.

Investigation on mesostructural characteristics of different pore types within asphalt mixtures under freeze–thaw cycles using CT scanning technology

The distribution of water within asphalt pavement contributes to water-induced damage, with pores serving as the primary conduit for water infiltration. However, understanding the microstructural changes in various pore types amid extreme water conditions remains limited. This study focuses on three type asphalt mixtures which common used in the surface-layer of asphalt pavement and utilises Computed Tomography (CT) technology to categorise internal pores in asphalt mixtures into isolated, semi-connected, connected, and open pores. Examining the impact of freeze–thaw cycles, the research quantifies the connectivity and evolution of each pore type in asphalt concrete. The findings reveal that after freeze–thaw cycles, small isolated pores emerge while some larger isolated pores amalgamate with open pores, leading to a reduction in isolated pores. Volumetric alterations predominantly occur in open pores, where semi-connected pores either expand autonomously or merge with existing connected pores. Overall, the pore network enlarges, yet its complexity remains relatively stable. Notably, microstructural parameters of isolated and semi-connected pores exhibit a weaker correlation compared to total and open pores, with the most robust correlation found between average coordination number, volume, and other microstructural characteristics. Among the pore types, open pores demonstrate the highest sensitivity to freeze–thaw cycles. Substantial variations in correlation coefficients and freeze–thaw sensitivity are observed across different pore types and within the same pore type with distinct microstructural parameters. Thus, a comprehensive analysis encompassing multiple microstructural parameters across diverse pore types is imperative for a thorough evaluation of pore micro characteristics.

Influence of Chemical, Morphological, Spectroscopic and Calorimetric Properties of Agroindustrial Cellulose Wastes on Drainage Behavior in Stone Mastic Asphalt Mixtures.

New asphalt mixtures have been improved by using fibers (polypropylene, polyester, asbestos, carbon, glass, nylon, lignin, coconut, sisal, recycled rubber, PET, wood, bamboo, and cellulose), reducing the temperature and compaction energy for their collocation, minimizing the impact on the environment, increasing the tenacity and resistance to cracking of hot mix asphalt (HMA), preventing asphalt drainage in a Stone Mastic Asphalt (SMA). Hence, this paper aims to evaluate the influence of the chemical (lignin content, ash, viscosity, degree of polymerization, and elemental analysis), morphological (SEM), spectroscopic (FTIR-ATR and XRD), and calorimetric (ATG and DSC) properties of celluloses from bagasse Agave tequilana Weber var. Azul (ABP), corrugated paperboard (CPB) and commercial cellulose fiber (CC) as Schellenberg drainage (D) inhibitors of the SMA. The ABP was obtained through a chemical process by alkaline cooking, while CPB by a mechanical refining process. The chemical, morphological, spectroscopic, and calorimetric properties were similar among the analyzed celluloses, but CPB and ABP cellulose are excellent alternatives to CC cellulose for inhibiting drainage. However, CPB is the most effective at low concentrations. This is attributed to its morphology, which includes roughness, waviness, filament length, orientation, and diameter, as well as its lignin content and crystallinity.