Cracking is a common pavement distress that would cause further severe problems if not repaired timely, which means that it is important to accurately extract the information of pavement cracks through detection and segmentation. Automated pavement crack detection and segmentation using deep learning are more efficient and accurate than conventional methods, which could be further improved. While many existing studies have utilized deep learning in pavement crack segmentation, which segments cracks from non‐crack regions, few studies have taken the exact pavement crack detection into account, which identifies cracks in the images from other objects. A two‐step pavement crack detection and segmentation method based on convolutional neural network was proposed in this paper. An automated pavement crack detection algorithm was developed using the modified You Only Look Once 3rd version in the first step. The proposed crack segmentation method in the second step was based on the modified U‐Net, whose encoder was replaced with a pre‐trained ResNet‐34 and the up‐sample part was added with spatial and channel squeeze and excitation (SCSE) modules. Proposed method combines pavement crack detection and segmentation together, so that the detected cracks from the first step are segmented in the second step to improve the accuracy. A dataset of pavement crack images in different circumstances were also built for the study. The F1 score of proposed crack detection and segmentation methods are 90.58% and 95.75%, respectively, which are higher than other state‐of‐the‐art methods. Compared with existing one‐step pavement crack detection or segmentation methods, proposed two‐step method showed advantages of accuracy.

The objective of this study is to characterize the rheological properties and aging mechanism of asphalt binders blended with high percentages of biobinders using Fourier transform infrared spectroscopy (FTIR). The petroleum asphalt was partially replaced by the biobinders at fractions of 30 and 70% by weight. Rotational viscometer (RV) and dynamic shear rheometer (DSR) tests were conducted for the rheological properties, and the rolling thin film oven (RTFO) test was conducted for the aging simulation. Loss of volatiles was obtained from the RTFO test, whereas the oxidation characterization was investigated through the FTIR test. The rheology results showed that the bioblended asphalt binder exhibit different rheological properties as compared with the control asphalt binder before and after the RTFO-aging. The mass loss test showed that the loss of volatiles of biobinders were much higher than the control asphalt binder. FTIR spectra analysis showed that additional $\mathrm{C}═\mathrm{C}$ , $\mathrm{C}─\mathrm{O}$ , $\mathrm{C}═\mathrm{O}$ and OH bonds were generated during the aging. Further chemical analysis revealed that the aging of biobinder originates from three aspects: the loss of volatiles, the dehydrogenation which formulates higher molecular weight compounds such as asphaltene, and the oxidation which resulted in chemicals such as acids, alcohol, and ester.

This study investigates and evaluates the storage stability of asphalt binder modified by bio-oil at high temperature. Five bio-asphalts are prepared by adding 10, 15, 20, 25, and 30% bio-oil into 70# petroleum asphalt. The bioasphalts are statically stored for 48 h at four different temperatures: 120, 140, 160, and 180°C. The softening point test, rotational viscosity test, dynamic shear rheometer (DSR) test, and Fourier transform infrared spectroscopy (FTIR) test are applied. The top and bottom sections of samples after thermal storage are analyzed for thermal storage stability from three aspects: physical properties, rheological properties, and functional group composition. The results show that after thermal storage, the bioasphalts segregated and the softening point, viscosity, and antirutting factor of the bottom sections are larger than those of the top sections. The viscosities of the top and bottom sections of bioasphalt with 20% bio-oil are 0.507 and $0.643\mathrm{Pa}·\mathrm{s}$ , respectively, under the storage temperature of 140°C. Moreover, the thermal storage stability of bioasphalts decreases with an increase in bio-oil content and storage temperature. Furthermore, based on rheological properties and functional group analysis, it is found that physical segregation and chemical reactions occurred, such as carbonation reactions, reactions between the oligomers, and volatilization of aromatic compounds. Overall, it is recommended that the storage temperature should be kept below 160°C and the bio-oil content should be less than 25%.

Disposal of plastic wastes causes negative impacts including degradation of land and ocean and climate change. Reusing plastic wastes in concrete is one of the effective methods of reducing plastic disposal. Polyethylene terephthalate (PET) is one of the most abundantly available plastic wastes as it is commonly used for plastic bottles and food containers. This paper investigates the effects of treating PET wastes using hydrogen peroxide solution (H₂O₂) and calcium hypochlorite solution (Ca(ClO)₂) before incorporating in concrete as coarse aggregate replacements. The physical and mechanical properties of concrete were analyzed for three different percentages, namely, 10%, 20%, and 30%, replacement of natural aggregates with plastic aggregates. For all percentage of replacements, it was found that chemically treated plastic aggregates have no effects on the fresh density, but the slump decreased due to roughened surface of treated plastic aggregates. Chemical treatment improved the bond strength between cementitious matrix and plastic aggregates and reduced the gap at the interfacial transition zone (ITZ). These phenomena contributed to the improvement the compressive strength and lower the permeability and porosity.