•The anti-rutting efforts focus on improving the rheological properties of asphalt.•Semi-flexible and cool asphalt pavements can help reduce rutting depth.•The applicability of wheel tracking test ...was systematically analyzed.•It is unnecessary to perform rutting tests at a rather high temperature.•Multiple-stress mode should be considered in performing laboratory rutting test.
Permanent deformation, mainly referring to rutting, is one of the main distress modes of asphalt pavement. Exploring effective methods to mitigate the rutting distress is of great significance for providing a long-life and safe road. The rutting solutions were first reviewed. It was found that the efforts from academic and engineering industries focused on enhancing the rheological properties of asphalt binder by adding modifying powder, fiber or mixture into binder or mixture, as well as strengthening aggregate interlock and applying novel pavement structure. Semi-flexible asphalt pavement was suggested to be a promising method to fight the rutting distress, because it has a high mechanical property without scarifying the flexibility of asphalt pavement. In order to consider the influence of temperature on rutting occurrence, cool asphalt pavements, especially heat-transfer induced structures, were reviewed and deemed to be a new strategy for reducing rutting susceptibility of asphalt pavement. In order to evaluate the effectiveness of above rutting solutions, many tests, such as multi-stress creep recovery test for asphalt binder and wheel tracking test for asphalt mixture, were reviewed. By linking the reported results of wheel tracking test with high-temperature rutting mechanism it was advised to develop a test method that could reproduce the real field pavement environment, including multiple stress mode, temperature gradient control system and pavement structure, to assess the rutting response of asphalt mixture. This review is expected to provide an overall insight on the existing rutting solutions and test methods, and recommend future studying areas relevant to rutting distress.
A nano-scale electrochemical sculpture (denoted here as NES) method has been developed to create TiO2 nanotube arrays on the surface of titanium sheets for improved bonding between titanium and ...carbon fiber reinforced epoxy composite laminates. For comparison, other surface treatments including anodization in NaOH, Na2SiO3, Na2C4H4O6 and EDTA electrolyte (denoted as NaTESi) and electrochemical etching in alkali solution (denoted as ALK) were carried out to investigate their effects on the surface morphology, wettability and the shear strength between titanium sheets and epoxy resin. The results from single-lap tests showed that the apparent shear strengths between titanium sheet and epoxy with NaTESi, ALK and optimized NES treatments have been improved by 37.2%, 53.9%, and 70.9%, respectively, in comparison with that of non-treated pristine samples. The samples in single-lap tests showed a mixture mode of cohesive and interfacial failures where the interfacial failure occurred at the epoxy/metal-oxide interface and the oxide films formed during the surface treatments remained intact. Utilizing the treated titanium sheets, fiber metal laminates (FMLs) were fabricated and their interlaminar shear strengths (ILSS) were found to increase by 43.5%, 56.1%, and 75.0%, respectively, compared to pristine samples, showing the promise of the nano-patterning technique.
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Hard metallic coatings can provide exceptional protection for industrial settings; however, they usually have a uniform microstructure and suffer from poor adhesion with substrates because of ...stress/strain incompatibility induced by the sharp interface. Here, a gradient structure that transitions from coarse-grained Ni to nanocrystalline/amorphous Ni–P alloy has been designed to improve the adhesion performance of the electrodeposited Ni–P coatings. Based on two measures of adhesion performance, a high interface shear strength of ∼282.6 MPa and high bending strength of ∼868.4 MPa have been determined for the gradient-structured Ni–P coatings on the CuCrZr alloy substrate, which are increased, respectively, by ∼90% and ∼60% from those of the conventional monolithic-structured Ni–P coating. Post-mortem fractographic analysis reveals that introducing the gradient structure accommodates plastic deformation of the coating and provides exceptional crack arrest capability, contributing to the enhancement of adhesion performances under both shearing and bending. The present work not only reveals how the adhesion performance can be significantly improved in gradient-structured Ni–P coatings, but also provides a promising methodology for manufacturing novel GS metallic coatings with a combination of excellent surface functions and strong interface adhesion.
The interfacial interactions and bonding of carbon fiber (CF) reinforced poly(ether-ether-ketone) (PEEK) composites is improved by applying polyether imide (PEI) and graphene oxide (GO) complex ...sizing at different ratios at the interface. The thermally stable polyether imide (PEI) and graphene oxide (GO) complex sizing is prepared and then coated on carbon fiber surfaces homogeneously. The sizing layer forms on the fiber surfaces, and multiple GO sheets are introduced successfully surrounding the carbon fibers. The surface morphologies of carbon fibers change distinctly with different GO contents. The interfacial shear strength (IFSS) increases from 43.4 MPa for bare fiber reinforced PEEK composites to 49.4 MPa for composites reinforced by carbon fibers coated with PEI only. However, a significant improvement is achieved when GO sheets are introduced to the CF surfaces, making the IFSS grow up to 63.4 MPa. Furthermore, the dynamic mechanical tests show that the normalized damping area results of carbon fibers coated with complex sizing decrease remarkably by about 50%. DMA results, interlaminar shear strength (ILSS) test and flexural test results are in agreement with each other, suggesting better interface bonding of composites by applying PEI and GO complex sizing. Besides, the interfacial interaction mechanism in modified composites is proposed. The enhanced interfacial performance is caused by the positive effect of complex interface layer.
This paper investigated shear-related roughness classification based on Fuzzy comprehensive evaluation, and established a new strength model of natural rock joint. The joint profiles were extracted ...from 3D data to evaluate roughness, and a series of direct shear tests were carried out on three kinds of natural rock joints. The height statistical parameters Sm, Sq, Ss and Sk, and the textural statistical parameters Si, Sc, and Z2 were measured by Talysurf morphology instrument. Considering the existence of strong positive relations between Sm and Sq, and Z2 and Si, the four morphological parameters of Si, Sq, Sc, and Sk are considered as the main influencing factors related with rock joint shear behaviors. A new fracture roughness coefficient FRC is proposed based on fuzzy comprehensive evaluation (FCE), which considers that the influence of multi morphology parameters on the roughness of rock joint surface, and generally, the FRC is higher than the JRC. Compared with the previously published shear strength models, the proposed FRC-JCS shear strength model, which can more comprehensively reflect the influence of joint surface morphology parameters to shear strength, are in better agreement with the experimental data.
Dopamine modified aramid fiber (AF) surface was grafted with amino functionalized graphene oxide to improve the interfacial adhesive performance. The self-polymerized polydopamine (PDA) coating and ...subsequent amino GO grafting on the AF surface attributed to the increase in its surface roughness and surface-active groups. The functional groups, chemical composition and surface topography of unmodified and modified AF was investigated by Fourier transform infrared (FTIR) spectroscopy, X-ray photoelectron spectroscopy (XPS) and Scanning electron microscopy (SEM). The interfacial properties were analyzed by measuring interfacial shear strength (IFSS) of unmodified and modified AF embedded epoxy matrix. Further, the properties were tuned by optimizing the reaction temperature and concentration of ethylenediamine. The IFSS of AF/epoxy composites was increased by 34% after grafting amino graphene oxide.
•The self-polymerized polydopamine) (PDA) layer was deposited on aramid fibers.•An efficient route to functionalize aramid fibers based on dopamine chemistry was developed.•With PDA coating and further amino GO grafting, the rougher fiber surface significantly improved the IFSS.
Carbon fiber (CF) has rarely been presented as a promising electromagnetic wave (EMW) absorber because of its excessive electrical conductivity. Herein, the continuous preparation of carbon ...nanotubes/carbon fiber (CNTs/CF) multiscale reinforcements and microwave absorbers was realized by one-step chemical vapor deposition (CVD) at different temperatures. Beneficial from the intertwined CNTs, good graphitization and crystallinity, and satisfactory epoxy resin wettability, CNTs/CF650 and its composites show excellent tensile, interfacial and interlaminar shear strength. Importantly, CNTs/CF650 obtains a high-performance EMW absorption ability with a minimum reflection loss (RLmin) of −56.11 dB at 7.36 GHz, and delivers an effective absorption band (EAB) of 3.6 GHz at an ultrathin thickness of 1.18 mm. Notably, CNTs/CF700 exhibits the widest EAB (4.2 GHz) at merely 1.35 mm, basically covering the entire Ku-band. The superior RLmin and boosted EAB stem from the synergistic effects of multiple heterointerfaces, enriched defects, proper electronic conductivity, and rational impedance matching. Therefore, the work demonstrates a facile and efficient strategy to develop strong EMW absorbers based on CF with light weight, thin thickness, and high strength.
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Carbon fiber reinforced composites (CFRC) are in huge demand in aviation industry for reducing the fuel consumption, despite the unfavorable electromagnetic interference (EMI) shielding property. In ...this work, carbon fiber fabrics (CF) were coated by a thin layer of nickel (Ni) using electroless plating to increase the electrical conductivity of the composites. Dopamine was then self-polymerized on Ni coated CF (CF-Ni) surfaces to enhance the interfacial interactions between fibers and epoxy matrix. The results showed that the introduction of 0.39 wt% of polydopamine (PDA) content leads to a significant increase of interlaminar shear strength (ILSS), tensile strength and modulus by 70.7%, 22.7% and 15.3%, respectively, compared with CF-Ni/epoxy composites with free of PDA. The dominant facture mechanisms changed from fiber pulling-out and/or debonding to fiber breakage after the introduction of PDA. Compared with CF/epoxy composites, the EMI shielding effectiveness (SE) of CF-Ni/epoxy composites increased by 77.2% and slightly decreased with the increase of the PDA content. In order to further optimize the overall performances of the composites, the laminates structures were specially designed by replacing 2 plies of CF-Ni-PDA with CF-PDA in the middle according to EMI shielding mechanisms. The composites with special laminate stacking exhibited outstanding ILSS (61.2 MPa) and EMI SE (31.0 dB), which are dominant over most reported structural composites. The effects of humidity on the mechanical and EMI shielding properties were evaluated as well, indicating that the composites played a huge application potential in aircraft.
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The main objective of this study is to evaluate and compare the performance of different machine learning (ML) algorithms, namely, Artificial Neural Network (ANN), Extreme Learning Machine (ELM), and ...Boosting Trees (Boosted) algorithms, considering the influence of various training to testing ratios in predicting the soil shear strength, one of the most critical geotechnical engineering properties in civil engineering design and construction. For this aim, a database of 538 soil samples collected from the Long Phu 1 power plant project, Vietnam, was utilized to generate the datasets for the modeling process. Different ratios (i.e., 10/90, 20/80, 30/70, 40/60, 50/50, 60/40, 70/30, 80/20, and 90/10) were used to divide the datasets into the training and testing datasets for the performance assessment of models. Popular statistical indicators, such as Root Mean Squared Error (RMSE), Mean Absolute Error (MAE), and Correlation Coefficient (R), were employed to evaluate the predictive capability of the models under different training and testing ratios. Besides, Monte Carlo simulation was simultaneously carried out to evaluate the performance of the proposed models, taking into account the random sampling effect. The results showed that although all three ML models performed well, the ANN was the most accurate and statistically stable model after 1000 Monte Carlo simulations (Mean R = 0.9348) compared with other models such as Boosted (Mean R = 0.9192) and ELM (Mean R = 0.8703). Investigation on the performance of the models showed that the predictive capability of the ML models was greatly affected by the training/testing ratios, where the 70/30 one presented the best performance of the models. Concisely, the results presented herein showed an effective manner in selecting the appropriate ratios of datasets and the best ML model to predict the soil shear strength accurately, which would be helpful in the design and engineering phases of construction projects.
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