Evaluation of Susceptibility of Asphalt Binders to Rutting through MSCR Test

Using modified asphalt binder is one of the most effective methods to solve the rutting problem of asphalt pavement, but the traditional G ∗ / sin δ parameter is not enough to characterize the rutting resistance of modified asphalt in field use. In order to accurately evaluate the high temperature performance of asphalt and establish the relationship between the rutting resistance of binder and mixture, two kinds of matrix asphalt and three kinds of modified asphalt were selected for DSR and MSCR tests. G ∗ / sin δ , nonrecoverable creep compliance Jnr, recovery rate R, and other parameters were used to characterize the permanent deformation resistance of the binder, and the correlation between these parameters and the results of rutting test was analyzed. The results show that Jnr3.2 can accurately characterize the permanent deformation resistance of asphalt, while the stress sensitivity index Jnrdiff is not applicable to all types of modified asphalt. In contrast, Jnrslope can better reflect the stress sensitivity of asphalt, and Jnrslope is significantly correlated with the results of rutting test.

Modelling of Deformation Resistance with Big Data and Its Application in the Prediction of Rolling Force of Thick Plate

The precision of traditional deformation resistance model is limited, which leads to the inaccuracy of the existing rolling force model. In this paper, the back propagation (BP) neural network model was established according to the industrial big data to accurately predict the deformation resistance. Then, a new rolling force model was established by using the BP neural network model. During the establishment of the neural network model, the data set of deformation resistance was established, which was calculated back from the actual rolling force data. Based on the data set after normalization, the BP neural network model of deformation resistance was established through the optimization of algorithm and network structure. It is shown that both the prediction accuracy of the neural network model on the training set and the test set are high, indicating that the generalization ability of the model is strong. The neural network model of the deformation resistance is compared with the theoretical one, and the maximum error is only 3.96%. Furthermore, by comparison with the traditional rolling force model, it is found that the prediction accuracy of the rolling force model imbedding with the present neural network model is improved obviously. The maximum error of the present rolling force model is just 3.86%. The research in this paper provides a new way to improve the prediction accuracy of rolling force model.

Full-Scale Model Experimental Study of the Flexural Behavior of Hollow Slabs Strengthened by UHPC

The hollow slabs strengthened by ultrahigh performance concrete (UHPC) composite beam show many advantages over traditional reinforcement methods. In this paper, full-scale model load tests were carried out on an nonstrengthened prestressed concrete hollow slab and an UHPC-strengthened prestressed concrete hollow slab, comparing the load deflection, crack width, bearing capacity, deformation resistance, and self-vibration frequency of the two. Static loading experimental results indicate that UHPC enhances the overall performance of prestressed concrete hollow slabs by decreasing deflection and crack width and improving bearing capacity. The strengthening effects of UHPC on a prestressed concrete hollow slab’s flexural behavior are also discussed, such as deflection, crack width, bearing capacity, deformation resistance, self-vibration frequency, flexural behavior, and cracking load. Deflection and crack width under a load of 800 kN decreased by 45.8% and 56.3%, respectively, and the initial self-vibration frequency, ultimate bearing capacity, and cracking load increased 19.2%, 21.4%, and 50%, respectively. The plane assumption can be made generally throughout the overall test process while using UHPC strengthening, which significantly constrains crack width and improves stiffness and deformation capacity. The UHPC layer and the prestressed concrete hollow slab were connected by shear studs to produce a good composite action between them, and the bending performance and bearing capacity of the whole structure were clearly improved. In addition to experiments, a validated numerical model is developed to verify the flexural performance of hollow slab strengthened by UHPC.

A Facile Nitriding Approach for Improved Impact Wear of Martensitic Cold-Work Steel Using H2/N2 Mixture Gas in an AC Pulsed Atmospheric Plasma Jet

In this study, we propose a rapid plasma-assisted nitriding process using H2/N2 mixture gas in an atmospheric pressure plasma jet (APPJ) system to treat the surface of SKD11 cold-working steel in order to increase its surface hardness. The generated NH radicals in the plasma region are used to implement an ion-bombardment for nitriding the tempered martensite structure of SKD11 within 18 min to form the functional nitride layer with an increased microhardness around 1095 HV0.3. Higher ratios of H/E and H3/E2 were obtained for the values of 4.514 × 10−2 and 2.244 × 10−2, referring to a higher deformation resistance as compared with the pristine sample. After multi-cycling impact tests, smaller and shallower impact craters with less surface oxidation on plasma-treated SKD11 were distinctly proven to have the higher impact wear resistance. Therefore, the atmospheric pressure plasma nitriding process can enable a rapid thermochemical nitriding process to form a protective layer with unique advantages that increase the deformation-resistance and impact-resistance, improving the lifetime of SKD11 tool steel as die materials.

The Influence of Zero Shear Viscosity of TLA-Modified Binder and Mastic Composition on the Permanent Deformation Resistance of Mastic Asphalt Mixture

Mastic asphalt (MA) has been particularly popular in recent years for bridge pavements due to many advantages such as easy application, good waterproofing properties, and high durability. However, the drawback of mastic asphalt in comparison to other asphalt mixtures is its lower resistance to permanent deformation. Trinidad Lake Asphalt (TLA) is often applied to make mastic asphalt resistant to permanent deformation. Practical experience demonstrates that serious failures may occur if MA pavement design and materials selection is not taken into account sufficiently. Therefore in this study, the influence of two parameters: zero shear viscosity (ZSV) of TLA-modified binder and mastic composition described by the filler–binder ratio, on the permanent deformation resistance of the MA mixture was evaluated. The primary purpose of determining the ZSV of the TLA-modified binders was to evaluate the rutting potential of the binders. The permanent deformation (rutting) resistance of the MA mixtures was evaluated based on static and dynamic indentation tests. The optimum content of TLA in the base bitumen and the optimum filler–binder ratio in the MA mixture were obtained based on multiple performance evaluations for modified binder, mastic and MA mixtures, i.e., 20% and 4.0, respectively.