Enhui Yang

Analysis of measured strain response of asphalt pavements and relevant prediction models

Abstract In order to investigate the actual strain response of asphalt pavement under real condition, three types of asphalt pavement sections with typical surface structures are built. The effects of axle configuration, axle load, speed and testing temperature on strain response of asphalt pavement were analysed through in situ dynamic loading. Experimental results indicate that the strain response at the bottom of the asphalt surface layer increases with increasing axle load and temperature, but decreases with the rise of speed. On the other hand, the temperature exerts different influence levels on pavement sections with different structures. It is also concluded that the tandem axle load could lead to a greater strain response than that of single axle load. Applying the analysis of variance, the effects of pavement surface temperature, axle load, speed and their double interactions are studied as well. Finally, the paper proposes prediction models of the strain response at the bottom of asphalt layer by means of multivariate regression analysis.

Asphalt Concrete Layer to Support Track Slab of High-Speed Railway

Asphalt concrete (AC) is a traditional material that is used to construct highway pavement and offers the advantages of good bearing capacity, waterproofing, shock absorption, and noise reduction. In recent years, AC also has been used to construct railway infrastructure as part of the rapid development of high-speed rail in China. The study presented in this paper focused on the material composition and mechanical response of railway asphalt concrete (RAC) on the basis of mechanistic models and laboratory experiments. According to the material test results, the air voids of the material RAC-25 used for railway infrastructure should be controlled from 1% to 3%. The optimal asphalt content should be obtained from parameter tests. The recommended asphalt content should be less than 5.8%. Load-bearing infrastructure with the use of RAC-25 to replace partially the surface layer of subgrade, which was a stabilized layer on top of the subgrade, may yield a better performance. This design was No. 1 asphalt concrete railway substructure (ACRS-1). On the basis of the test results, the model with a 12-cm depth of graded gravel subgrade surface layer replaced by RAC-25 showed much better capacity and stability than other models. By comparison, the model reinforced by RAC-25 showed a higher K30 value, less deformation, good temperature sensitivity, and better loading performance. In summary, the ACRS-1 reinforced by RAC-25 was found to be a suitable type of structure for high-speed railway infrastructure.

Experimental study of a new modified waterproof asphalt concrete and its performance on bridge deck

The employment of asphalt concrete on the bridge surface paving has been widely used in long-span bridges owing to its merits such as light weight, seamless, good performance and simple maintenance. Currently, three types of asphalt materials – namely Guss asphalt , stone mastic asphalt and epoxy asphalt concrete – are principally applied in bridge deck pavement. However, these asphalt pavements have their own disadvantages. In order to further enhance the overall performance of asphalt concrete and its engineering applicability on bridge surface, in this research a new modified waterproof asphalt concrete is produced. The new modified asphalt from two aspects of the asphalt binder material and mixture were developed. To evaluate the performance of the new asphalt material and verify the feasibility of its application, a series of tests on bitumen and asphalt mixture were conducted. In addition, a comparative evaluation between the newly developed asphalt mixture and traditional ones was conducted. All in all, the results of this research could make a great contribution to the application of asphalt concrete technology on bridge surface paving.

High-Order Spectral Finite Elements in Analysis of Collinear Wave Mixing

Implementing collinear wave mixing techniques with numerical methods to detect acoustic nonlinearity due to damage and defects is of vital importance in nondestructive examination engineering. However, numerical simulations in existing literatures are often limited due to the compromise between computational efficiency and accuracy. In order to balance the contradiction, spectral finite element (abbreviated as SFE) with 3 × 3 and 8 × 6 nodes is developed to simulate collinear wave mixing for 1D and 2D cases in this study. The comparisons among analytical solutions, experiments, finite element method (FEM), and spectral finite element method are presented to validate the feasibility, efficiency, and accuracy of the proposed SFEs. The results demonstrate that the proposed SFEs are capable of increasing computational efficiency by as much as 14 times while maintaining the same accuracy in comparison with FEM. In addition, five 3 × 3 nodes’ SFEs or one 8 × 6 nodes’ SFE per the shortest wavelength is sufficient to capture mixing waves. Finally, the proposed 8 × 6 nodes’ SFE is recommended for collinear wave mixing to detect damage, which can offer more accuracy with similar efficiency compared to 3 × 3 nodes’ SFE.

Automated Survey of Railway Conditions: A Preliminary Investigation

Railway condition survey is limited by available time, particularly for high-speed railway due to the need to use its full capacity every day. Therefore, railway condition survey at high-speed at high-automation level becomes necessary. In addition, different from highway pavement condition assessment, safety is the primary factor for railway condition survey. The railway survey frequency is usually daily or weekly, while highway or runway pavement surveys are commonly conducted on annual basis. Rail profile measurement in the transverse direction, missing or broken fastener detection and slab surface crack identification are three primary railway survey items. Currently, manual or semi-automated methods are becoming feasible for railway condition surveys, but most of the applications are based on low resolution of data and have poor precision and accuracy. The repeatability and reliability of their analysis results cannot be assured. Based on the successful applications of three-dimensional (3D) laser imaging for highways and runways, the team is developing a 3D digital railway surface evaluation system. This system consists of high-performance 3D laser profilers to acquire surface details in 3D of rail tracks and supporting elements and structures at resolutions finer than 1mm. A computer vision framework is being developed to acquire and process various positioning and visual data streams in a synchronous approach. This paper discusses the status of current railway survey technologies and limitations, presents the planned implementation of new 3D laser imaging technology for high-speed and complete coverage, and possible solutions to detecting rail surface defects. Especially, fastener inspection algorithm is being developed and tested. Preliminary results reveal that the proposed 3D system under development and the fastener recognition algorithms are substantially more capable in terms of high data quality and automation level for data analysis. The objective is to initially supplement and ultimately replace traditional methods of rail safety and condition evaluation.

Using combined Avrami-Ozawa method to evaluate low-temperature reversible aging in asphalt binders

This paper aims to reasonably evaluate the reversible aging resistance of asphalt binders and comprehend the effects of low-temperature gradually hardening on fundamental properties of asphalt binders. To do so, extended bending beam rheometer (ExBBR) test with prolonged different conditioning times were performed on different kinds of asphalt binders, and viscoelastic mechanics model (Burgers model) was employed for describing the rheological properties. The combined Avrami-Ozawa equation was applied to characterise the non-isothermal crystallization process of asphalt binders which have a significantly different degree of physical hardening. The results showed that stiffness or m-value obtained from extended BBR test with logarithmic conditioning time has high coefficient of determination. Predicted stiffness and m-value from proposed empirical formula can be used to estimate extended BBR low temperature limiting grade (LTPG) that could be applicable for quality control (QC) purposes in the future. Lastly, the combined Avrami-Ozawa method can be successfully used to describe the non-isothermal crystallization process of asphalt binders used in this study.

Automatic classification of pavement crack using deep convolutional neural network

ABSTRACT The classification of pavement crack heavily relies on the engineers’ experience or the hand-crafted algorithms. Convolutional Neural Network (CNN) has demonstrated to be useful for image classification, which provides an alternative to traditional imaging classification algorithms. This paper proposes a novel method using deep CNN to automatically classify image patches cropped from 3D pavement images. In all, four supervised CNNs with different sizes of receptive field are successfully trained. The experimental results demonstrate that all the proposed CNNs can perform the classification with a high accuracy. Overall classification accuracy of each proposed CNN is above 94%. Upon the evaluation of these neural networks with respect to accuracy and training time, we find that the size of receptive field has a slight effect on the classification accuracy. However, the CNNs with smaller size of receptive field require more training times than others.

Evaluation and optimisation of stone matrix asphalt (SMA-13) mix design using weight-matrix method

The mix design of the stone matrix asphalt (SMA) mixture is critical to its performance and thereby has attracted considerable attention. In this research, abiding by the principals of orthogonal experimental design, a series of laboratory tests are conducted to assess and optimise the SMA-13 mixture mix designs. Different levels of three critical factors, gradation, asphalt-aggregate ratio, and fibre contents, are applied in the factorial experimental designs. Five performance measures, residual stability, dynamic stability, fatigue lifespan, bending strength, and coefficient of friction, are tested. With the laboratory testing results, weight-matrix analysis is employed to identify the impact of different levels of different factors on overall performance. Based on the results, the influences of the three factors are ranked: gradation, asphalt-aggregate ratio, and fibre contents, from the most influential to the least. Furthermore, analyses are conducted to determine the optimum SMA-13 mix design for four representative climate zones in China. Results are verified with the compared mixture groups.