The linear viscoelastic behavior of materials is represented using mechanical models of choice, which are further utilized in different numerical investigations, such as finite element simulations and discrete element simulations. Burger's model is one of the widely adopted mechanical models and remains highly favored in contemporary research due to its multiple advantages. Specifically, it excels in representing long-term creep and stress relaxation behavior in a relatively simplified manner. Accurate identification of the long-term behavior for the viscoelastic material, particularly asphalt concrete, is crucial, as it serves as a key indicator of asphalt pavement performance over its service life. However, past research studies show that the parameters of Burger's model should be back-calculated from experimental data only within a limited range of frequency, otherwise, the parameters fail to represent the true material behavior. To the best of the authors’ knowledge, there is no approach for researchers to obtain the critical frequency range in which the experiments should be performed. Therefore, this study proposes a novel framework to find the critical frequency range to obtain appropriate model parameters of Burger's model, to better characterize the viscoelastic behavior of the materials. To examine the framework, asphalt concrete mixtures are used as examples in this study. Necessary laboratory tests including complex modulus tests and stress relaxation tests, are performed on two distinctive types of asphalt concrete mixtures. The generalized Maxwell model with different number of Maxwell chains are used to evaluate the performance of Burger's model. Furthermore, since commercially available finite element packages generally do not have a direct built-in Burger's model, the article shows a way of implementing Burger's model in finite element simulation. The simulations corresponding to the laboratory tests are carried out in both frequency domain and time domain to thoroughly evaluate the performance of Burger's model. The optimal frequency range of 0.1–20 Hz for the examined mixtures is found to significantly improve the accuracy of the descriptive master curve. The results also suggest that the generalized Maxwell model requires a minimum of four Maxwell chains to maintain good performance in accurately characterizing the behavior of asphalt mixtures. However, adding more Maxwell chains beyond a critical limit may not provide significant benefits. Finite element simulations demonstrate that the stress relaxation behavior predicted by the obtained Burger's model parameters aligns more closely with experimental data over longer time intervals. This makes Burger's model a strong choice for aiding in the design of simulations for studies focused on the long-term behavior of materials.

Due to the complex organic properties of asphalt materials, the heating process during asphalt pavement construction will lead to the release of asphalt VOCs‧ Asphalt VOCs volatilization will cause irreversible harm to both the environment and health of construction workers‧ Researchers in the field of road construction have carried out extensive research on various emission reduction materials and technologies based on release mechanism of asphalt VOCs‧ There are no comprehensive research and intuitive comparison on emission reduction materials due to the differences between quantitative standards for emission reduction effects‧ This paper summarizes the current research status of asphalt VOCs emission reduction, including the development history of emission reduction technology and reduction mechanism of various asphalt VOCs emission reduction materials mainly based on inhibitors, warm mixing agents and flame retardants‧ In addition, the emission reduction effects of different emission reduction materials are compared and the improvement trend research direction of new and efficient asphalt VOCs reduction technology and materials are proposed to achieve green and low-emission construction‧ Finally, around the environmental protection theme of VOCs emission reduction, this study also put forward the prospect of full life cycle emission mechanism and feasibility of efficient composite materials design to support the urgent need for green transport.

Optimizing asphalt mix design at the indoor stage is of significant importance for enhancing the rutting resistance of asphalt mixture, which is affected by its structural characteristics. In this work, the coordination number of particle contact force (CN_pcf) was proposed as an indicator to represent contact characteristics of skeleton structure aggregates in asphalt mixture. Nine asphalt mixtures with different gradations were designed, and the relationship of CN_pcf with the number of aggregate contact zones (CZ) was established by combining rutting tests and digital image processing technique (DIP). The Mann-Whitney U test was implemented to analyze the distribution properties of inter-particle contacts before and after the rutting test. In addition, the resistance to the further expansion of rutting was analyzed. The results revealed a significant positive correlation (PCCs = 0.843, R² = 0.711) between CN_pcf and CZ. The content of coarse aggregates in the dominant structure did not exhibit monotonic related to anti-rutting performance of the asphalt mixture. Therefore, an optimum aggregate content of 57% was utilized. The Mann-Whitney U test revealed that the mesoscale skeleton structure of the asphalt mixes before and after rutting exhibited excellent stability. This study further indicated the applicability of combining CN_pcf to adjust the mix design to enhance the rutting resistance of asphalt mixture and to prevent rutting expansion in flexible pavement.

Asphalt material is an irreplaceable material in road construction. However, it releases VOCs (Volatile Organic Compounds), which do cause pollution to the surrounding environment, during its full life cycle, especially in high-temperature paving stage and summer service time. Asphalt VOCs release mechanism and effective emission reduction technologies are therefore urgently needed. The chemical analysis of VOCs from asphalt binder always invariably excludes a vast number of compounds of unknown relevance, making the quantitative analysis lower data accuracy. In order to address this problem, fingerprint database was developed and introduced in this study, with the detected VOCs data from 104 kinds of asphalt binders. The analysis parameters, including fingerprint components and calibration curves were optimized through quantitative study. With the help of a self-developed fingerprint database, the calculation formulas of single VOC and total released VOCs were established for quantitative analysis of VOCs from asphalt binder. In addition, the influencing mechanism of heating temperature and asphalt types on VOCs volatilization characteristic were explored to achieve emission reduction in asphalt industry.