The purpose of this paper is to study the different strain distributions of CEAC (cement-emulsified asphalt concrete) pavement between the macro- and meso-scale, using a three-dimensional macroscopic finite element ANSYS model of pavement composed of hot mix asphalt (HMA), CEAC, and stone mastic asphalt (SMA). Applying digital image processing technology, the composition of the CEAC material at the meso-scale is identified as a three-phase material that includes cement-emulsified asphalt mastics, aggregates, and air voids. A two-dimensional mesoscopic finite element submodel measuring 80 × 80 mm was identified in a local region and built. Boundary conditions from the global CEAC pavement model were applied to the submodel. Eight control points in the CEAC submodel were selected for analysis. A comparison of the calculated strains of the CEAC local region at the macro- and meso-scales shows that the strain distributions at the meso-scale are not as uniform as those at the macro-scale. The extreme strain at the meso-scale is larger than that at the macro- scale. The reserve strength factors of mastic and aggregates of CEAC at the meso-scale are 31.82% and 49.07%, respectively, compared with 93.2% at the macro-scale. These values indicate that analyses at the macro- and meso-scales yield results that are not only different but can also have a significant effect on the potential failure mechanism of the CEAC component in the pavement.

Asphalt Emulsion—Cement Concrete (AECC) is currently considered as a typical semi-flexibility material. One of the disadvantages of this material is brittle fracture and lacking ductility. This study aims at accelerating the basic mechanical properties of AECC using fibers and different aggregates size. The mix of AECC was introduced and the different content of fibers and aggregates size were studied. The results showed that the smaller aggregates size could improve the young's modulus and compressive strength as well as fiber. The modulus-compressive strength ratio of fiber reinforced AECC is always below 500.

Traditional detection methods for pillar porcelain insulators, both domestically and internationally, are predominantly direct contact-based, which have certain limitations and drawbacks. These methods pose significant operational risks and are incapable of performing online detection of pillar porcelain insulators in their energized state. This paper proposes a monitoring system for fracture failure of porcelain insulators by combining experimental analysis and finite element simulation. The interface bonding hypothesis and load loading hypothesis are made when the model is established. Taking the actual production of double-section pillar porcelain insulators as the research object, the structural static test is conducted to measure some material parameters of the porcelain column. Based on the theory of finite element analysis, a full-scale model of the double-section pillar porcelain insulator is established to analyze the stress response of the porcelain column and the mechanical behavior of the entire insulator under different boundary loads. A non-contact optical monitoring system for the double-section pillar porcelain insulator is constructed based on the Digital Image Correlation (DIC) method. The results of the monitoring system are compared with those of the finite element analysis, showing that the system has high accuracy in identifying high-stress states, with a minimum relative error of only 0.7%. This system demonstrates strong feasibility for early warning of fracture failure risks.