Recycling crushed waste oyster shells (WOS) as a fine aggregate is an attractive method of disposal. However, its use in geopolymer mortar has not been reported. The influence of PVA fibres on the engineering properties of the new geopolymer mortar is still unclear. To bridge the gap, this study investigated the influence of various PVA fibre contents (0–1.05 vol%) on the flowability, compressive, flexural strengths, drying shrinkage, sorptivity, chloride resistance, porosity, fibre dispersion, embodied CO₂ emissions (ECO₂e), and embodied energy (EE) of the geopolymer mortar. The results indicated that the inclusion of 0.15–1.05 vol% of PVA fibres improved the flexural strength by 10.10–42.31% and reduced the drying shrinkage by 13.37–65.79%. The flowability and compressive strength decreased by 10.78–34.28% and 7.50–27.65%, respectively, but they were sufficient for construction. The sorptivity increased by 1.45–15.16%, and the chloride resistance decreased by 15.09–56.35%, but the geopolymer mortar was still classified as low chloride penetrability. In summary, the optimal content of PVA fibres is 0.45 vol%, and the geopolymer mortar has good engineering properties and eco-efficiency. The cost analysis and high-temperature resistance of the geopolymer mortar are neglected in this study, which should be evaluated in future work.

The coastal zone is essential to economic and social development. However, coastline evolution is a complex research topic, owing to the intersection and coupling of different fields such as wind, wave, and current. Research is further complicated by variations in these fields’ temporal and spatial scales. This study acquired and preprocessed multi-phase Landsat remote sensing satellite images of the eastern coast, from Wailuo to Zhuzi, from 1987 to 2021. Then, the decoded and extracted instantaneous coastline images were corrected, and quantitative analysis was carried out through the Digital Coastline Analysis System (DSAS). The results showed that trends of coastline evolution in the study area in the medium–long term were overall balanced. All the transects manifested temporal and spatial differences, and erosional hot spots were mainly concentrated on the coastal cape and its vicinity. To investigate storm-induced beach erosion in the short term, the 400 m coastline of Baimao in the area was selected as a field site, and the field survey was conducted during two storms. The distribution of the dynamic parameters of sediment deposition was also investigated. The results showed that the beach in the field site had an excellent ability to resist storm erosion and that the topographic change was greatly affected by geological conditions in the area, such as reef masking and a typical headland beach. The grain size parameters of the beach sediments were sensitive to storms, reflecting the adjustment of the beach surface during typhoons. This study shows how a multi-timescale analysis could represent an efficient approach to understanding the dynamic evolution of the coastline. It showed a detailed description of the historical coastline evolution of the eastern coast of the Leizhou Peninsula after 1987. Additionally, the coastline evolution and sediment distribution for the sedimentation dynamic environment of Baimao tourist area in the short term were also investigated. In conclusion, this study can contribute to the rational utilization of coastal resources, to coastal disaster prevention, and the mitigation of local coastal areas.

Traditional concrete materials have limitations in terms of load-bearing capacity and ductile failure. In contrast, Engineered Cementitious Composites (ECCs), with their superior strain-hardening behavior and multiple cracking characteristics, have attracted widespread attention in the field of high-performance materials. In this study, ECC specimens incorporating different types of fibers (polyethylene (PE) fibers, polyvinyl alcohol (PVA) fibers) at varying contents were tested to systematically analyze their influence on mechanical properties. Compressive, flexural, and uniaxial tensile strength tests were conducted to evaluate the mechanical performance of ECCs. In addition, scanning electron microscopy (SEM) was employed to examine the fracture surfaces of the fibers, providing deeper insights into the interfacial behavior and fracture morphology of the different fiber-reinforced systems. Fracture surface analysis reveals that the interfacial bonding characteristics between different fibers and the matrix significantly influence fracture behavior. Moreover, as the tensile performance of ECCs is influenced by the interaction of multiple factors, traditional constitutive models exhibit limitations in accurately predicting its complex nonlinear behavior. To address this limitation, an Artificial Neural Network (ANN) approach was adopted to develop a predictive model based on bilinear stress–strain relationships. The model was constructed using ten key input parameters, including matrix composition and fiber properties, and was able to accurately predict the first cracking strain, first cracking stress, ultimate strain, and ultimate stress of ECCs. Sensitivity analysis revealed that fiber tensile strength and fiber content were the most significant factors influencing the tensile behavior. The predicted tensile curves showed strong consistency with the experimental results, thereby confirming the reliability and applicability of the proposed ANN-based model.