Modeling the complex behavior of concrete for a specific mixture is a challenging task, as it requires bridging the cement scale and the concrete scale. We describe a multiscale analysis procedure for the modeling of concrete structures, in which material properties at the macro scale are evaluated based on lower scales. Concrete may be viewed over a range of scale sizes, from the atomic scale (10⁻¹⁰ m), which is characterized by the behavior of crystalline particles of hydrated Portland cement, to the macroscopic scale (10 m). The proposed multiscale framework is based on several models, including chemical analysis at the cement paste scale, a mechanical lattice model at the cement and mortar scales, geometrical aggregate distribution models at the mortar scale, and the Lattice Discrete Particle Model (LDPM) at the concrete scale. The analysis procedure starts from a known chemical and mechanical set of parameters of the cement paste, which are then used to evaluate the mechanical properties of the LDPM concrete parameters for the fracture, shear, and elastic responses of the concrete. Although a macroscopic validation study of this procedure is presented, future research should include a comparison to additional experiments in each scale.

Climatic changes lead to many extreme weather events throughout the globe. These extreme weather events influence our behavior, exposing us to different environmental conditions, such as poor indoor quality. Poor indoor air quality (IAQ) poses a significant concern in the modern era, as people spend up to 90% of their time indoors. Ventilation influences key IAQ elements such as temperature, relative humidity, and particulate matter (PM). Children, considered a vulnerable group, spend approximately 30% of their time in educational settings, often housed in old structures with poorly maintained ventilation systems. Extreme weather events lead young students to stay indoors, usually behind closed doors and windows, which may lead to exposure to elevated levels of air pollutants. In our research, we aim to demonstrate how real-time monitoring of air pollutants and other environmental parameters under extreme weather is important for regulating the indoor environment. A study was conducted in a school building with limited ventilation located in an arid region near the Red Sea, which frequently suffers from high PM concentrations. In this study, we tracked the indoor environmental conditions and air quality during the entire month of May 2022, including an extreme outdoor weather event of sandstorms. During this month, we continuously monitored four classrooms in an elementary school built in 1967 in Eilat. Our findings indicate that PM2.5 was higher indoors (statistically significant) by more than 16% during the extreme event. Temperature was also elevated indoors (statistically significant) by more than 5%. The parameters’ deviation highlights the need for better indoor weather control and ventilation systems, as well as ongoing monitoring in schools to maintain healthy indoor air quality. This also warrants us as we are approaching an era of climatic instability, including higher occurrence of similar extreme events, which urge us to develop real-time responses in urban areas.

Corrosion-induced degradation in concrete and reinforced concrete (RC) structures, often initiated within the first few decades of their lifespan, significantly challenges seismic resistance. While existing research tools can assess performance, they fall short in predicting changes in seismic resistance resulting from alterations in the core properties of RC structures. To bridge this gap, we introduce a numerical seismic resistance prediction method (SRPM) specifically designed to predict changes in the seismic resistance of structures, including those reinforced with carbon-fiber-reinforced polymer (CFRP), known for its non-corrosive properties. This study utilizes classical models to estimate corrosiveness and employs these models alongside section strength predictions to gauge durability. The nonlinear static pushover analysis (POA) model is implemented utilizing SAP-2000 and Response-2000 software. A comparative analysis between steel-reinforced and carbon-fiber-reinforced polymer concrete (CRC) structures reveals distinct differences in their seismic resistance over time. Notably, steel-reinforced structures experience a significant decrease in their ability to dissipate seismic energy, losing 54.4% of their capacity after 170 years. In contrast, CFRP-reinforced structures exhibit a much slower degradation rate, with only 25.5% reduction over the same period. The discrepancy demonstrates CFRP’s superior durability and ability to maintain structural integrity in the face of seismic stresses.