The role of critical infrastructures in maintaining the functioning of the economy and society and ensuring national security, particularly their durability in delivering essential services during crises, including natural disasters such as earthquakes, is critical. This work introduces an analytical methodology to quantify potential earthquake damage to power stations and evaluate the cost-effectiveness of measures to enhance their seismic resistance. By employing fragility curves and probabilistic risk analyses, this approach provides a structured framework for the comprehensive assessment of risks and the identification of economically practical mitigation strategies. A detailed examination of strategies to protect critical power station components against seismic activity is presented, revealing that a minor investment relative to the overall project budget for earthquake-proofing measures is economically effective. This investment, representing a marginal fraction of 0.5% of the total project expenditure significantly reduces the seismic risk of power station failure by 36%. Reinforcing essential elements, including switching stations, water treatment facilities, and water tanks, is emphasized to ensure their continued operation during and after an earthquake. This research highlights the critical significance of integrating risk assessment with benefit-to-cost analysis in strategic decision-making processes, supporting the prioritization of investments in infrastructure enhancements. These enhancements promise substantial reductions of risks at minimal costs, thus protecting essential services against the impacts of natural disasters. This research contributes to state-of-the-art research in critical infrastructures resilience.

This study presents a novel framework for integrating corrosion effects into critical infrastructure seismic risk assessment, focusing on reinforced concrete (RC) structures. Unlike traditional seismic fragility curves, which often overlook time-dependent degradation such as corrosion, this methodology introduces an approach incorporating corrosion-induced degradation into seismic fragility curves. This framework combines time-dependent corrosion simulation with numerical modeling, using the finite–discrete element method (FDEM) to assess the reduction in structural capacity. These results are used to adjust the seismic fragility curves, capturing the increased vulnerability due to corrosion. A key novelty of this work is the development of a comprehensive risk assessment that merges the corrosion-adjusted fragility curves with seismic hazard data to estimate long-term seismic risk, introducing a cumulative risk ratio to quantify the total risk over the structure’s lifecycle. This framework is demonstrated through a case study of a one-story RC moment frame building, evaluating its seismic risk under various corrosion scenarios and locations. The simulation results showed a good fit, with a 3% to 14% difference between the case study and simulations up to 75 years. This fitness highlights the model’s accuracy in predicting structural degradation due to corrosion. Furthermore, the findings reveal a significant increase in seismic risk, particularly in moderate and intensive corrosion environments, by 59% and 100%, respectively. These insights emphasize the critical importance of incorporating corrosion effects into seismic risk assessments, offering a more accurate and effective strategy to enhance infrastructure resilience throughout its lifecycle.

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.

Rigid reinforced concrete (RC) frames are generally adopted as stiff elements to make the building structures resistant to seismic forces. However, a method has yet to be fully sought to provide earthquake resistance through optimizing beam and column performance in a rigid frame. Due to its high corrosion resistance, the integration of CFRP offers an opportunity to reduce frequent repairs and increase durability. This paper presents the structural response of CFRP beams integrated into rigid frames when subjected to seismic events. Without any design provision for CFRP systems in extreme events, multiscale simulations and parametric analyses were performed to optimize the residual state and global performance. Macroparameters, represented by the ductility ratio and microfactors, have been analyzed using a customized version of the modified compression field theory (MCFT). The main parameters considered were reinforcement under tension and compression, strength of concrete, height-to-width ratio, section cover, and confinement level, all of which are important to understand their influence on seismic performance. The parametric analysis results highlight the increased ductility and higher load-carrying capacity of the CFRP-reinforced tested component compared to the RC component. These results shed light on the possibility of designing CFRP-reinforced concrete components that could improve ductile frames with increased energy dissipation and be suitable for applications in non-corrosive seismic-resistant buildings. This also shows reduced brittleness and enhancement in the failure mode. Numerical simulations and experimental results showed a strong correlation with a deviation of about 8.3%, underlining the reliability of the proposed approach for designing seismic-resistant CFRP-reinforced structures.

This research focuses on the design and performance of Steel Fiber-Reinforced High-Strength Concrete (SFRHSC) to identify the optimal fiber content. The critical challenges involve the fiber content optimization and the effect of fiber distribution on the SFRHSC’s mechanical properties. This study uses the fiber weight ratio as it is more precise for quantifying fiber content than the traditional volume one. The available data obtained from experimental investigations of fifteen cylindrical specimens with systematically varied fiber ratios ranging from 0 to 60 kg/m³ were used. Following the experimental data, a 30 kg/m³ fiber content optimizes the mechanical properties of concrete with a compressive strength of 85–90 MPa, showing a superior Poisson ratio, energy dissipation, and structural ductility. To further recognize and replicate these findings, the behavior of SFRHSC cylinders was simulated using the Lattice Discrete Particle Model (LDPM). In the first stage, the parameters were calibrated by curve-fitting the experimental results with simulations of cube specimens for a uniaxial compression test. Then, the model was validated by simulating a loading–unloading cycle to fit the results. Subsequently, the effect of cracking for each fiber content and verbal compressive strength on the energy dissipation was examined for different SFRHSC strength values. These findings provide valuable insights for developing and optimizing SFRHSC for advanced structural applications.

Optimizing the service life of reinforced concrete structures requires replacing traditional Portland Cement (PC) with Slag-Blended Cements (SBCs) that offer refined pore networks, which are vital for inhibiting the propagation of corrosion-induced cracks. In this study, we propose an integrated framework combining Direct Current (DC)-accelerated corrosion tests with computational quantification of cracking. For comparison purposes, the concrete samples with similar compressive strengths (~60 MPa), obtained after 65 days from the mixing process, were exposed to impressed currents while the evolution of cracks was monitored using image processing in MATLAB. It was found that the slag-blended cement significantly delayed the appearance of the crack, which occurred at 141 h, compared with 57 to 70 h for the PC specimen. The delay in corrosion damage initiation by SBC is 1.7 times higher than that by PC. In terms of damage severity, SBC reduced both the total crack lengths by 56% (83 mm for SBC and 189 mm for PC) and the maximum crack width by 22% (0.70 mm for SBC and 0.90 mm for PC). After 111 h of corrosion under the same conditions, the SBC still retained its ability to reduce the crack length (188 mm), whereas PC formed 270 mm cracks. These findings provide a basis for future calibration of sophisticated mesoscale fracture models, such as the Lattice Discrete Particle Method (LDPM) and the Finite Discrete Element Method (FDEM), as well as for creating data sets for future data-driven durability assessment.