Chloride-induced corrosion poses a serious threat to the durability of coastal concrete structures. To enhance their safety, a novel and sustainable reinforcing approach employing textile-reinforced one-part engineered geopolymer composite (TREGC) is proposed in this study. The interfacial bond performance between TREGC and normal concrete (NC), a key factor governing structural durability and reliability, is systematically investigated through push-out tests on cylindrical specimens. A total of 72 specimens were fabricated to investigate the effects of surface treatment, reinforcement type, and chloride immersion duration. Three different failure modes were observed: interfacial debonding failure, epoxy debonding failure, and NC cohesion failure. Replacing EGC with TREGC reinforcement resulted in an approximately 20% increase in ultimate interfacial bond stress. Specimens with chiseled surface treatment exhibited the highest ultimate interfacial bond stress, with a 120% increase compared to those with smooth surface treatment. An interfacial bond stress-slip model was subsequently established for TRECC/TREGC-NC interfaces under chloride environments, which showed excellent agreement with experimental data with an average R2 of 0.96. Furthermore, the sustainability of the reinforcing materials was assessed, revealing that EGC provides remarkable environmental benefits over ECC by reducing carbon emissions and embodied energy by 26% and 27%, respectively.

To address the low resource utilization efficiency of incineration bottom ash (IBA) caused by its insufficient reactivity, this study systematically investigates the influence mechanisms of alkali activation modification on ash (IBA)-cement composite systems. IBA was activated using NaOH and Na2SiO3 as alkali activators, with particular emphasis on the enhancement of mechanical properties and the evolution of microstructure under different activator ratios. Results indicate that when the Na2O content concentration in the alkali activator is 0.8 %, the latent reactivity of IBA can be effectively activated, promoting the formation of high-strength gel in the hydration products, resulting in a 25 % increase in 28-day compressive strength compared to the control group. Notably, when the Na2O content increases to 1.6 %, excessive alkali not only disrupts the normal hydration process but also significantly intensifies the alkali-silica reaction (ASR), leading to severe degradation of specimen performance. In addition, it was observed that Na2SiO3 accelerates specimen hardening, necessitating strict control of its dosage within the range of 0.7-1.3 %. Excessive dosage may lead to overly rapid hardening, severely hindering the complete progression of hydration, while dosages below 0.7 % result in suboptimal performance improvement.

Corrugated steel plates exhibit strong stability and have been widely applied in engineering projects as beam and shear wall structures. Previous experimental studies have shown that corrugated steel plates are prone to cracking, compromising reliability during long-term service. This paper proposes a novel replaceable bolted built-up double corrugated steel plate (DCSP) shear wall with discontinuous connections. Experimental study was conducted to investigate the replaceability of the built-up members and the crack-resistant capacity. Four shear wall specimens embedded with double trapezoidal corrugated steel plates (DTCSP) and three specimens with double rectangular corrugated steel plates (DRCSP) were designed, fabricated, and tested under cyclic loading. Experimental results indicated that the proposed structure has higher crack-resistant capacity, the cracks initiated after buckling occurred, corresponding to a drift angle greater than 2.4 %. Within this drift angle range, the frame and corrugated steel plate were slightly damaged, and the corrugated steel plate could be replaced. The primary factor leading to the reduction of load is buckling rather than cracks. The hysteretic curve did not undergo substantial changes due to the appearance of the cracks. Specimens with DTCSP exhibited higher ultimate load but showed rapid strength deterioration and pronounced pinching behavior after buckling. In contrast, DRCSP demonstrated lower ultimate load but did not exhibit significant pinching behavior after buckling, and the hysteresis and skeleton curves presented a mild "double-peak and single-valley" characteristic. Through experimental research, the effects of parameters such as corrugation height, corrugation angle, and waist width on structural stability and load-carrying capacity have been preliminarily revealed. These findings were further validated through numerical simulations, and dimensional recommendations for structural design were proposed.

The synergistic combination of high-strength steel bars (HSSB) and ultra-high performance steel fiber-reinforced concrete (UHPSFRC) exploits their superior mechanical properties, leading to reduced material consumption and potentially lower carbon emissions. However, long-term corrosion, particularly in aggressive environments such as coastal regions, poses a threat to the bond performance of the HSSB-UHPSFRC. This study investigates the bond mechanism of corroded heat-treated ribbed bar Grade 600 steel (HTRB600) embedded in UHPSFRC through a combination of electrochemical accelerated corrosion tests, eccentric pull-out tests, and refined finite element modeling (FEM). The accelerated corrosion method achieved a uniform and stable corrosion level, making it suitable for analyzing the influence of various parameters on corroded bond performance. Key design variables include steel fiber volume fraction, cover thickness, anchorage length, stirrup configuration, and corrosion condition. Experimental results demonstrated that UHPSFRC provided superior corrosion protection for the embedded HSSB, resulting in a relatively low final corrosion level of approximately 4.1 %. At this corrosion level, bond strength increased slightly (4.5 %) compared to uncorroded control specimens. Increasing concrete cover thickness enhanced bond strength, but UHPSFRC achieved reliable bond performance under corrosion with thinner covers compared to normal concrete (NC). The relationship between bond strength and steel fiber volume fraction revealed an increase initially, followed by a plateau at a 2 % content. Furthermore, while bond force increased with increasing anchorage length up to 5d (where 'd' denotes bar diameter), a corresponding decrease in bond stress was observed. The incorporation of stirrups improved ductility but had a negligible effect on bond strength. A refined FEM, incorporating mechanical interlocking arising from rebar ribs and rust expansion under corrosion within the UHPSFRC confinement, was developed to analyze interfacial bond stress distribution and damage evolution. These findings provide valuable insights into the bond mechanism and offer practical design guidance for HSSB-UHPSFRC structures.

Corrosion of reinforcement is a crucial factor that significantly impairs the seismic performance of reinforced concrete (RC) columns in building structures. This paper examines three key parameters related to the seismic performance of RC columns: seismic failure modes, maximum bearing capacity, and effective stiffness. The design methodologies for RC columns vary significantly depending on the failure modes, as different failure modes involve distinct mechanical characteristics, thereby influencing the corresponding bearing capacity and effective stiffness. In this study, an intelligent approach is proposed, which first performs the classification of failure modes and subsequently predicts the associated bearing capacity and effective stiffness through regression analysis. Seven supervised learning algorithms and one deep learning algorithm were utilized in this study, with particular emphasis on the k-nearest neighbor (KNN) algorithm due to its simplicity and effectiveness. A comprehensive dataset comprising 221 corroded column specimens under cyclic loading tests was collected, and the findings indicate that the KNN-based model exhibits a high degree of accuracy in failure modes classification (accuracy=0.91), bearing capacity prediction (R2=0.99), and effective stiffness prediction (R2=0.95). Comparisons with other algorithms were conducted, and the results indicate that the KNN algorithm outperforms the others. Furthermore, the bearing capacity and effective stiffness predictions generated by the KNN algorithm were compared with empirical formulas from design codes, revealing the clear superiority of the proposed method. Thus, it can be concluded that machine learning techniques offer a promising alternative to traditional mechanics-driven models, particularly in the context of big data and the unique challenges posed by the complex mechanical behavior of RC columns in buildings.

This study investigated the effects of height-varying corrosion and different ultra-high performance concrete (UHPC) retrofitting sequences on the seismic performance of RC bridge piers. To this end, quasi-static tests were conducted on five RC bridge piers: an uncorroded control specimen (UC-0 %), a 10 % corroded specimen (CC10 %), a pre-retrofitted specimen (CC-3.3 %-PR), a mid-service retrofitted specimen (CC-6.6 %-MR), and a final retrofitted specimen (CC-10 %-FR). The experimental results revealed the formation of a double plastic hinge in the corroded specimen. Additionally, the bearing and deformation capacities of the height-varying corroded specimen (CC-10 %) were marginally reduced in comparison to the uncorroded specimen. UHPC retrofitting was effective in preventing plastic hinge formation within the corroded zone, leading to enhancements in the initial stiffness and ductility of the RC columns. However, the pre-retrofitted specimen (CC-3.3 %-PR) exhibited lower bearing and deformation capacity than the non-retrofitted specimen (CC-10 %) due to damage concentration at the pier bottom. The mid-service retrofitted specimens showed the optimal deformation capacity among the retrofitted group, while the final retrofitted specimen displayed diminished performance as a result of substantial pre-corrosion damage. A fiber-based finite element model (FEM) was developed to simulate the nonlinear seismic behavior of the five specimens. This model incorporated the interfacial behavior between the corroded RC section and the retrofitted UHPC section, as well as the shear behavior of the corroded regions. The proposed FEM was validated to accurately predict the hysteretic responses and damage distribution of piers.

This paper presents the first experimental study of the seismic performance of double-skin tubular columns (DSTCs) with polyethylene naphthalate (PEN) FRP tubes. Fiber-reinforced polymer (FRP)-concrete-steel DSTC represents a new type of combined structure. A DSTC has an external FRP tube with an internal steel tube, and concrete fills the gap between the two tubes. DSTCs limit the outward buckling of their steel tubes and have excellent seismic performance. Previous studies have shown that glass FRP (GFRP) fracture controls the ultimate failure of DSTCs with a GFRP tube. Therefore, the fracture strain of the FRP tube is a critical factor for DSTCs. The fracture strain of large-rupture-strain (LRS) FRPs is greater than 5 %, which gives DSTCs an advantage. Six fullscale DSTCs were tested in the paper to investigate the effects of FRP type, PEN FRP thickness and the axial compression ratio as well as the plastic hinge region is filled with concrete on the seismic performance of DSTCs. The experimental results indicate that the seismic performance of DSTCs with PEN FRP is equal to or slightly better than that of GFRP, and the energy dissipation capacity improved by 41.7 %. In addition, decreasing the axial compression ratio, increasing the thickness of PEN FRP, and filling the plastic hinge region with concrete appropriately increased the DSTC seismic performance.

The BFRP bar-reinforced coral aggregate concrete (BFRP-CAC) structure offers a promising design option for marine and coastal structures due to its eco-friendly nature and capability of corrosion resistance. Nonetheless, research on such structures remains relatively limited, particularly in the context of precast elements, which are crucial for enhancing construction efficiency and quality. This paper presents an experimental and numerical study on precast BFRP-CAC beam-column joints. Four specimens were first tested under constant axial loads and reversed cyclic lateral loads to assess their seismic performance. The variables included the type of concrete, the type of reinforcement, and the anchorage form. The seismic performance of specimens was evaluated in terms of failure modes, hysteretic behaviors, strength and stiffness degradations, energy dissipation capacities, and deformation components. Following that, parametric studies are performed based on the finite element models of specimens to investigate the influences of the axial load ratio, stirrups, and compressive strength of concrete on the seismic performance of joints. The results indicate that the use of CAC and BFRP bars led to a slightly reduced lateral resistance but enhanced deformation capacity in the specimens. Moreover, it was observed that the cast-in-place specimen has a slightly greater lateral resistance than the precast specimens. The latter, nonetheless, exhibit smoother stiffness degradations and superior energy dissipation capacities.

Engineered cementitious composites (ECC) has emerged as a promising self-reinforced material for 3D printed concrete structures, which could potentially remove the dependence on steel reinforcement. The interfacial crack resistance of 3D printed ECC (3DP-ECC) should be emphasized due to the inherent layered stacking process. Tensile strength and fracture toughness are two critical fracture parameters in describing the crack resistance. Determining realistic fracture parameters is crucial for guiding structural safety design. This study aims to develop a fracture mechanics model for determining the size-independent interfacial tensile strength and fracture toughness of 3DP-ECC based on boundary effect model (BEM). Firstly, the interfacial fracture behavior of 3DP-ECC was experimentally investigated by three-point bending tests. A fracture mechanics model was subsequently proposed to predict the size-independent tensile strength and fracture toughness by incorporating the material heterogeneity and discontinuity. The results show that the interfacial tensile strength and fracture toughness of 3DP-ECC could be extrapolated analytically once the peak load was obtained by the three-point bending fracture test, and the predicted values of tensile strength and fracture toughness were proved to follow normal distribution. Additionally, the peak load prediction lines and fracture failure curves with 95 % confidence interval for 3DP-ECC were further constructed using the determined fracture parameters, demonstrating good accuracy and reliability. This work offers a theoretical basis for the safe and reasonable design of 3DP-ECC structural members.

Chloride-induced corrosion of reinforced concrete (RC) structures in marine environments poses a significant challenge to the sustainability and long-term durability of coastal infrastructure worldwide. This phenomenon is characterized by extensive spatial impact, elevated chloride concentrations, and prolonged exposure periods. To address these challenges, this study proposes a multi-scale chloride corrosion assessment framework tailored for urban coastal regions. Using Xiamen, a coastal city, as a case study, we developed horizontal and vertical chloride corrosion zoning schemes were formulated based on the city-scale geographical and environmental characteristics. An integrated corrosion model was formulated, incorporating distance- and height-dependent parameters. By accounting for factors such as wind speed, water-cement ratio, distance from the coastline, material properties and exposure conditions, six distance-based and seven height-based models were validated against field monitoring data to accurately evaluate corrosion risks at the urban scale. Furthermore, probability analysis was employed to assess the durability and resilience of urban infrastructure under diverse environmental and structural conditions. The findings provide critical insights for urban planning and maintenance strategies, enhancing the long-term performance of coastal infrastructure.

Luffa sponge features a naturally optimized three-dimensional fibrous network, forming a lightweight and highly deformable bio-structure with high energy absorption capacity. Here we show that it can serve as a sustainable reinforcement to improve the impact resistance of cementitious composites. When embedded in cement paste, the luffa sponge forms a synergistic interface that enhances structural integrity and allows the composite to endure repeated impacts with minimal fragmentation. The composite maintains stable performance across a wide temperature range from –196 °C to 200 °C, showing low thermal sensitivity. Microscopic imaging and simulations reveal a gradual interfacial transition zone where hydrogen bonding leads to strength variation across the interface. This transition improves load transfer and contributes to overall durability. These findings highlight the potential of using bio-derived, architectured materials like luffa sponge to develop resilient and sustainable cement-based composites for structural applications. Naturally occurring luffa sponge features a 3D fibrous network, making it deformable with a high energy absorption capacity. Here, luffa sponge is used as a reinforcement to improve impact resistance in cementitious composites, which maintain their performance across a wide temperature range.

Textile reinforced engineered cementitious composite (TRECC), as a novel composite material for reinforcing existing normal concrete (NC) structures, requires excellent interfacial bond performance, particularly in chloride environments such as coastal regions. This study investigated the interfacial bond performance between TRECC and NC using push-out tests on cylindrical specimens. A total of 96 specimens were prepared, with variations in surface treatment methods, type of reinforcement layer, and chloride immersion durations. Four different failure modes were identified in the test: NC-ECC debonding, epoxy-ECC debonding, NC cohesive failure, and mixed NC-ECC cohesion failure. The analysis of the load-slip curve showed that the interfacial bond force transfer mechanism evolves from initial chemical and physical adhesion forces, to mechanical biting forces, and finally to a combination of friction forces and circumferential restraint forces provided by the TRECC. Compared with ECC, TRECC reinforcing technique enhances the ultimate interfacial bond stress by approximately 25 %. Microstructural analysis revealed the evolution of microcracks and the development of microscopic pores, which were the primary causes of interfacial bond performance deterioration. Two predictive models were developed at last to predict the ultimate interfacial bond stress of TRECC-NC under normal and chloride environments. Sound statistical results, as indicated by the standard deviation (<= 0.13 MPa) and coefficient of variation (<= 5.62 %), validate the robustness of the proposed models.

Bridge piers are among the most vulnerable and critical components subjected to earthquake loading. Extensive research has been dedicated to understanding the damage and failure mechanisms of bridge piers in the literature. However, there is limited investigation into their residual bearing capacity after earthquake events. This study developed a novel and unified evaluation framework for the residual bearing capacity of bridge piers, which linked the seismic damage, stiffness, and strength with residual bearing capacity. The Park damage-based failure criterion, structural damage indicators, and the farthest point method were introduced to realize the interconnection. Test data for reinforced concrete piers, including complete hysteresis curves from the Pacific Earthquake Engineering Research Center, were selected for analysis. These hysteresis curves were plotted individually for further examination. The results demonstrate that the residual drift ratio increases with the growth of the damage index, and a power exponential function is fitted to model this relationship. Compared to traditional qualitative or subjective judgment methods, the proposed approach not only yields more precise results but also offers a rapid evaluation model for bridge structures after earthquakes.

A typical offshore two-span RC bridge is selected to develop a time-variant finite element model (FEM), considering height-varying corrosion degradation and foundation scour. Using the damage index that accounts for time-varying degradation, seismic fragility analyses were conducted to evaluate the lifetime seismic damage evolution and seismic resilience. Analysis results indicate that, during the early phases of service, height-varying corrosion slightly decreases seismic fragility of RC piers rather than increasing it, as it mitigates the concentration of damage at the pier bottom. However, the damage transfers from pier bottom to the tidal and splash regions as time progresses, resulting in continuous increase in seismic fragility of substructure and subsequent reduction in resilience of bridge system. On the other hand, foundation scour exacerbates damage to the piles, thereby increasing seismic fragility of the entire bridge substructure during the early service stage. However, over long-term service, foundation scour ultimately reduces seismic fragility and enhances the seismic resilience of the bridge substructure. This occurs because intensified pile damage from increased scour depth helps to alleviate damage concentration in the tidal and splash regions of pier, leading to a more balanced distribution of damage between pier and pile and ultimately improving seismic resilience.

Calcium sulfoaluminate (CSA) cement has emerged as a low-carbon alternative to ordinary Portland cement (OPC), offering reduced CO2 emissions and rapid strength development. However, the role of the ferrite phase in CSA systems remains underexplored. This study investigates the influence of ferrite-phase composition on CSA cement properties through targeted clinker design, hydration analysis, and macro–micro performance testing. Nine clinker formulations were synthesized by systematically increasing the ferrite content (10–30%) while adjusting belite (C2S) proportions, using limestone, bauxite, and supplementary Fe2O3/SiO2. Results reveal that the ferrite phase enhances the formation and stabilization of ye’elimite (C4A3Š) during clinkering and reduces low-activity transitional phase products. Increasing the iron-phase content appropriately improves early strength by promoting ettringite (AFt) formation and refines pore structures to enhance later strength development. The maximum strength improvement is achieved when the target ferrite-phase content is set to 15%, showing a 25.1% increase in 1 d strength and an 11.5% increase in 28 d strength. While ferrite phases and C2S ensure long-term strength gains, excessive ferrite content reduces C4A3Š availability, limiting early AFt formation and compromising initial strength. These findings highlight the dual role of the ferrite phase in optimizing CSA cement performance and sustainability, providing a foundation for designing ferrite-rich, low-carbon binders.

With the continued development of sustainable island reef infrastructure, there is a growing demand for coral concrete that is low-carbon, environmentally friendly, and exhibits excellent mechanical performance. This study replaced cement with alkali-activated binders prepared from waste marble powder and ground granulated blast furnace slag as precursors to reduce carbon emissions. Stainless steel fibers (SSFs) and polyethylene fibers (PEs) were incorporated into the mixture to enhance the strength and toughness of the coral concrete. The flexural performance of hybrid fiber-reinforced alkali-activated coral concrete (HFRAACC) was assessed using four-point flexural tests and digital image correlation (DIC) technology. The results revealed that HFRAACC experienced flexural failure in three distinct stages: microcrack initiation, macrocrack propagation, and main crack development. The inclusion of SSFs significantly improved crack resistance, flexural strength, and deflection in the initial stages, while PEs mainly contributed to toughening effect in the later stages. When the SSF-to-PE ratio was 2:1, with a total fiber content of approximately 2 %, HFRAACC exhibited optimal flexural performance, achieving the best fiber synergy and the lowest damage evolution rate. Under these conditions, the equivalent flexural strength was 18 times greater than that of the fiber-free group. A model was developed to predict the equivalent flexural strength of HFRAACC, demonstrating good accuracy in its predictions.

Accurate prediction of structural seismic response is essential for damage evaluation and resilience quantification. Existing data-driven models for this problem require large amounts of training data to achieve demanded accuracy. However, the real structural seismic response data is scarce, which hinders the application of these models. To this end, this study proposes Augmented Neural Ordinary Differential Equations (ODEs) informed with domain knowledge for data-driven structural seismic response prediction, using limited data from sensing (i.e., one or two recorded measurements). The buildings are simplified to a multi-storey concentrated mass shear model, and the necessary physical parameters are estimated according to easily accessible building information. Furthermore, the physical information is updated using Bayesian inference to improve the robustness of the trained model for more reliable prediction. The discrepancy between the truth and the estimated physical term is learned by means of Neural ODEs. Additionally, the state space of ODEs is augmented to allow the model to use the additional dimensions to learn the highly nonlinear behavior of structural systems. The performance of the proposed model is demonstrated through both numerical and field-sensing examples. Compared with models of previous studies, the proposed framework achieved higher accuracy, generalization, and physical consistency. Benefiting from domain knowledge and the direct approximation of the governing dynamics, this model alleviates the reliance on large amounts of training data and offers significant potential in the seismic analysis of structures.

Reinforced concrete (RC) rectangular columns situated in coastal areas are susceptible to chloride ion-induced corrosion, which compromises their seismic performance. To investigate the influence of coupling between various engineering parameters and corrosion ratio on the seismic performance and failure mode of RC rectangular columns, eight RC rectangular column specimens were designed and tested under pseudo-static loading, including seven corroded columns and one uncorroded column. The examined parameters included corrosion ratio, axial load ratio, concrete strength, longitudinal reinforcement ratio, and stirrup ratio. Seismic performance was evaluated through cracking pattern, failure mechanism, hysteresis curve, skeleton curve, displacement ductility, secant stiffness, energy dissipation capacity, curvature distribution, displacement composition, and effective stiffness. The results indicate that the seismic performance of the corroded specimens deteriorates significantly with increasing corrosion ratios, particularly at equivalent corrosion levels when the stirrup ratio is low. This degradation can be mitigated by enhancing the concrete strength and increasing the longitudinal reinforcement ratio. Notably, one specimen exhibited shear compression failure, while the others displayed typical flexural failure. This observation indicates a potential transition towards brittle failure modes at higher axial load ratios and corrosion ratios.

Post‐hazard regional structural functionality assessment is crucial for community resilience quantification. The current practices performed by reconnaissance experts are time‐consuming and resource‐intensive. Recent studies have proven the feasibility of utilizing deep learning in automatic structural damage assessment. However, integrating damage assessments of transportation systems and building structures portfolios of the whole community remain unexplored. This study proposes a framework, which enables the evaluation of building structural damage and identification of road obstructions. Utilizing a newly annotated high‐resolution dataset with extensive damage classification and semantic segmentation labels, this model is specifically trained for post‐disaster analysis. The effectiveness and generalization of this methodology is demonstrated in Fort Myers Beach for evaluating the aftermath of Hurricane Ian. Besides, the Bayesian active learning is introduced to select the most valuable samples for fine‐tuning when the test images deviate from the characteristics of the training set, which enhances the robustness of the damage classification. Upon the damage identification, the regional functionality can be quantified based on the level of accessibility of households to different services. The results show the developed approach enables emergency responders to quickly use post‐disaster imagery to identify areas in need of assistance, efficiently route around obstructions, coordinate response efforts, and provide situational awareness.