ABSTRACT Steel bridge piers are critical components that exhibit vulnerability during earthquakes, making the study of their seismic performance essential. This paper develops a finite element model of steel bridge piers using a bilinear kinematic hardening constitutive model. Incremental dynamic analysis is performed under 150 seismic waves, and vulnerability curves are constructed using the maximum strain at the pier bottom and the maximum displacement at the pier top as damage indices. This paper investigates the effects of the maximum pier base strain and energy on the vulnerability of steel bridge piers, and proposes a composite damage index (DI) that incorporates the influence of hysteretic energy dissipation.

The cloud image method is widely used in the result vulnerability analysis because of its convenient calculation. However, there are some problems in the cloud image method, such as the engineering demand parameter (EDP) does not meet the lognormal distribution, the seismic intensity index ln(IM) does not meet the linear relationship with the engineering demand parameter (ln(EDP)), and the residual does not meet the normal distribution. Therefore, this paper introduces two methods of Box–Cox transform and 3-sigma criterion, and combines Latin hypercube sampling to propose a vulnerability analysis method that not only maintains the advantages of less analysis times of the cloud image method but also improves the normality of ln(EDP), the correlation between independent variables and dependent variables and the normality of residuals of cloud image method. Finally, taking a continuous beam bridge as an example, the time history analysis of the whole bridge model is carried out to verify whether the variables before and after the correction meet the normal distribution, and the effectiveness of the improved method is evaluated; By establishing the vulnerability curve of the cloud image method and the improved method, the cloud image method and the improved method are evaluated. The results show that the introduction of Box–Cox transformation and 3-sigma criterion can improve the linearity and normality of the probabilistic seismic demand model, and ensure the accuracy of the vulnerability calculation results. Using the Latin hypercube sampling method to consider the uncertainty of the structure can make the vulnerability results more realistic.

To tackle the safety performance concerns of Squat shear walls in nuclear island structures (which serve as shields for powerhouses) under seismic action, this research endeavors to explore the seismic performance of such shear walls with different reinforcement ratios. Pseudo-static loading tests were carried out on 6 shear wall specimens, which were divided into 3 groups (with different reinforcement ratios). The focus was on analyzing the specimens’ failure process, load-deformation hysteretic curves, shear strength, ductility, strain, and other crucial parameters. The experimental findings demonstrate that all specimens underwent shear failure, which was characterized by the compression of web concrete. A higher reinforcement ratio can alleviate the buckling extent of structural steel. Specifically, an elevated horizontally distributed steel ratio notably enhances the ductility and energy dissipation capacity of the specimens, thereby effectively improving the yield load, stiffness, and ductility of squat shear walls. Nevertheless, its influence on cumulative energy dissipation and crack development is limited. Based on the analysis of the specimens’ failure modes, hysteretic curves, skeleton curves, energy dissipation, and stiffness degradation laws, finite-element numerical analysis was carried out on selected specimens. Comparison with the experimental results showed a good consistency between the two. Ultimately, the influence of the reinforcement ratio on the seismic performance of the shear walls was ascertained, and the research on the variation rules of the seismic performance parameters of squat shear walls was completed after verification through finite-element modeling. Based on this, a nonlinear fitting approach was employed to construct a regression prediction model for the seismic performance of shear walls in the Hainan Changjiang Multipurpose Modular Small Reactor Technology Demonstration Project. Typical squat shear walls were chosen for seismic response analysis, and the corresponding outcomes were acquired. Finally, a series of seismic vulnerability curves for nuclear island shear walls with varying guarantee rates were formulated for verification.

Over recent decades, devastating earthquakes have frequently struck Iran, causing substantial damage upon its existing infrastructure. These seismic events have tragically resulted in extensive human casualties and severe economic losses, thereby underscoring the critical importance of assessing the impact of single or multiple seismic occurrences on various building types. This imperative has consequently garnered significant attention from the research community. The occurrence of a seismic event inherently carries the potential for widespread damage to infrastructure, particularly to existing buildings, which can subsequently lead to injuries and fatalities. It is therefore incumbent upon structural and earthquake engineers to minimize the extent of such damage, injuries, and human fatalities. Therefore, the assessment of the seismic resilience of critical structures assumes a pivotal role in comprehensive disaster prevention and mitigation strategies. Among societal cohorts, students and educational staff represent some of the most vulnerable populations susceptible to both natural and human-caused disasters. Ensuring the continuity and safety of their educational processes thus requires rigorous attention to the resilience of their educational environments. For the current case study, a school building situated in Tehran, with a total floor area of 1390 square meters, was selected as the representative sample. The objective was to thoroughly assess its seismic resilience, serving as a sample for educational facilities across the city. Initially, the structural performance was evaluated through nonlinear static analysis. Upon the identification of structural inadequacies, a comprehensive seismic retrofitting initiative was undertaken. After a thorough review of various structural strengthening methodologies, two distinct methods were ultimately adopted for the seismic upgrade of this school: Special Concentric Braced Frames (SCBF) and Reinforced Concrete (RC) Shear Walls. After retrofitting with these two methods, IDA, fragility, and vulnerability curves were drawn based on the results from both scenarios. Also, an estimate of implementation costs was made using PACT software. In this study, to verify the effectiveness and performance level of the retrofitting methods, the FEMA P-58 methodology was employed across various seismic risk levels (2%, 10%, 20%, and 50% in 50 years). The results of this process demonstrate a significant reduction in financial losses and recovery time for the structure retrofitted using the two mentioned scenarios. Furthermore, the overall resilience index has improved. However, retrofitting with reinforced concrete shear walls showed superiority compared to special concentric braced frames. Furthermore, a damage assessment was carried out in this research. This assessment utilized the FEMA P-58 methodology, with the PACT software serving as a key tool for its execution.

Abstract Key message Continuous monitoring of stem water potential and circumference variation reveals a relationship between apparent stem capacitance and Ψ-mapped embolism risk during drought, providing a mechanistic and practical proxy to assess hydraulic safety in mature conifers. Abstract Projected increases in drought frequency and intensity threaten the hydraulic function and survival of mature conifers. However, continuous in-situ monitoring of stem water status remains technically challenging, particularly within forest canopies. We deployed microtensiometers and precision dendrometers in a thinned Pinus sylvestris stand (Sierra Nevada, Spain) to monitor hourly stem water potential ( Ψ STEM ) and stem circumference variation ( SCV ). Stem hydraulic capacitance ( C S ) was derived in situ from SCV– Ψ STEM time series. Embolism risk, PLC (Ψ) , was estimated at diagnostic intervals by mapping in-situ Ψ STEM onto laboratory vulnerability curves. Continuous Ψ STEM closely matched independent leaf pressure-chamber measurements (R² = 0.78) and covaried with sub-daily SCV dynamics, validating both sensors. Midday SCV ( SCV MD ) covaried with midday Ψᴍᴅ (R² = 0.49) and with Ψ -mapped embolism risk ( PLC ( Ψ MD )) (R² = 0.51), indicating that greater shrinkage aligns with more negative tension and higher estimated risk. Across the dry-down, PLC ( Ψ ) indicated rising risk while C S declined; we interpret this as a plausible capacitance–risk linkage given our design. Concurrent eddy-covariance measurements showed late-summer attenuation of canopy latent energy ( LE ), with lower midday peaks and reduced diurnal amplitude-coincident with higher PLC ( Ψ ) estimates and declining C S . Mixed-effects modeling revealed that SCV was jointly driven by Ψ STEM , air temperature, vapor-pressure deficit, relative humidity, and most prominently soil water content. Together, these results demonstrate that non-destructive, high-temporal-resolution sensing resolves diel–seasonal hydraulics and support a capacitance–embolism risk trade-off. We further show that SCV MD provides a practical proxy for hydraulic status where direct tensiometry is impractical, informing physiologically based forest management. Graphical abstract

Introduction. Extreme storms with wind speeds exceeding 30–35 m/s pose a significant threat to navigation and coastal infrastructure in the Azov Sea. The complex bathymetry, shallow water, and coastal geometry amplify wave and surge effects, causing severe destruction. The increasing frequency of extreme weather events requires next-generation forecasting systems capable of capturing nonlinear multiscale interactions between wind, waves, and currents. Materials and Methods. A hybrid approach was developed, combining three-dimensional numerical hydrodynamic modelling based on the Navier-Stokes equations with Large-Eddy Simulation (LES) turbulence closure, ensemble probabilistic forecasting, and machine learning methods — including Physics-Informed Neural Networks (PINNs) and Fourier Neural Operators (FNOs). Atmospheric and oceanographic data from ERA5 and CMEMS reanalyses were used to reconstruct storm scenarios for 2010–2024. Ship-wave interactions were modeled in six degrees of freedom, while coastal infrastructure fragility was evaluated using probabilistic vulnerability curves. Validation was performed using Sentinel-1/3 satellite data processed by the “LBP-neural_network” software package and Copernicus Marine Service products. Results. Three representative storm scenarios were simulated. The significant wave height in the central Azov Sea reached up to 5.2 m, with surge amplitudes up to 1.5 m. The most hazardous conditions occurred in the Kerch Strait, where current velocities reached 1.1 m/s. Under wind speeds of 30–35 m/s, the probability of exceeding the critical 4 m wave height was 42%. Resonant ship motions with roll amplitudes up to 25° were detected, indicating a high capsizing risk. Risk maps identified the most vulnerable zones near Taganrog, Yeysk, and Port Kavkaz. The integration of PINNs and FNOs accelerated ensemble simulations by a factor of 10–12 while maintaining prediction errors below 8%. Discussion. The proposed hybrid methodology proved highly effective for modelling extreme hydrodynamic processes and navigation risks. The LES framework accurately reproduced wave breaking and vortex generation processes, while coupling with neural network surrogates combined physical consistency with computational efficiency. Conclusion. The approach improved forecast accuracy by 25–30% compared with conventional spectral models (SWAN, WAVEWATCH III). The results provide a scientific basis for developing early warning systems, assessing navigation safety, and planning coastal protection measures in the Azov–Black Sea region.

Abstract Background Although the extent and severity of fires is linked to moisture content in live and dead plant material, the ranges of moisture content occurring in live foliage are poorly defined. The biogeographical distribution of morphological ( e.g. , leaf mass per area) and physiological traits ( e.g. , water potential at turgor loss point) leads us to expect that ranges of moisture content in live foliage are similarly linked to climate, with lower ranges in species from more arid environments. We used pressure–volume and hydraulic vulnerability curves combined with measurements of leaf mass and leaf area to estimate the ranges of moisture content in leaves of some of the dominant Eucalyptus species in south-east Australia, from saturation to hydraulic failure. We also manipulated the moisture content of leaves of the study species by wetting and drying individual leaves which were then exposed to radiant heat to test time to ignition and combustion time across ranges of moisture content. Results The study species occupied different ranges of moisture content, which were limited by leaf saturation and the estimated point of hydraulic failure; saturated moisture contents ranged from 108–152%, and lethal moisture contents ranged from 59–80%. Species with more humid climatic ranges had higher ranges of moisture content. Higher moisture content was found to linearly increase time to ignition in leaves of all species. Time to ignition at the species-specific saturated and lethal moisture content, and the rate of change of time to ignition against moisture content, varied among species according to leaf mass per area, with leaves from species with higher leaf mass per area being slower to ignite. Conclusions We quantified ranges of moisture contents in live leaves and identified traits which could predict how they vary with environmental gradients. Leaf mass per area strongly affected time to ignition but appears to have counter-acting influences on ignitability by simultaneously affecting moisture content and rate of heating. While moisture content increased time to ignition, we found no evidence of a critical threshold of moisture content that determined whether leaves ignited. Models of live fuel moisture content could be constrained by plant traits; some, such as leaf mass per area, are easy to measure, although others, such as hydraulic vulnerability thresholds, are not.

Approach to develop vulnerability curves for tidal turbine blades

ABSTRACT This study advances the performance‐based plastic design (PBPD) method for the application of buckling‐restrained braces (BRB) in laminated bamboo frame (LBF) structures. A vulnerability analysis discusses the key parameters involved in the design method and their impact on the reinforcement effectiveness. Multistripe analysis was employed to generate vulnerability curves for both structures across various limit states, while Latin hypercube sampling (LHS) was utilized to sample modeling parameters. The addition of BRB supports markedly increases the lateral stiffness of LBF structures, thereby improving their seismic performance. The analysis reveals that the effectiveness of BRB diminishes from approximately 50% to around 20% as the ultimate drift ratio ( θ u ) increases. In the PBPD method, the important design parameter—story shear ratio ( p )—is also affected by θ u . As θ u rises, the p ‐value that achieves maximum median intensity in the vulnerability function increases. Furthermore, the inclusion of BRB reduces the overall modeling uncertainty of the structure, indicating that modeling uncertainty significantly influences the vulnerability curves of LBF structures. Under the excitation of near‐field earthquakes, the annual collapse probability of the BRBLBF structure was found to comply with existing regulations and requirements.

Drought remains one of the most damaging natural hazards to agricultural production and is projected to continue posing substantial risks to food security in the future, particularly in major rice-growing regions. Based on the RCP4.5 and RCP8.5 scenarios under CMIP5, this study used a process-based crop growth model to simulate the growth of rice in China in different future periods (short-term (2031–2050), medium-term (2051–2070), and long-term (2071–2090)). We fitted rice vulnerability curves to evaluate the rice drought risk quantitatively according to the simulated water stress (WS) and yield. The results showed that the drought hazard in major rice-growing areas in China (MRAC) were low in the middle and high in the north and south. The areas without rice yield loss will decline in the future, while the areas with a high yield loss will increase, especially in southwestern China and the middle and lower Yangtze Plain (MLYP). Owing to the markedly increased evaporative demand and the reduced moisture transport caused by a weakening East Asian summer monsoon, northeastern China will be a high-risk area in the future, with the expected yield loss rates in scenarios RCP4.5 and RCP8.5 being 39.75% and 45.5%, respectively. In addition, under the RCP8.5 scenario, the yield loss rate of different return periods in south China will exceed 80%. A significant gap between rice supply and demand affected by drought is expected in the short-term future. The gaps will be 67,770 kt and 78,110 kt under the RCP4.5-SSP2 and RCP8.5-SSP3 scenarios, respectively. The methodology developed in this paper can support the quantitative assessment of drought loss risk in different scenarios using crop growth models. In the context of the future expansion of Chinese grain demand, this study can serve as a reference to improve the capacity for regional drought risk prevention and ensure regional food security.

In this paper, the Changgangpo aqueduct is taken as the research object to establish a three-dimensional nonlinear finite element model of the ribbed arch aqueduct structure. This study focuses on the dynamic response analysis, damage evolution rule, and failure mode of the ribbed arch aqueduct structure at different seismic intensities. The results indicate that the displacement response of the aqueduct structure increases steadily with the duration of seismic activity. In addition, when material damage characteristics are considered, the displacement failure response of the structure also increases gradually. During a 20 s seismic event, the peak curvature response of the arch foot, accounting for damage conditions, reaches 0.0167, which is 31.1% lower than the 0.0219 observed under linear elastic conditions. This reduction is primarily caused by damage to and failure of the concrete, which increases structural damping and absorbs significant energy, thereby reducing the effect of earthquakes on the structure and decreasing internal forces. The study also analyzes the damage evolution process and typical damage states of the aqueduct structure, including the trough body, ribbed column, and arch rib. Severe damage occurs mainly in the trough body, abdominal arch, midspan ribbed column, and arch foot of the upper pier. The failure mechanism of the bearing members, such as the lower abdomen arch, ribbed column, and arch rib, is revealed to be primarily shear failure and bending failure. In addition, a vulnerability curve of the aqueduct structure is constructed to estimate the failure probability under seismic loads. The research results reveal the seismically vulnerable parts and seismic performance of ribbed arch aqueduct structures, which can provide a theoretical basis for the seismic design and reinforcement of similar aqueduct structures.

To more effectively account for the correlation between components in the seismic reliability analysis of reinforced concrete arch bridges, this study proposes a system seismic reliability analysis method based on the D-vine Copula function. First, based on the theories of seismic vulnerability and hazard, the seismic vulnerability curves of key components (arch ring, piers, main girder, columns) and the site hazard curves are obtained. Second, a trial algorithm is used to determine alternative combinations of Pair-Copula functions. The maximum likelihood estimation method is employed to solve for the parameter θ, and the optimal Pair-Copula function is selected based on AIC and BIC information criteria. The optimal Pair-Copula function for each layer in the D-vine structure is determined through hierarchical iteration, ultimately constructing a seismic reliability evaluation framework for arch bridge systems that incorporates component correlations. The results show that the damage probability of the arch ring is consistently the highest, followed by the piers and main girder, with the columns having the lowest probability. Compared to ignoring component correlation, the seismic reliability indices of the system under minor, moderate, severe damage, and complete failure states all decrease when correlation is considered, indicating that component correlation significantly affects system reliability. Ignoring correlation leads to an overestimation of the system’s seismic performance. The seismic reliability indices obtained by the D-vine Copula method and Monte Carlo simulation are in good agreement, with a maximum relative error not exceeding 2.26%, verifying the applicability and accuracy of the D-vine Copula method in the reliability analysis of complex structural systems. By constructing an accurate joint probability distribution model, this study effectively accounts for the nonlinear correlation characteristics between components. Compared to the traditional Monte Carlo simulation, which relies on large-scale repeated sampling, the D-vine Copula method significantly reduces computational complexity through analytical derivation, improving computational efficiency by over 80%.

Traditional pedestrian evacuation models struggle to balance global exit guidance with local, individual decision making under hazards. We address this by decomposing long-term objectives into Particle Swarm Optimization (PSO)-based micro-goals and proposing a hybrid Cellular Automaton (CA) and PSO model. The hybrid design reduces the decoupling between spatial discretization and individual choices and more tightly couples hazard and density fields with movement decisions. Two contributions are central. First, we develop an autonomous following pathfinding mechanism (AFPM) that linearly blends the direction toward a PSO micro-goal with a herd following direction and adds a small reward for directional consistency. This mitigates path chaos from purely autonomous moves and congestion aggregation from purely herding moves. Second, we build a multi-dimensional interpretability and robustness framework that combines the empirical Cumulative Distribution Function (CDF) and a kernel-smoothed Probability Density Function (PDF) of key evacuation times (T_clear, T_95%_alive) together with vulnerability curves, to analyze the data and assess robustness. It combines Shapley Sobol analysis to quantify parameter effects on clearance time T_clear and the 95% survival evacuation time T_95%_alive, with CDF/PDF summaries and vulnerability curves to assess anti-interference performance. Experiments use a simulated underground shopping mall. In a 60 pedestrian case, a geometry-only baseline yields T_clear ≈33 s; hazard- and density-aware strategies produce slightly longer T_clear but reduce peak bottleneck congestion by 20–30%. When one exit is closed, the exceedance probability at τ=70 s drops from 0.44 to 0.36, reducing long tail risk. Compared with geometry-based Dijkstra, the proposed model slightly increases clearance time while lowering peak congestion by 20–30%, achieving a balance between efficiency and safety. The model and evaluation protocol provide technical support for evacuation policy, facility layout, and emergency system design in large complex buildings.

Selection of the optimal intensity measure is an important contribution to reducing the numerous uncertainties in seismic inputs within the context of performance-based earthquake engineering, especially for unreinforced masonry buildings that exhibit strong nonlinear behaviour. While traditional metrics such as efficiency, sufficiency, and practicality have been successfully used to determine optimal intensity measures for seismic demand models and fragility curves, the impact of different intensity measures on the final vulnerability curves has not been sufficiently investigated. Therefore, a new vulnerability-based metric is proposed, based on the vulnerability curve variance and its first derivative, with the aim of determining the optimal intensity measure for new vulnerability models of mid-rise unreinforced masonry buildings. Both traditional and new metrics were used to evaluate the performance of common intensity measures, using a typical unreinforced masonry building located in Zagreb, Croatia as a case study. The new metric produced intensity measure rankings in line with traditional metrics, but additionally proved effective in quantifying the impact of intensity measure choice on the final vulnerability curve, making it a reliable tool for vulnerability modelling. Average spectral acceleration and peak ground velocity were among the best performing intensity measures, confirming their use for unreinforced masonry buildings.

This paper examines the seismic performance evaluation methodology for underground structures. Through analysis of seismic damage and failure characteristics of underground structures, this study proposes a novel evaluation approach for frame-type underground structures based on the sectional curvature deformation indicator of structural components. The research establishes a classification system for seismic performance levels with corresponding state descriptions. A comprehensive seismic vulnerability analysis is conducted on a typical two-story-three-span station structure, generating vulnerability curves based on the proposed indicator. For comparison with traditional methods, vulnerability curves are also developed using the interstory displacement angle indicator. The comparison results indicate that relying solely on interstory displacement angle provides an insufficient assessment of the seismic performance of underground structures. The proposed methodology more effectively captures the influence of critical parameters, such as the axial compression ratio of interior columns, on overall seismic performance. This methodology demonstrates robust applicability across diverse frame-type underground structures in practical engineering scenarios, enabling precise evaluation of their seismic performance.

Correction: Seismic Vulnerability Curves for Non-reinforced Asymmetric Masonry Buildings Retrofitted with External Shotcrete: A Case Study on Control and Switchgear Room of Power Substations

Generating vulnerability curves for seismic resilience assessment of steel pipe pile-supported wharves

Abstract This paper discusses the seismic performance of existing schools based on the analysis of a reinforced concrete school building located in Tijuana, Mexico. The building has an illustrative configuration and geometry of schools in the region. Ambient vibration tests and complementary studies were conducted to evaluate the actual behavior of the building, including concrete rebar scanning, carbonation detection, core sampling, and soil mechanical properties. The material characteristics and dynamic properties allowed the calibration of a detailed 3D model in OpenSees. Nonlinear static and dynamic analyses were conducted using the analytical model to obtain the response under 77 different ground motions. The reported damage was related to the actual capacities of schools based on a field inspection after the September 19, 2017 earthquake in Mexico. Vulnerability curves were then used to determine the probability of damage in structural and non-structural components and, therefore, the overall performance under the imposed scenarios.

Abstract From 10 to 15 April 2025, China experienced a rare persistent extreme wind-dust compound disaster that swept from north to south. Based on observational data, historical disaster records, and situations of various exposed elements, this study analyzed the formation mechanisms and evolution of this extreme event and conducted a rapid assessment of the associated loss and damage. The results indicate that the direct cause of this extreme wind-dust compound disaster was a strong cold vortex system generated in Mongolia, which moved eastward and southward, combined with the amplification effects of topography and urban structures, and the downward transmission of momentum from higher troposphere. The analysis revealed that approximately 697.47 million people were exposed to strong winds, while about 1,374.54 million people were exposed to high concentrations of PM10. The strong winds also caused varying degrees of damage to buildings, transportation networks, agricultural greenhouses, and forests. Based on vulnerability curves for wind-related loss and damage, it was estimated that the number of victims affected by this extreme wind-dust compound disaster ranged from 0.209 to 1.044 million, with casualties between 5 and 13 individuals. The number of damaged buildings was estimated to be between 2115 and 4607, and the area of affected crops was between 229 and 783 km2. The direct economic losses could reach as high as RMB 0.076–3.501 billion yuan. This study revealed the causes of this extreme wind-dust compound disaster and quantified the disaster loss and impact, providing new insights for the prevention of associated disasters.

In national building standards, HRB335 steel bars have been phased out, with HRB400 and higher-grade steel becoming standard for structural materials. The use of HRB400 reinforced concrete (RC) frame structures has grown, as earthquake-related casualties and economic losses are often caused by building collapse. This study evaluates the seismic performance of RC frame structures reinforced with HRB400 material, focusing on four key parameters: axial compression ratio, aspect ratio, concrete strength, and longitudinal reinforcement strength. Using a data detection method, the seismic vulnerability of these structures is assessed. Aftershock analysis reveals that with 160 aftershocks, the probability of slight damage is 0.92, moderate damage is 0.59, and serious damage is 0.29. This suggests that repeated aftershocks elevate the vulnerability curve, increasing the likelihood of structural damage. Thus, the inspection and evaluation of HRB400-reinforced structures is crucial for ensuring building safety in seismic regions.