Search Results (43)

The assessment of seismic performance of existing buildings has traditionally focused on structural safety and damage limitation, often neglecting the explicit quantification of the associated economic consequences. In recent years, performance-based earthquake engineering (PBEE) frameworks have enabled a direct link between structural response and probabilistic loss estimation, allowing economic metrics to be integrated into seismic risk evaluation. Among these, the Expected Annual Loss (EAL) represents a comprehensive indicator that accounts for seismic hazard, structural vulnerability, and exposure over the building’s lifetime. This study presents a performance-based seismic loss assessment of an existing reinforced concrete building, adopting EAL as a global metric for seismic performance evaluation. The case study concerns an existing hospital building designed primarily for gravity loads and representative of a large portion of the Italian building stock. A detailed nonlinear numerical model is developed using OpenSees ver. 3.8.0, incorporating shear-critical behavior through nonlinear link elements. Structural performance is evaluated through modal analysis, pushover analysis, and nonlinear time-history analyses using a set of ground motions selected and scaled according to intensity-based criteria. Seismic losses are estimated following the FEMA P-58 methodology, implemented through the PACT software ver. 3.1.2, integrating structural response demands, component fragility functions, collapse probability, and seismic hazard curves. Probabilistic loss curves are derived, and the EAL is computed as a synthetic indicator of economic seismic performance. The results highlight the effectiveness of EAL in capturing the combined effects of seismic hazard and structural vulnerability, demonstrating its potential as a robust decision-support metric for seismic risk mitigation, retrofit prioritization, and insurance-related applications for existing buildings. Full article

The quest for seismic resiliency requires designing for performance objectives beyond life safety. Functional recovery is an emerging objective often defined as the time required to restore a building’s basic functionality to the pre-event level. Nevertheless, quantifying functional recovery is a complex, computationally intensive process that is challenging to integrate into a standard design workflow. This study develops a machine learning (ML) model to map design and geometric features of steel special moment-resisting frames (SMRFs) to their functional recovery under two hazard levels: design-basis (DBE) and maximum considered (MCE) earthquakes. First, functional recovery time was quantified for an inventory of 100 steel SMRFs with varying heights by integrating FEMA P-58 loss-based methodology with the ATC-138 framework. The building information and calculated recovery times were then used in a standard ML pipeline including feature selection, hyperparameter tuning, cross-validation, model evaluation, and model explainability. The results suggest that the ML model can accurately estimate functional recovery using design and geometric features, achieving R² values of 89% and 93% on the test set for DBE and MCE levels, respectively. In addition, for the studied regular SMRF buildings, the results indicate that building weight and the average strong-column weak-beam ratio are influential design parameters that govern functional recovery time, suggesting that a recovery-oriented design of steel SMRFs may benefit from minimizing building weight and avoiding overt column upsizing. Full article

This study develops collapse fragility curves for a representative steel moment-resisting frame building exposed to idealized tsunami-loading scenarios, explicitly incorporating shoreline distance as an organizing spatial variable. Nonlinear static analyses are performed in SeismoStruct for braced and unbraced configurations, using the maximum interstory drift ratio as the engineering demand parameter. Drift-based damage states are defined according to ASCE 41-23 and FEMA 356 to interpret damage progression, while the probabilistic formulation focuses on the collapse limit state using a lognormal model with total dispersion based on FEMA P695. Triangular and rectangular tsunami-load distributions are considered to assess the influence of load-pattern assumptions. The braced model remains below global collapse within the analyzed intensity range and is retained as a comparative case, whereas the unbraced model reaches global instability and provides the collapse-response information used to construct the fragility curves. The median collapse inundation depth is approximately 14.1 m for the triangular distribution and 11.7 m for the rectangular distribution, corresponding to shoreline distances of approximately 97.5 m and 157.5 m, respectively. The results suggest that shoreline distance can support a spatial interpretation of collapse vulnerability for preliminary coastal-risk assessment, provided that the idealized and site-dependent nature of the adopted distance–depth–velocity scenarios is properly recognized. Full article

The piping systems are critical non-structural elements (NSEs) whose seismic performance directly affects the post-earthquake functionality of essential facilities. However, current seismic design provisions for such systems remain largely empirical, and behavioural factors are rarely calibrated using performance-based methods. This study implements an FEMA P695-inspired framework to calibrate the behaviour factor $\left(q_a\right)$for the installation of sway-braced suspended piping restraint systems in following the force-based requirements specified in Eurocode 8. The representative piping archetypes were developed and analysed using non-linear time history analyses under multiple seismic intensity levels derived from the floor response spectra (FRS) of prototype-reinforced concrete buildings. Fragility curves for two limit states were derived with displacement ductility adopted as the engineering demand parameter (EDP) and peak floor acceleration (PFA) used as the intensity measure (IM). The results show that increasing $\left(q_a\right)$ systematically shifts the fragility curves towards lower median PFA values, indicating higher seismic vulnerability at larger behaviour factor values. The effect of piping layout configuration was of secondary importance compared to the applied reduction factor. The implemented approach provides a rational basis for selecting behavior factors consistent with explicit performance objectives and supports further development of performance-oriented seismic design procedures for non-structural systems. The results show that increasing the behaviour factor $\left(q_a\right)$ leads to a systematic shift in the fragility curves towards lower median PFA values and a noticeable increase in the dispersion of the response. A quantitative analysis shows that increasing the behaviour factor $\left(q_a\right)$ from 1 to 4 results in a reduction of up to approximately 60% in median PFA, highlighting a significant increase in seismic vulnerability at higher behaviour factor values. Full article

This study presents a probabilistic assessment of seismic loss and recovery for residential buildings in Bucharest, Romania, using the FEMA P-58 framework implemented in SP3. A typology set is developed to represent the building stock, accounting for structural system, construction period, and height. The analysis evaluates scenario-based losses, functional recovery times, and expected annual loss (EAL) across seismic hazard levels representative of Vrancea earthquakes. Results show that frame-based systems are highly sensitive to building height, with the highest losses and longest recovery times in older mid- and high-rise buildings. For pre-1990 construction, masonry-infilled reinforced concrete frames are more representative than bare frames and drive the vulnerability of the older building stock. Reinforced concrete shear wall systems perform better, with lower losses and faster recovery across all categories. Nonstructural damage, especially drift-sensitive components, is a contributor to both repair cost and downtime. The results are interpreted comparatively, highlighting the role of structural system, code era, and height. While absolute values depend on modeling assumptions, the study provides a consistent basis for identifying vulnerable typologies and supporting risk mitigation and resilience planning. Full article

Rapid assessment of existing reinforced concrete (RC) buildings is essential for effective seismic risk mitigation, particularly in highly active regions such as Bingol, Turkiye. This study evaluates the local performance of three Rapid Visual Screening (RVS) methods—RBTY-2019, FEMA-P154, and IITK-GSDMA—using verified post-earthquake damage data from the 2003 Bingol Earthquake (SERU-2003). To overcome the limitations of traditional RVS approaches, an Artificial Neural Network (ANN) model was developed and trained with the same dataset to predict building damage levels based on structural deficiency parameters. The ANN achieved a regression coefficient above 0.90 and 100% consistency in test predictions, demonstrating superior accuracy and adaptability to local construction characteristics. A Local Scaling Function (LSF) was also proposed to translate RBTY-2019 performance scores into empirical damage states, achieving 100% consistency with observed data. The findings highlight the reliability of locally trained AI models and the importance of adapting national screening regulations to regional seismic experiences. This integrated ANN–RVS framework provides a practical, data-driven tool for local authorities to prioritize urban building stock and strengthen disaster risk management strategies. Full article

Reinforced concrete buildings with masonry-induced soft-storey irregularities exhibit extreme seismic vulnerability, a critical risk often underestimated by conventional code-based design. Standard equivalent static methods typically fail to capture the intense concentration of seismic demand at the flexible ground level, leading to unconservative designs that do not meet performance objectives. This research proposes a corrective linear–static methodology to address this deficiency. A new Equivalent Lateral Force profile (ELF_i1) was developed, derived from modal analyses of 235 representative soft-storey archetypes to accurately account for stiffness heterogeneity. This profile was integrated with a realistic response modification coefficient (R_i1 = 5.04), determined to be 37% lower than the normative R-factor (R = 8) prescribed by code. Nonlinear static analyses confirmed that conventional design resulted in “irreparable” damage (mean Global Damage Index = 0.82). In contrast, redesigning the structure using the proposed ELF_i1 and R_i1 methodology successfully mitigated damage concentration, upgrading structural performance to a “repairable” state (mean Global Damage Index = 0.52). Finally, Incremental Dynamic Analysis validated the approach; the redesigned structure satisfied FEMA P695 collapse prevention criteria, achieving an Adjusted Collapse Margin Ratio (ACMR) of 2.10. This study confirms the proposed method is a robust and practical design alternative for soft-storey mechanisms within a simplified linear framework. Full article

This study presents a framework for assessing the resilience of steel special moment-resisting frame (SMRF) buildings under sequential earthquake–flood hazards. Surrogate models, including a stacked attention-based LSTM network (Stack-AttenLSTM) and CatBoost, are developed to predict key engineering demand parameters (EDPs), particularly maximum inter-storey drift ratios (MIDRs), avoiding the need for computationally expensive nonlinear time history analysis (NLTHA). The predicted EDPs are integrated with the FEMA P-58 methodology to estimate repair costs and durations, while the REDi framework is used to capture recovery delays and functionality loss. A two-storey code-compliant SMRF building is evaluated under a design-basis earthquake (DBE) with and without a subsequent 4.0 m flood. Results show that the combined hazard nearly doubles repair costs (from 0.33 to 0.77 of replacement value), increases downtime from 194 to over 411 days, and reduces the resilience index (R_i) from 0.873 to 0.265. These findings highlight the severe impacts of cascading multi-hazard events and the need to extend performance-based design toward resilience-focused strategies. The proposed surrogate-based framework provides a practical tool for evaluating multi-hazard risks and guiding the design of more resilient structures. Full article

Small object detection, as an important research topic in computer vision, has been widely applied in aerial visual tasks such as remote sensing and UAV imagery. However, due to challenges such as small object size, large-scale variations, and complex backgrounds, existing detection models often struggle to capture fine-grained semantics and high-resolution texture information in aerial scenes, leading to limited performance. To address these issues, this paper proposes an efficient aerial small object detection model, EABI-DETR (Efficient Attention and Bi-level Integration DETR), based on the RT-DETR framework. The proposed model introduces systematic enhancements from three aspects: (1) A lightweight backbone network, C2f-EMA, is developed by integrating the C2f structure with an efficient multi-scale attention (EMA) mechanism. This design jointly models channel semantics and spatial details with minimal computational overhead, thereby strengthening the perception of small objects. (2) A P2-BiFPN bi-directional multi-scale fusion module is further designed to incorporate shallow high-resolution features. Through top-down and bottom-up feature interactions, this module enhances cross-scale information flow and effectively preserves the fine details and textures of small objects. (3) To improve localization robustness, a Focaler-MPDIoU loss function is introduced to better handle hard samples during regression optimization. Experiments conducted on the VisDrone2019 dataset demonstrate that EABI-DETR achieves 53.4% mAP@0.5 and 34.1% mAP@0.5:0.95, outperforming RT-DETR by 6.2% and 5.1%, respectively, while maintaining high inference efficiency. These results confirm the effectiveness of integrating lightweight attention mechanisms and shallow feature fusion for aerial small object detection, offering a new paradigm for efficient UAV-based visual perception. Full article

While urban green spaces are integral to urban resilience, their long-term dynamics under recurrent flooding have received limited scholarly attention. This study investigates two decades of green space change across 367 counties in the southeastern United States, integrating FEMA disaster records with multi-period land cover data. Employing generalized additive and logistic regression models, the impacts of flood frequency, development intensity, and socioeconomic drivers were assessed. Flood frequency was identified as the primary determinant of urban green space loss. Each additional flood event corresponded to a 0.36% reduction in the five-year green space change rate (p < 0.01), while extreme flood frequency (≥ 10 events) was associated with an 18-fold increase in the odds of long-term degradation. Development intensity exhibited a significant non-linear effect, with loss rates culminating at moderate-to-high intensities. Furthermore, household income functioned as a significant moderator; in extremely flood-prone areas, higher income correlated with enhanced resilience (OR = 0.155, p < 0.05). These findings demonstrate that recurrent floods function as a cumulative pressure. This research highlights the necessity of equitable green infrastructure planning that integrates flood risk with the complex, moderating role of socioeconomic capacity. Full article

Due to their potential to reduce greenhouse gas emissions, light-frame timber buildings (LFTBs) are widely used in seismically active regions. However, their construction in these areas remains limited, primarily due to the high costs associated with continuous anchor tie systems (ATSs), which are required to withstand significant seismic forces. To address this challenge, frictional seismic isolation offers an alternative by enhancing seismic protection. Although frictional base isolation is an effective mitigation strategy, its performance can be compromised by extreme ground motions that induce large lateral displacements, resulting in impacts between the sliders and the perimeter protection ring. The effects of these internal lateral impacts on base-isolated LFTBs remain largely unexplored. To fill this knowledge gap, this study evaluates the collapse capacity of a set of base-isolated LFTBs representative of Chilean real estate developments. Nonlinear numerical models were developed in the OpenSeesPy platform to capture the nonlinear behavior of the superstructure, including the impact effects within the frictional isolation system. Incremental dynamic analyses following the FEMA P695 methodology were performed using subduction ground motions. Collapse margin ratios (CMRs) and fragility curves were derived to quantify seismic performance. Results indicate that frictional base-isolated LFTBs can achieve acceptable collapse safety without ATS, even with compact-size bearings. Code-conforming archetypes achieved CMRs ranging from 1.24 to 1.55, indicating sufficient safety margins. These findings support the cost-effective implementation of frictional base isolation in mid-rise timber construction for high-seismic regions. Full article

To improve the post-earthquake resilience evaluation of concrete buildings with various construction types, this study presents a generalized recovery-based framework that ext-ends the FEMA P-58 methodology. The proposed method introduces a dynamic repair scheduling approach that incorporates two key construction-related parameters: the prefabrication ratio and the types of prefabricated components. These inputs govern the allocation of parallel or sequential repairs, enabling a more accurate estimation of recovery trajectories and downtime. Functional loss over time is modeled through component-level repair sequencing combined with mobilization delays. A case study involving three four-story prestressed concrete frame buildings (cast-in situ, partially prefabricated, and fully precast prestressed concrete (PCaPC) with mortise–tenon (MT) connections) demonstrated the framework’s applicability. The results show that higher prefabrication levels lead to significantly shorter median repair times, with up to a 97-day reduction observed for the fully prefabricated frame. Additionally, recovery differences emerge even between buildings with the same prefabrication ratio but different component configurations. Compared to conventional assessment methods, the proposed framework avoids the overestimation of mobilization and repair duration, offering a practical tool for the design and performance assessment of resilient precast and hybrid concrete building systems. Full article

Currently, seismic-resistant design is carried out by applying codes that are periodically updated based on research findings and lessons learned from major seismic events. In the case of buildings located on sloping terrains and those composed of reinforced concrete shear walls, there is a notable lack of specific design provisions in existing standards. For this reason, the methodology outlined in FEMA P695 was applied in the present study, with the aim of validating the response reduction factor used for designing this type of structure in Chile. Additionally, other parameters that allow for the evaluation of design performance or serve as complementary indicators—such as ductility, the overstrength factor, and the displacement amplification factor—were determined. To conduct this study, a series of archetype buildings were designed, varying the slope inclination from 0° to 45°. The results show that, although the current design approach ensures safety, it is necessary to specify different design parameters for the directions parallel and orthogonal to the slope in order to optimize the seismic performance of the buildings. Full article

Objective: To explore the possible association and trends between individual-level disaster preparedness status (for natural, technological, and human-caused hazards) and the level of pandemic preparedness during the COVID-19 pandemic among adults in the U.S. from 2021 through 2023. Methods: Multivariate logistic regression was conducted using data from the U.S. Federal Emergency Management Agency’s (FEMA) annual National Household Survey (NHS) from 2021 to 2023 to identify statistically significant variables associated with personal pandemic preparedness behavior among participants of the nationally representative survey during the COVID-19 pandemic. Results: Overall, the results showed that the proportion of respondents that were considered prepared for a pandemic peaked in 2021 (54.0%) and steadily decreased in the following years (2022: 43.3%; 2023: 41.3%) highlighting the need for pandemic preparedness resources and educational campaigns to be available prior to a pandemic occurring. The final multivariate logistic regression models featuring consistent significant covariates demonstrated a highly statistically significant relationship between individual-level disaster preparedness and pandemic preparedness across all three study years (2021: odds ratio (OR): 21.35, standard error (SE): 2.59, p < 0.001; 2022: OR: 9.26, SE: 0.87, p < 0.001; 2023: OR: 6.75, SE: 0.59, p < 0.001). Conclusions: The significant results suggest individuals who are prepared for a disaster have higher odds of being prepared for a pandemic. These findings support the continued increase in collaboration between emergency management and public health entities to jointly support the development of evidence-based resources to increase personal preparedness for both disasters and pandemics. Full article

Under earthquake action, concrete silos can undergo damage over a vast area or may even collapse. To aid seismic design, a numerical simulation of the seismic performance of column-supported reinforced concrete silos was performed, and the performance was quantitatively described. The focus of the research was on determining the damage levels of these silos by adopting an incremental dynamic analysis. The focus of the research was on determining the damage levels of these silos by adopting an incremental dynamic analysis. Four limit states were defined for the first time so as to better determine the damage states of column-supported reinforced concrete silos in the event of earthquakes and the vulnerability analysis of the silo structures was carried out. The analysis results show that volume of the stored grain directly determined its damage behavior. The silo with a greater amount of stored grain entered the plastic state earlier, and the damage effect was more evident. Under the most dangerous working conditions, i.e., the full state of the silo, the 50-year collapse exceedance probability of the silo reaching collapse (LS4) was less than 1% of the 50-year failure risk limit defined in the US seismic design code FEMA P750. This demonstrated that a column-supported reinforced concrete silo can maintain its high anti-collapse reserve capacity under the effect of rare earthquakes. Full article