Search Results (420)

The paper presents the main features of a Web-GIS platform designed to compute real-time scenario-based seismic risk assessments at the national level. Based on the Italian experience, the platform enables DRM scientist and policymakers to readily generate seismic scenarios supporting the entire DRM cycle, including training, emergency planning, calibrating operations during response, and providing seismic risk estimates for National Disaster Risk Assessment or seismic risk reduction programs. The platform is immediately operational, relying on preloaded freeware datasets on exposure and vulnerability, and requiring only basic earthquake parameters to perform real-time analysis. At a later stage, these datasets should be replaced with more detailed and accurate national-level data. The platform generates earthquake impact assessments that include physical damage, economic and human losses, and key emergency response indicators, such as estimated displaced population, required tent camps, and EMT and USAR needs. Its key innovation lies in the ability to operate at the national scale, offering immediate usability with the possibility of further customization. As a web-based service with a user-friendly graphical interface, it is particularly suited for civil protection and DRM experts. Full article

The aim of this study is to investigate how the positioning of outrigger systems affects the seismic performance of high-rise buildings with either reinforced concrete (RC) shear walls or buckling-restrained braces (BRBs) in the core. Two important questions emerge as the focus and direction of the study: (1) How does the structural performance change when outriggers are placed at various positions? (2) How do outrigger systems affect structural behavior under sequential earthquake scenarios? Nonlinear time history analyses were employed as the primary methodology to evaluate the seismic response of the two reinforced concrete buildings with 24 and 48 stories, respectively. Each building type was developed for two different core configurations: one with a reinforced concrete shear wall core and the other with a BRB core system. Each analysis model also includes outrigger systems constructed with BRBs positioned at different floor levels. Five sequential ground motion records were used to assess the effects of main- and aftershocks. The analysis results were evaluated not only based on displacement and force demands but also using a damage measure called the Park-Ang Damage Index. In addition, displacement-based metrics, particularly the maximum inter-story drift ratio (MISD), were also utilized to quantify lateral displacement demands under consecutive seismic loading. With the results obtained from this study, it is aimed to provide design-oriented insights into the most effective use of outrigger systems formed with BRB in high-rise RC buildings and their functions in increasing seismic resistance, especially in areas likely to experience consecutive seismic events. Full article

The increasing frequency and severity of natural disasters—such as floods, storms, droughts, and earthquakes—have created a growing demand for temporary housing. These facilities must be rapidly deployed to provide safe, functional living environments for displaced individuals. This study proposes a design methodology for temporary housing exteriors using the text-to-image capabilities of generative artificial intelligence (GenAI) to address urgent post-disaster housing needs. The approach aims to improve both the efficiency and practicality of early-stage design processes. The study reviews global trends in temporary housing and the architectural applications of GenAI, identifying five key environmental factors that influence design: type of disaster, location and climate, duration of residence, materials and structure, and housing design. Based on these factors, hypothetical disaster scenarios were developed using ChatGPT, and corresponding exterior designs were generated using Stable Diffusion. The results show that diverse, scenario-specific design alternatives can be effectively produced using GenAI, demonstrating its potential as a valuable tool in architectural planning for disaster response. Expert evaluation of the generated designs confirmed their ability to adhere to text prompts but revealed a significant gap in terms of architectural plausibility and practical feasibility, highlighting the essential role of expert oversight. This study offers a foundation for expanding GenAI applications in emergency housing systems and supports the development of faster, more adaptable design solutions for communities affected by natural disasters. Full article

Reinforced concrete (RC)–masonry hybrid systems are commonly found in both historical renovations and modern constructions, particularly in seismic regions. While combining the ductility of RC with the mass and stiffness of masonry offers potential advantages, these systems often exhibit complex and unpredictable seismic behavior due to the differing mechanical characteristics of the two materials. This study aims to evaluate the benefits and drawbacks of RC–masonry hybrid systems by performing a comparative numerical analysis of three structural configurations. As a representative case study, the historical İsa Divanlı Mosque in Kahramanmaraş, Turkey—severely damaged during the 6 February 2023 earthquakes—is modeled under three scenarios: (Configuration A) full RC structure with shear walls, (Configuration B) unreinforced masonry, and (Configuration C) the existing hybrid form with an RC dome and slabs over masonry walls. Finite element models were developed for each case, and their seismic responses were analyzed under identical loading conditions. The maximum spectral displacements were 55.3 mm, 45.8 mm, and 59.5 mm for the RC, masonry, and hybrid configurations, respectively. The Normalized Displacement Index (NDI) values reached 0.666 mm/MPa for the RC and hybrid systems, while the masonry configuration remained at 0.528 mm/MPa, reflecting its brittle behavior. The findings highlight the influence of structural typology on seismic vulnerability and demonstrate the potential risks and disadvantages of hybrid systems. This study contributes to the understanding of hybrid structural behavior and offers recommendations for the design and retrofit of such systems in seismic regions. Full article

This study focuses on determining stress distribution in elastic continuous beam foundations subjected to large eccentricities primarily induced by the overturning moments generated when horizontal forces, like those from earthquakes and wind, act on the superstructure. Traditional linear static solutions provide an incorrect stress distribution when a foundation loses partial contact with the ground, as they erroneously calculate tensile stress in the uplifted regions. This research aims to formulate a mathematical model that accurately calculates the corrected stress distribution. An optimization problem is defined to minimize the discrepancy between the external effects (loads and moments) from the superstructure and the internal resistance effects from the redistributed base stress under the condition of partial foundation uplift. To solve this, meta-heuristic optimization methods, including Artificial Bee Colony (ABC), Tree Seed Algorithm (TSA), and Biogeography-Based Optimization (BBO), are employed to derive accurate mathematical formulas. The performance of these methods is evaluated under varying soil conditions and loading scenarios. The Tree Seed Method has consistently delivered the most accurate results, with near-zero optimization errors. The findings provide the applicability of algorithmic methods and their potential for improving stress distribution modeling in elastic foundations. Full article

The historic mortuary at Zagreb’s Mirogoj Cemetery, built in 1886, sustained moderate damage during the 2020 Mw 5.3 earthquake. Aiming to preserve heritage value while meeting Croatia’s Level 4 seismic safety requirements, the structure was assessed using in situ and laboratory tests followed by macro-element modeling with 3Muri software. The study evaluated four scenarios: (A) post-earthquake damaged state, (B) reinforcement with new masonry and RC walls, (C) partial fiber-reinforced cementitious matrix (FRCM) plastering, and (D) systematic FRCM plastering. Results show that Case B improved Ultimate Limit State (ULS) scaling factors from 0.64/0.56 to 0.92/0.90 (X/Y), while Case D raised them to 1.03/1.17, satisfying Eurocode 8 and national renovation criteria. Systematic FRCM application improved story shear capacity by up to 57% and shifted failure modes from brittle shear to ductile rocking. Partial plastering proved insufficient, highlighting the need for comprehensive global retrofitting. While the solution is minimally invasive and reversible, uncertainties remain regarding long-term durability and out-of-plane performance. This hybrid retrofitting strategy offers a replicable model for heritage masonry buildings in seismically active regions. Full article

Rapid building damage assessments are vital for an effective earthquake response. In Japan, traditional Earthquake Damage Certification (EDC) surveys—followed by the issuance of Disaster Victim Certificates (DVCs)—are often inefficient. With advancements in remote sensing technologies and deep learning algorithms, their combined application has been explored for large-scale automated damage assessment. However, the scarcity of remote sensing data on damaged buildings poses significant challenges to this task. In this study, we propose an Uncertainty-Guided Fusion Module (UGFM) integrated into a standard decoder architecture, with a Pyramid Vision Transformer v2 (PVTv2) employed as the encoder. This module leverages uncertainty outputs at each stage to guide the feature fusion process, enhancing the model’s sensitivity to collapsed buildings and increasing its effectiveness under diverse conditions. A training and in-domain testing dataset was constructed using post-earthquake aerial imagery of the severely affected areas in Noto Prefecture. The model approximately achieved a recall of 79% with a precision of 68% for collapsed building extraction on this dataset. We further evaluated the model on an out-of-domain dataset comprising aerial images of Mashiki Town in Kumamoto Prefecture, where it achieved an approximate recall of 66% and a precision of 77%. In a quantitative analysis combining field survey data from Mashiki, the model attained an accuracy exceeding 87% in identifying major damaged buildings, demonstrating that the proposed method offers a reliable solution for initial assessment of major damage and its potential to accelerate DVC issuance in real-world disaster response scenarios. Full article

The growing deployment of electric vehicles (EVs) offers a unique opportunity to utilize them as mobile energy resources during large-scale emergencies. However, existing emergency dispatch strategies often neglect the compounded uncertainties of hazard disruptions, infrastructure fragility, and user behavior. To address this gap, we propose the Emergency-Responsive Aggregation Framework (ERAF)—a behaviorally informed, spatially aware, and probabilistic optimization model for resilient EV energy dispatch. ERAF integrates a Bayesian inference engine to estimate plug-in availability based on hazard exposure, behavioral willingness, and charger operability. This is dynamically coupled with a GIS-based spatial filter that captures road inaccessibility and corridor degradation in real time. The resulting probabilistic availability is fed into a multi-objective dispatch optimizer that jointly considers power support, response time, and delivery reliability. We validate ERAF using a high-resolution case study in Southern California, simulating 122,487 EVs and 937 charging stations across three compound hazard scenarios: earthquake, wildfire, and cyberattack. The results show that conventional deterministic models overestimate dispatchable energy by up to 35%, while ERAF improves deployment reliability by over 28% and reduces average delays by 42%. Behavioral priors reveal significant willingness variation across regions, with up to 47% overestimation in isolated zones. These findings underscore the importance of integrating behavioral uncertainty and spatial fragility into emergency energy planning. ERAF demonstrates that EVs can serve not only as grid assets but also as intelligent mobile agents for adaptive, decentralized resilience. Full article

This study investigates collaborative disaster response strategies involving the government and social organizations from a dynamic perspective, incorporating stochastic disturbances that influence emergency resource supply. To examine the strategic interactions among the participants, three stochastic differential game models are formulated under distinct scenarios: centralized decision making for collusive emergency response, decentralized emergency response without a cost-sharing contract, and decentralized emergency response with a cost-sharing contract. Under an infinite-horizon planning framework, the closed-form solutions for the optimal response efforts and the corresponding value functions are derived for all three scenarios and comparatively analyzed. The results indicate that compared with the purely decentralized scenario, introducing a cost-sharing mechanism achieves a Pareto improvement by optimizing both overall system efficiency and emergency supply availability. Although the centralized collusive model results in the highest expected level of emergency resource supply, it is also associated with the greatest uncertainty. Furthermore, a numerical simulation based on emergency resource allocation during the Wenchuan earthquake is conducted. The results show significant differences in resource availability and response performance under different response mechanisms. Centralized collaboration, together with a well-designed cost-sharing mechanism, can significantly enhance the robustness and efficiency of the overall system, offering important insights for optimizing real-world disaster response strategies. Full article

Pumping station structures are widely employed to supply circulating cooling water systems in nuclear power plants (NPPs) throughout China. Investigating their seismic performance under complex heterogeneous site conditions and load scenarios is paramount to meeting nuclear safety design requirements. This study proposes and implements a novel, efficient, and accurate viscous-spring boundary methodology within the ANSYS 19.1 finite element software to assess the seismic safety of NPP pumping station structures. The Maximum Initial Time-step (MIT) method, based on Newmark’s integration scheme, is employed for nonlinear analysis under coupled static–dynamic excitation. To account for radiation damping in the infinite foundation, a Compact Viscous-Spring (CVs) element is developed. This element aggregates stiffness and damping contributions to interface nodes defined at the outer border of the soil domain. Implementation leverages of ANSYS User Programmable Features (UPFs), and a comprehensive static–dynamic coupled analysis toolkit is developed using APDL scripting and the GUI. Validation via two examples confirms the method’s accuracy and computational efficiency. Finally, a case study applies the technique to an NPP pumping station under actual complex Chinese site conditions. The results demonstrate the method’s capability to provide objective seismic response and stability indices, enabling a more reliable assessment of seismic safety during a Safety Shutdown Earthquake (SSE). Full article

Earthquake hazards, such as strong ground motion, liquefaction, and landslides, pose significant threats to structures built on seismically vulnerable, loose, and saturated sandy soils. Therefore, a structural failure evaluation method that accounts for site-specific seismic responses is essential for developing effective and appropriate earthquake hazard mitigation strategies. In this study, a real-time assessment framework for structural seismic susceptibility is developed. To evaluate structural susceptibility to earthquakes, seismic fragility functions are employed as thresholds for structural failure and are linked to a geotechnical spatial grid that incorporates correlation equations for seismic load determination. The real-time assessment consists of the following procedures. First, the geotechnical spatial grid is constructed based on the geostatistical method to estimate the site-specific site response to be correlated with the earthquake hazard potential. Second, the peak ground accelerations are determined from seismic load correlation and assigned to the geotechnical spatial grid. Third, the damage grade of structure is determined by calculating the failure probabilities of defined damage levels and integrating the geotechnical spatial grids for the target structure in real time. The proposed assessment was simulated at Incheon Port, South Korea, using both an actual earthquake event (the 2017 Pohang Earthquake) and a hypothetical earthquake scenario. Full article

Understanding the dynamic response and failure mechanisms of rock slopes during earthquakes is crucial in sustainable geohazard prevention and mitigation engineering. The initiation of landslides involves complex interactions between seismic wave propagation, dynamic rock mass behavior, and crack network evolution, and these interactions are heavily influenced by the slope geometry, lithology, and structural parameters of the slope. However, systematic studies remain limited due to experimental challenges and the inherent variability of landslide scenarios. This study employs Discrete Element Method (DEM) modeling to comprehensively investigate how geological structure parameters control the dynamic amplification and deformation characteristic of typical bedding/anti-dip layered slopes consist of parallel distributed rock masses and joint faces, with calibrated mechanical properties. A soft-bond model (SBM) is utilized to accurately simulate the quasi-brittle rock behavior. Numerical results reveal distinct dynamic responses between bedding and anti-dip slopes, where local amplification zones (LAZs) act as seismic energy concentrators, while potential sliding zones (PSZs) exhibit hindering effects. Parametric analyses of strata dip angles and thicknesses identify a critical dip range where slope stability drastically decreases, highlighting high-risk configurations for earthquake-induced landslides. By linking the slope failure mechanism to seismic risk reduction strategies, this work provides practical guidelines for sustainable slope design and landslide mitigation in tectonically active regions. Full article

This study investigates cross-border cascading hazards and infrastructure vulnerabilities in the Sava River Basin, a seismically active and flood-prone region spanning the Slovenia–Croatia border. Conducted within the CROSScade project, the research focuses on assessing cross-border hazards and the vulnerabilities of levees and bridges. Key earthquake and flood scenarios were identified using advanced hydraulic and seismic modelling, forming the basis for evaluating the cascading effects of these events, including the potential failure of hydropower plants and associated flood protection systems. The analysis reveals that levees are particularly vulnerable to failure during the recession phase of flooding that follows an earthquake. At the same time, bridges are primarily affected by seismic loading, with minimal structural impact from flood forces. These findings underscore the pressing need for enhanced cross-border collaboration, updated design standards, and the reinforcement of critical infrastructure. The study provides essential insights for multi-hazard resilience planning and emphasises the importance of integrated risk assessments in managing cascading disaster impacts across national boundaries. Full article

When a building normally used for exhibitions is converted into a Fangcang shelter hospital in emergency situations, its original space combination, functional flow line, and safety exits are significantly changed. When the building becomes densely populated, if an accident such as a fire, explosion, or earthquake occurs, then safe evacuation will be a serious challenge. This study systematically considers the characteristics of the building space and functional flow line after the conversion of an exhibition building to a Fangcang shelter hospital. Pathfinder software was used to simulate representative scenarios of a Fangcang shelter hospital and to analyze the main spatial factors affecting evacuation efficiency in terms of evacuation time, spatial congestion characteristics, and the exits used by personnel. Then, a targeted design optimization strategy was proposed based on the accessibility of safety exits and the internal space layout of the building. Finally, a simulation was used to verify the effectiveness of the design strategy. The results of this study provide solid theoretical support and methodological guidance for the spatial arrangement of exhibition buildings converted into Fangcang shelter hospitals so as to effectively improve the efficiency of safe evacuation and promote the resilience and safety of exhibition buildings. Full article

Limited labeled imagery and tight response windows hinder the accurate damage quantification for post-disaster assessment. The objective of this study is to develop and evaluate a deep learning-based Domain-Adaptive Segmentation (DASeg) workflow to detect post-disaster damage using limited information available shortly after an event. DASeg unifies three Vision Foundation Models in an automatic workflow: fine-tuned DINOv2 supplies attention-based point prompts, fine-tuned Grounding DINO yields open-set box prompts, and a frozen Segment Anything Model (SAM) generates the final masks. In the earthquake-focused case study DASeg-Quake, the pipeline boosts mean Intersection over Union (mIoU) by 9.52% over prior work and 2.10% over state-of-the-art supervised baselines. In a zero-shot setting scenario, DASeg-Quake achieves the mIoU of 75.03% for geo-damage analysis, closely matching expert-level annotations. These results show that DASeg achieves superior workflow enhancement in infrastructure damage segmentation without needing pixel-level annotation, providing a practical solution for early-stage disaster response. Full article