Search Results (111)

Accurate and rapid prediction of structural responses to seismic loading is critical for ensuring structural safety. Recently, there has been active research focusing on the application of deep learning techniques, including Physics-Informed Neural Networks (PINNs) and Long Short-Term Memory (LSTM) networks, to predict the dynamic behavior of structures. While these methods have shown promise, each comes with distinct limitations. PINNs offer physical consistency but struggle with capturing long-term temporal dependencies in nonlinear systems, while LSTMs excel in learning sequential data but lack physical interpretability. To address these complementary limitations, this study proposes a hybrid LSTM-PINN model, combining the temporal learning ability of LSTMs with the physics-based constraints of PINNs. This hybrid approach allows the model to capture both nonlinear, time-dependent behaviors and maintain physical consistency. The proposed model is evaluated on both single-degree-of-freedom (SDOF) and multi-degree-of-freedom (MDOF) structural systems subjected to the El-Centro ground motion. For validation, the 1940 El-Centro NS earthquake record was used, and the ground acceleration data were normalized and discretized for numerical simulation. The proposed LSTM-PINN is trained under the same conditions as the conventional PINN models (e.g., same optimizer, learning rate, and loss structure), but with fewer training epochs, to evaluate learning efficiency. Prediction accuracy is quantitatively assessed using mean error and mean squared error (MSE) for displacement, velocity, and acceleration, and results are compared with PINN-only models (PINN-1, PINN-2). The results show that LSTM-PINN consistently achieves the most stable and precise predictions across the entire time domain. Notably, it outperforms the baseline PINNs even with fewer training epochs. Specifically, it achieved up to 50% lower MSE with only 10,000 epochs, compared to the PINN’s 50,000 epochs, demonstrating improved generalization through temporal sequence learning. This study empirically validates the potential of physics-guided time-series AI models for dynamic structural response prediction. The proposed approach is expected to contribute to future applications such as real-time response estimation, structural health monitoring, and seismic performance evaluation. Full article

Modeling mainshock–aftershock ground motions is essential for seismic risk assessment, especially in regions experiencing frequent earthquakes. Recent studies have often employed Copula-based joint distributions or machine learning techniques to simulate the statistical dependency between mainshock and aftershock parameters. While effective at capturing nonlinear correlations, these methods are typically black box in nature, data-dependent, and difficult to generalize across tectonic settings. More importantly, they tend to focus solely on marginal or joint parameter correlations, which implicitly treat mainshocks and aftershocks as independent stochastic processes, thereby overlooking their inherent spectral interaction. To address these limitations, this study proposes an explicit and parameterized modeling framework based on the evolutionary power spectral density (EPSD) of random ground motions. Using the magnitude difference between a mainshock and an aftershock as the control variable, we derive attenuation relationships for the amplitude, frequency content, and duration. A coherence function model is further developed from real seismic records, treating the mainshock–aftershock pair as a vector-valued stochastic process and thus enabling a more accurate representation of their spectral dependence. Coherence analysis shows that the function remains relatively stable between 0.3 and 0.6 across the 0–30 Rad/s frequency range. Validation results indicate that the simulated response spectra align closely with recorded spectra, achieving R² values exceeding 0.90 and 0.91. To demonstrate the model’s applicability, a case study is conducted on a representative frame structure to evaluate seismic vulnerability and economic loss. As the mainshock PGA increases from 0.2 g to 1.2 g, the structure progresses from slight damage to complete collapse, with loss rates saturating near 1.0 g. These findings underscore the engineering importance of incorporating mainshock–aftershock spectral interaction in seismic damage and risk modeling, offering a transparent and transferable tool for future seismic resilience assessments. Full article

Corrosion can accelerate the deterioration of the mechanical properties of steel structures. However, few studies have systematically evaluated its impact on seismic performance, particularly with respect to seismic economic losses. In this paper, the seismic fragility and loss assessment of a multi-story steel frame with viscous dampers (SFVD) building are investigated through experimental and numerical analysis. Based on corrosion and tensile test results, OpenSees software 3.3.0 was used to model the SFVD, and the effect of corrosion on the seismic fragility was evaluated via incremental dynamic analysis (IDA). Then, the economic losses of the SFVD during different seismic intensities were assessed at various corrosion times based on fragility analysis. The results show that as the corrosion time increases, the mass and cross-section loss rate of steel increase, causing a decrease in mechanical property indices, and theprobability of exceedance of the SFVD in the limit state increases gradually with increasing corrosion time, with an especially significant impact on the collapse prevention (CP) state. Furthermore, the economic loss assessment based on fragility curves indicates that the economic loss increases with corrosion time. Thus, the aim of this paper is to provide guidance for the seismic design and risk management of steel frame buildings in coastal regions throughout their life cycle. Full article

Seismic isolation systems are an effective passive protection strategy that decouples structures from ground motion. Their performance depends heavily on the elastomeric materials used, which must retain mechanical integrity under environmental stressors. In recent years, low-cost isolators made from natural and recycled rubber have gained attention as an affordable solution for protecting low-rise buildings in seismic-prone developing regions, particularly due to their environmental benefits and ease of installation. However, their long-term performance under real environmental conditions remains insufficiently explored. This study evaluates the durability of two types of low-cost seismic isolators: those made with natural rubber matrices (UN-FREIs) and those that use recycled rubber matrices (UR-FREIs). Mechanical tests were carried out before and after exposing the specimens to accelerated aging and low-temperature conditions, simulating environmental degradation. Changes in stiffness, damping, and energy dissipation were analyzed for both the rubber matrix and the scaled isolator prototypes. The findings indicate that both materials degrade over time, with recycled rubber exhibiting greater susceptibility to stiffness loss at low temperatures. Nevertheless, both isolator types maintained functional performance after aging, supporting their applicability in regions with moderate thermal variations. These results provide evidence for the feasibility of adopting low-cost isolators in low-rise buildings exposed to variable climates, while also emphasizing the need for standardized durability protocols during the design stage. Full article

This study investigates the influence of bedrock material conditions on the seismic behavior of the Niedzica earth dam in southern Poland. It examines the dam’s dynamic response to a real seismic event—the 2004 Podhale earthquake—and evaluates how different foundation conditions affect structural performance under spatially varying ground motions. A spatially varying ground motion excitation model was developed, incorporating both wave coherence loss and wave passage effects. Seismic data was collected from three monitoring stations: two located in fractured bedrock beneath the dam and one installed in the surrounding intact Carpathian flysch. From these recordings, two key spatiotemporal parameters were experimentally determined: the seismic wave velocity and the spatial scale parameter (α), which reflects the degree of signal incoherence. For the fractured bedrock beneath the dam, the wave velocity was 2800 m/s and α = 0.43; for the undisturbed flysch, it was 3540 m/s and α = 0.82. A detailed 3D finite element model of the dam was developed in ABAQUS and subjected to time history analyses under three excitation scenarios: (1) uniform input, (2) non-uniform input with coherence loss, and (3) non-uniform input including both coherence loss and wave passage effects. The results show that the dam’s seismic response is highly sensitive to the choice of spatiotemporal parameters. Using generalized values from the flysch reduced predicted shear stresses by up to 16% compared to uniform excitation. However, when the precise parameters for the fractured bedrock were applied, the reductions increased to as much as 24%. This change in response is attributed to the higher incoherence of seismic waves in fractured material, which causes greater desynchronization of ground motion across the dam’s foundation. Even small-scale geological differences—when properly reflected in the spatiotemporal model—can significantly influence seismic safety evaluations of large-scale structures. Ultimately, shifting from regional to site-specific parameters enables a more realistic assessment of dynamic stress distribution. Full article

Engineered laminated bamboo frame structures have seen notable advancements in China, driven by their potential in sustainable construction. However, accurately predicting their seismic performance remains a pivotal challenge. Structural and non-structural damage caused by earthquakes can severely compromise building operability, lead to substantial economic losses, and disrupt safe evacuation processes, collectively exacerbating disaster impacts. To address this, three laminated bamboo frame models (3-, 4-, and 5-story) were developed, integrating energy-dissipating T-shaped steel plate beam–column connections. Two engineering demand parameters—peak inter-story drift ratio (PIDR) and peak floor acceleration (PFA)—were selected to quantify seismic responses under near-field and far-field ground motions. The study systematically evaluates suitable intensity measures for these parameters, emphasizing efficiency and sufficiency criteria. Regarding efficiency, the applicable intensity measures for PFA differ from those for PIDR. The measures for PFA tend to focus more on acceleration amplitude-related measures such as peak ground accelerations (PGA), sustained maximum acceleration (SMA), effective design acceleration (EDA), and A₉₅ (the acceleration at 95% Arias intensity), while the measures for PIDR are primarily based on spectral acceleration-related measures such as S_a(T₁) (spectral acceleration at fundamental period), etc. Concerning sufficiency, significant differences exist in the applicable measures for PFA and PIDR, and they are greatly influenced by ground motion characteristics. Full article

Traditional seismic risk assessments often require specialized expertise and extensive computational time, making probabilistic seismic risk evaluations less accessible to practitioners and decision-makers. To reduce the barriers related to applications of quantitative seismic risk analysis, this paper develops a Quick Loss Estimation Tool (QLET) designed for rapid seismic risk assessment of Canadian buildings. By approximating the upper tail of a seismic hazard curve using an extreme value distribution and by integrating it with building exposure-vulnerability models, the QLET enables efficient computation of seismic loss curves for individual sites. The tool generates seismic loss exceedance probability curves and financial risk metrics based on Monte Carlo simulations, offering customizable risk assessments for various building types. The QLET also incorporates regional site proxy models based on average shear-wave velocity in the uppermost 30 m to enhance site-specific hazard characterization, addressing key limitations of global site proxy models and enabling risk-based seismic microzonation. The QLET streamlines hazard, exposure, and vulnerability assessments into a user-friendly tool, facilitating regional-scale risk evaluations within practical timeframes, making it particularly applicable to emergency preparedness, urban planning, and insurance analysis. Full article

This paper presents a framework for evaluating the impact of seismic retrofitting alternatives on seismic risk, specifically focusing on economic losses, social losses, environmental losses, resilience, and vulnerability of reinforced concrete (RC) structures. From a cost-effectiveness perspective, this study concentrates on the retrofitting of ground story columns, which has proven to be highly effective in enhancing the performance of the structure, particularly when its behavior is mainly governed by column capacities and story response. The methodology is divided into three main parts. The first part involves a global damage evaluation, which is estimated using a seismic vulnerability assessment based on the collapse fragility function. This function is derived from capacity curves obtained through nonlinear pushover analysis. The second part focuses on assessing seismic risk for various earthquake intensities, where fragility functions and consequence functions are derived and evaluated for structural components. This allows for the calculation of losses in terms of social, economic, and environmental impacts. The third part addresses the functionality and recovery of the structure, along with its resilience, by considering repair times and associated delays. Indices are developed for all direct and indirect losses, and weightage factors are assigned to each category to optimize the selection of the most suitable retrofitting alternative for specific scenarios. To illustrate this framework, a five-story hospital building is used as an example, as hospitals are critical structures that need to remain operational after earthquakes. Four retrofitting alternatives are proposed to identify the optimal choice that effectively meets all desired functions. Full article

The occurrence of extreme disasters, such as seismic hazards, can significantly disrupt transportation and distribution networks (DNs), consequently impacting the post-disaster recovery process. Restoring load using distributed generation represents an important approach to improving the resilience of DNs. However, using these resources to provide resilience is not enough to justify having them installed economically. Therefore, this paper proposes a two-stage stochastic mixed-integer programming (SMIP) model for the configuration of stationary energy storage systems (SESSs) and mobile energy storage systems (MESSs) during earthquakes. The proposed model comprehensively considers both normal and disaster operation scenarios of DNs, maximizing the grid’s economic efficiency and security. The first stage is to make decisions about the location and size of energy storage, using a hybrid configuration scheme of second-life batteries (SLBs) for SESSs and fresh batteries for MESSs. In the second stage, the operating costs of DNs are evaluated by minimizing normal operating costs and reducing load loss during seismic events. Additionally, this paper proposes a scenario reduction method based on hierarchical sampling and distance reduction to generate representative fault scenarios under varying earthquake magnitudes. Finally, the progressive hedging algorithm (PHA) is employed to solve the model. The case studies of the IEEE 33-bus and 12-node transportation network are conducted to validate the effectiveness of the proposed method. Full article

The Lower Tagus Valley (LTV) region has the highest population density in Portugal, with over 3.7 million people living in the region. It has been struck in the past by several historical earthquakes, which caused significant economic and human losses. For a proper seismic hazard evaluation, the area needs detailed V_s30 and soil classification maps. Previously available maps are based on proxies, or an insufficient number of velocity measurements followed by coarse geological generalizations. The focus of this work is to significantly improve the available maps. For this purpose, more than 90 new S-wave seismic velocities measurements obtained from seismic refraction and seismic noise measurements, doubling the number used in previously available maps, are used to update available V_s30 and soil classification maps. The data points are also generalized to the available geological maps using local lithostratigraphic studies and, for the first time, satellite images of this area. The results indicate that lithological and thickness changes within each geological formation prevent a simple generalization of geophysical data interpretation based solely on geological mapping. The maps presented here are the first attempt to produce maps at a scale larger than 1:1,000,000 in Portugal, with direct shear wave velocity measurements. A tentative approach to produce more detailed maps using machine learning was also carried out, presenting promising results. This approach may be used in the future to reduce the number of shear wave measurements necessary to produce detailed maps at a finer scale. Full article

Liquid-storage tanks are critical components in industrial plants, especially during seismic events. Tank failures can cause significant economic losses, operational disruptions, and environmental damage. Therefore, accurate design and performance evaluation are essential to minimize these risks. However, past earthquakes have highlighted the need for a better understanding of tanks’ seismic behavior. This requires selecting the appropriate seismic input and ground motion records to properly simulate tank responses. This study examines the seismic behavior of various tank types using different earthquake record sets, including both far-field and near-field events. The tanks were modelled with varying geometries, such as diameter–height ratios, wall thickness, liquid height, and radius. Time-history analyses were conducted to generate fragility curves and evaluate the seismic performance of the tanks based on specific limit states. The findings show that the choice between far- and near-field records significantly influences seismic response, particularly in terms of fragility curve variation. The fragility curves derived from this analysis can serve as valuable tools for risk assessments by governments and stakeholders, helping to improve the safety and resilience of industrial plants. Full article

Post-earthquake fires (PEFs) pose a significant secondary hazard in earthquake-prone regions, compounding the destruction caused by seismic events and threatening structural safety. This review explores the interplay between seismic damage and fire resistance, focusing on ignition sources such as damaged utility systems and overturned appliances, and their cascading effects on structural integrity. Advanced performance-based design approaches are evaluated, emphasizing the integration of probabilistic risk assessments, sequential analysis, and hybrid fire simulations to address multi-hazard scenarios. Key findings of current studies reveal that seismic damage, including spalling, cracking, and loss of fireproofing, substantially reduces the fire resistance of materials like steel and reinforced concrete, exacerbating structural vulnerabilities. Despite advancements, critical gaps persist in experimental data, probabilistic modeling, and comprehensive performance-based design guidelines for PEF scenarios. Addressing these deficiencies requires enhanced data collection, improved modeling techniques, and the integration of PEF considerations into building codes. This study provides a comprehensive review of PEF damage assessment and underscores the need for a holistic, multi-hazard design paradigm to enhance structural resilience and ensure safety in regions subject to seismic and fire risks. These insights provide a foundation for future research and practical applications aimed at mitigating the compounded effects of earthquakes and fires. Full article

The Pacitan Regency is at risk of megathrust earthquakes and tsunamis due to the seismic gap along the southern region of Java Island, making risk-reduction efforts crucial. This research aims to analyse the tsunami risk associated with a potential megathrust earthquake scenario in Pacitan’s coastal areas and develop sustainable mitigation strategies. The research employs spatial analysis to evaluate the risk and subsequently formulate strategies for long-term mitigation. A weighted overlay method was utilised to integrate hazard (H) and vulnerability (V) datasets to produce a tsunami risk map (R). The hazard component was modelled using a tsunami propagation simulation based on the Shallow Water Equations in the Delft3D-Flow software, incorporating an earthquake scenario of Mw 8.8 and H-loss calculations in ArcGIS Pro 10.3. The vulnerability assessment was conducted by overlaying population density, land use, and building footprint from the Global Human Settlement Layer (GHSL) datasets. Finally, sustainable strategies were proposed to mitigate the tsunami risk effectively. The results show that Pacitan faces significant tsunami disaster risk, with tsunami waves at the coast reaching 16.6 m. Because the coast of Pacitan is densely populated, mitigation strategies are necessary, and in the present contribution, the authors developed holistic spatial planning, which prioritise the preservation and restoration of natural barriers, such as mangroves and coastal forests. Full article

The vulnerability curve serves as a precise evaluation metric for structural seismic performance and a critical component in earthquake loss assessment. In this study, the orthogonal expansion method for random ground motion generation is integrated with the probability density evolution method (PDEM) to address the dynamic reliability and vulnerability of general Multi-Degree of Freedom (MDOF) nonlinear structures. By employing dynamic reliability as a constraint and vulnerability as an evaluation index, the guided firework algorithm (GFWA) is introduced to optimize the design of viscoelastic damper (VED) structure systems. To validate the proposed methods, several examples are presented, including the generation of artificial waves, the vulnerability analysis of a five-story reinforced concrete (RC) structure, and a comparative study of GFWA and genetic algorithm (GA) optimization for VED parameters to assess the optimization efficiency. The results demonstrate that the proposed vulnerability method achieves satisfactory accuracy and is well suited for evaluating damper structure optimization designs. Furthermore, GFWA outperforms GA significantly in terms of efficiency and feasibility, offering a promising approach for optimization design in architectural structures. Full article

Flexible pavements stand out as the most commonly used worldwide, compared to rigid and composite pavements, owing to their versatility and widespread application. The use of hot mix asphalt (HMA) in flexible pavements causes significant environmental concerns due to high CO₂ emissions and energy consumption, whereas warm mix asphalt (WMA) technologies have gained popularity in recent decades, offering a more sustainable alternative by enabling asphalt production at lower temperatures. WMA technologies can be categorized into three main groups: foaming, organic additives, and chemical additives, with each offering distinct benefits for performance and environmental impact. One of the chemical additives used in WMA production is Cecabase RT BIO10. In this study, virgin bitumen with 50/70 penetration was modified by adding Cecabase RT BIO10 at four levels: 0%, 0.3%, 0.4%, and 0.5% by weight. The experimental design employed a Taguchi L16 orthogonal array to systematically evaluate the effects of various factors on modified bitumen performance. Binders were prepared at four temperatures (110 °C, 120 °C, 130 °C, and 140 °C), four mixing durations (15, 20, 25, and 30 min), and four mixing speeds (1000, 2000, 3000, and 4000 rpm), enabling an efficient analysis of each parameter’s impact. The prepared binders were subjected to a series of tests, including penetration, softening point, flash point, rotational thin film oven test (RTFOT), elastic recovery, Marshall stability, ultrasonic pulse velocity (UPV), and FTIR analysis. These tests were conducted to investigate the effects of various parameters and levels on the binder properties. Additionally, stiffness and seismic modules were evaluated to provide a more comprehensive understanding of the binder’s performance. The experiment results revealed that the penetration, elastic recovery percentage, and Marshall stability increased with increasing additive content while the softening point and RTFOT mass loss decreased. At a high service temperature of 40 °C, the stiffness modulus of the modified bitumen decreased slightly. At a low service temperature of −10 °C, it decreased further. Additionally, the incorporation of Cecabase RT BIO10 led to an increase in the seismic modulus. Through optimization using the Taguchi method, the optimal levels were determined to be a 0.4% Cecabase RT BIO10 ratio, 140 °C mixing temperature, 30 min mixing time, and 1000 RPM mixing speed. The optimal responses for each test were identified and integrated into a unified optimal response, resulting in a comprehensive design guide with 95% confidence level estimates for all possible level combinations. Full article