Search Results (34)

Post-earthquake fires are typically of great concern for fire protection services, which are expected to be in high demand immediately after a strong earthquake. The post-earthquake functionality of fire stations is necessary after strong earthquakes to reduce potential fire damage and improve emergency services. A reliable assessment of the seismic vulnerability and expected damage for fire stations is therefore a necessary step towards the identification of the most vulnerable structures and the prioritization of seismic retrofit activities. This article presents the development of a methodology for the damage assessment of fire stations based on earthquakes scenarios. The framework is based on four models: seismic hazard, inventory, fragility and impact. The seismic hazard model represents ground shaking in terms of intensity measure at each station using a ground motion prediction equation for Eastern Canada. The inventory model categorizes all the fire stations in building classes based on construction material and seismic code level. The fragility model associates building classes with fragility functions that provide the relationship between intensity measure and expected damage probabilities. The impact model converts damage probabilities into a mean damage state. All Montreal fire stations were selected as case study demonstrations. Simulations were conducted by varying the epicenter location and magnitude for a total number of 345 scenarios. Simplified relationships that correlate the earthquake magnitude and expected damage were developed. The study showed that, for magnitude 6 earthquakes, 45% of stations on average would sustain at least moderate damage. The methodology is particularly useful for emergency planning and prioritization of seismic retrofit activities. Full article

This study evaluates the seismic fragility and code compliance of reinforced concrete buildings in Turkey following the 6 February 2023 Kahramanmaraş earthquake. Sixty representative buildings were modeled in SAP2000, consisting of thirty structures designed according to TEC-1975 and thirty according to TEC-1998. These models were subjected to three-dimensional nonlinear time history analyses using ground motions scaled to match the seismic characteristics of the earthquake. Structural performance was assessed by comparing calculated displacement demands with capacity thresholds defined by modern code provisions. The results show that buildings designed under TEC-1998 generally performed better than those constructed according to TEC-1975, particularly in terms of deformation capacity and collapse resistance. Fragility curves and exceedance probabilities were developed to quantify damage likelihoods across different performance levels. When compared with post-earthquake field observations, the analytical models produced lower collapse rates, which may suggest the presence of widespread code noncompliance in the actual building stock. These findings highlight the critical importance of ensuring adherence to seismic design regulations to improve the resilience of existing structures. Full article

Seismic risk assessment is pivotal for ensuring the reliability of prefabricated subway stations, where selecting optimal intensity measures (IMs) critically enhances probabilistic seismic demand models and fragility analysis. While peak ground acceleration (PGA) is widely adopted for above-ground structures, its suitability for underground systems remains debated due to distinct dynamic behaviors. This study identifies the most appropriate IMs for soft soil-embedded prefabricated subway stations at varying depths through nonlinear finite element modeling and develops corresponding fragility curves. A soil–structure interaction model was developed to systematically compare seismic responses of shallow-buried, medium-buried, and deep-buried stations under diverse intensities. Incremental dynamic analysis was employed to construct probabilistic demand models, while candidate IMs (PGA, PGV, and v_rms) were evaluated using a multi-criteria framework assessing correlation, efficiency, practicality, and proficiency. The results demonstrate that burial depth significantly influences IM selection: PGA performs optimally for shallow depths, peak ground velocity (PGV) excels for medium depths, and root mean square velocity (v_rms) proves most effective for deep-buried stations. Based on these optimized IMs, seismic fragility curves were generated, quantifying damage probability characteristics across burial conditions. The study provides a transferable IM selection methodology, advancing seismic risk assessment accuracy for prefabricated underground infrastructure. Through a systematic investigation of the correlation between IM applicability and burial depth, coupled with the development of fragility relationships, this study establishes a robust technical framework for enhancing the seismic performance of subway stations, and provides valuable insights for seismic risk assessment methodologies in underground infrastructure systems. Full article

To meet the increasing demand for resilient infrastructure in seismic and high-impact areas, accurate prediction and reliability analysis of the performance of composite structures under impact loads is essential. Conventional techniques, including experimental testing and high-quality finite element simulation, require considerable time and resources. To address these issues, this study investigated individual and hybrid models including support vector regression (SVR), Gaussian process regression (GPR), and improved eliminate particle swamp optimization hybridized artificial neural network (IEPANN) models for predicting the failure strength of composite concrete developed by combining normal concrete (NC) with ultra-high performance concrete (UHPC) and polyurethane-based polymer concrete (PUC), considering different surface treatments and subjected to various static and impact loads. An experimental dataset was utilized to train the ML models and perform the reliability analysis on the impact dataset. Key parameters included compressive strength (Cfc), flexural load of the U-shaped specimens (P), density (ρ), first crack strength (N1), and splitting tensile strength (ft). Results revealed that all the developed models had high prediction accuracy, achieving NSE values above acceptable thresholds greater than 90% across all the datasets. Statistical errors such as RMSE, MAE, and PBIAS were calculated to fall within acceptable limits. Hybrid IEPANN appeared to be the most effective model, demonstrating the highest NSE value of 0.999 and the lowest RMSE, PBIAS, and MAE values of 0.0013, 0.0018, and 0.001, respectively. The reliability analysis revealed that impact times (N1 and N2) reduced as the survival probability increased. Full article

The structural integrity of buried pipelines is threatened by the effects of Permanent Ground Deformation (PGD), resulting from seismic-induced landslides and lateral spreading due to liquefaction, requiring accurate analysis of the system performance. Analytical fragility functions allow us to estimate the likelihood of seismic damage along the pipeline, supporting design engineers and network operators in prioritizing resource allocation for mitigative or remedial measures in spatially distributed lifeline systems. To efficiently and accurately evaluate the seismic fragility of a buried operating steel pipeline under longitudinal PGD, this study develops a new analytical model, accounting for the asymmetric pipeline behavior in tension and compression under varying operational loads. This validated model is further implemented within a fragility function calculation framework based on the Monte Carlo Simulation (MCS), allowing us to efficiently assess the probability of the pipeline exceeding the performance limit states, conditioned to the PGD demand. The evaluated fragility surfaces showed that the probability of the pipeline exceeding the performance criteria increases for larger soil displacements and lengths, as well as cover depths, because of the greater mobilized soil reaction counteracting the pipeline deformation. The performed Global Sensitivity Analysis (GSA) highlighted the influence of the PGD and soil–pipeline interaction parameters, as well as the effect of the service loads on structural performance, requiring proper consideration in pipeline system modeling and design. Overall, the proposed analytical fragility function calculation framework provides a useful methodology for effectively assessing the performance of operating pipelines under longitudinal PGD, quantifying the effect of the uncertain parameters impacting system response. Full article

Based on the incremental dynamic analysis (IDA) method, this paper conducts seismic fragility analysis of a CFST plane frame, a CFST spatial frame under 1D (one-dimensional) ground motions, and a CFST spatial frame under 2D (two-dimensional) ground motions, with different attacking angles. Firstly, nine-story, three-span CFST frame structures (including the plane frame and spatial frame) were modeled in OpenSees, based on the accurate simulation of the hysteresis performance of the test CFST frames. Then, twenty-five groups of ground motions were employed to analyze the seismic response. Lastly, the IDA curve clusters, probabilistic demand models, and seismic fragility curves of frame structures were researched, respectively. The analytical results showed that the exceeding probability of the spatial frame under 2D ground motions was successively greater than that under 1D ground motions, and greater than the plane frame, and the maximum difference at each performance level was up to 6% and 16%, respectively. The fragility analysis result of the spatial frame was sensitive to the attacking angle of ground motion, and the exceeding probability of the 135°, 150°, and 165° fragility curves was larger than that of the 0° (original attacking angle) fragility curve at each performance level. The research results provide a reference for seismic fragility analysis of CFST frame structures employing the IDA method. Full article

Machine learning (ML) approaches, widely used in civil engineering, have the potential to reduce computing costs and enhance predictive capabilities. However, many ML methods have yet to be applied to develop models that accurately analyze the nonlinear dynamic response of cross-fault hydraulic tunnels (CFHTs). To predict CFHT models and fragility curves effectively, we identify the most effective ML techniques and improve prediction capacity and accuracy by initially creating an integrated multivariate earthquake intensity measure (IM) from nine univariate earthquake IMs using principal component analysis. Structural reactions are then performed using incremental dynamic analysis by a multimedium-coupled interaction system. Four techniques are used to test ML–principal component analysis (PCA) feasibility. Meanwhile, mathematical statistical parameters are compared to standard probabilistic seismic demand models of expected and computed values using ML-PCA. Eventually, multiple stripe analysis–maximum likelihood estimation (MSA-MLE) is applied to assess the seismic performance of CFHTs. This study highlights that the Gaussian process regression and integrated IM can improve reliable probability and reduce uncertainties in evaluating the structural response. Thorough numerical analysis, using the suggested methodology, one can efficiently assess the seismic fragilities of the tunnel by the predicted model. ML-PCA techniques can be viewed as an alternate strategy for seismic design and CFHT performance enhancement in real-world engineering. Full article

Rocking walls can control the overall deformation pattern and the distribution of plastic energy dissipation in structures, suppressing the occurrence of weak layers. In the case of step-terrace frame structures, issues such as severe lateral stiffness irregularities, abrupt changes in floor-bearing capacity, and concentrated deformation in upper ground layers exist. To improve the yielding and failure modes of step-terrace frame structures in mountainous regions, this paper proposes a structural system combining step-terrace frame structures with energy dissipation rocking walls attached to their bottoms, aiming to control the yielding mechanism of the structure, further reduce the seismic response, limit residual deformation, and propose a structural system of step-terrace frame structures with buckling-restrained braces (BRBs) and energy dissipation rocking walls. Two sets of numerical models for step-terrace frame structures with different numbers of dropped layers and spans were established. Through simulating low-cycle repeated loading tests on step-terrace frame structures, the rationality of the models and parameters was verified. Incremental dynamic analysis (IDA) was employed to systematically investigate the vulnerability of step-terrace frame structures with energy dissipation rocking walls under different dropped layer and span configurations. This investigation covered aspects such as IDA curve clusters, percentile curves, seismic demand models, fragility functions, failure state probabilities, vulnerability indices, collapse resistance factors, and safety margins. The results indicated that the change in dropped layer numbers had a far greater impact on the vulnerability of step-terrace frame structures with energy dissipation rocking walls than the change in dropped span numbers. Under seismic excitations with the same peak ground acceleration (PGA), rocking walls can limit the depth of structural plasticity development, reduce the dispersion of peak responses, and lower the probability of exceeding various performance levels, thereby exhibiting good collapse resistance. The addition of buckling-restrained braces (BRBs) can further enhance the seismic performance and collapse resistance of the rocking wall frame structure. By analyzing the correlation between seismic intensity measures and peak structural responses, the validity of using peak ground acceleration as a scaling indicator for incremental dynamic analysis (IDA) has been verified. Full article

Aftershocks typically occur multiple times following major earthquakes, potentially inflicting enhanced damage. It is crucial to quantify the impact of aftershocks on the seismic performance of low-ductility reinforced concrete (RC) frames with different mainshock-induced damage states. For this purpose, this study investigated the aftershock fragility of low-ductility RC frames with different damage states induced by mainshocks via the case study of a six-story RC frame without a seismic design. The models of the low-ductility RC frames with different damage states were established via OpenSees software 2.5.0. Incremental dynamic analysis (IDA) was carried out to establish damage states induced by a mainshock. Then sixty-five real aftershocks were inputted to analyze the structures with different main-induced damage states. Aftershock fragility curves of low-ductility RC frame structures with different damage states were obtained. The results show that the exceedance probability of the low-ductility RC frame with mainshock-induced damage is higher than that of the intact low-ductility structure, corresponding to each limit state. The severity of the mainshock-induced damage directly amplifies the demand for a low-ductility RC frame in the subsequent aftershocks. As the mainshock-induced damage increases, the exceedance probability of the low-ductility RC frame undergoing more severe damage under aftershocks significantly increases. Full article

Demands to advance toward more resilient and sustainable cities in terms of reducing casualties, economic losses, downtime, and environmental impacts derived from earthquake-induced damage are becoming more frequent. Indeed, accurate evaluations of the seismic performance of buildings via numerical simulations are crucial for the sustainable development of the built environment. Nevertheless, performance estimations could be influenced by alternative probabilistic methods that can be chosen throughout the procedure of building-specific risk assessment, specifically in the construction and validation of fragility functions. This study evaluates the numerical impacts of selecting different probabilistic models on seismic risk metrics for reinforced concrete dual wall–frame buildings. Specifically, alternative probabilistic models are implemented and evaluated for (i) the identification and elimination of unusual observations within the simulated data (i.e., outliers); (ii) the selection and implementation of different Probability Distribution Functions (PDFs) to estimate fragility functions at different limit states (LSs); and (iii) the application of goodness-of-fit tests and information criteria to assess the validity of proposed PDFs. According to the results, the risk measures showed large variability at the extreme building LS (collapse). On the other hand, for a lower LS (service level), the measures remain similar in all the cases despite the methods selected. Further, the variability observed in the collapse response is up to two times that after eliminating data outliers. Finally, the large variability obtained with the evaluated alternative probabilistic modeling methods suggests re-opening the technical discussion over the state of the practice often used in earthquake engineering to improve the decision-making process, mitigating earthquake-induced consequences in an environmentally, economically, and socially beneficial manner. Full article

The overhead gas-insulated transmission line (GIL) in ultra-high-voltage converter stations, distinct from traditional buried pipelines, demands a thorough investigation into its seismic behavior due to limitations in existing codes. A refined finite element model is established, considering internal structure, slip between various parts, and the relative displacement at the internal conductor joint. Seismic analysis reveals the vulnerability of the GIL at the corner of the pipeline height change, with two failure modes: housing strength failure and internal conductor displacement exceeding the limit. Furthermore, the acceleration amplification coefficient of the support generally exceeds 2.0. Two retrofit methods, namely increasing the fundamental frequency of all supports and fixing the connections between all supports and the housing, have been proposed. The results indicate the effectiveness of both methods in reducing the relative displacement. Fixing all the supports effectively reduces the stress, whereas the other one yields the opposite effect. The seismic performance of a GIL is determined not by the dynamic amplification of supports, but by the control of relative displacement between critical sections, specifically influenced by the angular deformation of the pipeline’s first-order translational vibration mode along the line direction. Seismic vulnerability analysis reveals a reduction of over 50% in the failure probability of the GIL after the retrofit compared to before the retrofit, with the PGA exceeding 0.4 g. Full article

The effect of an intensity measure’s (IM’s) sufficiency property on the probabilistic assessment of reinforced concrete (RC) structures due to floor-to-floor structural pounding conditions is examined. In the first part of this investigation, efficiency and sufficiency properties of 23 scalar IMs are verified. Then, the magnitude M_w and the distance R_rup are examined as elements in a vector with an efficient scalar IM to evaluate whether they have any significant effect on the structural response. Subsequently, probabilistic seismic demand models (PSDMs) are developed using linear regression analyses based on a scalar IM and a vector-valued IM. Fragility curves are developed based on these PSDMs, and the influence of M_w and R_rup on the evaluation of the minimum required separation gap distance d_g,min due to the pounding effect is examined. More than two hundred nonlinear time history analyses are performed based on the Cloud Analysis method. Seismic displacement demands that control of the global state of the structure, as well as the probability of structural pounding, are examined. The results of this research indicate that once M_w or R_rup is increased, fragility curves are shifted to greater values of IM, and the probability of the exceedance of a certain performance level is reduced. Also, the predictive power of R_rup seems to be greater than the one of M_w. On the other hand, it is revealed that M_w and R_rup induce variabilities in the demand solutions for adequate separation gap distance between the adjacent structures. Therefore, variation in M_w or R_rup may lead, in some cases, to unacceptable evaluations of the pounding effect in the capacity levels of structures. Full article

In order to address the difficulty in determining the seismic damage probability of continuous girder bridges under construction, the seismic vulnerability analysis method of the construction state is proposed in this study. Firstly, taking a long-span prestressed concrete composite box girder bridge with corrugated steel webs (OSW) as an example, the finite element models (FEMs) of dynamic calculation in different phases of cantilever construction are simulated by OpenSEES. Secondly, by selecting reasonable seismic waves and seismic intensity measures, the non-linear time-history analysis is carried out, followed by the demand parameters and damage indexes suitable for the construction state proposed. Finally, the probabilistic seismic demand model (PSDA) of the continuous box girder bridge during the construction stage is constructed by using the “cloud method”, and the seismic vulnerability curves of the piers and temporary bearings are established to evaluate the seismic performance during the construction stage. The results indicate that the damage probability of piers and temporary bearings increases with the progress of construction. The initial formation of the cantilever structure and the sudden change in the size of the construction segmental girder correspond to a high probability of damage, and seismic protection measures should be strengthened during this construction state. Moreover, significantly higher damage probability of the components under construction compared to the completed bridge after it is built. Full article

It is known that the extradosed cable-stayed bridge, a hybrid bridge, possesses the virtues of both classic cable-stayed bridges and girder bridges in mechanical behaviors. In this paper, the sensitivity of seismic fragility demand parameters (SFDP) of a high-speed railway extradosed cable-stayed bridge is studied systematically along with the consideration of structural parameter uncertainty. Based on the probability distribution and correlation of random parameters, the Latin hypercube sampling method is adopted herein. The dynamic 3D finite element model of the employed bridge is established by using powerful and attractive OpenSEES nonlinear software. A nonlinear incremental dynamic analysis is performed to consider the randomness of structural parameters using sampling analysis. Some important conclusions are drawn indicating that the structural design parameter uncertainty predominantly has influence on the SFDP for fragility analysis of bridge structures. The design parameters of extradosed cable-stayed bridges are categorized and identified as primary, secondary and insensitive parameters. The high sensitivity parameters of extradosed cable-stayed bridges for fragility analysis include friction coefficient of bearing, concrete bulk density, damping ratio, peak compressive strength of confined concrete, component size and peak strain of confined concrete. Additionally, the strength and strain of unconfined concrete cannot be ignored. Furthermore, the uncertainty of structural design parameters fails to be responsible for the cable force responses due to larger girder stiffness. The structural design parameter uncertainty has a significant influence on the responses of extradosed cable-stayed bridges for seismic fragility analysis. Full article

In the current study, a simplified seismic life cycle cost (LCC) estimation procedure is proposed utilizing the mean values of the structure’s main input variables. The main input variables of the building are used for constructing a relationship between the structural fundamental period (T) and an average estimation of the LCC (LCCavg). Using the actual building properties related to damage probability, the T–LCCavg relationship is used to obtain the final LCC (LCCfin). The equivalent single degree of freedom (ESDOF) model and SAC-FEMA framework are utilized for damage probability calculation. The dispersion measure in demand is approximately calculated based on the mean plus one standard deviation of the seismic hazard response spectrum, and, then, verified through nonlinear time history (NLTH) analyses of the original structure. Five and three-story steel buildings are used as case studies for verification of the proposed method. The analysis results indicate that the proposed procedure provides reasonable LCC estimations for low-rise buildings dominated by the fundamental mode of vibration. Full article