Search Results (22)

This study presents a probabilistic seismic fragility assessment of a jointed rock slope by integrating field characterization, incremental dynamic analysis (IDA), and numerical modeling. Dominant joint sets are identified through field mapping, and key discontinuity parameters are estimated for the Barton–Bandis non-linear shear strength criterion. Dynamic simulations are performed using the distinct element method with the continuously yielding (C-Y) joint model to capture progressive shear degradation. Twenty real earthquake ground-motion records are scaled incrementally to perform IDA, with critical block displacement and cumulative joint slip adopted as engineering demand parameters (EDPs). A probabilistic seismic demand model (PSDM) is developed to correlate peak ground acceleration (PGA) with EDPs. Kinematic analysis indicates that planar failure along joint set 1 is the most likely failure mechanism (90% probability), followed by wedge failure along the intersection of joint sets 1 and 2 (52%). Fragility curves are derived for three displacement-based damage states: minor (1 cm), moderate (5 cm), and severe (15 cm). The results demonstrate that seismic deformation is strongly controlled by discontinuity geometry and progressive joint slip, with the slope exceeding the severe damage state at PGA levels as low as 0.4 g, indicating high seismic vulnerability. This highlights the importance of integrating field characterization with dynamic numerical modeling for reliable seismic stability assessment of such discontinuous rock mass. Future work should incorporate larger datasets, in situ testing, and 3D modeling to enhance assessment reliability. Full article

This research aims to assess and quantify the significance of incorporating the seismic performance of global and local engineering demand parameters (EDPs) within probabilistic frameworks when structural pounding of adjacent buildings occurs. For this purpose, the seismic performance of six-story and twelve-story reinforced concrete (RC) frames subjected to floor–floor pounding is assessed. The pounding is caused by an adjacent shorter and stiffer structure with the top contact point at the middle of the tall building’s total height. Displacement-based and ductility-based EDPs are evaluated at different performance levels (PLs) and at different separation distances (d_g). The seismic performance of the RC frames without considering pounding is also evaluated. Incremental dynamic analyses (IDAs) are performed, and probabilistic seismic demand models (PSDMs) are developed to establish the fragility curves of the examined RC frames. The probability of earthquake-induced pounding between adjacent structures is properly involved with the median value of S_a,T1 that corresponds to an acceptable capacity level (acceptable PL) of an EDP. The results of this study indicate that excluding structural pounding consequences from the probabilistic frameworks related to the seismic risk of colliding buildings leads to unsafe seismic assessment or design provisions. Full article

Pulse-like ground motions can cause severe damage to buried cast iron (CI) pipelines, which necessitates the selection of optimal seismic intensity measures (IMs) to estimate pipeline repair rates. Such a selection is essential for mitigating uncertainty in the seismic risk assessment of buried CI pipelines. For the first time, this study systematically screens the optimal scalar and vector IMs for buried cast iron pipelines with lead-caulked joints under pulse-like ground motions by a symmetrical evaluation based on the criteria of efficiency, sufficiency, and proficiency, providing a new method for reducing uncertainty in pipeline seismic risk assessment. We initiate the study by selecting 124 pulse-like ground motions from the NGA-West2 database and identifying 19 scalar and 171 vector IMs as potential candidates. A two-dimensional soil–pipe model is introduced, incorporating variability in the sealing capacity of lead-caulked joints along the axial direction. CI pipeline repair rates are calculated across various scaling factors and apparent wave velocities, yielding 1116 datasets pertinent to CI pipeline damage. The repair rate is adopted as the engineering demand parameter (EDP) to evaluate the efficiency, sufficiency, and proficiency of candidate IMs. Through comprehensive analysis, peak ground velocity (PGV) and the combination of PGV and the time interval between 5% and 75% of normalized Arias intensity ([PGV, Ds_5–75]) are determined as the optimal scalar- and vector-IMs, respectively, for assessing the repair rate of buried CI pipelines under pulse-like ground motions. 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

The proliferation of tunnel and subway networks in urban areas has heightened concerns regarding their vulnerability to seismic-induced liquefaction. This phenomenon, wherein saturated sandy soils lose strength and behave like a liquid under seismic waves, poses a catastrophic threat to the structural integrity and stability of underground constructions. While extensive research has been conducted to evaluate liquefaction triggering, most existing approaches rely on single ground motion intensity measures (e.g., PGA, I_A), which often fail to capture the combined effects of amplitude, energy, and duration on liquefaction behavior. In this study, the seismic response of saturated sandy soil from Yinchuan was analyzed using the Dafalias–Manzari constitutive model implemented in the OpenSeesPy platform. The model parameters were carefully calibrated using laboratory triaxial results. A total of ten real earthquake records were applied to evaluate two critical engineering demand parameters (EDPs): surface lateral displacement (SLD) and the maximum thickness of the liquefied layer (MTL). The results show that both SLD and MTL exhibit weak correlations with conventional intensity parameters, suggesting limited predictive value for engineering design. However, by applying Partial Least Squares (PLS) regression to combine multiple intensity measures, the prediction accuracy for SLD was significantly improved, with the correlation coefficient increasing to 0.81. In contrast, MTL remained poorly predicted due to its strong dependence on intrinsic soil characteristics such as permeability and fines content. These findings highlight the importance of integrating both seismic loading features and geotechnical soil properties in performance-based liquefaction hazard evaluation. Full article

To accurately assess the seismic damage of high-rise structures under long-period ground motions (LPGMs), a 36-story SRC frame-RC core tube high-rise structure was designed. Twelve groups of LPGMs and twelve groups of ordinary ground motions (OGMs) were selected and bidirectionally input into the structure. The spectral acceleration S_90c considering the effect of higher-order modes was adopted as the intensity measure (IM) of ground motions, and the maximum inter-story drift angle θ_max under bidirectional ground motions was taken as the engineering demand parameter (EDP). Structural Incremental Dynamic Analysis (IDA) was conducted, the structural vulnerability was investigated, and seismic vulnerability curves, damage state probability curves, vulnerability index curves, as well as the probabilities of exceeding performance levels and vulnerability index of the structure during 8-degree frequent, design, and rare earthquakes were obtained, respectively. The results indicate that structural damage is significantly aggravated under LPGMs, and the exceeding probabilities for all performance levels are greater than those under OGMs, failing to meet the seismic fortification target specified in the code. When encountering an 8-degree frequent earthquake, the structure is in a moderate or severe damage state under LPGMs and is basically intact or in a slight damage state under OGMs. When encountering an 8-degree design earthquake, the structure is in a severe damage or near-collapse state under LPGMs and is in a moderate damage state under OGMs. When encountering an 8-degree rare earthquake, the structure is in a near-collapse state under LPGMs and in a severe damage state under OGMs. Full article

In seismic performance assessment, the development of building fragility curves is critical for performance-based engineering. Traditional methods for time history analysis, reliant on detailed ground motion (GM) inputs, often suffer from inefficiency and a lack of automation. This study proposes an accurate fragility assessment methodology, which is assisted by machine learning (ML) and particle swarm optimization (PSO), adept at handling scenarios with both scarce and sufficient fragility data. Under scenarios of scarce data, the integrated algorithms of PSO and ML are utilized, focusing on selecting GMs that may induce maximum inter-story drifts. When the dataset is sufficient, an ML fusion model is utilized to predict engineering demand parameters (EDPs), facilitating the generation of more accurate fragility curves. The effectiveness of this method is demonstrated through a case study on a high-rise reinforced concrete (RC) building, revealing a marked improvement in the precision of GM selection and the estimated range of fragility curves over traditional approaches. The proposed methodology aids in advancing structural optimization and the development of early-warning systems for seismic events, thus holding the potential to enhance current seismic risk mitigation strategies. Full article

Ground-motion intensity measures (IMs), which quantify and describe the characteristics of earthquake ground motion, are of utmost importance in the assessment of seismic risk and the design of resilient structures with large spans. The appropriate selection of a ground-motion IM is crucial in establishing a reliable and robust correlation between seismic hazards and structural demands. The current study presents a novel ground-motion IM that incorporates the influence of multiple vibration modes and period elongation resulting from isolation based on the velocity spectrum. A comprehensive study has been conducted to examine the efficiency of 37 different ground-motion IMs on a roof-isolated large-span structure with engineering demand parameters (EDPs), using far-field ground-motion data. The initial examination of the proposed intensity measure involves a planar lumped-mass model. Subsequently, a numerical model of a large-span roof-isolated structure, specifically the Beijing Workers’ Stadium, is constructed and examined. The results suggest that the proposed intensity measure (IM) demonstrates satisfactory adequacy and achieves optimal efficiency when considering three different engineering demand parameters among 37 other ground-motion intensity measures. Full article

A proposal to control the structural pounding hazard imposed on multistory reinforced concrete (RC) structures is presented. The main goal is to guarantee the seismic performance of a structure with an acceptable (predefined) risk-targeted parameter without the need to eliminate structural pounding collisions. The key target parameters of this study are the annual probability of exceeding an engineering demand parameter (EDP) capacity level and the separation distance d_g between adjacent structures. In this direction, a method that ensures the performance level of critical EDPs due to structural pounding conditions is proposed. The new method involves two decision frameworks that define (a) the optimal separation gap distance $\left({\mathrm{d}}_{\mathrm{g},\mathrm{m}\mathrm{i}\mathrm{n}}^{{\mathrm{P}}_{\mathrm{t}}}\right)$ at a targeted value of pounding risk (probability per year) P_t (Decision A) and (b) the minimum acceptable structural pounding risk ${\mathrm{P}}_{\mathrm{m}\mathrm{i}\mathrm{n}}^{{\mathrm{d}}_{\mathrm{g},\mathrm{t}}}$ at a targeted value of separation gap distance d_g,t (Decision B). The demand parameters that are incorporated in the proposed method are the peak relative displacement δ_max at the top level of colliding without considering pounding conditions and any other critical EDP due to the structural pounding effect. The overall method is based on two distinct acceptable performance objectives, the POs-δ_max and the POs-EDP, defined as a function of P vs. d_g. For this purpose, a seismic hazard curve compatible with Eurocode’s 8 hazard zone is adopted, and the corresponding demand hazard curves of δ_max and EDP are developed. The proposed method is implemented to study the floor-to-floor structural pounding hazard of an eight-story RC frame taking into account different risk-targeted scenarios. The results show that the seismic risk (probability per year) of exceeding the EDP’s capacity level is significantly increased due to structural pounding in comparison to the case of no pounding. Calibration of the structural pounding risk can be obtained by adjusting the separation gap distance d_g between the adjacent structures based on the acceptable POs. The POs-δ_max is not always an accurate criterion for verifying the capacity level of the critical EDP. Finally, with the proposed method, a variety of POs-EDPs can be used to control the structural pounding risk in terms of ${\mathrm{d}}_{\mathrm{g},\mathrm{m}\mathrm{i}\mathrm{n}}^{{\mathrm{P}}_{\mathrm{t}}}$ and/or ${\mathrm{P}}_{\mathrm{m}\mathrm{i}\mathrm{n}}^{{\mathrm{d}}_{\mathrm{g},\mathrm{t}}}$. Full article

The effect of the vertical component of earthquakes on the structural behaviour of unreinforced masonry (URM) walls is usually not considered by technical codes for ordinary buildings. Recent scientific literature, however, indicates that the earthquake vertical component may play a significant role in the crack pattern of URM walls and their collapse. This paper investigates the effect of the vertical seismic component on the capacity and damage scenario for a two-story regular URM wall, described with a detailed micro-modelling approach. Pushover and nonlinear time history analyses are carried out with and without the vertical component and under different dead loads representative of typical stress states for URM structures. The inter-story drift and roof drift ratios are introduced as Engineering Demand Parameters (EDPs), and their correlation with the Ground Motion Parameters (GMPs) of the horizontal and vertical components is discussed. The results show a very good correlation between the seismic demand and the GMPs of the vertical component, demonstrating the influence of the vertical component on the global seismic response. Moreover, the study shows that the influence of the vertical component increases with the vertical load applied to the structure, which indicates that the vertical ground motion component cannot be a priori neglected for URM walls when moderate to large vertical GMPs are expected. Full article

The structural response of buildings to earthquake shaking is of critical importance for seismic design purposes. Research on the relationship between earthquake ground motion intensity, building response, and seismic risk is ongoing, but not yet fully conclusive. Often, probability demand models rely on one ground motion intensity measure (IM) to predict the engineering demand parameter (EDP). The engineering community has suggested several IMs to account for different ground motion characteristics, but there is no single optimal IM. For this study, we compile a comprehensive list of IMs and their characteristics to assist engineers in making an informed decision. We discuss the ground motion selection process used for dynamic analysis of structural systems. For illustration, we compute building responses of 2D frames with different natural period subjected to more than 3500 recorded earthquake ground motions. Using our analysis, we examine the effects of different structural characteristics and seismological parameters on EDP-IM relationships by applying multi-regression models and statistical inter-model comparisons. As such, our results support and augment previous studies and suggest further improvements on the relationship between EDP and IM in terms of efficiency and sufficiency. Finally, we provide guidance on future approaches to the selection of both optimal intensity measures and ground motions using newer techniques. Full article

Probabilistic seismic demand analysis (PSDA) is known as one of the critical intermediate steps in the performance-based earthquake engineering (PBEE) design framework. Accuracy of the PSDA is influenced by various sources of uncertainties and mostly by that stemming from the ground motion-related variabilities. By taking a representative reinforced concrete (RC) continuous girder bridge as the case study, twenty-eight commonly used seismic intensity measures (IMs) were investigated in terms of the effectiveness, efficiency, practicality, proficiency, and sufficiency assessments. Probabilistic seismic demand models (PSDMs) of several critical bridge engineering demand parameters (EDPs) were developed under both the near-field and far-field ground motions through the nonlinear time history analyses (NTHAs). In addition, effects of ground motion-related uncertainties, such as the bin-to-bin (BTB) and record-to-record (RTR) variabilities, on the PSDA of highway bridges were also investigated. It is concluded that (1) IM efficiency contributes significantly to reflecting the RTR variability of ground motions and an efficient IM may reduce the influence of RTR variability in the estimation of structural demands; (2) IM sufficiency reflects the statistical independence of IM and ground motion parameters, and a sufficient IM is helpful in rendering the prediction of structural demands; and (3) uncertainties stemming from both the BTB and RTR variabilities of the seismic records have significant influences on the PSDA and the developed PSDMs of highway bridges. Full article

To rank the pulse-like ground motions based on the damage potential to different structures, the internal relationship between the damage potential of pulse-like ground motions and engineering demand parameters (EDPs) is analyzed in this paper. First, a total of 240 pulse-like ground motions from the NGA-West2 database and 16 intensity measures (IMs) are selected. Moreover, four reinforced concrete frame structures with significantly different natural vibration periods are established for dynamic analysis. Second, the efficiency and sufficiency of the IMs of ground motion are analyzed, and the IMs that can be used to efficiently and sufficiently evaluate the EDPs are obtained. Then, based on the calculation results, the principal component analysis (PCA) method is employed to obtain a comprehensive IM for characterizing the damage potential of pulse-like ground motions for specific building structures and EDPs. Finally, the pulse-like ground motions are ranked based on the selected IM and the comprehensive IM for four structures and three EDPs. The results imply that the proposed method can be used to efficiently and sufficiently characterize the damage potential of pulse-like ground motions for building structures. Full article

Several methodologies for assessing seismic risk extract information from the statistical relationship between the intensity of ground motions and the structural response. The first group is represented by intensity measures (IMs) whilst the latter by engineering demand parameters (EDPs). The higher the correlation between them, the lesser the uncertainty in estimating seismic damage in structures. In general, IMs are composed by either a single (scalar-based IMs) or a group of features of both the ground motion and the structure (vector-valued IMs); the latter category provides higher efficiency to explain EDPs when compared to the first one. This paper explores how to find new vector-valued IMs, which are highly correlated with EDPs, by means of multi-regression analysis. To do so, probabilistic nonlinear dynamic analyses have been performed by considering a seven-story reinforced concrete building as a testbed. At a first stage, 30 scalar-based IMs have been correlated with 4 EDPs (i.e., 120 groups of IM-EDP pairs have been studied). Afterwards, the structural responses have been classified as elastic, inelastic and a combination of both. It has been analyzed how efficiency behaves when making these classifications. Then, 435 vector-valued IMs have been created to enhance the predictability of the scalar EDPs (i.e., 1740 groups of IM-EDP pairs have been analyzed). Again, the most efficient IMs have been identified. Sufficiency, which is another statistical property desired in IMs, has also been examined. Results show that the efficiency and sufficiency to predict the structural response increase when considering vector-valued IMs. This sophistication has important consequences in terms of design or assessment of civil structures. Full article

The complexity of earthquakes and the nonlinearity of structures tend to increase the calculation cost of reliability-based design optimization (RBDO). To reduce computational burden and to effectively consider the uncertainties of ground motions and structural parameters, an efficient RBDO method for structures under stochastic earthquakes based on adaptive Gaussian process regression (GPR) metamodeling is proposed in this study. In this method, the uncertainties of ground motions are described by the record-to-record variation and the randomness of intensity measure (IM). A GPR model is constructed to obtain the approximations of the engineering demand parameter (EDP), and an active learning (AL) strategy is presented to adaptively update the design of experiments (DoE) of this metamodel. Based on the reliability of design variables calculated by Monte Carlo simulation (MCS), an optimal solution can be obtained by an efficient global optimization (EGO) algorithm. To validate the effectiveness and efficiency of the developed method, it is applied to the optimization problems of a steel frame and a reinforced concrete frame and compared with the existing methods. The results show that this method can provide accurate reliability information for seismic design and can deal with the problems of minimizing costs under the probabilistic constraint and problems of improving the seismic reliability under limited costs. Full article