Performance-based Earthquake Engineering Research Articles

Sufficiency assessment of intensity measures for natural and spectral-matched ground motion records

A correct Intensity Measure (IM) selection is essential for Performance-Based Earthquake Engineering (PBEE) applications, as any probabilistic seismic demand model (PSDM) depends significantly on the IM. If a single IM can describe the complexity of the corresponding ground motion record, it can be defined as sufficient in an absolute sense. However, this is unlikely because a single number should be able to inform on the frequency content, the amplitude, the duration, the energy content, etc. For this reason, literature studies have defined sufficiency in a relative sense to investigate whether one IM is more sufficient (i.e., more informative) than another in predicting the structural response. This work explores the relative sufficiency of eight scalar IMs through Nonlinear Response History Analyses (NRHAs) using two sets of 20 pairs of ground motion records. Both sets are spectrum-compatible and consist of unscaled natural and spectral-matched records. Also, both Cloud and Incremental Dynamic Analysis procedures are used. This study demonstrates that Cloud analysis cannot be used in its conventional form to study sufficiency when spectral-matched accelerograms are used. When natural accelerograms are employed, the results clearly indicate the existence of a sufficient IM among those selected. Conversely, it is more difficult to define the relative sufficiency of the IMs for spectral-matched records because the operation of record adjusting leads to similar structural demands. This result could question either the validity of using spectral-matched accelerograms for PBEE due to the lack of aleatory variability in the structural demand or the necessity of having a sufficient IM when a PSDM is fitted in a PBEE analysis using spectral-matched accelerograms.

Probabilistic resilience assessment framework of structures considering the combined functionality-recovery-duration uncertainty

In the current stage, the risk-guided performance-based earthquake engineering (PBEE) has become the main direction in the earthquake community. As an important part of risk, seismic resilience indicators have been increasingly emphasized and elevated to new levels in recent years. Seismic resilience refers to the capacity of social entities to reduce disaster risks and to facilitate recovery efforts with the least social disruption in possible. Currently, the calculations of resilience indicators are commonly based on the deterministic approach. In fact, resilience indicators are also random variables, and the corresponding recovery time, recovery function or residual function in resilience calculation may vary within a range for different intensity levels and limit states. Therefore, characterizing resilience indicators through probabilistic models or confidence intervals can be a more practically valuable and meaningful strategy for future research. In this paper, a probabilistic resilience assessment framework of structures is proposed, and a sinusoidal-based continuous recovery function characterized by different limit states and recovery modes is given. The combined uncertainties of functionality, recovery and duration are incorporated into the framework, and an application example via the reinforced concrete frame is given to implement the framework. Besides, the sensitive analysis of different variables to the resilience assessment result is performed, and the comparison between the deterministic and probabilistic analysis is further discussed. In general, the framework consists of three parts, i.e., (1) Generating samples, fragility and damage states; (2) Calculating total stochastic recovery functions for resilience analyses; and (3) Performing probabilistic seismic resilience analyses. If deterministic analysis is used, the resilience index is only a value, while if probabilistic analysis is used, the resilience index will be a variable with a corresponding probability and distribution range. Compared with other variables, the amplitude and wavelength have a stronger influence in the result of resilience index. This is because these two parameters are function-dependent and will directly affect the envelope curve in the resilience calculation. Although the changes in coefficient of variation (COV) will affect the curve results, the macro characteristics are consistent when comparing different target resilience index. Moreover, as the intensity rises, there is a statistical decrease in both the average residual functionality and resilience indicators, along with a statistical increase in the average recovery durations. The annual exceeding probability decreases as the target resilience level increases, while the life-cycle exceeding probability increases when the target resilience level decreases for the same year. In a sense, the integrated probabilistic resilience framework realizes the decoupling of resilience indicators for different performance groups and limit states, and provides a reference for the further stochastic resilience assessment from a probabilistic perspective.

Collapse fragility analysis of historical masonry buildings considering in-plane and out-of-plane response of masonry walls.

This paper explores the seismic fragility assessment of historical masonry buildings in the context of performance-based earthquake engineering, using multiple-record incremental dynamic analyses (MR-IDA). The methodology is applied to two case studies, the first being a stiff monumental structure, and the second a tall and slender masonry building. Both case studies are modelled in the OpenSees software using three-dimensional macroelements that account for the in-plane (IP) and out-of-plane (OOP) response of masonry walls. Simultaneously, the numerical models account for the influence of non-linear connections in floor-to-wall interfaces and wall-to-wall interlocking. The record-to-record variability induced by the random nature of the ground motion is addressed through earthquake selection consistent with the variability of European hazard. Ground motion records are normalised at a uniform level of seismic intensity to be sequentially increased for the computation of IDA curves. Once IDA curves and fragility functions are derived, the failure results are thoroughly discussed. The fragility functions accounting for the uncertainties arising from the record-to-record variability are contrasted against the results of the seismic assessments affected by multiple sources of uncertainty in material and modelling parameters from a previous study. Finally, the fragility curves derived from the methodology presented herein are directly compared with fragility functions from probabilistic seismic demand analysis (PSDA). Overall, IDA-based fragility functions are found to provide more conservative predictions than the ones obtained from the cloud-based approach using unscaled records.

Auto-WoodSDA: A scalable end-to-end automation framework to perform probabilistic seismic risk and recovery assessment of new residential woodframe buildings

The seismic performance of residential woodframe buildings has a widespread and lasting impact on the socioeconomic vitality of a community. To enable efficient seismic risk and resilience assessment, a comprehensive framework that is rooted in performance-based earthquake engineering (PBEE) methodology is proposed. The framework is formulated as a computational workflow which is operationalized as an automation program dubbed “Auto-WoodSDA”. The end-to-end platform is developed to perform four major tasks: (1) generate code-compliant seismic design, (2) create numerical models, (3) perform nonlinear analyses, and (4) assess earthquake-induced financial losses and functional recovery time. Given the user inputs, Auto-WoodSDA sequentially executes the four tasks without intermediate human intervention to produce seismic performance metrics such as the expected annual loss. It is presented as a ready-to-implement platform that is computationally efficient and scalable in performing large-scale seismic risk and resilience assessment. An example building from the existing literature is used to demonstrate the key features of the automation framework and verify the results. The results underscore the ability of the AutoWoodSDA computational workflow to automate the generation of reliable new code-compliant woodframe building designs, perform nonlinear analysis, and assess the earthquake-induced impacts using PBEE principles.

Long‐range Ising model for regional‐scale seismic risk analysis

AbstractThis study introduces the long‐range Ising model from statistical mechanics to the performance‐based earthquake engineering (PBEE) framework for regional seismic damage analysis. The application of the PBEE framework at a regional scale involves estimating the damage states () of numerous structures, typically performed using fragility function‐based stochastic simulations. However, these simulations often assume conditional independence or employ simplistic dependency models among the of structures, leading to significant misrepresentation of regional risk. The Ising model addresses this issue by converting the available information on binary (safe or failure) into a joint probability mass function, leveraging the principle of maximum entropy. The Ising model offers two main benefits: (1) it requires only the first‐ and second‐order cross‐moments, enabling seamless integration with the existing PBEE framework, and (2) it provides meaningful physical interpretations of the model parameters, facilitating the uncovering of insights not apparent from data. To demonstrate the proposed method, we applied the Ising model to 156 buildings in Antakya, Turkey, using post‐hazard damage evaluation data, and to 182 buildings in Pacific Heights, San Francisco, using simulated data from the Regional Resilience Determination tool. In both instances, the Ising model accurately reproduces the provided information and generates meaningful insights into regional damage. The study also investigates the change in Ising model parameters under varying earthquake magnitudes, along with the mean‐field approximation, further facilitating the applicability of the proposed approach.

Optimal intensity measure for seismic performance assessment of shield tunnels in liquefiable and non-liquefiable soils

Relating the ground motion intensity measure (IM) and the structural engineering demand parameter is a crucial step in the performance-based earthquake engineering framework. This study investigates the selection of IM for development of probabilistic seismic demand model of urban shield tunnels subjected to earthquake ground motions in liquefiable and non-liquefiable soils. Nonlinear dynamic effective stress analyses are conducted to develop a database of the intensity measures and structural seismic responses exposed to ground shaking and soil liquefaction. Two advanced soil constitutive models (i.e., Pressure DependMultiYield03 and PressureIndependMultiYield for liquefiable and non-liquefiable soils, respectively) are employed to capture the nonlinear behavior. A suite of 23ground motion intensity measures is selected and assessed based on the evaluation criteria of correlation, efficiency, practicality and proficiency. Eventually, the multi-level fuzzy comprehensive evaluation method is employed to comprehensively consider the four evaluation criteria and establish the optimal ground motion IM suitable for probabilistic seismic demand analysis of shield tunnel structures. The obtained results show that the sustained maximum acceleration is the optimal IM for evaluating the structural seismic response, followed by the peak ground acceleration in both liquefiable and non-liquefiable soils. Peak pseudo velocity spectrum, displacement square integral and Housner spectral intensity are found to be not suitable for the probabilistic seismic demand analysis of shield tunnel structures.

Vine-copula-based multi-dimensional fragility analysis of nuclear power plant under sequential earthquakes

Seismic resilience of critical infrastructure, such as nuclear power plants, is paramount in ensuring nuclear safety. This study presents a comprehensive analysis of the seismic fragility of nuclear power plants under sequential earthquakes, employing the innovative vine-copula theory. The methodology integrates advanced modeling techniques, including layered shell elements and plastic damage softening constitutive modeling, to capture the intricate behavior of nuclear power plants under seismic loading. The seismic sequence is derived from the Wenchuan earthquake data, considering both mainshocks and aftershocks. A set of random seismic peak ground accelerations (PGAs) is generated based on the distribution of giant earthquake PGAs. Utilizing seismic attenuation theory, corresponding random aftershock PGAs are generated. The resulting mainshock-aftershock sequence, modulated within the real seismic sequence, serves as the input for numerical simulations. The vine-copula theory is employed for multi-dimensional fragility analysis, providing a flexible framework to model the complex nonlinear dependencies among structural response parameters. The vine-copula model is applied to fit seismic response data, allowing the construction of fragility surfaces under sequential earthquakes. This approach, rooted in performance-based earthquake engineering (PBEE), enables a more realistic representation of the seismic risk profile. The findings demonstrate that seismic fragility trends for nuclear power plants increase with higher mainshock and aftershock intensity measures (IMs). The impact of aftershocks on the structural performance, often overlooked in traditional studies, is elucidated through the proposed methodology. The study contributes valuable insights into nuclear safety assessments by quantifying the influence of sequential earthquakes on the fragility of nuclear power plants.

Analysis of High-Rise Building Using Opensees

Numerical simulation has increasingly become an effective method and powerful tool for performance-based earthquake engineering research. Most existing numerical analyses use general-purpose commercial software, which can limit in-depth investigations on specific, complex topics. Consequently, this research focuses on the dynamic analysis of high-rise reinforced concrete (RC) frame-core tube structures using the open-source finite element (FE) code OpenSees to perform nonlinear seismic analyses. Various shear walls, a frame-core tube structure, and a tall building are simulated. The rationality and reliability of the proposed analysis method are validated through comparison with available experimental data and the analytical results of a well-validated commercial FE code. The research outcomes will provide a useful reference and an effective tool for further numerical analysis of the seismic behavior of tall buildings.

Collapse mechanisms and fragility curves based on Lumped Damage Mechanics for RC frames subjected to earthquakes

Reinforced concrete structures under earthquakes present nonlinear behavior with cracking evolution and plastic strains that can lead to failure due to large displacements with development of collapse mechanisms. This manuscript presents a methodology to apply Lumped Damage Mechanics (LDM) in a Performance-Based Earthquake Engineering (PBEE) framework, to evaluate the seismic vulnerability of reinforced concrete frames. The lumped damage model represents the evolution of damage and plasticity lumped into local inelastic hinges at the nodes of the elements. This paper proposes a novel procedure to identify and characterize global collapse mechanisms from the internal variables of damage using system reliability theory. In this way, the internal variables of damage are used as engineering demand parameters (EDPs) to calculate the fragility curves of the structure, which are also compared with usual interstory drift fragilities. To evaluate the seismic vulnerability, incremental dynamic analyses are conducted. The main results demonstrate efficiency of LDM in a PBEE framework, and that the internal variables of damage are objective indicators of collapse for RC frames. Results show how to identify the global failure mechanisms that are more likely to appear for each frame. For regular frames, high correlation is observed between the local hinges forming each global collapse mechanism. This allows collapse mechanisms to be readily characterized by the strongest link in a parallel system.

Selection of optimal intensity measures for seismic performance evaluation of underground utility tunnel and internal pipeline system

Seismic intensity measures (IMs), which are closely related to both earthquake hazards and structural responses, play a critical role in the performance-based earthquake engineering (PBEE) framework. This paper aims to investigate and define the most representative IMs for probabilistic seismic demand model (PSDM) for the longitudinal utility tunnel and internal pipeline system. Similar to the requirements by the Chinese Code for seismic design of urban rail transit structures, the utility tunnel in this study is assumed being buried in four typical engineering site classes for the analyses. Soil-tunnel-pipeline interactions are simulated using a double-beam system resting on a nonlinear foundation. Soil-tunnel interaction, tunnel-pipeline interaction and joint connections are modeled as nonlinear springs with different mechanical properties. A series of 17 pairs of outcrop ground-motion records and 27 commonly used IMs are selected in the analyses. Engineering demand parameter (EDP) is defined based on the maximum joint opening and the maximum strain of the utility tunnel and internal pipeline, respectively. The selected IMs for predicting the seismic responses of tunnel-pipeline systems are tested using different criteria, i.e., correction, efficiency, practicality, and proficiency. The final decision-making procedure employs a fuzzy multi-criteria decision method. The numerical results indicate that: (1) The velocity-related IMs are the most representative IMs based on the four criteria for structures buried in four sites of different conditions; (2) The optimal seismic IMs vary with different criteria, site classes and structure types. According to the fuzzy multi-criteria decision approach, optimal IMs for the tunnel-pipeline system are PGV, PGV, EPV and HI for site classes I – IV, respectively. The proposed optimal IMs can be utilized to construct seismic fragility curves of utility tunnel, internal pipeline and tunnel-pipeline systems in four different site classes.

A direct analytical derivation of the multi-dimensional fragility spaces of structures under nonstationary mainshock-multi-aftershock sequences

Performance-based earthquake engineering (PBEE) is a popular direction in the earthquake community, and at this stage, risk-based PBEE has become mainstream. In the risk-based probabilistic framework, seismic fragility analysis constitutes the most important link, and corresponding research on the mainshock–aftershock sequence has received widespread attention in recent years. Since a mainshock is often accompanied by multiple aftershocks and there is great uncertainty in the vibration characteristics of aftershocks, a seismic fragility analysis of structures under a stochastic mainshock-multi-aftershock sequence is meaningful and necessary. The corresponding questions, such as how to derive the multi-dimensional analytical fragility form under a stochastic mainshock-multi-aftershock sequence and how to correlate multiple intensity measures with multiple demand parameters, still require further investigation. In this paper, a direct analytical derivation of the multi-dimensional seismic fragility spaces of structures under nonstationary stochastic mainshock-multi-aftershock sequences is introduced. The methodology framework, implementation steps, and application examples are also provided in detail. Moreover, two scenarios, the one-mainshock-one-aftershock and one-mainshock-two-aftershocks, are considered, and the obtained multi-dimensional analytical fragility spaces for both scenarios are validated. In general, the matching accuracy of the fragility results for both scenarios is proven to be high, and the direct analytical derivation of the multi-dimensional fragility spaces is validated to be ideally consistent, which further provides a reference for multi-dimensional risk analysis under nonstationary stochastic mainshock-multi-aftershock sequences in future work.

Performance-based earthquake early warning for tall buildings

The ShakeAlert Earthquake Early Warning (EEW) system aims to issue an advance warning to residents on the West Coast of the United States seconds before the ground shaking arrives, if the expected ground shaking exceeds a certain threshold. However, residents in tall buildings may experience much greater motion due to the dynamic response of the buildings. Therefore, there is an ongoing effort to extend ShakeAlert to include the contribution of building response to provide a more accurate estimation of the expected shaking intensity for tall buildings. Currently, the supposedly ideal solution of analyzing detailed finite element models of buildings under predicted ground-motion time histories is not theoretically or practically feasible. The authors have recently investigated existing simple methods to estimate peak floor acceleration (PFA) and determined these simple formulas are not practically suitable. Instead, this article explores another approach by extending the Pacific Earthquake Engineering Research Center (PEER) performance-based earthquake engineering (PBEE) to EEW, considering that every component involved in building response prediction is uncertain in the EEW scenario. While this idea is not new and has been proposed by other researchers, it has two shortcomings: (1) the simple beam model used for response prediction is prone to modeling uncertainty, which has not been quantified, and (2) the ground motions used for probabilistic demand models are not suitable for EEW applications. In this article, we address these two issues by incorporating modeling errors into the parameters of the beam model and using a new set of ground motions, respectively. We demonstrate how this approach could practically work using data from a 52-story building in downtown Los Angeles. Using the criteria and thresholds employed by previous researchers, we show that if peak ground acceleration (PGA) is accurately estimated, this approach can predict the expected level of human comfort in tall buildings.

Seismic fragility analysis of structures via an Adaptive Gaussian Mixture Model and its application to resilience assessment

Seismic fragility analysis and seismic resilience assessment are pivotal tasks within the performance-based earthquake engineering framework. The former aims to quantitatively assess the probability of engineering structures sustaining various degrees of damage when subjected to earthquakes of varying intensity levels. In contrast to many traditional seismic fragility methods, this paper introduces a precise and versatile approach grounded in reliability analysis, with the goal of eliminating the restrictive lognormal assumption. Initially, the proposed method involves conducting seismic reliability analysis of structures using the Fractional Exponential Moments-based Maximum Entropy Method (FEM-MEM). This approach efficiently yields failure probabilities. Subsequently, an Adaptive Gaussian Mixture Model (AGMM) is presented for fitting a set of failure probability points, producing comprehensive and continuous seismic fragility curves. Notably, AGMM offers remarkable flexibility in modeling fragility curves, ensuring precise estimations for subsequent resilience assessments. Building upon the results of the fragility analysis, the paper proceeds to assess the seismic resilience of structures. The proposed method’s feasibility and effectiveness are validated through two illustrative numerical examples. The results demonstrate that, in comparison to the conventional lognormal assumption, the proposed method offers superior accuracy and broader applicability for conducting seismic fragility analyses of structures.

Fusing physics-based and machine learning models for rapid ground-motion-adaptative probabilistic seismic fragility assessment

Performance-based earthquake engineering (PBEE) has asserted probabilistic seismic fragility assessment (PSFA) as the main research content in light of its irreplaceable significance for seismic decision-making in recent decades. Among the multiple approaches of PSFA implementation, the classical linear regression method (LRM) dominates over practice regarded as one of the most widely-used. However, the general LRM adopts quantile regression method (QRM) on the group of fragility curves to approximate a deterministic probability density distribution (PSD) of structural fragility against certain intensity measure (IM) of potentially confronting earthquake. Consequently, the QRM-derived fragility representation might not be credible enough while evaluating a newly-occurred seismic event owing to its neglect of specificity of stochastic ground motion. To address this issue, a fusing physics-based and machine learning models towards rapid ground-motion-adaptative probabilistic seismic fragility assessment (GmaPSFA) is proposed in present study. With sophisticated framework design and novel fragility hyperparameters estimation, the involved design philosophy and mechanism translating are both elaborated. To validate the method, both the LRM and GmaPSFA were conducted on a six-story frame structure, where a novel fully-automatic batch processing approach fusing APDL and coding languages was propounded for structural analysis. The comprehensive validating cases confirmed the powerful capability and significant superiority of proposed GmaPSFA in realizing rapid ground-motion-adaptative probabilistic seismic fragility assessment catering for modern PBEE.

Earthquake-induced loss assessment of hybrid self-centering piston-based braced frame with friction springs and SMA bars

A novel Self‐Centering Piston-Based Bracing (SC-PBB), integrating Friction Springs (FSs) and Shape Memory Alloy (SMA) bars, offers a promising solution for curtailing seismic damage in braced frame structures. Nevertheless, this hybrid SC-PBB may incur higher construction costs compared to conventional bracing archetypes. Accordingly, it is imperative to investigate whether the initial cost increase can be offset over the structure's lifespan. This study quantifies earthquake-induced financial losses in braced frames equipped with SC-PBBs (SC-PBBFs) compared to those equipped with Buckling-Restrained Bracings (BRBs). A building-specific Performance-Based Earthquake Engineering (PBEE) framework is employed to evaluate potential economic losses under far-field ground motions. The analysis quantifies total, collapse, irreparable, and repair losses by incorporating seismic hazards, structural demands, and damage consequences. Results reveal higher total and collapse losses for BRBFs, although their lower repair costs for non-structural components mitigate repair loss. Additionally, the low-rise SC-PBBF archetype could recoup initial construction expenses over its expected lifespan, unlike its BRBF counterpart.

Predictive models for assessment of buried pipeline response under seismic landslides in Iran

In seismic regions both in Iran and around the world, subterranean gas pipelines inevitably extend through high-risk areas prone to seismic landslides. The seismic landslide-pipe failure mechanism constitutes a continuum geomechanical challenge influenced by factors such as sliding mass configuration, pipe positioning relative to potential slope failure surfaces, and seismic input characteristics. In this study, response of steel pipeline buried in sand under seismic landslide action is analyzed by finite difference models using an advanced soil constitutive model. The numerical model is first validated based on the shaking table test results and then several dynamic analyses are performed using the selected records of the Iranian ground motions database. The outcomes of the dynamic analysis demonstrate that Arias Intensity (Ia) can be identified as an optimal intensity measure (IM) for predicting the seismic response of a slope-pipe system in terms of maximum pipe deflection, axial strain, and shear stress. Predictive models are then developed based on the optimal IM for estimating the pipe deflection, axial strain, and shear stress subjected to a seismic landslide. These proposed predictive models offer valuable insights for assessing the response of buried pipelines to seismic landslides in Iran within the framework of performance-based earthquake engineering.

Seismic risk assessment of highway bridges in western Canada under crustal, subcrustal, and subduction earthquakes

This study conducts seismic risk assessment of highway bridges in western Canada. The performance-based earthquake engineering (PBEE) framework is enhanced to assess the expected annual repair cost ratio (ARCR) and annual restoration time (ART) of a benchmark bridge class under the region’s three types of earthquakes - shallow crustal earthquakes (CEs), deep subcrustal earthquakes (SCEs), and megathrust Cascadia subduction earthquakes (CSEs). First, event-specific seismic hazard models are considered, whereas event-consistent ground motions are selected for non-linear time history analyses. Compared with those from CEs and SCEs, CSE ground motions feature a much longer duration. This long-duration effect is captured by validating the numerical model of the bridge column against (1) a cyclic pushover test under standard versus long-duration loading protocols and (2) a shaking table test excited by six consecutive ground motions. Besides, the Park and Ang damage index is utilized as the column’s engineering demand parameter (EDP) and updated as a demand-capacity ratio model when reaching four different damage states. A comprehensive list of ground motion intensity measures (IMs) is considered where the spectra acceleration at one second, Sa(1.0), is chosen as the most suitable IM based on its performance in proficiency, efficiency, practicality, and EDP-IM correlation across all three earthquake events. Subsequently, component- and system-level fragility models are derived under each earthquake type using the cloud analysis that convolves the seismic demands with capacity models for multiple bridge components. To further quantify and propagate the epistemic uncertainty associated with the development of probabilistic seismic demand models (PSDMs), the bootstrap resampling technique is utilized to generate numerous seismic demand datasets and develop a stochastic set of seismic fragility curves. Finally, the bootstrapped, event-dependent fragility models are combined with the respective hazard models and probabilistic loss functions to assess the expected ARCR and ART for the benchmark bridge class. This study underscores the significantly higher seismic risk of highway bridges when facing CSEs, followed by CEs and SCEs.

Investigating the Reliability of Ground Motion Intensity Measures

The uncertainty and unreliability in the probabilistic seismic demand models (PSDMs) can be addressed in the framework of performance‐based earthquake engineering (PBEE). Some characteristics have been introduced and extensively investigated in the earthquake engineering literature for appropriateness (i.e., optimality) of various intensity measures, such as efficiency, effectiveness, sufficiency, practicality, and hazard computability. The reliability of the intensity measures can also be considered as another important criterion for intensity measure (IM) selection, which has not been investigated extensively. In this paper, a framework has been developed and implemented to investigate the reliability of various intensity measures alongside the number of adopted earthquake records. In this regard, the inverse of the mean coefficient of variation (IMCV), which is detected to be in a direct and linear relationship with the number of earthquake records, is adopted as the main criterion to compare the reliability of ground motion intensity measures. A simple relation has been proposed and calibrated for the studied IMs that provide the required number of earthquake records to satisfy an intended level of reliability. As a case study, a significant number of recorded ground motions at Zagros and non‐Zagros zones (two major seismic regions in Iran) with rock and soil conditions are selected, and the most reliable ground motion intensity measure is introduced at various seismic regions and soil types by exploiting the developed framework and the proposed relationship.

Avaliação sísmica em um pórtico de concreto armado considerando a modelagem com plasticidade concentrada e distribuída

Abstract Researchers must decide on how they will model the non-linear material response in a Finite Element simulation to assess seismic vulnerability. This paper aims at giving an insight into these modelling decisions by comparing Fiber and Lumped Plasticity Finite Element Models in static and dynamic non-linear analysis in a RC frame. The methodology is based on the performance-based earthquake engineering to determine the expected damage on structures. The results indicate that both models are in good agreement with the static analysis, and when considering Extensive and Complete Damage Limit States on the dynamic analysis. The choice between them depends on the main goals of the research and resources available, since they have a significant difference in processing time.

Seismic loss assessment of code-compliant moment-resisting RC buildings located on different soil conditions of Mexico City

This research aims to estimate the expected economic losses associated with the repair cost of a set of code-compliant moment-resisting reinforced concrete buildings located on different soil conditions in Mexico City. The loss assessment methodology is based on the second generation of the Performance-Based Earthquake Engineering (PBEE) framework, which quantifies the seismic performance of buildings in terms of metrics such as economic losses, downtime, and casualties, which are more meaningful to owners and stakeholders for the decision-making process. The methodology uses a probabilistic approach that takes into account uncertainties in seismic intensity, structural response, component damage, and consequence prediction. The seismic response of structures was calculated in terms of inter-story drifts and floor accelerations to assess the damage to their structural and non-structural components. In addition, taking into account the seismic hazard of the site, the expected annual losses (EAL) are calculated to provide insight into the seismic performance evaluation of structures with different characteristics in terms of the financial impact in seismic-prone regions like Mexico City.