Performance-based Earthquake Engineering Research Articles

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.

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.

Modeling and material uncertainty quantification of RC structural components

It is well established that various sources of uncertainties play a critical role in the safety assessment of engineering structures. Some widely used frameworks, such as performance-based earthquake engineering (PBEE), explicitly consider the ground motion record-to-record randomness, while the material and modeling uncertainty remain to be primarily based on judgments or limited analysis. This paper presents the results of a comprehensive uncertainty quantification and sensitivity analysis of a reinforced concrete structural component. First, different modeling strategies are adopted to develop several parent models. Next, various sources of uncertainty are propagated through the parent models to generate thousands of children models. The children models are further combined with material uncertainty to produce grandchildren models, and nonlinear transient simulations are conducted using an innovative artificial acceleration at different seismic intensity levels. The results are post-processed using a range of probabilistic, statistical, and machine learning methods. The study finds that the modeling strategy and its associated variability can cause significant bias and dispersion in the drift response, while material uncertainty has a relatively minor effect. The study quantifies the importance of modeling uncertainty, which is often overlooked in engineering practice.

Research on seismic fragility of subway station based on incremental dynamic analysis method

Seismic intensity measure is an significant parameter that affects the accuracy of structural seismic risk assessment, and plays an important role in the performance-based earthquake engineering research framework. Taking a two story, three span, and shallow buried subway station as the research object, a two-dimensional finite element analysis model of soil structure underground in a typical engineering site was established using ANSYS. Ten earthquake records were selected from PEER as input, and the structural seismic fragility analysis method based on incremental dynamic analysis (IDA) method was introduced into the subway station structure. The maximum story drift angle was used as the structural damage index, and three typical seismic intensity measures were selected, the exploration is conducted on the seismic intensity measures applicable to shallow buried subway stations and the variation pattern of seismic response of subway stations with increasing seismic amplitude. The seismic fragility curve of shallow buried subway station structures is established to obtain the failure probability of the structure at different seismic intensity levels. The analysis results indicate that for shallow buried subway stations, PGA is the most suitable seismic intensity measure, and the comparison with existing empirical fragility curves shows that the vulnerability analysis method is feasible and can quantitatively provide the failure probability of structures at different performance levels, providing reference for seismic design of underground structures.

A KDE-based non-parametric cloud approach for efficient seismic fragility estimation of structures under non-stationary excitation

With the development of performance-based earthquake engineering, the risk-informed assessment framework has received broad recognition over the world, of which the probability seismic fragility analysis is an important step. The classic seismic fragility adopts the lognormal assumption and forms a parametric derivation. With the development of fragility theory, researchers are hoping to seek out non-parametric approaches to express the intrinsic fragility in a pure analytical form without any distribution assumptions. Besides, how to keep the calculation efficiency (e.g., combining with cloud approach) and how to consider the non-stationary stochastic responses (e.g., combining with non-stationary stochastic excitation model) are critical aspects in fragility that deserve further attention of researchers. In this paper, a kernel density estimation (KDE) based non-parametric cloud approach is proposed for efficient seismic fragility estimation of structures under non-stationary excitation. First, the methodology framework of the efficient approach is illustrated. Then, the procedures of non-stationary stochastic seismic response of structures and KDE-based non-parametric cloud approach for efficient seismic fragility are demonstrated. After that, an application example via a three-span-six-story reinforced concrete frame is given for implementation, followed with a parametric analysis of critical factors. During the process, the classic parametric linear-regression based cloud approach (cloud-LR) and benchmark Monte-Carlo-simulation based cloud approach (cloud-MCS) are also incorporated for validation. In general, the analysis verifies the effectiveness of the non-parametric cloud-KDE approach without requiring more computation work (i.e., same as the parametric cloud-LR approach and much less than the benchmark cloud-MCS approach). Meanwhile, the non-parametric cloud-KDE approach indicates a comparable accuracy with the classic fragility approaches (i.e., less deviation than the parametric cloud-LR approach and much closer to the benchmark cloud-MCS approach), and with the increase of stochastic cloud-point number, the corresponding fitting degree of cloud-KDE approach is growing better. The research provides a new sight for the development of non-parametric seismic fragility approach, and the corresponding findings can be further combined with the probabilistic hazard and risk analysis for a non-parametric assessment procedure in performance-based earthquake engineering.

Optimal intensity measures in probabilistic seismic demand model of subway station

Ground motion intensity measure (IM), which is a key link between the seismic hazard analysis and structural seismic response analysis, plays an important role in the performance-based earthquake engineering framework. The objective of this paper is to evaluate the most commonly used IMs with respect to their capability to predict the seismic response of underground subway station structures. Because the properties of the surrounding soil has significant influence on the seismic response of subway station structure, four typical classes of engineering sites ranging from Class I to IV according to Chinese code for seismic design of urban rail transit structures are selected in this study. Dynamic time history analyses considering nonlinear soil-structure interaction (SSI) are performed on four two-dimensional finite element models consisting of two-storey three-span subway stations embedded in four different engineering sites in this paper. Both the near-fault without velocity pulse and far-fault ground motions are used as the seismic inputs for the nonlinear SSI models in this study. Ground motion excitation is converted into equivalent seismic load at the artificial boundary for the discretized finite element model to realize the seismic load input. The applicability of 20 ground motion IMs commonly used in earthquake engineering research are investigated in this study. Statistical regression analysis is carried out for those IMs and engineering demand parameters (EDPs) of the subway station structure measured by maximum inter-storey displacement ratio obtained from nonlinear time history analyses. Based on the criteria of efficiency, practicality, proficiency and sufficiency, the optimal IMs in probabilistic seismic demand model that can best estimate the seismic response of the subway station structure are identified among those commonly used IMs. It is found that for sites of Class I and Class II, the Arias intensity followed by the velocity spectrum intensity are the optimal candidates, and for sites of Class III and Class IV, the Arias intensity is the optimal IM.

Uncertainty and bias in fragility estimates by intensifying artificial accelerations

To comply with the objectives of Performance-Based Earthquake Engineering and gain a comprehensive understanding of a structure’s seismic response, the utilization of multiple ground motion records selected or scaled at various hazard levels is often necessary. Incremental Dynamic Analysis (IDA) and cloud analysis methods represent wide-range probabilistic approaches employed for this purpose. However, due to their computational complexity, researchers and engineers have sought alternative solutions. One such solution is the application of intensifying artificial accelerations (IAAs). By employing IAAs, the structural response can be recorded from linear elastic to nonlinear, and ultimately up to the collapse capacity, all within a single simulation.This paper presents a comprehensive summary of various generations of IAAs and their unique characteristics. To assess their performance on nonlinear single degree-of-freedom systems, the IAAs are compared against IDA results. As IAAs are typically generated to be independent of specific hazard levels, a series of generic (i.e., standardized) ground motion sets are used for IDA. Our objective is to quantitatively evaluate the bias in the mean response estimation by employing different generations of IAAs, developed based on various base response spectra and optimization objectives. Additionally, this paper provides a simplified estimation of fragility curves based on IAAs, and compares the resulting uncertainty with those generated through IDA. The findings aim to enhance the understanding of IAAs’ capabilities and limitations in capturing the seismic response characteristics of structures.

Modelling of non-structural components of an industrial multi-storey frame for seismic risk assessment

Seismic risk assessment of industrial facilities is complex due to the presence of different types of equipment. It represents a research issue that requires further investigation. To this end, some analytical approaches have been developed in the framework of performance-based earthquake engineering. Nonetheless, their accuracy in the case of complex critical facilities, such as nuclear and non-nuclear industrial plants, is still under investigation. Thus, the proposed study intends to research in depth, in a risk assessment framework, some critical aspects related to: (1) modelling of industrial facilities and their secondary equipment with different degrees of accuracy, also taking into account their dynamic interaction; (2) selection of seismic records for fragility analysis, due to the narrow distribution of frequency values for non-structural components; (3) effectiveness of performance-based earthquake engineering applied to this particular class of coupled structure-equipment for risk assessment. In this context, the proper selection of seismic records becomes relevant, and SCoRes, an innovative algorithm for accelerograms selection is worthy of investigation. On these premises, two different configurations of a primary industrial structure, i.e. a moment resisting frame and a braced frame, equipped with non-structural components and subjected to shake table test campaigns are selected as case studies. For the two configurations, a vulnerability assessment of two vertical tanks installed on the first floor was carried out. Along these lines, to establish the effectiveness of the proposed method for both the moment resisting frame and braced frame configurations, the mean annual frequency of exceedance of the bottom-wall strain of the above-mentioned tanks, both at the design basis and safe shutdown earthquake has been evaluated.

Repair cost assessment of longitudinal continuous ballastless track structure on high-speed railway bridge with spatially distributed interlayer area damage

In the context of the performance-based earthquake engineering, a scalar engineering demand parameter (EDP) is commonly utilized for a performance group of components with sheared demand quantity to further assess seismic damage and repair cost (RC). However, a longitudinally continuous ballastless track structure on a high-speed railway bridge (HSRB) may suffer from spatially distributed interlayer area damage (IAD) subjected to earthquake, which hinders the conventional demand evaluation by scalar EDP. Our work leverages a vector-based EDP, LD with variable dimensionality, to quantify all IAD through the track structure. Correspondingly, a vectorized damage measure (DM) is derived with uncertainty quantification. A piecewise linear repair cost model is proposed to map and aggregate the DM entries pertaining to different damage states to RC. In case study, the RC of the track structure is assessed in a three-span simply-supported HSRB. The result shows that greater accuracy in RC is gained by LD with a higher ratio rγ of the cost per meter of repair to replacement and a greater critical replacement length LDS,1 in the RC model. With high LDS,1 and rγ, an alluring finding is that repairing several slightly damaged regions may be more expensive than replacing a few seriously damaged regions.

Artificial Neural Network Technique For Seismic Fragility Analysis Of A Storage Tank Supported By Multi-Storey Frame

Abstract Fragility function, which defines the conditional probability of exceeding a limit state given an intensity measure (IM) of the earthquake, is an essential ingredient of modern approaches like the performance-based earthquake engineering methodology. However, the generation of such curves generally entails a high computational effort to account for epistemic and aleatory uncertainties associated with structural analysis and seismic load. Moreover, a certain probability function, such as the log-normal distribution, is usually assumed in order to carry out the conditional probability of failure of a structure, without any prior information on the correct probability distribution. In this paper, an artificial neural network (ANN) model is proposed to carry out fragility curves in order to avoid the aforementioned problems. In this respect, this paper investigates the following aspects: (i) implementation of an efficient algorithm to select proper seismic intensity measures as inputs for ANN, (ii) derivation of surrogate models by using the ANN techniques, (iii) computation of fragility curves by means Monte Carlo Simulations and (iv) validation phase.

Hazard‐consistent simulated earthquake ground motions for PBEE applications on stiff soil and rock sites

AbstractGround motion record selection is a standard step in state‐of‐the‐art performance‐based earthquake engineering (PBEE) applications. It links the structural response to seismic hazard of the site of interest. In this process, suites of hazard‐consistent ground motion recordings of a wide range of intensity levels are selected (and often scaled) from a database of ground motions to be used as input to nonlinear dynamic response analysis. The ideal practice would be to select ground motions from a database of recorded accelerograms in such a way that they are consistent with the seismic hazard at as many intensity measure (IM) levels as possible and for all important causative scenarios. However, the available databases are not heavily populated, especially for the large‐magnitude short‐distance scenarios. Therefore, synthetic ground motions are the natural candidates to enlarge the database of recordings for scenarios that are important to the site hazard but lack, completely or partially, recorded accelerograms. The usage of such recordings, however, can be recommended only after they are proven to be “realistic” through a battery of seismological and statistical tests. In this study, we propose and implement a multi‐fold testing framework for such an evaluation. We first generate a ground motion database of simulated ground motions (SDB) whose values of the parameters of the causative earthquakes are, to the extent possible, the same of those that caused the ground motions in a mirror database of recorded ground motions (RDB). We then utilize the conditional spectrum (CS) approach computed for a hypothetical rock site in Perugia, Italy, to select hazard consistent records separately from the RDB and SDB databases. A comprehensive set of comparisons of distributions of several IMs, computed from the selected sets, and of distributions of engineering demand parameters (EDPs), that such record sets induce on simple SDoF structures suggests the adequacy of using the proposed simulated ground motions for structural response analyses of structures on stiff and rock sites.