Ground Motion Record Selection Research Articles

Damage Evaluation and Seismic Assessment of a Typical Historical Unreinforced Masonry Building in the Zagreb 2020 Earthquake: A Case Study—Part I

The city of Zagreb, the national capital and economic hub of Croatia, is situated in a seismically active region and hosts a significant array of historical buildings, from the medieval to Austro-Hungarian periods. These buildings possess varying but generally high degrees of vulnerability to seismic loading. This was highlighted in the Zagreb earthquake of 22 March 2020, emphasizing the need for seismic retrofitting in order to preserve this architectural heritage. In this paper, the seismic capacity of one such unreinforced masonry building is considered through a number of analysis methods, including response spectrum, pushover, and out-of-plane wall failure analyses. Given the advantages and disadvantages of the individual methods, their applicability and value in a seismic analysis is considered. Ambient vibration measurements before and after the Zagreb 2020 earthquake, used for model calibration, are also presented. Conclusions are drawn from each individual analysis and later compared. In conclusion, no single analysis method considers all relevant failure modes, and a combination of nonlinear static or dynamic analysis and out-of-plane analysis is recommended. Due to the large volume of the material, it is published in two parts, with ground motion record selection, dynamic analysis, and a comparison of the results published in part two.

Characteristics and selection of near-fault simulated earthquake ground motions for nonlinear analysis of buildings

Earthquake-induced ground shaking near rupturing faults is highly sensitive to the rupture characteristics, seismic wave propagation patterns and site conditions, and field recordings of near-fault shaking are relatively sparse. These challenges complicate the assessment of the seismic performance of near-fault structures. A common approach to representing near-fault ground motion in engineering analysis is to explicitly consider and select records with strong directivity pulses (pulse records). We use three-dimensional high-resolution physics-based earthquake simulations to test this approach in the context of scenario-based ground motion record selection, and to study the important characteristics of near-fault ground shaking. We highlight the deficiencies associated with classifying near-fault simulated records as “pulse” or “non-pulse,” based on the presence of a single dominating pulse in the velocity time history. We show that this approach is inadequate for characterizing near-fault shaking on soft soils which can be dominated by both forward rupture directivity and basin amplification effects. We conduct ground motion selection experiments for the analysis of near-fault structures with and without explicit classification of the pulse features in the records, and evaluate the bias in the predicted structural demands. We find that the maximum interstory drift demands on building structures imposed by unscaled site-specific simulated ground motion records selected based on relevant spectral shape features are not sensitive to the classification of records as pulse/non-pulse. Therefore, with regard to predicting the maximum interstory drifts in near-fault buildings, we do not find justification for the binary pulse classification of near-fault records.

Optimal Acceleration and Energy-Based Record Selection Using Artificial Intelligence Approaches and NP

ABSTRACT The new trend toward modern earthquake-resistant design of buildings based on nonlinear dynamic analysis accounting for peak and energy demands requires efficient ground motion record selection procedures. For this reason, in the present work, two record selection strategies based on acceleration and input energy spectrum considering the spectral shape via Np are presented. Furthermore, both record selection strategies are optimized by means of four artificial intelligence (AI) techniques: Genetic Algorithms (GA), Harmony Search (HS), Particle Swarm Optimization (PSO) and Vibrating Particle System (VPS). In particular, the effectiveness of each AI approach toward the best set of ground motion records for nonlinear dynamic analysis is compared. For this aim, spectral acceleration and input energy design spectra were considered, as well as 1024 seismic records obtained from the Pacific Earthquake Engineering Research Center. For all the AI or meta-heuristic approaches, the fitness function used is focused on minimizing the difference between the average spectrum of eleven ground motion records and the design spectrum using the well-known parameter Np, which represents the spectral shape in a range of periods. In addition, a penalization is included for those spectra with very large or low demands. Thus, 24 sets of eleven seismic records that can be used for nonlinear dynamic analysis of structures with a fundamental period of vibration of 0.6, 1.2 and 1.8 seconds were obtained and purposes. The results demonstrate the ability of the two records selection strategies analyzed and the four meta-heuristic procedures, achieving results quickly and simply regardless of the type of demands, intensities and periods considered. Finally, it is concluded that the VPS algorithm is better in comparison with GA, HS, and PSO since it obtains superior results in almost all the selected cases.

A closer look at hazard-consistent ground motion record selection for building-specific risk assessment: Effect of soil characteristics and accelerograms’ scaling

Conditional spectrum (CS) record selection is a standard tool for the selection of ground motion recordings consistent with the hazard at a site of interest. For many important applications the seismic hazard is computed for reference rock conditions and the effects of local site conditions are investigated downstream via soil dynamics. Ideally, when selecting for rock conditions, the recordings should be real, recorded on rock sites, and strong enough to push the structure into its severe nonlinear range. However, rock-recorded ground motions are often scarce and the analyst is usually left with the suboptimal option of augmenting the set with scaled motions and motions recorded at soil stations. We investigated how this practice can affect the structural response estimates by means of nonlinear dynamic analyses of a comprehensive set of single-degree-of-freedom (SDOF) systems. We first performed site and structure-specific CS record selection using ground motion databases of only soil-recorded motions versus databases of only rock recorded ones. In addition, we performed the CS based on extreme cases of using ground motions scaled by either only small or only large factors. Our focus was on the statistical comparison of the common intensity measures (IMs) of the selected records and, more importantly, of the structural response estimates when these extreme opposite selection choices are made. We show no significant statistical differences in the distributions of the IMs and structural responses, while the fragility and response hazard remain almost identical, for all practical purposes. These results imply that, as long as hazard consistency is accurately enforced in the ground motion record selection, using CS, selecting soil-recorded motions or record scaled up to 10, will not bias the response estimates. Finally, repeating the above procedure for response prediction of one multiple degrees of freedom (MDOF) system suggests that our conclusions are applicable also to more complex structural systems.

Impact of local site effects on seismic risk assessment of reinforced concrete bridges

In most practical applications of performance-based earthquake engineering, the local site characteristics are considered simplistically, and soil-structure interaction effects are ignored. Within such a conventional approach, the ground motion record selection uses the time-averaged shear-wave velocity in the top 30 m of the soil profile (VS30) as the main proxy to represent the site where the structure is located. This study aims to assess the impact of local site effects on the risk assessment of reinforced concrete (RC) bridges by incorporating the local-site response and soil-structure interaction effects more realistically within a more detailed approach. For this purpose, seismic risk assessment of RC bridge structures with various configurations located on varying site characteristics was carried out using different levels of refinement in the numerical modelling. Local site amplification was incorporated using site response analysis, and p-y models were used to consider foundation flexibility. Cloud analyses were then carried out on both modelling approaches to obtain and compare the corresponding scenario-based seismic loss estimates for the structures. Moreover, the results of numerical analyses were scrutinized in terms of peak demand to capacity ratio values, and statistical hypothesis testing was used to quantify the similarity between the two approaches further. In some cases of site response modeling, especially when the fundamental periods of the bridge structure and site are sufficiently close, higher displacement demands on bridge piers were obtained, likely leading to higher direct seismic losses.

Seismic fragility assessment for a RC building in seismically stable Brazil: A sensitivity analysis

While Brazil is located in a markedly seismically stable region, most buildings are designed with little to no consideration for seismic activity. For this reason, a thorough investigation of building fragility is a requisite for precise risk estimates. However, some constraints currently affect broad seismic fragility assessments in the country, causing inherent uncertainties in different steps of fragility estimation. This paper focuses on comparing how different variables stemming from such uncertainties may affect seismic fragility, in order to evaluate which may be more important for future assessments. Herein, a low-rise, open ground, reinforced concrete building is evaluated, and the following variables’ sensitivity to the fragility response are compared: ground motion record selection; intensity measure (IM) selection; structural model parameter values; failure mode and limit state capacity. A cloud-based approach is used, employing a surrogate demand model for non-collapse data and a Logistic model for the inclusion of collapse data. The sensibility analysis results indicate that, for this assessment, failure mode variability due to detailing practices may cause the largest global impact on fragility variability, with a greater effect on intermediate intensity values. On the other hand, column backbone parameter uncertainty can be the most important factor on some of the smaller intensity values, while record selection influence, conditioned on the number of records used and on IM sufficiency, can have a smaller impact than the other variables.

Multi-functional solution model for spectrum compatible ground motion record selection using stochastic harmony search algorithm

Multi-functional solution model for spectrum compatible ground motion record selection using stochastic harmony search algorithm

A generalized ground-motion model for consistent mainshock–aftershock intensity measures using successive recurrent neural networks

Several recent studies have investigated the risk posed to structures by earthquake sequences, proposing state-dependent fragility/vulnerability models for assets in damaged conditions. However, a critical component for such efforts, i.e., ground-motion record selection, has received relatively minor consideration. Specifically, utilization of “consistent” mainshock (MS)–aftershock (AS) ground motions is desirable in practical applications. Such consistency in selecting MS–AS sequences requires proper consideration of the correlations between and within the intensity measures of MS and AS ground motions. Most of the studies in this domain utilize spectral accelerations as the considered ground-motion intensity measures and rely on empirical linear correlation models between the intensity measures of MS and AS ground motions for developing, for instance, record selection approaches. This study proposes a generalized ground-motion model (GGMM) to estimate consistent 30 × 1 vectors of intensity measures for mainshocks (denoted as IMMS) and aftershocks (denoted as IMAS) using a framework of successive long-short-term-memory (LSTM) recurrent neural network (RNN). The vectors of IMMS and IMAS consist of geometric means of significant duration (D_{5 - 95,geom}), Arias intensity (I_{a,geom}), cumulative absolute velocity (CAV_{geom}), peak ground velocity (PGV_{geom}), peak ground acceleration (PGA_{geom}) and RotD50 spectral acceleration (S_{a} left( T right)) at 25 periods for both MS and AS ground motions. The proposed RNN-based GGMM is trained on a carefully selected set of ~ 700 crustal and subduction recorded MS–AS sequences. The inputs to the framework include a 5 × 1 vector of source and site parameters for MS and AS recordings. The residuals of the trained LSTM-based RNN are further used to develop empirical covariance structures for IMMS and IMAS. The proposed framework is finally illustrated to select MS–AS ground motions based on IMMS and IMAS using a multi-criteria objective function. The selected MS–AS ground motion sequences are then used to perform non-linear time-history analyses of a case-study two-spanned symmetric bridge structure. The obtained engineering demand parameters are evaluated and critically discussed.

HaselREC: an automated open-source ground motion record selection and scaling tool

haselREC: an automated open-source ground motion record selection and scaling tool

Efficient selection of up to three-component ground excitation sets for earthquake engineering applications

Ground motion record selection methodologies are commonly developed to ensure that the input excitation used in response history analyses embodies essential conditions such as spectral compatibility, hazard and intensity measure consistency, seismological and site-specific criteria, always performing in a computationally efficient manner. A methodology utilizing genetic algorithms is revisited here, expanded to select multi-component ground motions and satisfying the typically required selection objectives of earthquake engineering applications, while ensuring increased efficiency. Multi-objective optimization is performed, claimed to be superior in delivering robust results that account for spectral compatibility in first and second order statistics (mean and standard deviation) in a wide range of spectral values, as well as satisfying seismological and site-specific criteria. A unique contribution is the ability to include probability distribution targets in specific ordinates of the spectrum, on top of the mean and standard deviation, allowing for more refined ground motion sets that can be used to reduce the number of records required in response history analyses. Additionally, a novel benchmarking process to assess the efficiency of ground motion record methodologies is introduced here, in terms of providing sets that are globally-optimal solutions to the optimization problem. Through this benchmarking algorithm, the proposed methodology appears to be impeccable in extracting the best possible ground motion sets.

Correlation of spectral acceleration values in Iranian ground motions

Spectrum compatibility is commonly used as a tool for ground motion record selection in order to perform dynamic analysis. Conditional mean spectrum calculation, which can be used as a target spectrum, requires obtaining correlation coefficients between spectral acceleration values at multiple periods. To date, the correlation coefficients have not been evaluated exclusively from ground motions recorded in Iran. This study represents results obtained from the calculation of correlations for spectral acceleration values from Iranian ground motion data and Zagros and Alborz-central Iran seismic regions, separately. The obtained results can be used for conditional mean spectrum calculations at Iranian sites. The observed correlation coefficients for Iranian records are compared to the correlations developed from the Western United States ground motion data. It is seen that correlation coefficients obtained from the Western United States ground motion data are less than the ones calculated in the study and therefore would cause further reducing of the target spectrum of interest.

Application of Conditional Mean Spectrum in the Seismic Assessment of a Braced Frame Steel Structure

Detailed engineering of critical infrastructure and tall buildings require that their response be estimated from nonlinear response history analysis (NLRHA) by subjecting the structure to suites of earthquake accelerograms. Selection of ground motion records due to future earthquake events represents an important step in the robust assessment of structural response. As per the current practice, both site-specific uniform hazard spectrum (UHS) and conditional mean spectrum (CMS) are employed as the target spectra for ground motion record selection. The CMS approach is superior considering that it represents realistic seismic events and also consider the multiple natural periods of the structure. The paper presents the application of conditional mean spectrum in the seismic assessment of an eight-story ordinary braced steel structure built on an example site. The NLRHA was conducted using the ground motions spectrally matched to the CMS at different conditioning periods. It was found that the CMS spectrally matched to larger modal period always result in larger seismic demands. A comparison was also made between seismic demands obtained from UHS & CMS indicating that the structural response parameters are almost the same in both cases except the story shears & drifts which is dominated by UHS in lower floors and by CMS in upper floors.

Mainshock‐consistent ground motion record selection for aftershock sequences

SummaryIn recent years, the additional risk posed to the built environment due to aftershock sequences and triggered events has been brought to attention, and several efforts have been directed towards developing fragility functions for structures in damaged conditions. Despite this rise of interest, a rather fundamental component for such tasks, namely that of aftershock ground motion record selection, has remained under‐scrutinized. Herein, we propose a pragmatic procedure that can be applied for the selection of mainshock‐aftershock ground motion pairs using consistent causal parameters and accounting for the correlation between their spectral accelerations. In addition, a structural analysis strategy that can be employed for the analytical derivation of damage‐dependent fragility functions is outlined and presented through a case study. A more conventional back‐to‐back IDA analysis is also carried out in order to compare the derived damage‐dependent fragility functions with the ones obtained with the proposed procedure. The results indicate that record selection remains a crucial factor even when assessing the structural vulnerability of damaged buildings, and should thus be treated cautiously.

A spectral-acceleration-based combination-type earthquake intensity measure for high-rise stack-like structures

Ground motion intensity measures are of great importance for the seismic design of structures. A well-chosen intensity measure will reduce the detailed ground motion record selection effort for the nonlinear dynamic structural analyses. In this article, a spectral-acceleration-based combination-type earthquake intensity measure is presented. This intensity measure considers the higher modes effect and period elongation effect due to nonlinear deformation at the same time. The modal mass participation factors are determined to take weighting coefficients and the product of elastic first-mode period T1 and a constant C is expressed to represent the elongated period. Therefore, the proposed intensity measure is a combination of earthquake ground motion characteristics, elastic structural responses, higher modes participation, and the period elongation effect due to inelastic structural behaviors. Four three-dimensional models of reinforced concrete stack-like structures including a 240 m-high chimney, a 180 m-high chimney, a 120 m-high chimney, and a 42.3 m-high water tower are established and analyzed in ABAQUS to investigate the correlation between the intensity measure and the maximum curvatures under 44 far-field ground motions and 28 near-fault ground motions with a pulse-like effect. With the optimal vibration modes and the proper period elongation coefficient, the efficiency of the introduced intensity measure is compared with the other 15 intensity measures. The results indicate that the proposed intensity measure is believed to be a good choice for high-rise stack-like structures, especially under the near-fault ground motions with pulse-like effect.

Nationwide Earthquake Risk Model for Wood-Frame Houses in Canada

Quantitative seismic risk assessments involve hazard characterization, exposure database, vulnerability assessment, and uncertainty modelling, and promote consistent risk management actions, when conducted systematically across a country. This study implements a performance-based earthquake engineering methodology to develop a nationwide earthquake risk model for Canadian wood-frame houses by integrating probabilistic seismic hazard analysis results provided by the Geological Survey of Canada and seismic fragility functions derived from incremental dynamic analysis. To facilitate the implementation of the seismic risk analysis method, an in-house probabilistic seismic hazard analysis tool for Canada is developed and used to verify the accuracy of the adopted approach of approximating the upper tail of the seismic intensity measure distribution and to generate detailed seismic disaggregation results for ground motion record selection and seismic fragility modelling purposes. By integrating the preceding two elements via Monte Carlo methods, a full seismic risk curve can be obtained in a computationally efficient manner. The approach is applied to 1,620 representative locations used for the 2016 Canadian Census and thus facilitates the development of seismic risk maps of key risk metrics that are derived from exceedance probability curves in terms of earthquake damage/loss ratio. The developed seismic risk maps serve as valuable decision-support tools to implement risk-based management strategies consistently across Canada.

Ground Motion Record Selection using Multi-objective Optimization Algorithms: A Comparative Study

Performing time history dynamic analysis using site-specific ground motion records according to the increasing interest in the performance-based earthquake engineering has encouraged studies related to site-specific Ground Motion Record (GMR) selection methods. This study addresses a ground motion record selection approach based on three different multi-objective optimization algorithms including Multi-Objective Particle Swarm Optimization (MOPSO), Non-dominated Sorting Genetic Algorithm II (NSGA-II) and Pareto Envelope-based Selection Algorithm II (PESA-II). The method proposed in this paper selects records efficiently by matching dispersion and mean spectrum of the selected record set and target spectrums in a predefined period. Comparison between the results shows that NSGA II performs better than the other algorithms in the case of GMR selection.

Development of Fragility Curves for Existing Residential Steel Buildings with Concentrically Braced Frames

The objective of this study is to develop analytical fragility curves for an ensemble of 3- to 6-story existing residential steel buildings with concentrically braced frames in two directions, designed during 2010 and 2015, and located in Qazvin, Iran. The buildings are modeled three-dimensionally in the OpenSees, considering braces buckling behavior. Maximum interstory drift ratio ( ) and spectral acceleration at fundamental period of the structure with 5% viscous damping ( ) are considered as Damage index ( ) and Intensity measure ( ), respectively. Limit states are specified as discussed in FEMA 356. Ground motion record selection and uncertainties assessment is carried out based on FEMA P695 methodology. Analysis is performed using truncated incremental dynamic analysis ( ). Fragility function is defined as a log-normal cumulative distribution function ( ) and maximum likelihood method is used to estimate fragility parameters. According to the fragility curves obtained, seismic vulnerability of the structures is generally increased as the number of stories rises. Concentration of the inelasticity is also found to be mainly at the first story level. The results also confirm the fact that the record to record variability is the main source of uncertainty in structural probabilistic evaluation.

Nonlinear Static and Dynamic Analyses of RC Buildings

This study aims to compare pushover and nonlinear time history analyses for existing low- and mid-rise RC buildings to better understand the applicability limits, advantages and disadvantages of nonlinear static and dynamic analyses. The 4- and 7-story buildings designed according to the pre-modern and modern Turkish Earthquake Codes represent the existing low- and mid-rise RC buildings based on inventory results of more than 475 real residential buildings located in Turkey. Eight different ground motion records were used during nonlinear time history analyses selected from destructive earthquakes over past several decades. The outcomes show that the displacement demands obtained from time history analyses differ over a wide range of values, emphasizing the importance of ground motion record selection. The pushover analysis may cause underestimation of the maximum interstory drift ratio for the mid-rise buildings. Besides, it definitely misses the beam damages at the first story. In conclusion, the pushover analysis seems to reflect the nonlinear time history analysis confidently at moderate level earthquakes. However, the results start to deviate as the ground motions get stronger. It is hard to specify a single value for the safe use of pushover analysis considering all parameters in the study. The outcomes of the current study indicate that the pushover analysis provides reasonably well estimates up to 1 and 0.75% roof drift ratios which approximately correspond to 1.5 and 1% interstory drift ratios for low- and mid-rise buildings, respectively. Beyond these limits, the pushover analysis may give misleading demand estimates.

A Ground Motion Record Selection Approach Based on Multiobjective Optimization

ABSTRACTThe evaluation of the seismic safety and reliability of buildings and building contents within a probabilistic framework often requires response history analyses using site-specific ground motion records. The ground motion selection method proposed in this paper addresses this issue by a stochastic search procedure in which record sets are selected such that first- and second-order statistics (median and dispersion) satisfy predefined ground motion spectrum targets over a wide period range. Once a ground motion record set is selected, it can be used for seismic assessment of a broad class of buildings within the target period range at the given location.

Reliable seismic collapse assessment of short-period structures using new proxies for ground motion record selection

One of the important steps in seismic collapse assessment of structures by using nonlinear dynamic analyses is the appropriate selection of ground motion records. Epsilon (eSa), eta (η), and gamma (γ) for long-period structures, are proxies that have been recently proposed for Ground Motion Record Selection (GMRS). In this study, two parameters, named γs, are proposed, which have considerable correlation with the collapse capacity of short-period structures having fundamental period less than 1 s. One of these parameters is a linear combination of eSa, epsilon of Pseudo Spectral Acceleration (PSA) at 1.5 times of the fundamental period of the structure (eSa(1.5T1)) and ePGV. The other one is a linear combination of eSa, eSa(1.5T1) and epsilon of spectrum intensity, eSI. To obtain and optimize γs, the Particle Swarm Optimization (PSO) algorithm is applied. Since the parameters proposed as γs have significant correlation with the collapse capacity of short-period structures, they can be used as efficient proxies for GMRS in seismic collapse assessment of short-period structures. The results show that GMRS using γs leads to reduction in the dispersion of structural collapse capacity in comparison with GMRS based on eSa or η.