Mohsen Kohrangi

This study presents and validates the 3D physics-based numerical simulation of the 2023 Mw 7.8 Kahramanmaraş earthquake, which caused widespread damage and thousands of fatalities across a vast region spanning Türkiye and Syria. A 325 × 355 km numerical domain was set up to include models of the causative fault of the Mw 7.8 event and a crustal velocity profile of the area. Different published kinematic rupture models were tested, with the final selection based on the evaluation of the model performance to fit the recorded ground motions. Results of the numerical simulations, performed through the spectral element code SPectral Elements in Elastodynamics with Discontinuous Galerkin (SPEED) up to a maximum frequency of 1 Hz, are enriched in the high-frequency range employing a technique based on artificial neural networks (ANN2BB) to produce broadband ground motions of practical interest for engineering applications. Simulated ground motions were validated in time and frequency domains, and across multiple intensity measures (IMs) using various techniques. The performance of simulated ground motions is tested against specific complex phenomena of the event, including directivity, directionality, and basin effects. Although some discrepancies remain due to model simplifications and uncertainties, results show good agreement with recordings, most IMs achieving “good to excellent” fit, as measured using quantitative goodness-of-fit criteria, and median normalized residuals generally below ±0.30. The study demonstrates that a 3D physics-based simulation framework can effectively characterize the main properties of ground shaking in large magnitude events with major uncertainties, which is particularly important in regions with sparse seismic instrumentation. However, this exercise has proven that a full reproduction of complex characteristics of large-magnitude events using a simplified and computationally feasible model poses various challenges.

Seismic resilience is assessed for a hydrodesulphurization unit of a midsize crude oil refinery, with a focus on both direct physical damage and indirect business interruption (BI) losses. The aim is to develop a rigorous analytical methodology for assessing interconnected crude oil refinery units via tailored risk metrics. This study focuses exclusively on earthquake‐induced direct and indirect economic losses, whereas material release and its potential consequences, including damage propagation (e.g., domino effects), will be addressed in a dedicated study. First, the structural performance of the constituent assets is evaluated by means of multiple‐stripe analysis using hazard‐consistent ground motions. Detailed asset‐level damages are evaluated, followed by a repair workflow to enable a comprehensive quantification of recovery and economic impact. As even moderate damage to supporting systems, such as piping or instrumentation, can lead to prolonged downtime, direct physical damage accounts for only 1.2% of the total average annual loss (AAL), while BI indirect losses account for the remaining 98.8%. In this, modelling and analysis choices can be key: (i) the granularity of risk assessment (record‐based vs. fragility‐based), (ii) capacity correlation among identical assets, and (iii) operational conditions in terms of tank fill levels. While the coarse fragility‐based approach yields similar AALs compared to the detailed record‐based approach when hazard consistency is maintained, assumptions about capacity correlation and, more significantly, operational conditions have a substantial impact on risk estimates. Findings emphasize the need to prioritize continuity strategies, for example, redundancy and rapid restart, over asset hardening alone.

Seismologists traditionally define the usable bandwidth of ground motion records based on signal‐processing principles that ensure acceptable signal‐to‐noise ratios. Engineers rely on these records to assess the responses of structures whose fundamental periods, T , fall within the bandwidth. The upper bound of this interval, T _UP , depends on the long‐period cut‐off of the filter applied to the accelerograms, T _C . This study examines whether, and to what extent, ground motion filtering may lead to underestimating the response of systems with T  ≤ T _UP , especially for structures experiencing period elongation in the post‐elastic range. If a systematic bias exists, current T _UP values may be overly permissive. To address this concern, we computed benchmark responses for single‐degree‐of‐freedom (SDOF) systems with varying T to several high‐quality records processed with very long cut‐off periods. These ground motions were then incrementally filtered, and the SDOF systems’ responses reassessed. By systematically comparing the benchmark response estimates with those obtained from the degraded records, we identified an engineering‐based upper bound period of the usable bandwidth of given ground motions, T _UP‐ENG . This threshold is such that the response bias of a structure with T  ≤ T _UP‐ENG remains below a predefined tolerance with certain statistical confidence, and varies based on whether the record is used for linear or nonlinear analyses of brittle or ductile structures. Our findings show that traditional T _UP estimates are generally unconservative, i.e., T _UP‐ENG ≤ T _UP , even for elastic analyses. This discrepancy becomes critical when predicting severe inelastic responses of systems with T near T _UP , since the underestimation could be significant. To preserve structural response fidelity, we recommend adopting the application‐specific engineering‐based definition of the upper bound of the usable bandwidth of ground motions, which is more restrictive than the commonly accepted signal‐processing‐based single value.

This study presents a methodology to optimize the analytical derivation of seismic fragility curves of structures located at a given site. Hazard-consistent ground motions in a Multiple Stripe Analysis (MSA) framework are used for this task. The approach aims to reduce the high computational cost typically associated with conducting numerous nonlinear dynamic analyses especially on complex structural models, without compromising the accuracy of the results. The process begins by initializing the fragility parameters’ values from simplified analyses, which are then iteratively updated through a Bayesian approach that incorporates Markov Chain Monte Carlo and Metropolis–Hasting sampling, thereby drastically reducing the number of required analyses. Validation on both SDOF and MDOF structures across various damage states demonstrated convergence to benchmark results within a few iterations. An automated stopping criterion, based on prior and posterior comparison of the fragility parameters’ values, enhances the efficiency of the method. Sensitivity analysis shows that a smaller number of stripes each with fewer records than those utilized in conventional methods can yield stable results, significantly reducing computational demands. In addition, a user-friendly Python tool is provided to facilitate both the reproducibility of the presented results and the application of the proposed method to real-life cases.

The objective of this study is to investigate whether the additional damage to building components caused by vertical ground shaking and its impact on estimated monetary losses warrants the extra computational effort needed to include this feature for standard risk assessment applications. As a case study, we consider a 2D model of a modern nine‐story steel frame building located at a high seismic hazard site in California. The structural and nonstructural demands are assessed via nonlinear dynamic analysis carried out using hazard‐consistent bi‐directional (horizontal & vertical) ground motion records. We estimated the seismic losses with and without the vertical ground motion using a component‐based loss estimation approach based on FEMA‐P58. We also explored the sensitivity of the loss estimates to the characteristics of the input vertical acceleration fragility curves. Analysis results indicate a modest increase in the average annual losses (AAL) when the vertical component is included, consistent with the relatively small fraction of the total building replacement cost assigned to components sensitive to vertical motion. We also investigate the sensitivity of the loss estimates to the conditioning ground motion intensity measure adopted in the risk assessment procedure. Considerable discrepancies are observed in the loss estimates on an intensity basis and, to a lesser degree, on a risk basis. Among the tested intensity measures, average spectral acceleration performs better than single‐period spectral accelerations in two regards: it provides higher efficiency, and it maintains good consistency of the selected records with the site hazard while using lower levels of ground motion amplitude scaling. Whereas single‐period spectral ordinates that will approximate these advantages may exist, finding them requires some investigation.

Considering earthquake sequences in seismic hazard and risk analyses has become increasingly important. Many sequences around the world demonstrated that limiting the consideration to only mainshocks leads to underestimation of hazard and, more importantly, risk. Among the methods to simulate earthquake sequences, the epidemic-type aftershock sequence (ETAS) model has shown notable accuracy in representing these complex sequences making it a valuable tool for seismic hazard and risk assessment. However, the ETAS model is rather complex and for regional applications it requires many parameters to be calibrated. The calibration is most effective when a long instrumental catalog complete to low-magnitude events is available. However, this is rarely the case. Our study investigates the possibility of using the ETAS model with parameter values calibrated for a region with many recent sequences (namely central Italy) to simulate realistic sequences in two other crustal seismicity regions, namely Türkiye and Croatia. We compare three options (1) using a set of ETAS parameters calibrated based on local data, (2) fixing most ETAS parameters to values derived from a well-studied region with many recent sequences (central Italy) while locally calibrating the total background rate and productivity term (SimplETAS [SE] parameter set, akin to the simplETAS methodology of Mancini and Marzocchi (2023), and (3) fixing all ETAS parameters to values from central Italy except for the total background rate (Set of Central Italy [SCI] parameter set). The results show that simplified approaches based on central Italy data (SE and SCI) can produce simulated earthquake sequences that align well with the observed data even for Croatia and Türkiye. This reflects the applicability of modeling earthquake sequences for hazard and risk applications in many crustal regions where good quality observed instrumental catalogs complete to low-magnitude events are not available or they are available but do not contain significant sequences.

Unreinforced masonry (URM) buildings are highly susceptible to cumulative damage, as demonstrated by the damage observations collected during and after numerous earthquake sequences. However, most previous numerical studies assessing cumulative damage in URM buildings have failed to fully capture the extent of the phenomenon observed in real events. This article aims to address this gap by applying a newly developed methodology for modeling the accumulation of damage in URM buildings in risk assessment case studies. This methodology quantifies the cumulative damage using an energy‐ and displacement‐based damage index (DI) within a component‐based framework. The methodology is validated using data from the URM school building in Visso that sustained severe, progressive damage during the 2016 Central Italy earthquake sequence. Additionally, this DI is employed to develop hazard‐consistent, damage‐state‐dependent fragility curves for five case‐study URM buildings through consecutive nonlinear dynamic analyses. The fragility analysis results align with real‐world observations, indicating a significant reduction in structural capacity due to cumulative damage. These set of fragility curves are then utilized in a risk assessment exercise. The last part of this study compares the impact on risk estimates when incorporating damage accumulation and earthquake sequences using the proposed methodology versus the conventional approach, which assumes only independent mainshocks affecting buildings in their intact state. The results reveal that the conventional approach underestimates the average annual losses for these five URM buildings in Central Italy by 45%–85%. Although the level of underestimation may vary for other URM buildings in other regions, it is undeniable that the conventional approach consistently underestimates the risk for URM structures by a significant margin.

A fully probabilistic earthquake risk model was developed for five countries in Central Asia, providing updated earthquake loss estimates with a higher level of detail on all components with respect to previous studies in the region. Additionally, a regionally consistent approach that, on the one hand, allows for direct comparisons at different disaggregation levels (e.g., country and oblast) was used. On the other hand, this updated earthquake risk assessment aims to facilitate initiating a policy dialogue regarding national and regional disaster risk financing and insurance applications. This earthquake risk model made use of a regional probabilistic seismic hazard analysis and a comprehensive exposure database on which different types of assets and sectors were included and for which two scenarios (the years 2020 and 2080) were modeled. For each type of asset, a unique vulnerability function was derived and later used for convolution with the hazard data, which allowed for the estimation of the loss exceedance curve, at different disaggregation levels, from where other risk metrics such as the average annual loss (AAL) and specific return period losses were obtained. The regional earthquake AAL for the five countries and for the 2020 exposure scenario has been estimated to be around USD 2 billion, with the Kyrgyz Republic and Tajikistan being the countries with the highest earthquake risk levels in the region. Besides the probabilistic earthquake risk results, as-if scenarios were modeled using a pseudo-deterministic approach to assess the human and economic losses for realistic and representative earthquakes for the main cities within earthquake-prone regions in the five countries of the study area.