Probability Of Damage Research Articles

Impact of the structural system type on the seismic fragility of a multi-tower cable-stayed bridge

The present study investigates the seismic fragility of a six-tower cable-stayed bridge and delves into the influence of different structural system types on this bridge. SeismoStruct software is applied to establish the numerical model of a six-tower cable-stayed bridge, and its accuracy is verified through a shaking table test. Then, the seismic fragility curves of this bridge are generated through incremental dynamic analysis to assess its seismic performance under longitudinal earthquakes. Then, the impact of the different structural system types (the number of towers and the girder–pier connection form in the longitudinal direction) on the seismic fragility of the cable-stayed bridge is analysed. The results show that the fixed bearing is the most vulnerable component, and the middle pier is greatly threatened by earthquakes. With the decrease in the number of towers, there is a slight impact on the seismic fragility of the fixed bearing, and the middle pier is no longer the most vulnerable bridge pier. Moreover, the damage sequence of different components in the six-tower cable-stayed bridge is changed in the longitudinal consolidated structural system. The damage probability of the transition and the side piers is greater than that of the middle pier.

Experimental and numerical simulation of seismic behavior of reinforced concrete frames infilled with refractory straw blocks

Recent earthquakes have highlighted the vulnerability of infilled reinforced concrete structures due to the insufficient consideration of infill masonry walls' contribution to strength and stiffness. This study presents a novel refractory straw block (RSB) designed to address these challenges and improve the seismic performance of reinforced concrete (RC) frames. Unlike traditional infills, RSB is characterized by low-elastic-modulus, low-density, and high-ductility. Quasi-static tests were performed on three types of frames: unfilled, infilled hollow grouted bricks (HGB), and infilled RSBs. Failure model, stiffness, and load-displacement response of three specimens were investigated and analyzed. The results indicate that RSBs as infill material does not alter the failure mode and constitutive relationship of bare frame, while HGBs leads to shear failure. The peak load for the specimen IF-HGB was 69.3 kN at 1.1 % drift, compared to 38.8 kN at 2.4 % drift for the specimen IF-RSB, and 36.4 kN at 2.0 % drift for the specimen BF. The strengths of specimens IF-HGB and IF-RSB were 1.90 and 1.07 times that of specimen BF, respectively. The stiffness of specimen IF-HGB was 3.7 times that of the other specimens, but its allowable displacement was only 61 % of theirs. Dynamic time-history analyses were also performed on structures with no longitudinal infill (BF), with RSBs (SBF), and with fired bricks (FBF). At the design level of rare events (magnitude 8, PGA 400 gal), severe damage occurred, but collapse was limited. When the PGA increased further, the collapse probability of model FBF rose rapidly, whereas the collapse probabilities of models SBF and BF remained low and similar. Accounting for the confining effect of walls, model FBF showed a higher probability of severe damage than models SBF and BF, particularly under minor earthquakes. The maximum inter-storey drift ratio of the model SBF and FBF were respectively 1.2 times and 1.7 times that of the model BF, which shows that straw blocks as infill can greatly avoid the effect of infill on the seismic behavior of the structure. The study also emphasized the often-overlooked confining effect of masonry on columns, which can lead to unrealistic damage assessments and seismic shear force distributions.

Numerical Analysis of the Cell Droplet Loading Process in Cell Printing

Cell printing is a promising technology in tissue engineering, with which the complex three-dimensional tissue constructs can be formed by sequentially printing the cells layer by layer. Though some cell printing experiments with commercial inkjet printers show the possibility of this idea, there are some problems, such as cell damage due the mechanical impact during cell direct writing, which include two processes of cell ejection and cell landing. Cell damage observed during the bioprinting process is often simply attributed to interactions between cells and substrate. However, in reality, cell damage can also arise from complex mechanical effects caused by collisions between cell droplets during continuous printing processes. The objective of this research is to numerically simulate the collision effects between continuously printed cell droplets within the bioprinting process, with a particular focus on analyzing the consequent cell droplet deformation and stress distribution. The influence of gravity force was ignored, cell droplet landing was divided into four phases, the first phase is cell droplet free falling at a certain velocity; the second phase is the collision between the descending cell droplet and the pre-existing cell droplets that have been previously printed onto the substrate. This collision results in significant deformation of the cell membranes of both cell droplets in contact; the third phase is the cell droplet hitting a rigid body substrate; the fourth phase is the cell droplet being bounced. We conducted a qualitative analysis of the stress and strain of cell droplets during the cell printing process to evaluate the influence of different parameters on the printing effect. The results indicate that an increase in jet velocity leads to an increase in stress on cell droplets, thereby increasing the probability of cell damage. Adding cell droplet layers on the substrate can effectively reduce the impact force caused by collisions. Smaller droplets are more susceptible to rupture at higher velocities. These findings provide a scientific basis for optimizing cell printing parameters.

Transfer learning for probabilistic localization of hidden cracks in concrete structures

AbstractThe utility of discriminative supervised learning models built using multiple training-data sources is investigated for hidden crack localization in concrete. Feed-forward neural network (FFNN) is chosen as the model architecture, and transfer learning is used to assimilate the information obtained from different sources (computational physics simulations and laboratory experiments). The labeled training data consists of values of a damage index and the known locations of hidden cracks. The classification models need to learn how the presence of damage (hidden cracks) affects the damage index at different sensors for different test conditions. To this end, diagnostic FFNN models are built by sequentially adding and training new hidden layers to assimilate labeled information from computer models (different model geometries, test conditions, crack lengths, crack locations) and laboratory experiments on a plain cement slab. These transfer learning-based models are then used to localize damage in concrete specimens that reflect real-world conditions (i.e., specimens with steel reinforcement and randomly distributed aggregate). The actual damage state in these specimens is determined by extracting cores and performing petrographic studies on the extracted cores. The damage probability estimated by transfer learning-based models is compared with the petrographic damage rating index (DRI) to identify the most suitable approach to train the diagnostic models. The transfer learning-based diagnostic methodology shows promise and could be used in various structural health monitoring applications, where sufficient labeled data are typically not available from a single data source.

Bidirectional seismic fragility analysis of double-deck viaduct frame piers based on stripe-cloud method

To evaluate the influence of bidirectional seismic action on the seismic fragility of double-deck viaduct fram pier (DVFP), this study employs a vector-valued intensity measure (IM) [PGA, Sa (T1, 5 %)], in tandem with the stripe-cloud method. The study compares the median values of Sa and the damage probability difference index (DI) to analyze the fragility of DVFP under both unidirectional and bidirectional seismic actions. Additionally, this research investigates the sensitivity of bidirectional seismic fragility of DVFP to the incidence angles. The results indicate a notable decrease in the median Sa values for DVFP are observed under bidirectional seismic action, with decreases of 28.6 %, 24.3 %, 20.9 %, and 18.8 % corresponding to four damage states, as compared to those under unidirectional seismic action, and the corresponding parameter DIs are measured at 0.122, 0.182, 0.245, and 0.291, respectively. Notably, the most severe damage to DVFP occurs when the bidirectional seismic incidence angle is within the range of 120–135°. At this angle, the median Sa values at four damage states are 85.8 %, 86.1 %, 87.6 %, and 88.6 %, respectively, compared to the angle of 0°. Therefore, neglecting the influence of bidirectional seismic incidence angles may lead to an underestimation of the bidirectional seismic fragility of DVFP.

Shifts in geographic vulnerability of US corn crops under different climate change scenarios: corn flea beetle (Chaetocnema pulicaria) and Stewart’s Wilt (Pantoea stewartii) bacterium

Abstract Changing climate patterns will likely affect insect pressure on many agricultural crops. Mild winters may decrease the number of insects that experience reduced fecundity or that are killed during hard freezes. This may result in larger populations in subsequent years and allow for range expansion. Direct effects from pests are compounded by indirect effects, such as crop damage resulting from insect-vectored diseases. Corn flea beetle (Chaetocnema pulicaria) infestations have both direct and indirect effects on crops. This beetle is a pest on all types of corn in the United States, including sweet corn and grain corn (sometimes referred to as dent corn). It is responsible for damage to plant foliage and also serves as the primary overwintering vector for Pantoea stewartii bacterium, which causes Stewart’s Wilt, a disease that can severely impact the health and productivity of corn. Evidence suggests that warmer winters will contribute to a geographic range expansion for the corn flea beetle. Here we show the projected northward expansion of economically damaging crop losses caused by Stewart’s Wilt: (A) from 1980 to 2011, (B) projected by mid-century, and (C) projected by end-century. Our work suggests that climate change and associated increasing winter temperatures in the United States will lead to a dramatic increase in the probability of severe damage from corn flea beetle across the United States, including the Corn Belt. Predicted increases in pest and disease pressure will have negative ramifications for corn production and are likely to exacerbate issues associated with specific management tactics, such as pesticide application.

Design of Bayesian evaluation test for missile damage effectiveness based on multiple damage level standards

The qualified missile damage effectiveness is an important guarantee for giving full play to combat effectiveness. In order to test whether the missile damage effectiveness meets the standard, it is particularly necessary to carry out damage effectiveness identification test research. In view of the limitation that the existing "single-shot damage probability" damage effectiveness quantitative characterization index is difficult to fully describe the missile damage effectiveness based on a single damage standard, considering the different damage level results formed by a single missile hitting the target, the damage effectiveness is characterized by the probability of occurrence of different damage level results. Missile identification from the perspective of multiple damage level standards is conducive to comprehensive inspection of missile damage effectiveness. In addition, in order to overcome the problem of insufficient information in small sample missile assembly tests, the Bayesian method is combined with the system contribution degree to fuse multi-source prior information in the identification test design, and a test scheme with full information utilization and controllable risks for both parties is designed. The example shows that compared with the quantitative characterization index of a single damage standard, this study can fully describe the missile damage effectiveness, and compared with the improved binomial distribution hypothesis test method, the superiority of this method is verified.

Detection and Prediction of Probe Mark Damage in Wafer Testing

In wafer testing, the test probe needs to contact the surface of the semiconductor wafer to measure electrical parameters such as resistance, capacitance, and current. The probe mark damage frequently occurs on the machine during wafer testing. This phenomenon causes inaccuracies in electrical parameter testing, significantly reducing the yield in IC packaging processes and resulting in substantial manufacturing cost losses. Therefore, this study proposed an effective probe mark damage detection and prediction method to prevent significant yield reduction due to inaccurate testing. This study uses importance analysis from random forests and correlation analysis to identify the critical parameters influencing probe mark damage. Introducing these parameters into a Sparse Transformer with hybrid normalization can successfully train an intelligent model for predicting the occurrence of probe mark damage. The model accurately predicts the probability of probe mark damage and promptly adjusts machine parameters to avoid inaccuracies in electrical parameter settings. The proposed approach can outperform other methods, achieving two very high accuracies of 95.1% (at room temperature) and 93.5% (at high temperature) and significantly reducing the occurrence of large-area probe mark damage.

Lamb Wave Probabilistic Damage Identification Based on the Exchanging-Element Time-Reversal Method.

The commonly used baseline-free Lamb wave damage identification methods often require a large amount of sensor data to eliminate the dependence on baseline signals. To improve the efficiency of damage localization, this paper proposes a new Lamb wave damage location method, namely the probabilistic exchanging-element time-reversal method (PEX-TRM), which is based on the exchanging-element time-reversal method (EX-TRM) and the probabilistic damage identification method. In this method, the influence of the damage wave packet migration on the correlation coefficient between the reconstructed signals of each sensing path and the initial excitation signal is analyzed, and the structure is divided into multiple regional units corresponding to the damage to locate damage. In addition, the influence of the number of sensing paths on the location accuracy is also analyzed. A method of damage probability imaging based on structural symmetry is proposed to enhance location accuracy in the case of sparse sensing paths. The experimental and simulation results verify that the method can achieve damage location with fewer excitation times. Moreover, this method can avoid the problem that the damage wave packet is difficult to extract, improve the efficiency of damage location, and promote the engineering application of the Lamb wave damage location method.

Study on the Susceptibility of Steel Arches with Letting Pressure Nodes Based on Incremental Dynamic Analysis

When soft rock tunnels pass through fractured fault zones, they are particularly susceptible to extrusion and large-scale deformations, especially during seismic events. To address these challenges, this study introduces an innovative yield-support steel arch design featuring a circumferential letting pressure node at its core. This design delivers incremental support resistance within the deformation zone and a susceptibility curve is applied to evaluate the damage probability of the steel arch with a letting pressure node under seismic loading conditions. Measurements of the surrounding rock pressure and structural forces on the steel arch with the letting pressure node were conducted at the Baoshan Jewel Mountain Tunnel in China. The field experiment results revealed a 23% reduction in the surrounding rock pressure and an 11% decrease in the internal forces of the support structure. These findings demonstrate the successful application of the letting pressure node-supported steel arch in mitigating large deformations in soft rock environments. Additionally, using finite element software ANSYS 2022, a seismic time-history analysis was conducted, employing the relative deformation rate of the letting pressure node steel arch as the damage index and the peak ground acceleration (PGA) as the strength parameter to generate the incremental dynamic analysis (IDA) curve. According to the susceptibility curve derived from the incremental dynamic analysis, at the design ground motion level of 8 degrees, the letting pressure node steel arch has a 94% probability of exceeding its normal service life limit and experiencing damage. The findings of this study offer a novel approach to addressing large deformations in soft rock tunnels. The proposed susceptibility curves for steel arches with letting pressure nodes provide a robust foundation for predicting the damage probability of yielding support structures under seismic conditions.

Turning waste concrete powder into high calcium alkali-activated cementitious materials and artificial aggregates

In order to handle the environmental pollution caused by waste concrete powder, recycled concrete powder (RCP) is utilized to prepare high calcium alkali-activated cementitious materials and artificial aggregates. This study first investigates the high calcium alkali-activated cementitious materials, exploring the effects of different mineral admixtures, liquid-to-solid ratios (L/S), RCP/slag, Na2SiO3 modulus, and Na2O content. The results illustrate that slag powder is the best mineral admixture and the most critical factor affecting cementitious materials. Increasing the slag dosage enhances the generation of C-(A)-S-H, improves the microstructure, and increases compressive strength, with a maximum compressive strength reaching 68.42 MPa. According to these test results, the impact of various factors on RCP aggregates is further explored. The results illustrate that the L/S and slag content are primary factors influencing particle size distribution and strength. Increasing these factors leads to larger aggregate particle sizes and higher strength. The compressive strength of the aggregates at 7d reaches 93.24–-99.5 % of that at 28d, with a maximum strength of 8.2 MPa. Additionally, slag content (10–30 %) and Na2O content significantly impact the physical properties of aggregates, improving apparent density and bulk density while reducing water absorption. To verify the applicability of RCP aggregates, they were used in concrete, and the effects of aggregate strength and replacement rate on concrete performance were explored. The results display that as aggregate strength rises, the mechanical properties of the concrete improve. When RCP aggregates are incorporated, the mechanical properties of the natural concrete decline only slightly (<16.70 %). The probability of aggregate damage increases with decreased RCP aggregate strength or increased RCP aggregate content under pressure. RCP aggregate concrete exhibits better shrinkage resistance compared to natural concrete. The process of utilizing RCP is low-energy, non-polluting, and results in high-performance products, making the large-scale effective utilization of RCP feasible.

Structural and non-structural fragility curves for low-rise mainshock-damaged buildings subjected to aftershocks

The seismic response of mainshock-damaged buildings under aftershocks is an important topic in terms of the lateral response of damaged structures. The majority of current seismic design standards just consider a single earthquake (mainshock/design earthquake) and they don’t take into account the influence of aftershocks on the seismic design process. The aftershocks could have significant effects on the seismic response of mainshock-damaged structures. This situation was reported in some of the previous earthquake events in which the aftershocks caused additional damage to the structures. In this study, the fragility curves for structural and non-structural Drift-Sensitive Components (DSCs) and Acceleration-Sensitive Components (ASCs) of two low-rise mainshock-damaged moment resisting steel and reinforcement concrete buildings under the effect of aftershocks with different intensities were presented. The intensity of the mainshocks was adjusted until the intact buildings experienced three levels of damage states including slight, moderate and extensive damage states. After that, the fragility curve of the structural and non-structural components of the mainshock-damaged buildings under the effect of aftershocks was evaluated by the Incremental Dynamic Analysis (IDA). The results show that the effect of aftershocks on the probability of damage to structural and non-structural components of mainshock-damaged structures is related to the level of the initial damage. For slightly and moderately mainshock-damaged buildings, the probability of exceedance of the damage under aftershocks is relatively similar to the intact buildings, however, the aftershocks significantly increase the probability of damage to the extensively mainshock-damaged buildings. Although extensive initial damage causes a significant increase in the probability of damage to non-structural DSCs, the damage probability of non-structural ASCs remains relatively as similar to intact buildings. Regarding the HAZUS manual, the results show that the probability of damage exceedance of the structural components is higher than non-structural ASCs, however, the opposite observation was reported from the previous earthquakes. Therefore, in this study, four levels of damage threshold for non-structural ASCs are proposed.

Оценка потенциального ущерба почвам от аварийных разливов нефти и нефтепродуктов на территории Арктического региона

The intensification of economic activities by oil and gas companies in the Arctic has significantly increased the risk of environmental damage, necessitating compensation for potential harm caused by these businesses. A major risk factor in this context is accidental oil spills, which are particularly challenging to predict, thereby complicating the assessment of their consequences and the development of preventive measures. The most advanced forecasting methods rely on probabilistic assessments of spill risk factors, which require special field studies and statistical data. This research considers the key approaches to the economic assessment of environmental damage, emphasizing the need to consider the unique characteristics of the Arctic.The goal of the study is to estimate the most probable soil damage from accidental oil spills using a simulation model. It will be especially relevant for territories where the area affected by accidental oil spills is considerable or has increased significantly over the past few years, according to available statistical data. In the Arctic, the Usinsky District of the Komi Republic is one such region. Using the case of this district, an assessment of potential damage is conducted for three scenarios with varying levels of pollution. The results enable an evaluation of potential damage, providing different values corresponding to multiple scenarios with distinct probabilities. The findings can inform oil and gas companies in developing preventive measures and assist regulatory authorities in determining appropriate environmental reparations from companies.

Fragility curves of a slender structure fitted with tuned mass dampers subjected to turbulent wind and seismic loading

In the context of structural performance assessment, several studies have employed fragility curves and surfaces to evaluate the damage probability for predefined intensity levels of a single or multiple hazards. Further, some of these studies have considered the use of tuned mass dampers (TMDs) to reduce the response of structures under wind or seismic loading. In this work, fragility curves and surfaces of a slender structure fitted with TMDs subjected to turbulent wind and seismic loading alone and simultaneously are developed. For the numerical analyses, simulated records for wind and earthquake ground motion are considered. For the development of fragility curves and surfaces, three damage states that include local and global behavior of the structure are considered. The analysis results indicate that, for the structure considered, higher probability of damage is found from wind action than from earthquake, and that an important reliability enhancement is achieved with the use of TMDs.

Hybrid Bayesian-Copula-based damage probability estimation for steel-concrete composite tall buildings under concurrent seismic and wind loads

Hybrid Bayesian-Copula-based damage probability estimation for steel-concrete composite tall buildings under concurrent seismic and wind loads

Quantitative method for the probability of structural damage based on moment theory

In the context of uncertainty in the inverse problem of damage identification, this study proposes a moment theory based probabilistic damage identification (MbPDI) method. Noise errors in the identification process are treated as uncertain parameters, while structural stiffness parameters are treated as functions of noise errors. A limit state function for damage identification is defined, and its probability is computed. Utilizing the concept of moment theory, the expansion series is performed for the limit state function around the most probable point of failure, with gradient information derived using sensitivity matrices. Based on the gradient information and uncertainty inputs, damage probabilities for various elements can be obtained. Additionally, this paper addresses the calculation of structural damage probabilities under the non-normal distribution of random variables by transforming non-normal variables into equivalent normal variables. The proposed probability index and expected index of structural damage in the probabilistic damage identification method has a clear physical meaning, and the calculation has high accuracy. The proposed method is validated through a mathematical example and a numerical simulation. Meanwhile, the influence of damage extent, noise level, and modal order on identification results are analyzed. Experimental validation of the method is also presented.

Seismic risk assessment of partially self-centering braced frames designed with multiple-objective-based method

Partially self-centering building structures are promising seismic resilient systems by balancing the reduction of residual deformations, nonstructural loss, and initial construction costs. This research seeks to establish a multiple-objective-design (MOD) approach for partially self-centering buckling restrained braced frames (PSBRBFs) and explore the risks associated with collapse, demolition, and nonstructural damage in PSBRBFs designed using the MOD approach. The peak displacement is set as an objective for achieving the desired collapse-prevention performance while the residual displacement is set as another objective to ensure the expected post-earthquake repairability. To this end, the step-by-step procedures of the MOD method are introduced based on the prediction models of peak and residual displacements of PSBRBFs. 6 building cases are designed with the MOD method. The dynamic results demonstrate that analyzed PSBRBFs can simultaneously achieve the targeted peak and residual displacements, validating the effectiveness of the MOD method. Seismic fragility assessments are conducted utilizing incremental dynamic analyses (IDAs) to investigate the influence of different performance objectives (i.e., different target peak and residual displacements) on the collapse, demolition, and nonstructural damage probabilities of PSBRBFs. And seismic risks of the designed PSBRBFs are investigated with the consideration of earthquake hazard risks. Results indicate that the demolition risks of the designed PSBRBFs are all larger than the corresponding collapse risks. Based on the analysis results, high PID and low RID design targets were recommended for practical applications to achieve excellent performance against demolition and comparable performance in avoiding collapse and nonstructural damage.

Hail hazard modeling with uncertainty analysis and roof damage estimation of residential buildings in North America

This research presents a statistical approach for hail risk modeling that incorporates the uncertainties of hail model prediction to provide insight into assessing the roof damage of a residential house in hail events. By quantifying the inherent uncertainties in evaluating hailstorm characteristics, this study extends the current existing hail models. The hail data are sourced from the Community Collaborative Rain, Hail and Snow Network (CoCoRaHS) in the U.S. In the modeling process, the largest hail diameter reported in the CoCoRaHS database serves as a primary input variable to estimate the number of observations for the largest hail diameter, hailstorm duration, and hit rate. The assessment of hail risk in this study focuses on the probability of hail damage and resultant repair costs for five types of roofs in North America (unrated roof and impact-resistant roofs with UL 2218 rating classes 1 to 4). The probability of hail damage is calculated as the failure probability by integrating all individual hailstone hits having variable diameters during a hailstorm with fragility curves, which estimate the probability that hailstones will fracture asphalt shingles (allowing water infiltration) or that they dislodge enough granules to cause visible damage requiring replacement for aesthetic reasons. The results reveal that an impact-resistant roof (impact-resistant rating classes 1 to 4) is associated with lower hail risks, with 60 % to 98 % reduction on average compared to unrated roofs. This study provides a comprehensive uncertainty modeling approach for hail hazard and risk, enabling better-informed decision-making and risk management strategies.

Life-Cycle Cost Assessment of the Base-Isolated-Reinforced Concrete Structure

Seismic isolation structures have excellent seismic mitigation effects, but implementing isolation measures may increase the initial cost of the structure. This paper presents a method to calculate the seismic loss and assess the life-cycle cost of isolated structures, which is convenient for owners to make decisions. The life-cycle cost assessment model is divided into two parts: initial cost assessment and seismic loss assessment over life-cycle period. Among them, the assessment method of the isolation layer is proposed, including the cost assessment of isolation bearings and dampers. The assessment method of seismic loss considers direct loss, indirect loss, casualties and integrating casualties into a unified assessment system. Direct loss includes building loss, indirect loss includes rental loss, relocation loss, income loss, personal property loss and business inventory loss. The seismic loss model is associated with seismic damage probability, which is obtained through seismic vulnerability and seismic probability risk assessment. The 8-story base-isolated-reinforced concrete structure illustrates the feasibility of the life-cycle-cost assessment model. The example shows that the initial cost of the isolated structure exceeds that of the nonisolated structure, however, the rental loss, income loss, personal property loss and casualties are much lower than those of nonisolated structures. The income loss of the isolated structure is the maximum proportion in life-cycle cost, and the casualty loss is the minimum proportion in the seismic loss, due to its excellent seismic mitigation effects.

Operational status effect on the seismic risk assessment of oil refineries

The operational status of an oil refinery (type and scale of operations that take place at any time instance) largely determines the amount of fuel produced, circulated within the facility, and stored in tanks. This status is affected by seasonality, periods of peak or low demand, as well as periods of routine maintenance. However, it is an aspect that is typically neglected even though it stands out among the factors that determine the seismic performance of several critical industrial assets, such as the storage tanks, as well as the consequences of any potential failure. An open-source refinery testbed is employed herein to demonstrate the effect of the refinery's operational status on the seismic risk estimates. Alternative realistic operational scenarios are developed following typical industry practices and are arranged over a time period between two refinery major maintenance shutdown events. The most probable damage state is selected for each asset to identify the most vulnerable ones. Based on the type and importance of the impacted assets, the potential consequences are determined at the facility level. Resulting estimates are very different if an earthquake strikes during a regular/high/low-demand period, or a maintenance period. The framework can be utilized to identify the locations within the refinery that may trigger cascading failures and secondary damages, should their assets be damaged by a seismic event. The outcomes can be exploited by stakeholders, risk engineers, and emergency action planners for developing customized and businesslike procedures to enhance the seismic resilience of the facility.