Seismic Damage Assessment Research Articles

Effects of Velocity Pulse-Like Ground Motions on the Seismic Failure Behavior of Masonry Minarets

ABSTRACT This research is motivated by post-earthquake observations of significant structural damage to minarets during the 2023 Kahramanmaraş earthquakes. It is thought that the near-fault velocity pulse-like ground motions played a crucial role in this phenomenon. Although the seismic performance of minarets has been extensively studied, including a large body of literature on numerical and experimental analyses, no attention has been paid to the seismic damage assessment of minarets subjected to strong velocity pulse-like ground motions. The present study aims to investigate the effects of near-fault strong velocity pulse-like ground motions with different velocities on the seismic failure behavior of masonry minarets. A 33-meter-high stone masonry minaret was selected for this purpose. Nonlinear behavior of masonry unit is modeled using Concrete Damage Plasticity (CDP). For the nonlinear analysis, three near-fault strong velocity pulse-like ground motions recorded during February 6, 2023, Kahramanmaraş earthquake (M7.7) and one non-pulse-like ground motion were selected. Displacements, strains, stresses and damage patterns in masonry minarets subjected to near-fault velocity pulse-like and non-pulse-like ground motions were obtained and thoroughly evaluated across different ground velocities. The velocity, the number of pulses and the pulse duration of velocity-pulse-like ground motions have a significant influence on the structural damage behavior of minarets. The results provide a detailed understanding of how minarets respond to different velocity pulse-like ground motion scenarios, offering valuable insights for the design, rehabilitation, and retrofitting of both new and existing minarets.

Spatial distribution of damage potential of the 2023 Pazarcik Turkey earthquake using inelastic-response spectra of recorded and simulated ground motions

On 6 February 2023, a devastating earthquake of magnitude 7.7 struck the southeastern part of Turkey, followed by multiple aftershocks. The sequence of earthquakes caused extensive damage in Southern Turkey and Northern Syria. This study evaluates the destructive potential of ground shaking resulting from the Pazarcik mainshock by developing spatial distribution of inelastic demand spectra across the region by using the recorded ground motions. These spectra provide an additional step toward more realistic estimates of the damage potential of ground shaking than the traditional elastic response spectra. Given the recorded ground motions, we also developed simulated ground-motion time series at numerous un-instrumented sites. We used these recorded and simulated motions to estimate ductility demands across the affected area. Constant-ductility spectra were derived using recording stations within 100 km of the fault rupture. The results indicated that in the near-fault area, and for structural periods of 0.5 and 1.0 s, the yield strength demand at a ductility level of 3 exceeded the levels specified in the local seismic design code for a 475-year return period. Our findings demonstrate that with more refinement and efficiency of the ground-motion simulation approach, the development of near-real-time spatial distribution of ductility demand is a promising approach for rapid seismic damage assessment of earthquakes.

Image-based assessment of seismic damage in RC exterior beam-column joints

Seismic damage to reinforced concrete (RC) beam-column joints in reinforced concrete (RC) structures significantly impacts their stability and safety after an earthquake. Cracks caused by earthquakes weaken these joints, reducing their ductility, strength, and stiffness. Therefore, a systematic method for assessing damage in RC beam-column joints is crucial. This study introduces a new method that uses image analysis, along with ranking algorithms and machine learning, to assess seismic damage in RC exterior beam-column joints. The study identified three key indicators of severe damage in joints: drift ratio, strength, and stiffness. The method uses image analysis to extract features from preprocessed, binary images of cracks. These features capture both the texture and geometry of the cracks. The chosen features, including crack area, aspect ratio, and distribution of line widths, along with structural parameters like geometry and bond index, were selected using F-test and MRMR algorithms. Seismic damage assessments were conducted on 115 images from 37 specimens using four machine learning models (Regression Trees, Support Vector Machine, Gaussian Process Regression, and Gradient Boosting). The study achieved a high R-squared value of 0.80, indicating strong accuracy, for assessing seismic damage based on drift ratio using the image-based method. This demonstrates that image analysis techniques can effectively link surface crack patterns to quantifiable image features, leading to a more precise assessment of seismic damage.

Seismic Damage Assessment of Existing Planar Steel X- or V-Braced Frames Using the Hybrid “M and P” Technique

Seismic Damage Assessment of Existing Planar Steel X- or V-Braced Frames Using the Hybrid “M and P” Technique

Seismic damage assessment of bonded versus unbonded laminated rubber bearings: A deep learning perspective

Laminated Rubber Bearings (LRBs), widely employed in highway bridges worldwide, are vulnerable to shear failure, squeezing or displacing during seismic events, potentially compromising bridge safety. Establishing a reliable approach for assessing the damage of LRBs is crucial for evaluating the seismic performance of bridges and preventing serious damage. To address this concern, this paper proposes a novel approach for LRBs seismic damage assessment based on computer vision (CV) technique. First, quasi-static loading tests are conducted on both bonded and unbonded LRBs to effectively enhance the understanding of their nonlinear properties. Subsequently, a large number of bearing samples are investigated to develop a comprehensive image database for a CV-based damage assessment model. A deep convolutional network (CNN) is designed to segment damage pixels, which are then combined with damage indicators to quantify the impact of various influencing factors on seismic damage using the interpretable machine learning technique, Shapley value. The results demonstrate that the CNN model achieves high-precision pixel segmentation and accurate predictions of seismic damage to LRBs, with RMSE consistently below 0.009 and R2 exceeding 95 %. The primary factor influencing LRB damage is the type of constraint, which interacts with loading characteristics and geometric dimensions to produce various coupled effects. This high-precision CV-based approach shows significant potential for estimating seismic damage states of critical bridge components and building seismic protection.

Research and Modification on the Park-Ang Damage Index for Railway Rectangular Piers

ABSTRACT This study addressed the issue of distortion in evaluating the seismic damage state of railway bridge piers using the original Park-Ang damage index. By constructing a parameterized co-simulation program with two finite element models, OpenSees and Abaqus, five sets of flexural failure and five sets of flexural-shear failure rectangular pier quasi-static test results were selected to validate the rationality of the calculation program. Four hundred and eighty parameterized calculations were conducted using this program. The combination coefficient β and critical damage index DI within the Park-Ang damage index were modified using nonlinear regression algorithm and convolutional neural network algorithm. The adaptability of the damage index calculation was ultimately verified through an engineering case study of a simply supported beam bridge. The research findings are as follows: 1) The main factor influencing β is the longitudinal reinforcement ratio, while the axial compression ratio, shear span ratio, volumetric stirrup ratio, aspect ratio, concrete strength, and steel strength are secondary parameters influencing β. 2) Compared to the nonlinear regression algorithm, the convolutional neural network algorithm can better establish a calculation model between pier structural parameters and β, clarifying their relationship. 3) It is recommended to use critical values of 0.11, 0.29, 0.49, and 1.00 for assessing pier damage as no, slight, moderate, severe, and collapse damage when using the damage index calculation model. 4) The Park-Ang index corrected by convolutional neural networks demonstrates improved accuracy and computational stability, making it suitable for practical assessment of seismic damage in bridge structures.

Seismic damage assessment of hybrid tenon-mortise-in-situ UHPC connection piers

Based on the proposed static test carried out on one whole cast-in-place pier specimen and three assembled pier specimens with different connection modes, the damage process of the four specimens under horizontal reciprocating load is analyzed and their damage conditions are evaluated by using the damage classification methods and different damage models commonly used at home and abroad, and the damage modes of the three assembled piers differ to different extents from that of the whole cast-in-place specimen. Compared with the whole cast-in-situ specimen, the damage modes of the three assembled piers have different degrees of difference, and the damage value of the specimen with splice joints located in the pier body is smaller than that of the other assembled piers under the same displacement amplitude; parameter expansion analysis is carried out on the UT-2 specimen to study the effect of different parameter changes on the damage performance under the proposed static cyclic loading. The results show that the larger the axial pressure ratio is, the larger the damage is. The larger the length to slenderness ratio, the smaller the damage. When the hoop ratio is from 0 % to 0.262 %, the damage value changes obviously. When the longitudinal reinforcement ratio is between 0.7 % and 1.94 %, the abutment damage decreases with the increase of longitudinal reinforcement ratio. The ratio of the cam width to the abutment section length is suggested to be 0.49–0.69. The related research can provide reference for the engineering design and seismic damage assessment of assembled RC abutments.

Study on seismic failure mechanism and damage model of unconstrained adobe block walls

Through the quasi-static cyclic in-plane loading test of three kinds of unconstrained adobe block walls, namely plain adobe wall, modified mud adobe wall and modified adobe wall, the failure mode and seismic performance of each specimen were clarified. Using residual deformation and cumulative energy dissipation as failure parameters, a two-parameter seismic damage model of unconstrained adobe block walls was established. and a calculation method for the adjustment coefficients of energy consumption items was provided. The results showed that the failure mode of the typical unconstrained adobe block wall under earthquake action was not affected by the modification of adobe materials, and the final failure mode was shear failure along the mud crack and the inclined crack extending through the block. Furthermore, the proposed seismic damage model can well reflect the evolution law of earthquake damage of adobe block walls, and the recommended damage index boundary values for five performance levels were given, providing a reference for performance-based seismic design and damage assessment of adobe block walls.

Impact of local site conditions on seismic performance of free‐spanning submarine pipelines: Underwater shaking table tests and numerical simulations

AbstractLocal site conditions may pose a significant influence on the seismic responses of submarine pipelines by altering both the offshore motion propagation and soil‐structure interaction (SSI). This paper aims to provide an in‐depth understanding of the influence regularity of local site conditions on the seismic performance of free‐spanning submarine pipelines (FSSPs). For this purpose, a suite of underwater shaking table tests were performed to investigate the seismic responses of FSSP subjected to the offshore spatial motions at three site categories. Response comparison factor () is defined to quantify the structural response discrepancies caused by the seismic inputs at different sites. The test results indicate that responses of the studied model FSSP gradually increase as spatial offshore motions at softer soil sites are employed as inputs; and the values of vary with a maximum magnitude of up to 40%–60% for different response indices when the site soil changes from fine sand to clay. Subsequently, the corresponding numerical simulations are carried out to reproduce the seismic responses of the test model. The experimental and numerical results meet a good agreement, indicating that the developed numerical modeling method can accurately predict the seismic responses of FSSPs. Following this verified modeling method and using the p‐y approach to address the SSI effect, fragility surfaces of the studied FSSP are derived in terms of PGA and site parameter (shear‐wave velocity in the top 30 m of the soil profile) via probabilistic seismic demand analyses. The impact of local site conditions on the seismic performance of the FSSP is quantitatively examined by comparing the fragility curves corresponding to various . Furthermore, a fast seismic damage assessment method is proposed for efficiently evaluating the performance of FSSPs buried in various offshore soil conditions. This approach proves beneficial for designers and decision‐makers, enabling accurate estimation of seismic damage and facilitating the implementation of post‐earthquake maintenance measures for FSSPs.

Seismic performance and damage assessment of bridges during the 2023 Kahramanmaras, Türkiye earthquakes (Mw = 7.8, Mw = 7.6)

This article presents a summary of the damage observed in bridges in the regions affected by the 6 February 2023 Kahramanmaras, Türkiye earthquake sequence. A bridge database was developed based on the observations from multiple reconnaissance groups that visited the bridges. These reconnaissance groups collectively visited 140 individual bridges that were subjected to various intensities of ground shaking. The severity of the observed damage ranged from no damage to total collapse. The types of damage to bridge components mainly included cracking and shifting of abutments, failure of pier cap shear blocks, shifting or dislodging of bearing pads, cracking of girders and loss of prestress, plastic hinging at pier bases, residual pier drift, and distress to deck surfaces, handrails, and carried utilities. Recorded and estimated seismic intensity measures are presented for each bridge site, and statistical information and correlations were developed considering the intensity of shaking, bridge parameters, and observed damage. Observations from a few visited sites are presented as case studies to illustrate the common failure mechanisms. The bridge database and presented results are expected to serve as a reference for further analysis, such as statistical verification, correlation, or damage estimations, and discussion regarding the mitigation of the observed vulnerabilities of bridges in Türkiye and those with similar construction worldwide.

Seismic Damage Assessment of RCC Structure Considering Infill Walls and Coupled Forces

Seismic Damage Assessment of RCC Structure Considering Infill Walls and Coupled Forces

Seismic Damage Analysis of Zamora Bridge in Ecuador

The Zamora Bridge, located in the Zamora-Chinchipe Province in the southeastern part of Ecuador, on the Pacific Rim seismic belt, serves as the sole river-crossing channel from the Mirador Copper Mine area to the exterior. Constructed and opened for traffic in 2013, this bridge is designed as a low-pier continuous girder bridge, featuring a three-span prestressed concrete continuous box girder for the main beam, with a span arrangement of 45.5+140+45.5 meters, and utilizes basin-type rubber bearings throughout. On May 6, 2019, and November 28, 2021, the Zamora Bridge experienced two significant seismic events. The initial seismic damage investigation revealed that the piers and foundation maintained their load-bearing capacity largely intact; the basin-type rubber bearings predominantly suffered shear failure and displacement, losing their horizontal limit capacity. Additionally, abutment blocks sheared, padstones cracked locally, and the main girder exhibited residual displacement. Following the first earthquake, repair work was undertaken based on the damage results, switching to friction pendulum seismic isolation bearings to enhance the seismic resilience of bridge. The subsequent seismic damage assessment indicated the overall stable condition of the bridge, with no observable damage, deformation, or settling to the main structure, thus maintaining basic traffic functionality. However, shear and deformation occurred to the bolts and pins fixing the direction of the friction pendulum isolation bearings, along with residual displacements after the activation of the seismic isolation function, and cracks developed in the abutment padstones and mortar layers. To delve into the performance and damage probability of vulnerable components of low-pier continuous girder bridges under various seismic intensities, numerical models of the Zamora Bridge equipped with basin rubber bearings and friction pendulum bearings were separately established using OpenSees finite element software. An analysis of the bearings' longitudinal seismic susceptibility was conducted by integrating the demand-capacity ratio and IDA method. The findings indicate that bearings, padstones, and anchor bolts are the vulnerable components necessitating reinforcement for such bridges. Compared to the basin rubber bearings, friction pendulum bearings significantly reduce the probability of bearing damage and demonstrate an excellent seismic isolation effect.

Quantum‐enhanced machine learning technique for rapid post‐earthquake assessment of building safety

AbstractFast, accurate damage assessment of numerous buildings for large areas is vital for saving lives, enhancing decision‐making, and expediting recovery, thereby increasing urban resilience. The traditional methods, relying on expert mobilization, are slow and unsafe. Recent advances in machine learning (ML) have improved assessments; however, quantum‐enhanced ML (QML), a rapidly advancing field, offers greater advantages over classical ML (CML) for large‐scale data, enhancing the speed and accuracy of damage assessments. This study explores the viability of leveraging QML to evaluate the safety of reinforced concrete buildings after earthquakes, focusing on classification accuracy only. A QML algorithm is trained using simulation datasets and tested on real‐world damaged datasets, with its performance compared to various CML algorithms. The classification results demonstrate the potential of QML to revolutionize seismic damage assessments, offering a promising direction for future research and practical applications.

Fragility of Indonesian houses: scenario damage analysis of the 2006 Yogyakarta and 2009 Padang earthquakes

Indonesia is located in one of the most seismically active regions in the world and often experiences damaging earthquakes. In the past the housing sector has sustained higher earthquake related damage and losses than other sectors. This is often attributed to the fact that the most common houses in Indonesia are non-engineered, built with poor quality workmanship, poor quality materials and without resilient seismic design features. However little effort has been made to quantify how fragile Indonesian houses are, or how their fragility may vary according to the population density or relative wealth of a region. It is not possible to derive empirical fragility functions for Indonesia due to insufficient damage data. The aim of this study is to determine whether existing earthquake fragility functions can be applied to common house types in Indonesia. Scenario damage analyses simulating the 2006 Yogyakarta and 2009 Padang events were undertaken several times testing different fragility functions. The simulated damage results were then compared to the damage observed post event to determine whether an accurate damage prediction could be achieved. It was found that the common house types in Yogyakarta and Central Java vary according to age of construction, location and relative wealth of a region and can be reasonably well represented by existing fragility functions. However, the houses in Padang and surrounding West Sumatra did not vary in a predictable manner and are more fragile than anticipated. Therefore, the fragility of the most common house types in Indonesia differs between Central Java and West Sumatra. This has important implications for seismic damage and risk assessment undertaken in Indonesia.

Seismic Damage and Behavior Assessment of Drift-Hardening Concrete Walls Reinforced by LBUHS Bars.

This paper experimentally and analytically investigated the damage and seismic behavior of concrete walls reinforced by low-bond ultra-high-strength (LBUHS) bars. To this end, four half-scale rectangular concrete walls were fabricated and tested under reversed cyclic loading and constant axial compression. The test variables were the shear span ratio and the axial load ratio. Based on the test results, the propagation of cracks on the wall surface, the maximum strain capacity of concrete, the hysteresis loops and envelope curves, the residual drifts, and the strain distributions of LBUHS rebars were presented and discussed. The experimental results showed that all the test walls could exhibit drift-hardening capability until at least a 2.0% drift ratio if LBUHS rebars were anchored by nuts at their ends. The test results also indicated that the maximum strain capacity of concrete was above 0.86%, much larger than the currently recommended 0.4%. After unloading from the transient drift ratios of 2.0% and 2.5% for the walls with shear span ratios of 1.5 and 2.0, respectively, the measured residual drift ratios were controlled below 0.4%, which is less than the critical drift ratio (0.5%) having 98% repairable probability recommended in the FEMA document (P-58) for general concrete structures. Furthermore, a numerical method was presented to evaluate the cyclic response of the test walls, and a comparison between the experimental and the calculated results verified the reliability and accuracy of the proposed numerical method.

A numerical model database for rapid seismic damage assessment of typical regular reinforced concrete frame structures in urban building clusters

A vast city usually encompasses hundreds of thousands or even millions of buildings, majority of which are regular buildings with typical structural configurations. In the seismic damage simulation of cities, efficient and reliable simplified models are required to represent these buildings. A numerical model database of typical regular reinforced concrete (RC) frame structures was developed, utilizing shear models to simulate these RC frame structures. In contrast to existing shear models that are automatically generated based solely on the fundamental rules regulated by the theories of structures and the design codes, the shear models in this study were calibrated using refined numerical models to guarantee precise depiction of RC frame structures. The effects of reinforcement corrosion and the year of construction on structural performance were also considered. First, 108 RC frame structures were designed with typical configurations, strictly adhering to the regulations of design codes. Second, the refined models of the RC frame structures were established with modified material parameters to account for reinforcement corrosion, resulting in 540 refined models. Afterward, the parameters of each shear model were calibrated through cyclic pushover analysis of the corresponding refined numerical model. Finally, the characteristic points of the shear models were further modified to consider the different redundant capacities of the structures constructed in three time phases due to the update of design codes, by which a simplified numerical model database containing 1620 shear models was developed. The models' accuracy in predicting fundamental periods and seismic damage states was verified by comparing them to the refined models and three real RC frame buildings. The effects of the reinforcement corrosion and year of construction on the seismic damage states of the RC frame structures were also discussed. The developed numerical model database can be utilized for the seismic damage assessment of RC frame structures in urban building clusters.

Field Observations and Numerical Investigations on Seismic Damage Assessment of RC and Masonry Minarets During the February 6th, 2023, Kahramanmaraş (Mw 7.7 Pazarcık and Mw 7.6 Elbistan) Earthquakes in Türkiye

ABSTRACT On February 6, 2023, two massive earthquakes struck the EasternAnatolian Fault Line (EAF) at 9-hour intervals. The Mw 7.7 and Mw 7.6 earthquakes were located in Pazarcık and Elbistan districts inKahramanmaraş province. These earthquakes directly damaged 11 provinces in Eastern and Southeastern Anatolia (Kahramanmaraş,Hatay, Adyaman, Osmaniye, Gaziantep, Şanlurfa, Malatya, Diyarbakır,Adana, Kilis, and Elazığ), causing substantial loss of life and property. This study aims to present the field investigation of reinforced concrete (RC) and masonry minarets in 11 cities around the area after these earthquakes and the structural performance and collapse mechanism of two minarets selected as case studies. For this purpose, the damaged or collapsed minarets in the region affected by the earthquakes were determined and the reasons were explained. In addition, an RC and a masonry minaret in the İslahiye district were chosen as case studies, and finite element models (FEM) were created.The validity and correctness of the reasons for damages determined by field observations were further demonstrated by numerical findings.It was determined that nearly all of the damaged and collapsed minarets did not obtain proper engineering services. Additionally, it is believed that the lack of any norms or regulations for these unique constructions is a significant weakness that places engineers in a challenging situation throughout the design phase

Relationship between peak ground acceleration and damages indices for steel sheet pile quay wall in Bejaia-Algeria

Purpose The purpose of this paper is the dynamic analysis and seismic damage assessment of steel sheet pile quay wall with inelastic behavior underground motions using several accelerograms. Design/methodology/approach Finite element analysis is conducted using the Plaxis 2D software to generate the numerical model of quay wall. The extension of berth 25 at the port of Bejaia, located in northeastern Algeria, represents a case study. Incremental dynamic analyses are carried out to examine variation of the main response parameters under seismic excitations with increasing Peak ground acceleration (PGA) levels. Two global damage indices based on the safety factor and bending moment are introduced to assess the relationship between PGA and the damage levels. Findings The results obtained indicate that the sheet pile quay wall can safely withstand seismic loads up to PGAs of 0.35 g and that above 0.45 g, care should be taken with the risk of reaching the ultimate moment capacity of the steel sheet pile. However, for PGAs greater than 0.5 g, it was clearly demonstrated that the excessive deformations with material are likely to occur in the soil layers and in the structural elements. Originality/value The main contribution of the present work is a new double seismic damage index for a steel sheet pile supported quay wharf. The numerical modeling is first validated in the static case. Then, the results obtained by performing several incremental dynamic analyses are exploited to evaluate the degradation of the soil safety factor and the seismic capacity of the pile sheet wall. Computed values of the proposed damage indices of the considered quay wharf are a practical helping tool for decision-making regarding the seismic safety of the structure.

Endurance time analysis for seismic performance of underground structures subjected to mainshock–aftershock sequences

The seismic response analysis of subway underground structures only considers the impact of a single mainshock, ignoring the aftershocks, which may cause more serious secondary damage within a short time after strong earthquakes. To investigate the seismic performance of underground structures under sequential earthquakes and improve the understanding of aftershocks, we analyzed the dynamic response of subway station structures under mainshock–aftershock sequences. A typical two-story and three-span subway station was selected as the prototype, and a finite element model of a soil–underground structure interaction was established. Based on the basic concept of endurance time and design response spectrum of relevant seismic standards in China, an endurance time acceleration function was generated, and nine mainshock–aftershock sequences were constructed. Thereafter, the seismic responses of subway stations under the action of mainshock–aftershock sequences, such as lateral deformation characteristics and damage failure law, were discussed and analyzed. The results show that the endurance time method can be used as a new and efficient method to study the seismic performance of underground structures subjected to mainshock–aftershock sequences. The effects of aftershocks on the damage and lateral displacement of underground structures were preliminarily revealed. The structural deformation response of each layer varies greatly due to the different damage states of the mainshock. The maximum story drift θ of the structure increases with the increase of loading seismic intensity. From the perspective of seismic damage and relative deformation, the structural dynamic response, considering the effect of sequential earthquakes, is greater than that of the mainshock alone, which reflects the disadvantage of aftershocks in seismic design. The results provide a reference for seismic analysis and damage assessment of structures under sequential earthquakes.

Machine learning prediction models for ground motion parameters and seismic damage assessment of buildings at a regional scale

This study examines the feasibility of using a machine learning approach for rapid damage assessment of reinforced concrete (RC) buildings after the earthquake. Since the real-world damaged datasets are lacking, have limited access, or are imbalanced, a simulation dataset is prepared by conducting a nonlinear time history analysis. Different machine learning (ML) models are trained considering the structural parameters and ground motion characteristics to predict the RC building damage into five categories: null, slight, moderate, heavy, and collapse. The random forest classifier (RFC) has achieved a higher prediction accuracy on testing and real-world damaged datasets. The structural parameters can be extracted using different means such as Google Earth, Open Street Map, unmanned aerial vehicles, etc. However, recording the ground motion at a closer distance requires the installation of a dense array of sensors which requires a higher cost. For places with no earthquake recording station/device, it is difficult to have ground motion characteristics. For that different ML-based regressor models are developed utilizing past-earthquake information to predict ground motion parameters such as peak ground acceleration and peak ground velocity. The random forest regressor (RFR) achieved better results than other regression models on testing and validation datasets. Furthermore, compared with the results of similar research works, a better result is obtained using RFC and RFR on validation datasets. In the end, these models are utilized to predict the damage categories of RC buildings at Saitama University and Okubo Danchi, Saitama, Japan after an earthquake. This damage information is crucial for government agencies or decision-makers to respond systematically in post-disaster situations.