Post-earthquake Emergency Response Research Articles

A Semantic Augmented Approach to FEMA P-58 based Dynamic Regional Seismic Loss Estimation Application

Regional seismic loss estimation (RSLE) is a crucial process in both immediate post-earthquake emergency response and long-term reconstruction endeavors. Over the years, significant progress has been made in RSLE: sensing approaches such as field investigation and remote sensing offers a comprehensive overview necessary for real-time disaster response, while simulation techniques such as the methodology proposed in Federal Emergency Management Agency (FEMA) P-58 series provide insights into the mechanism of disaster development and its potential long-term impacts on urban assets. Nonetheless, challenges persist in the realm of practical RSLE applications. Firstly, a dynamic understanding of a disaster event and its influence is deemed important for effective emergency responses while challenging to achieve in current approaches. Secondly, stakeholders with varying roles, including administrators, rescue teams and ordinary citizens have distinct information requirements for RSLE. Thirdly, the complexity of seismic loss estimation, involving diverse data sources such as building information models, performance models, fragility data and sensor observations, poses interoperability issue. To tackle these issues, this article introduces a dynamic, multi-granularity, ontological representation scheme tailored for RSLE decision-supporting systems. This scheme operates across various scales, from individual building components to broader regional scales by synergistically employing FEMA P-58 guidelines and Semantic Web technologies. Upon the corresponding semantics, a question-and-answer agent powered by large language model is further developed to facilitate interaction requirements within the RSLE process via FEMA P-58 pipeline. The practical efficacy of this approach is validated through a prototype deployed under a real earthquake event, demonstrating its value in real-world scenarios.

Multilevel assessment method for post-earthquake functionality of medical buildings considering component–department–floor interdependencies

The assessment of the post-earthquake functionality of medical buildings (PEFMB) is critical for the post-earthquake emergency response, recovery, and resilience-based seismic design of medical buildings. Hospitals are complex functional systems that exhibit multilevel functional coupling from components to departments to floors. Existing methods have challenges, including the difficulty of considering the impact of different departments located on different floors on medical functions, and a lack of multilevel performance improvement strategies for enhancing post-earthquake medical functionality. A multilevel assessment method for the PEFMB that considers component–department–floor interdependencies (CDFI) was developed in this study. This method establishes a functional logical relationship between components and departments using fault tree models of typical departments. A multilevel functional coupling relationship among the components, departments, and floors was established by incorporating floor nodes to reflect the impact of departments located on different floors. This enabled the assessment of the PEFMB considering the CDFI. Furthermore, methods for identifying critical failure paths in the PEFMB were developed, and multilevel performance improvement strategies by adjusting medical equipment and departments along the critical failure path were recommended. The proposed method is demonstrated using an outpatient building. The main conclusions are as follows. (1) The proposed multilevel assessment method enables quantitative assessment of the PEFMB and exhibits good scalability. (2) This method provides a clear and intuitive visualization of the critical failure path in healthcare functionality under seismic conditions. The proposed multilevel improvement strategies can enhance the post-earthquake functionality of medical buildings at multiple levels, which provides a valuable reference for the seismic design of medical buildings.

Multi-scale image-based damage recognition and assessment for reinforced concrete structures in post-earthquake emergency response

As cities continue to develop, the significance of resilience and intelligence is increasing. In post-earthquake emergency response, there is a continuous demand for efficient and accurate methods of structural state assessment. This study employs deep learning (DL) techniques to propose a multi-scale image-based damage recognition and assessment method for reinforced concrete (RC) structures. First, an RC structural damage recognition task framework and a structural mechanical damage image dataset are established. Second, a DL model is selected to conduct the experiments and enhance its performance through transfer learning. Then, a multi-scale correlated structural state assessment procedure is introduced where local, component, structural, and regional scales are linked. Finally, an engineering case is presented to describe the application steps of the method in real-world scenarios, demonstrating its feasibility. Nevertheless, the proposed method lacks comprehensive validation across various geotechnical conditions and detailed structural configurations, which may limit its generalizability. This study has the potential to enhance the efficiency and scope of post-disaster emergency response and contribute to the development of sustainable cities.

Cascaded framework for earthquake building damage detection combining spatial and frequency domain feature integration

Abstract. Building collapse is a major cause of casualties after an earthquake, so accurately extracting building damage information is critical for post-earthquake assessment and rescue. Currently, most deep learning methods focus on the end-to-end detection of building collapse. However, in real-world earthquake scenarios, the end-to-end computational process often lacks flexibility and struggles to meet the requirements of rapid emergency response. To address this issue, this paper proposes a cascaded framework that combines pre-earthquake building extraction and post-earthquake building damage classification. The proposed framework includes two sections: (1) Progressive building semantic segmentation model in the joint frequency domain. This model is designed to accurately extract buildings prior to an earthquake, with the goal of minimizing error propagation throughout the cascading process. The model addresses the spatial similarity of buildings under complicated backgrounds, as well as the high internal heterogeneity of buildings, by utilizing frequency domain techniques. It compensates for the shortcomings of traditional models in terms of incomplete information extraction through the effective integration of global and local information. Finally, the model employs edge priors for edge regularization. (2) Rapid building damage classification process. Based on the accurate building extraction results, a fast and efficient classification process is developed. This process uses a simple and lightweight classification network to effectively extract building damage information caused by the earthquake. The superiority of the proposed framework is validated through comparison with traditional cascading architectures and end-to-end models. The results show that the cascading framework not only provides accurate pre-earthquake building extraction, but also enables efficient and accurate post-earthquake damage classification, which meets the requirements of rapid post-earthquake emergency response. This balance of accuracy and speed is essential for effective disaster management and recovery.

Implications of 5G rollout on post-earthquake functionality of regional telecommunication infrastructure

Telecommunication infrastructure (TI) is becoming increasingly vital in modern society, where information exchange is needed in almost all aspects of the built environment, business operations, and people's daily lives. The ongoing 5G rollout will lead to a paradigm shift in regional TI deployment landscape, with increased seismic hazard exposure particularly due to the densely deployed small cells. As TI is known to be vulnerable to seismic hazard impacts yet necessary for post-earthquake emergency response, this study carries out a pioneering effort in quantifying the post-earthquake TI failures and functionality to better support risk mitigation decision-making. We propose a novel seismic risk assessment framework for regional 5G TI, by holistically integrating regional seismic hazard analysis, infrastructure seismic exposure data, electric power infrastructure seismic fragility modeling and network connectivity analysis, as well as wireless TI functionality modeling. The proposed framework is evaluated based on a hypothetical regional infrastructure testbed located in Memphis, Tennessee, subjected to several earthquake scenarios. From a reference heterogeneous 5G TI deployment scenario, the results indicate that significant performance degradation of 5G TI is expected especially after major earthquake events. Enabled by the proposed framework, we further compared the efficacy of several risk mitigation strategies and pertinent implications are provided.

BIM-based method for post-earthquake medical functionality assessment of hospital departments considering functional coupling

Hospitals play an important role in post-earthquake emergency response and recovery, and the assessment of post-earthquake medical functionality is important for ensuring hospital functionality after earthquakes. Such assessments of hospital departments currently face the following challenges: (1) lack of unified modeling rules and integrated platforms to manage the associated data; (2) the complex functional coupling relationships between different components and medical equipment are not often considered; (3) lack of unified communication platforms, which hinders collaboration among researchers from different fields. Therefore, this paper proposes a BIM-based method for post-earthquake medical functionality assessment (PEMFA) of hospital departments considering functional coupling. Specifically, first, multi-level of detail (LOD) BIM modeling rules for structural components, nonstructural components, and medical equipment oriented towards PEMFA are suggested. Thereafter, a conversion method for the medical functionality assessment model and PEMFA method based on BIM are proposed. Subsequently, the PEMFA method for departments is proposed, emphasizing functional coupling. Finally, a typical medical building is selected as an example to demonstrate the proposed method. The results indicate the following: (1) the fragility data for various components and equipment of medical buildings can be integrated using the proposed multi-LOD modeling rules; (2) the mapping relationship between medical functional logic and BIM has been established, through which the functional coupling relationship between different components and equipment can be fully considered, thus providing an important method for the PEMFA of hospital departments and displaying results.

Shaking table tests of a switching power cabinet considering physical damage and functionality loss

Switching power cabinets are critical equipment that converts alternating current (AC) to direct current (DC) for electrical power system of telecommunication buildings. Post-earthquake damage to the cabinet may result in entire functionality loss of telecommunication buildings, which will have a significant impact on post-earthquake emergency response. In this study, unidirectional shaking table tests were conducted separately in X-direction and Y-direction to evaluate the seismic responses of a switching power cabinet. The seismic input motion was generated based on required response spectrum of YD 5083 code. The peak table acceleration levels were scaled from 0.3 g to 2.5 g in order to capture progressive damage of the switching power cabinet. Based on the test results, the physical damage and functionality loss of tested cabinet were analyzed first. Then the response characteristics of the cabinet were evaluated and explained in terms of the natural frequency, acceleration, and deformation response. Both outside cabinet and in-cabinet acceleration amplification factors were analyzed. The seismic fragility curves of switching power cabinet were also developed considering four observed seismic damage states.

Evaluation of seismic response of server cabinets through shaking table tests

Telecommunication system is one of the critical lifeline systems for national life and post-earthquake emergency response. Telecommunication equipment is the necessary components to preserve communication functionality of telecommunication system. The severe damage and functionality loss of data center buildings resulting from damage to telecommunication equipment are frequently reported following earthquakes. Thus, there is an increasing need to understand the performance of telecommunication equipment during earthquakes.Seismic investigation of three server cabinets in internet data center buildings are presented in this study. The seismic damage and dynamic characteristics of server cabinets were evaluated and explained in terms of the natural frequency, stress, acceleration, dynamic amplification factor, and deformation by triaxial shaking table tests. The input acceleration time histories were generated based on the required response spectra in YD 5083 code and AC 156 code, with seismic intensities ranging from 0.1 g to 1.2 g. Based on the test results, the effects of different mass distributions inside the cabinets and earthquake inputs were investigated. The seismic damage limit states of server cabinets were identified based on observed damage phenomenon. The corresponding seismic fragility models of server cabinets were developed based on shaking table test data. The results show that the Power Distribution Units inside the cabinets still worked normally and the output voltage was normal for all loading cases although the frame of cabinets suffered severe seismic damage. The normal functionality of server cabinets including more electronic devices and equipment should be carefully checked by shaking table tests.

Digitalization and Spatial Documentation of Post-Earthquake Temporary Housing in Central Italy: An Integrated Geomatic Approach Involving UAV and a GIS-Based System

Geoinformation and aerial data collection are essential during post-earthquake emergency response. This research focuses on the long-lasting spatial impacts of temporary solutions, which have persisted in regions of Central Italy affected by catastrophic seismic events over the past 25 years, significantly and permanently altering their landscapes. The paper analyses the role of geomatic and photogrammetric tools in documenting the emergency process and projects in post-disaster phases. An Atlas of Temporary Architectures is proposed, which defines a common semantic and geometric codification for mapping temporary housing from territorial to urban and building scales. The paper presents an implementation of attribute specification in existing official cartographic data, including geometric entities in a 3D GIS data model platform for documenting and digitalising these provisional contexts. To achieve this platform, UAV point clouds are integrated with non-metric data to ensure a complete description in a multiscalar approach. Accurate topographic modifications can be captured by extracting very high-resolution orthophotos and elevation models (DSM and DTM). The results have been validated in Visso (Macerata), a small historical mountain village in Central Italy which was heavily damaged by the seismic events of 2016/2017. The integrated approach overcomes the existing gaps and emphasizes the importance of managing heterogeneous geospatial emergency data for classification purposes. It also highlights the need to enhance an interoperable knowledge base method for post-disaster temporary responses. By combining geomatic tools with architectural studies, these visualization techniques can support national and local organizations responsible for post-earthquake management through a 3D modelling method to aid future transformations or interventions following other natural disasters.

Collapsed Building Detection in High-Resolution Remote Sensing Images Based on Mutual Attention and Cost Sensitive Loss

Detection of collapsed buildings based on high-resolution remote sensing images is of significance to post-earthquake emergency response and post-disaster reconstruction. In recent years, the UNet network architecture has been applied in detection of collapsed buildings to good effect. However, most existing methods directly fuse features of encoder and decoder subnets, which results in redundant or mutually exclusive information, thus weakening the capability of expressing details of the outline of collapsed buildings in detail. In addition, using these methods, the collapsed building samples in post-earthquake damage scenes are difficult to be acquired or account for a small proportion of the total detected image. These approaches indistinguishably processed the misclassified samples with different types in training processes, while ignoring the enhanced learning of collapsed building samples. Hence, a multimodule concatenation based on U-Shape network (MC-UNet) for detecting post-earthquake collapsed buildings based on a Mutual Attention Module (MAM) and Cost Sensitive loss (CS loss) was proposed. To begin, a MAM was designed in skip connections in UNet to fully utilize high-level and low-level feature information, as a result, feature expressive capability can be enhanced; on this basis, a novel CS loss was designed to force the model to focus more on the learning of collapsed building samples. Experiments on three groups of datasets (Mexico dataset, HTI dataset, and YSH dataset) about post-earthquake collapsed buildings indicate the scheme proposed remarkably outperforms some state-of-the-art algorithms.

Resilience assessment of the interdependent transportation–healthcare system during emergency response

The emergency medical response after a strong earthquake relies on a robust transportation–healthcare system and effective management. This article proposes a resilience assessment framework for the interdependent transportation–healthcare system (ITHS) integrating physical loss and organisational management during post-earthquake emergency response. Considering the earthquake-induced injured people, the seismic damage to transportation, and the quantification of the condition of the patients after being treated, a novel metric is proposed to evaluate the response effort during the first 72 h. Bi-objective optimisation is developed to solve the real-time dispatching and treating problems instead of overwhelming one single hospital. In addition, the separate impact of disrupted transportation and damaged healthcare on the interdependent system is calculated to measure the cascading effect. It is shown that proper resource allocation and practical management are crucial to guarantee the desired level of the response effort.

Post-Earthquake Functionality Assessment of Urban Road Network Considering Emergency Response

ABSTRACT As one of the most important urban infrastructure systems, the road network plays a vital role in post-earthquake emergency response. Quantitative evaluation of the emergency response functionality of road network under earthquakes can provide decision support for emergency planning and future construction. In this paper, a novel network performance metric is proposed to consider both the special traffic demand in emergency response and the supply capability of road network. On this basis, an integrated probabilistic assessment framework for post-earthquake network emergency response functionality is presented, considering various uncertainties. In the framework, a penalty-based approach is proposed to consider the impact of partially degraded links on network functionality. At last, the proposed methodology is illustrated on the road network of Tangshan city, China, under different seismic scenarios.

Emergency Response System Combining the Internal and External Domains (ERSCIED)

Agent-based modeling is a promising approach for developing simulation tools for natural hazards in different areas, such as during urban search and rescue (USAR) operations. The previous studies aimed to develop a dynamic agent-based simulation model in post-earthquake emergency response operations combining rescuers and victims using geospatial information systems and multi-agent systems (GISs and MASs, respectively). We use multi-agent system engineering (MaSE) to construct this model and cluster points are proposed to assemble rescuers and victims. We also proposed an approach for dynamic task allocation and for establishing collaboration among agents based on contract net protocol (CNP) and the [Formula: see text]-means clustering method. Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) and expert evaluation is used to sort the priorities of cluster points. The experimental background is set in the central area of Chengdu, Sichuan Province, China. 200 victims with different demands and 30 rescuers with the same rescue capability are randomly distributed in this area. We use different victim speeds to simulate different degrees of seismic damage. Compared with normal search and rescue, the ERSCIED can make some use of the capabilities of the victims for the improvement of emergency effectiveness when the victims and rescuers have a similar speed (1:1) or the victims are not much slower than the rescuers (1:2). When the victims are much slower than the rescuers (1:10), the rescuers have to wait for a long time at the cluster points and it will lead to a waste of resources. The parameters of rescuers and victims can be changed to meet different emergencies and the ERSCIED can provide effective auxiliary decision-making information for decision-makers.

Rapid Estimation of Earthquake Fatalities in Mainland China Based on Physical Simulation and Empirical Statistics-A Case Study of the 2021 Yangbi Earthquake.

At present, earthquakes cannot be predicted. Scientific decision-making and rescue after an earthquake are the main means of mitigating the immediate consequences of earthquake disasters. If emergency response level and earthquake-related fatalities can be estimated rapidly and quantitatively, this estimation will provide timely, scientific guidance to government organizations and relevant institutions to make decisions on earthquake relief and resource allocation, thereby reducing potential losses. To achieve this goal, a rapid earthquake fatality estimation method for Mainland China is proposed herein, based on a combination of physical simulations and empirical statistics. The numerical approach was based on the three-dimensional (3-D) curved grid finite difference method (CG-FDM), implemented for graphics processing unit (GPU) architecture, to rapidly simulate the entire physical propagation of the seismic wavefield from the source to the surface for a large-scale natural earthquake over a 3-D undulating terrain. Simulated seismic intensity data were used as an input for the fatality estimation model to estimate the fatality and emergency response level. The estimation model was developed by regression analysis of the data on human loss, intensity distribution, and population exposure from the Mainland China Composite Damaging Earthquake Catalog (MCCDE-CAT). We used the 2021 Ms 6.4 Yangbi earthquake as a study case to provide estimated results within 1 h after the earthquake. The number of fatalities estimated by the model was in the range of 0–10 (five expected fatalities). Therefore, Level IV earthquake emergency response plan should have been activated (the government actually overestimated the damage and activated a Level II emergency response plan). The local government finally reported three deaths during this earthquake, which is consistent with the model predictions. We also conducted a case study on a 2013 Ms7.0 earthquake in the discussion, which further proved the effectiveness of the method. The proposed method will play an important role in post-earthquake emergency response and disaster assessment in Mainland China. It can assist decision-makers to undertake scientifically-based actions to mitigate the consequences of earthquakes and could be used as a reference approach for any country or region.

ShakeMap operations, policies, and procedures

The US Geological Survey’s ShakeMap is used domestically and globally for post-earthquake emergency management and response, engineering analyses, financial instruments, and other decision-making activities. Recent developments in the insurance, reinsurance, and catastrophe bond sectors link payouts of potentially hundreds of millions of dollars to ShakeMap products. Similarly, building codes, post-earthquake building damage forensic evaluations, and geotechnical evaluations often rely on estimated peak response-spectral values for site-specific evaluations that may lead to costly analyses, retrofits, or other expenditures. Given such activities, financial, engineering, and other technical users demand processing specifications and a metadata trail for actuarial, escrow, and forensic purposes for each significant earthquake. Recent inquiries include how and why maps change with time, how to interpret metadata, and how to obtain the creation and update history of various map layers. Similarly, the collection of ShakeMap scenarios and historical ShakeMaps—either created in earlier versions or rerun as part of the latest version of the ShakeMap Atlas—warrant a full explanation of the inputs, processing, and archiving given their contribution to fragility curve development and loss model calibration. For these reasons, in addition to event-specific ShakeMap metadata and a comprehensive online ShakeMap Manual, we have crafted this practice paper to answer several of the most frequently asked technical questions. We also describe an application programming interface (API) for accessing site-specific shaking metrics and their uncertainties for earthquake forensic purposes in a consistent fashion. In all, we describe the advantages of employing ShakeMaps for these critical purposes as well as describe their limitations and uncertainties, offering an extensive set of instructions and disclaimers that can be referenced by ShakeMap users.

Traffic efficiency of post-earthquake road network in fault region retrofitted by friction core rubber bearing

The post-earthquake emergency response depends on the traffic efficiency of the transportation network system. The bridge is the key factor affecting the reliability of the transportation network. Due to factors such as low design standards and performance degradation, the bridges built in the early days had low seismic performance. In fault regions, the pulse effect will also increase the seismic demand of the structure. In this paper, a friction core rubber bearing (FCRB) is proposed for seismic retrofit of road network bridge. Then calculate the fragility of bridges with and without retrofit under pulse and non-pulse effect, and the bridge traffic capacity under several road network conditions. The total travel time of the road network is used as a quantitative index of the reliability of the transportation network, and the prioritization of bridge retrofit under the limited budget and the assessment method of road network seismic risk are proposed. By comparing the difference of total travel time of road networks under different working conditions, the influence of pulse effect and the effect of FCRB are analyzed. Finally, a case is given to illustrate the effectiveness of FCRB in retrofitting the road network bridge and the necessity of considering the pulse effect. The results show that: it is necessary to consider the influence of pulse effect in road network risk assessment with high earthquake magnitude; the bridge retrofit prioritization takes into account the bridge traffic flow and the bridge traffic capacity, which is easy to calculate and can identify the critical bridges that have an important influence on traffic efficiency; with the increase of earthquake magnitude, the seismic risk of road network presents a geometric increase trend; FCRB can significantly reduce the road network seismic risk, and the seismic risk can be reduced by more than 50% if 20 bridges are retrofitted; with the increase in the number of retrofitted bridges, the decreasing trend of the annual seismic risk changes from fast to slow, and finally tends to be flat, which verifies the effectiveness of the retrofit prioritization.

Modeling of rapid evaluation for seismic stability of soil slope by finite element limit analysis

The rapid evaluation of post-earthquake landslides and unstable slopes (whether they will be revived by aftershocks) is a key task in the post-earthquake emergency response phase. Stability chart and Newmark model is generally used for rapid evaluation of seismic stability of soil slopes. In this study, a novel method for directly estimating static, pseudo-static safety factors and critical accelerations of soil slopes is proposed; this method overcomes the limitations of stability chart and Newmark model. Based on finite element limit analysis and Mohr-Coulomb criterion, safety factors and critical acceleration of typical slope models are studied via the parametric method. First, a stability chart of safety factors under static and pseudo-static states is calculated by finite element limit analysis. Correspondingly, the critical acceleration under static condition is obtained. Next, the seismic weighting factor and slope angle weighting factor are put forward, and a rapid evaluation model of safety factors is established. Finally, according to the correlation between safety factors and critical acceleration under static conditions, a rapid evaluation model for critical acceleration is proposed. The proposed method is compared with the results of the Newmark model and finite element limit analysis. The results show that the prediction accuracy of the proposed method is closer to the results of finite element limit analysis than those of Newmark model. The proposed seismic stability model is reliable and efficient and can be used to evaluate the stability of soil slope at the initial design stage and provide reference for further seismic design.

Landslide Susceptibility Mapping Using Ant Colony Optimization Strategy and Deep Belief Network in Jiuzhaigou Region

Landslidesusceptibility mapping (LSM) is the primary link of geological disaster risk evaluation, which is significant for postearthquake emergency response and rebuilding after disasters. Existing LSM studies applying deep learning (DL) methods have shortcomings such as easy overfitting, slow convergence, and insufficient hyperparametric optimization. In response to these problems, this study proposes an ensemble model based on ant colony optimization strategy and deep belief network (ACO-DBN). In ACO-DBN, DL optimization strategies were added to DBN and their combined parameters were optimized with ACO. Next, Pearson's correlation coefficient and random forest importance ranking methods were utilized to optimize landslide causative factors. Then, the Jiuzhaigou earthquake region was selected as an example to explore the applicability of this model. Besides, we conducted the Wilcoxon signed rank test in order to verify that the differences were statistically significant. In a comprehensive comparative all indexes and landslide density, the model proposed in this article shows good rationality, scientificity, and interpretability. The newly occurred landslide site further demonstrates that heuristically optimized DL could make scientific and accurate evaluation of landslide susceptibility.

Post-Earthquake Emergency Response Time to Locations of Fire Ignition

ABSTRACT This paper investigates fire department response time to locations of ignition after an earthquake and proposes a framework to identify vulnerable areas in a community by considering both the likelihood of ignition and potential delays in response of the fire department. Delays are calculated as a function of bridge damage and blocked roadways due to building debris. Uncertainty in bridge performance and debris accumulation are incorporated into the analysis. The framework is applied to a case study to demonstrate how the proposed work can be used to plan fire department resources, and minimize losses from postearthquake fires.

Improving post-earthquake emergency response using indoor tracking

Localization and indoor tracking of rescuers and victims are essential during emergency management in post-earthquake conditions because those allow search and rescue teams to be faster and more efficient. While several indoor tracking technologies have been developed over the past years, localization and tracking are still a challenge during emergency conditions when power and telecommunication networks are often missing. This article presents a new indoor positioning technique for emergency support that is based on the ultra-wideband network using fixed nodes (anchors) and moving nodes (tags) in the form of a smart watch. The main challenge addressed by the system design is a self-calibrating positioning that is able to transfer also the user’s vital signals parameters. This article describes the system architecture and the key aspects of the prototype components. Two applications for indoor tracking and emergency rescue are illustrated while the performance of the system is validated by performing tests in a complex building.