Seismic Resilience Assessment Research Articles

Seismic Resilience Assessment of the Hybrid Bridge Pier Based on Fragility Analysis

Seismic Resilience Assessment of the Hybrid Bridge Pier Based on Fragility Analysis

Fragility Analysis and Resilience Assessment of the Single-Column Pier Steel-Concrete Composite Bridge Subjected to Seismic Loads

Abstract With the advantages of a small footprint, wide under-bridge view, and beautiful appearance, single-column pier bridges are widely used in urban bridge networks. However, single-column pier bridges are prone to damage during earthquakes or heavy vehicle use, which can seriously affect normal operations and postdisaster recoveries. Therefore, there is an urgent need to carry out seismic resilience assessments of single-column pier bridges and formulate disaster prevention and mitigation measures from the aspects of design, maintenance, and postearthquake recovery. This paper first establishes a resilience assessment framework for the single-column pier bridge and optimizes a functionality recovery model after an earthquake. Then, a numerical model of a sample bridge is built for resilience fragility analysis. Nonlinear dynamic time history analysis is performed to build a probabilistic seismic demand model, and moment–curvature analysis is performed to build a probabilistic seismic capacity model. Finally, a seismic resilience assessment of the single-column pier bridge is obtained based on the seismic fragility, and a sensitivity analysis is carried out for the pier height, pier section dimension, span and vehicle load level to improve the resilience of the single-column pier bridge.

Seismic resilience assessment of extended pile shaft supported coastal bridges considering scour and uniform corrosion effects

The resilience-informed assessment for coastal highway bridges exposed to multiple hazards plays a crucial role in the decision-making process for their operation, maintenance, and management during the bridge’s long-term service period. This study performs a seismic resilience assessment for a coastal reinforced concrete (RC) bridge under the combined effects of scour and uniform corrosion. Toward this goal, an extended pile shaft supported coastal RC bridge is taken as the benchmark and fifteen scenarios are generated to cover three regular scour conditions and five different corrosion levels. To inform the bridge management, the probabilistic distribution of the bridge service time corresponding to different corrosion levels is developed. Subsequently, the finite element model (FEM) for each scenario of the benchmark coastal highway RC bridge is developed, involving the soil-pile interaction and considering the uncertainty of structural and geotechnical parameters, as well as earthquake ground motions. The failure mode of the corroded extended pile shaft is identified as a flexural failure by comparing their flexural and shear capacities. Finally, a resilience loss ratio is proposed in this study for the first time to quantify the impacts of corrosion level and scour depth changes on seismic resilience across different ground motion intensities. Results indicate that both the seismic fragility and resilience decrease as the corrosion intensifies over time. Specifically, at a given intensity measure (IM) level, the resilience loss ratio increases as the corrosion level intensifies. For the studied benchmark bridge, the scour significantly increases the structural fundamental period, consequently reducing the curvature demand on the pile shaft. As a result, the scour generally decreases the failure probability and the earthquake-induced functionality loss for the extended pile shaft. As scour depth increases, the resilience loss of the bridge at a given corrosion level decreases.

Seismic fragility and resilience assessment of shallowly buried large-section underground civil defense structure in soft soils: Framework and application

The assessment of fragility of underground civil defense structures is of paramount importance in ensuring their functionality and enhancing safety in seismic-prone regions. This study aims to explore the evolution law of seismic fragility for a shallowly buried large-section underground civil defense structure in soft soils, employing advanced data-based approaches. To achieve this, a two-dimensional (2D) nonlinear finite element model of the soil-civil defense structure interaction system was established, integrating data-based parameters and insights. Subsequently, the cloud and incremental dynamical analysis (IDA) methods were employed to develop a probabilistic seismic demand model for the shallowly buried large-section civil defense structure, effectively utilizing data-based approaches to account for the nonlinear characteristics of the soil and the uncertainties of input seismic motions. Based on this model, seismic fragility curves were generated using different seismic intensity measures (IMs), and the evaluation of IMs was carried out by the efficiency and practicality analyses of IMs. These curves were then systematically compared with other existing empirical and analytical fragility curves. The developed fragility curves were subsequently applied to assess seismic risk and resilience for a typical underground civil defense structure in soft soils, offering valuable data-driven insights into the structure's performance under various scenarios. The results indicated that the seismic fragility of the civil defense structure increases with the softening of the soil. Moreover, this study highlighted the substantial influence of structural typologies and local soil conditions on the fragility of civil defense structures, particularly the seismic fragility of underground structures characterized by shallowly buried and large-section, and demonstrating the utility of data-based approaches in comprehending complex interactions. The efficiency and practicality analyses highlighted that ground surface IMs outperform bedrock IMs and acceleration-type IMs over velocity-type IMs. The proposed seismic fragility curves indicated that the exceedance probability for each damage state gradually approaches 100% with the increase of seismic intensity. Finally, a case study was presented on the use of seismic fragility curves to assessment of seismic risk and seismic resilience of civil defense structure. The outcomes of this research, enriched by data-based approaches, can serve as invaluable references for seismic performance assessment, risk analysis, and resilience evaluation of typical civil defense structures in similar soft soil sites.

Lifetime seismic resilience assessment of a sea-crossing cable-stayed bridge exposed to long-term scour and corrosion

In the marine environment, bridges are exposed to long-term foundation scour and structural corrosion. Consideration of scour and corrosion effects is of crucial importance for the lifetime seismic resilience assessment of existing sea-crossing bridges. This study presented a framework of seismic resilience assessment for sea-crossing bridges exposed to long-term scour and corrosion. Three typical recovery functions were employed to establish the post-earthquake functionality recovery model considering underwater repair. The time-variant model of scour depth was developed by fitting the annual measured data with the empirical function. The time-variant corrosion model induced by chloride was developed by considering different exposure zones. Then, the models of scour depth and corrosion were applied to an example cable-stayed bridge to assess the lifetime fragility and resilience of the bridge. It is concluded that the developed scour depth model agrees well with the measured data and can reasonably estimate the time-variant scour depth. Compared to scour, corrosion dominates the increase in lifetime fragility and resilience loss for the bridge. Scour and corrosion effects significantly reduce the bridge's functionality and increase the difficulty of the recovery process. Ignoring the effects of scour and corrosion can lead to an overestimation of the seismic resilience of the bridge.

Probabilistic seismic hazard assessment framework for Uganda: a stochastic event-based modelling approach

Uganda lies between the eastern and western arms of the East African Rift System, the largest seismically active rift above sea level. With increasing population, urbanisation and rapid construction, seismic risk in the country is escalating fast and is compounded by the high vulnerability of the building stock and inadequate disaster prevention and mitigation strategies. Hence, there is an urgent need to assess Uganda’s resilience against seismic risks. This paper presents a Monte-Carlo based probabilistic seismic hazard model for Uganda, as the first step towards the development of a seismic risk and resilience assessment framework for the country. In addition to fault segment data, earthquake catalogues are compiled for the period between 1900 and 2022 to estimate recurrence parameters for source zones in the area of interest. Area source zones incorporating focal mechanisms are used to stochastically model a national hazard framework for Uganda. A logic tree approach is applied to implement four ground motion prediction equations for both stable continental and active shallow crust geologies. Mean hazard curves, uniform hazard spectra, earthquake disaggregation and spectral pseudo-accelerations for major Ugandan cities are derived in addition to hazard maps for the country. The findings are largely consistent with previous regional studies and confirm that western Uganda is exposed to the highest level of seismicity. The model presented herein can be used to kick-start the update and continuous improvement of Uganda Seismic Design Code and the National Policy for Disaster Preparedness and Management.

Seismic Performance Assessment of Composite Frame–High-Strength Steel Plate Wall Core Tube Resilient Structural System

Against the backdrop of China’s continuous promotion of green and low-carbon transformation and the development of construction industrialization, high-strength composite structural systems have significant development prospects. However, their research and application in the field of construction are insufficient. In response to this issue, the study proposes a new high-performance structural system, namely the composite frame–high-strength steel plate wall core tube resilient structural system, which includes a core tube composed of double steel plate concrete composite shear walls and replaceable energy dissipation coupling beams, as well as composite frames. The highest strength grades of the steel plate and concrete used in the composite walls of the core tube are Q550 and C100, respectively. Using a 200 m building as an example, this study designs and establishes models for this high-performance structure and a conventional reinforced concrete frame–core tube structure. Subsequently, the dynamic elastoplastic time history analysis and seismic resilience assessment of structures are conducted under design basis earthquakes (DBEs), maximum considered earthquakes (MCEs), and extremely rare earthquakes (EREs). Research has shown that, compared to conventional structures, the thickness of shear walls of new high-performance structures can be effectively reduced, which helps decrease the self-weight of the structure and improve the available space in buildings. Additionally, high-performance structures exhibit a better performance in controlling the story drift ratio, lower plastic damage and overall stiffness degradation of the structure, and better seismic performance. The seismic resilience of the high-performance structure has been significantly enhanced, especially in terms of minimizing casualties, thereby better ensuring the safety of people’s lives and property.

Priority of developing public open spaces based on seismic resilience assessment for Tehran, Iran

Priority of developing public open spaces based on seismic resilience assessment for Tehran, Iran

Surrogate model-assisted seismic resilience assessment of the interdependent transportation and healthcare system considering a two-stage recovery strategy

In this study, a two-stage post-earthquake recovery strategy optimization model is proposed for determining resource inputs and obtaining the optimal restoration sequence after earthquakes. An artificial neural network-based surrogate model for predicting the functionality of the interdependent transportation and healthcare system (ITHS) is established to avoid the significant time consumption arising from traffic assignment and path selection in functionality evaluation and recovery optimization. It is applied to the two-stage optimization and resilience assessment under different seismic scenarios, which can greatly improve computational efficiency. The resilience-based two-stage optimization decision-making method assisted by the surrogate model is applied to a real example and provides practical support for recovery strategies of the ITHS.

Seismic Resilience of Interdependent Built Environment for Integrating Structural Health Monitoring and Emerging Technologies in Decision-Making

The functionality of interdependent infrastructure and resilience to seismic hazards has become a topic of importance across the world. The ability to optimize an engineered solution and support informed decision-making is highly dependent on the availability of comprehensive datasets and requires substantial effort to ingest into community-scale models. In this article, a comprehensive seismic resilience modeling methodology is developed, with detailed multi-disciplinary datasets, and is explored using the state-of-the-science algorithms within the interdependent networked community resilience modeling environment (IN-CORE). The methodology includes a six-step chained/linked process consists of: (a) community data and information, (b) spatial seismic hazard analysis using next-generation attenuation, (c) interdependent community model development, (d) physical damage and functionality analysis, (e) socio-economic impact analysis and (f) structural health monitoring (SHM) and emerging technologies (ET). An illustrative case study is presented to demonstrate the seismic functionality and resilience assessment of Shelby County in Memphis, Tennessee, in the United States. From the discussion of results, it is then concluded that data from structural health monitoring and emerging technologies is a viable approach to enhance characterising the seismic hazard resilience of infrastructure, enabling rapid and in-depth understanding of structural behaviour in emergency situations. Moreover, considering the momentum of the digitalization era, setting an holistic framework on resilience that includes SHM and ET will allow reducing uncertainties that are still a challenge to quantify and propagate, supported by sequential updating techniques from Bayesian statistics.

Seismic Resilience Evolution of Shield Tunnel with Structure Degradation

The structural performance of shield tunnel structures is highly susceptible to degradation under complex environmental loads, with the most common manifestation being bolt preload loss. In this study, a shield tunnel numerical simulation model was established to analyze the seismic response of shield tunnels with varying degrees of bolt preload loss. Firstly, the deformation patterns of shield tunnel structures under seismic loads were analyzed. Subsequently, ellipticity and joint opening were selected as seismic resilience assessment indicators based on the mechanical response. A seismic resilience assessment model was then established, including three states: normal state, affected state, and recovered state. The results show a direct relationship between the recovery capacity of tunnel structures and the initial performance of the lining structure, as well as the magnitude of the load. The lower the degree of structure degradation, the greater the structural recovery capacity. Additionally, there is a positive correlation between residual deformation and the initial performance loss of shield tunnel structures, as well as the intensity of seismic loads. This study contributes to enriching the theoretical framework for the seismic resilience assessment of shield tunnels, which have significant implications and provide valuable references for engineering safety.

Fragility functions for corroded reinforced concrete columns

Fragility functions for structural members play an important role in the FEMA P-58 methodology for the seismic performance assessment of structures. In this study, fragility functions were developed for aged reinforced columns with corroded reinforcing bars. To this end, an experimental database containing 120 specimens subjected to repeated cyclic loads was compiled from 20 previous studies. The experimental specimens were categorized into three groups: no corrosion damage (NCD), low corrosion damage (LCD), and high corrosion damage (HCD). These damage states were identified by experimental hysteretic responses in terms of the drift angle, which are linked to common methods of repair, including structural repair, structural enhancement, and component replacement. The obtained drift angles were used to fit the log-normal fragility functions of the NCD, LCD, and HCD columns. The effect of reinforcement corrosion was examined by comparing the fragility functions of uncorroded and corroded columns. According to the principles suggested by FEMA P-58, the developed fragility functions were mostly judged to have a high level of quality. The fragility medians of the corroded columns showed a clear decreasing trend along with an increasing degree of corrosion damage. However, the corrosion of the reinforcing bars had a limited effect on the fragility dispersion. The maximum differences in the exceedance probability were calculated by comparing the fragility curves for the LCD and NCD columns, which were greater than 20 % for all concerned damage states. For the HCD columns, the corrosion of the reinforcing bars led to the maximum difference in the exceedance probability, even beyond 50 %, compared to the results for the NCD columns. The above results reveal the significant effect of the corrosion of the reinforcing bars. The specific fragility functions developed for the corroded reinforced concrete columns will facilitate the seismic loss and resilience assessment of aging reinforced concrete building structures.

Nonlinear analysis model and seismic resilience assessment of LEM-filled CFS residence

Lightweight EPS materials (LEM)-filled cold-formed steel (CFS) shear wall structure is a new type of green, low-carbon and prefabricated rural residence, which has drawn in expanding consideration due to the promotion of the rural revitalization strategy. However, most of the existing research on this type of residence has focused on its behaviours of components, with little attention was paid to its overall response to resist earthquake disasters. During the past two decades, significant advancements have been made in effectively mitigating building collapses and reducing casualties resulting from earthquakes. Thus, the concept of seismic resilience is proposed, and the seismic performance requirements of structural design have been elevated from “safety” to “resilience”. To analyze the seismic resilience of LEM-filled CFS residence, this paper proposed a strut and tie- equivalent spring model to establish the simplified analysis model of a single composite wall, and the precision of the model was confirmed by test results, in which the nonlinear characteristic and the supporting effect of fillers was considered. Subsequently, three LEM-filled CFS residences are designed using the direct displacement-based design method. Then the three-D models are established for nonlinear analysis, and the inter-drift ratio (IDR) and residual inter-drift ratio (RIDR) are adopted to estimate the seismic response of the three archetypes. The seismic resilience of the three archetypes are assessed based on FEMA P58. This paper would provide a guidance for the nonlinear analysis and seismic resilience assessment of this type of residences, and promote the application and popularization of this kind of residence.

An asynchronous simulation algorithm for post‐earthquake functional recovery of interdependent infrastructure systems

AbstractThe seismic resilience assessment of infrastructure systems not only requires evaluation of immediate damages after earthquakes, but also estimate of functional losses during the post‐earthquake recovery process. Infrastructure systems are interdependent during post‐earthquake recovery. To accurately consider this interdependence in resilience assessment, many studies have adopted post‐earthquake recovery simulation methods. In this study, an efficient asynchronous simulation algorithm is proposed, which does not require synchronous checking of the states of infrastructure elements at each time step, but rather asynchronously derives the functional recovery time of each element based on its dependency relationships. This study proves that the time complexity of the proposed asynchronous algorithm is proportional to the scale of the infrastructure system and is independent of the time step size. Furthermore, a case study of post‐earthquake recovery of a portfolio of buildings considering safety cordon areas is used to demonstrate that the asynchronous algorithm can significantly reduce the simulation time of large‐scale infrastructure systems compared to synchronous algorithms.

Fragility and Recovery Models for Energy, Water, and Wastewater Systems for Seismic Regional Risk and Resilience Assessment: State-of-the-Art Review and Database

Fragility and Recovery Models for Energy, Water, and Wastewater Systems for Seismic Regional Risk and Resilience Assessment: State-of-the-Art Review and Database

Probabilistic framework for seismic resilience assessment of transmission tower-line systems subjected to mainshock-aftershock sequences

Immediate damage to electricity transmission systems after strong earthquakes can significantly cause widespread power outages and impede maintenance activities. Whereas previous seismic resilience assessments have investigated comprehensively the recovery capability of structures under isolated mainshocks, the effect of aftershocks has received less attention. This paper introduces a probabilistic framework for resilience assessment incorporating the effect of aftershocks and utilizes it to investigate the seismic performance of a transmission tower-line system (TTLS) under mainshock-aftershock (MSAS) sequences. Exceedance probabilities for different damage states of the TTLS are analyzed using fragility curves. Multiple decision variables (including functionality loss, recovery time, recovery function and resilience indicator) are subsequently calculated to quantify the effect of aftershocks. Meanwhile, the seismic resilience of the TTLS is further assessed by considering the uncertainties associated with those decision variables. The results reveal that aftershocks exert a significant influence on the seismic resilience of the TTLS, particularly when it experiences minor or moderate damage following the mainshocks. However, as the damage to the TTLS worsens due to larger mainshocks, the role of subsequent aftershocks becomes comparatively less influential. The proposed framework provides valuable insights for infrastructure systems before and after earthquake, effectively mitigating the adverse effects of sequential earthquakes.

Physics-Informed Deep Learning-Based Real-Time Structural Response Prediction Method

High-precision and efficient structural response prediction is essential for intelligent disaster prevention and mitigation in building structures, including post-earthquake damage assessment, structural health monitoring, and seismic resilience assessment of buildings. To improve the accuracy and efficiency of structural response prediction, this study proposes a novel physics-informed deep-learning-based real-time structural response prediction method that can predict a large number of nodes in a structure through a data-driven training method and an autoregressive training strategy. The proposed method includes a Phy-Seisformer model that incorporates the physical information of the structure into the model, thereby enabling higher-precision predictions. Experiments were conducted on a four-story masonry structure, an eleven-story reinforced concrete irregular structure, and a twenty-one-story reinforced concrete frame structure to verify the accuracy and efficiency of the proposed method. In addition, the effectiveness of the structure in the Phy-Seisformer model was verified using an ablation study. Furthermore, by conducting a comparative experiment, the impact of the range of seismic wave amplitudes on the prediction accuracy was studied. The experimental results show that the method proposed in this paper can achieve very high accuracy and at least 5000 times faster calculation speed than finite element calculations for different types of building structures.

Resilience-based post-earthquake recovery strategies for substation systems

Electrical substation systems require significant manpower and material resources for repair after an earthquake; thus, repair efficiency directly affects economic loss. To quantify the functional recovery process of substation systems, this study proposes a seismic resilience assessment framework based on the functional characteristics of substation systems. Reliability models of the equipment and systems were constructed to characterise the structural connection features and power transmission paths of substation systems, and the system functional state matrix was obtained through a seismic simulation. Moreover, factors influencing functional recovery and repair path control parameters were proposed to determine efficient post-earthquake recovery strategies. The Monte Carlo method was used to construct a post-earthquake recovery strategy analysis framework for a substation system. By analysing a typical 220 kV substation using static-based repair strategies, we obtained the functional recovery process and seismic resilience level. Furthermore, based on the actual functional requirements, a dynamic recovery strategy analysis method was proposed based on an improved genetic algorithm. Notably, optimal recovery strategies for different earthquake intensities and recovery priorities were obtained through iterative reproduction analysis.

Full-scale experimental study on seismic performance of repaired precast shear walls

To improve the framework of seismic resilience assessment and design of precast concrete (PC) structures, and to contribute to the development of loss consequence functions for PC shear walls (PCSWs), a repair method for seismically damaged PCSWs using grouted sleeve connections was investigated and the seismic performance of repaired PCSWs (RPCSWs) was verified in this study. Specifically, full-scale experimental investigations were conducted involving a reinforced concrete shear wall (RCSW) as a counterpart and two RPCSWs, which were repaired based on two damaged PCSWs (one without grouting defects and the other with a 60% defect ratio) previously tested, aiming to identify the effect of grouting defects on the damage mode of PCSWs and the corresponding repair effect. Two specimens were repaired with reference to the concrete replacement method for the RCSW. The seismic performances of the RCSW, two RPCSWs, and PCSW without grouting defects were compared. Test results indicated that the damage evolution and failure modes of the RPCSWs were similar with those of the RCSW and PCSW without grouting defects. The relative differences in the loads and displacements of the critical points of the four specimens were generally less than 5.9%. Although the seismic performance of the PCSW with grouting defects was significantly different from those of the RCSW and PCSW without grouting defects, it was restored, thus verifying the reliability and versatility of the repair method. The research outcomes can provide important reference for the repair of seismically damaged PCSWs connected using grouted sleeves as well as lay a foundation for advancement of loss consequence functions for such shear walls.

Quantification and Reduction of Uncertainty in Seismic Resilience Assessment for a Roadway Network

The nation’s transportation systems are complex and are some of the highest valued and largest public assets in the United States. As a result of repeated natural hazards and their significant impact on transportation functionality and the socioeconomic health of communities, transportation resilience has gained increasing attention in recent years. Previous studies on transportation resilience have heavily emphasized network functionality during and/or following a scenario hazard event by implicitly assuming that sufficient knowledge of structural capacity and environmental/service conditions is available at the time of an extreme event. However, such assumptions often fail to consider uncertainties that arise when an extreme hazard event occurs in the future. Thus, it is essential to quantify and reduce uncertainties to better prepare for extreme events and accurately assess transportation resilience. To this end, this paper proposes a dynamic Bayesian network-based resilience assessment model for a large-scale roadway network that can explicitly quantify uncertainties in all phases of the assessment and investigate the role of inspection and monitoring programs in uncertainty reduction. Specifically, the significance of data reliability is investigated through a sensitivity analysis, where various sets of data having different reliabilities are used in updating system resilience. To evaluate the effectiveness of the model, a benchmark problem involving a highway network in South Carolina, USA is utilized, showcasing the systematic quantification and reduction of uncertainties in the proposed model. The benchmark problem result shows that incorporating monitoring and inspection data on important variables could improve the accuracy of predicting the seismic resilience of the network. It also suggests the need to consider equipment reliability when designing monitoring and inspection programs. With the recent development of a wide range of monitoring and inspection techniques, including nondestructive testing, health monitoring equipment, satellite imagery, LiDAR, etc., these findings can be useful in assisting transportation managers in identifying necessary equipment reliability levels and prioritizing inspection and monitoring efforts.