Fragility Assessment Research Articles

Fragility Assessment of Tunisian Banks Amid Crisis: Index-Based Detection and Evaluation Strategies

The banking sector plays a pivotal role in the economic stability of any nation, and assessing the fragility of banks becomes paramount during times of crisis. This study focuses on the Tunisian banking landscape, employing innovative index-based methods to detect and evaluate fragility in the face of economic upheavals. The research combines a comprehensive analysis of financial indicators, market dynamics, and macroeconomic factors to construct a robust fragility index tailored to the unique characteristics of Tunisian banks. The methodology integrates both quantitative and qualitative metrics to gauge the vulnerability of the banking sector, providing a nuanced understanding of potential stress points. By identifying early warning signals through the proposed index, policymakers and financial institutions can proactively address emerging challenges, contributing to the resilience and stability of the banking sector in Tunisia. The study not only enhances the academic discourse on financial fragility assessment but also offers practical insights for regulatory bodies and industry stakeholders to strengthen the foundations of the Tunisian banking system in times of crisis.

Simplified state‐dependent seismic fragility assessment

AbstractEarthquakes are clustered in time and space; therefore, structures may be subjected to multiple consecutive instances of potentially damaging shaking, with insufficient in‐between time for repair operations to take place. Methodologies to evaluate the risk dynamics in this situation require vulnerability models that are able to capture the transitions between damage states, from the intact conditions to failure, due to multiple damaging earthquakes, that is, state‐dependent fragility curves. One of the state‐of‐the‐art methods for the assessment of structure‐specific state‐dependent fragility curves relies on a variant of incremental dynamic analysis (IDA), which is often termed back‐to‐back or B2B‐IDA. The computational costs typically involved in B2B‐IDA motivate attempts to simplify the evaluation of state‐dependent fragility curves. This paper presents a simplified method for multi‐story moment‐resisting frame structures, based on pushover analysis in conjunction with a predictive model for the main features of a damaged structural system, such as residual deformations and loss of stiffness and/or strength. The predictive model enables the probabilistic definition of the post‐earthquake pushover curve of a damaged structural system, given the displacement demand imposed by a preceding damaging shock. The state‐dependent fragility curves are then evaluated via IDA of single‐degree‐of‐freedom oscillators based on these pushover curves. Illustrative applications validate the ability of the proposed methodology to provide state‐dependent fragilities with reduced computational costs compared to the back‐to‐back IDA method.

A novel framework for effective structural vulnerability assessment of tubular structures using machine learning algorithms (GA and ANN) for hybrid simulations

Abstract Seismic vulnerability assessments are conventionally conducted by using sophisticated nonlinear analytical models, leading to aggressive computational demands. Previous attempts were made to reduce computational efforts for establishing vulnerability assessment of structures; however, the area of super tall and tubular structures still faces considerable lack. Advent of efficient machine learning (ML) has enabled engineering practitioners to automate the processes for fragility analysis; however, its application for high-rise tubular structures is not yet exploited, and most implementations are limited to basic ML. In this work, an attempt was made to reduce computational demand for the fragility assessment process for tubular structures by employing genetic algorithms (GAs) for nonlinear structural modeling, and development of artificial neural network (ANN) using deep learning for fragility development. Consequently, a simple lumped parameter model had been developed using open-source code of ZEUS-NL, containing parameters selected by GA to acutely account for convoluted interactive behavior of structural systems and dynamic demands. Subsequently, incremental dynamic analysis (IDA) was performed on the optimized model. A new framework has been established to develop and train ANN architecture by amalgamating Weka’s capability of data preprocessing with deep learning. The established ANN model resulted in correlation coefficient of 0.9972 and R 2 of 0.95, demonstrating adequate performance.

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.

Virtual modelling based fragility assessment of structures under bushfire propagation

Driven by increased human activities in rural-urban interfaces, the construction of residential or commercial buildings in these areas is experiencing a notable growing trend. In comparison to those built in urban regions, these structures, constructed in rural-urban interfaces, are in closer proximity to natural vegetation, therefore facing a heightened bushfire risk. The timely execution of Structural Protection Plans (SPP) is of utmost importance in the case of bushfire threats, where a swift response within a short timeframe is necessary, considering the diverse fragility characteristics of structural components. To address this, the present study introduces a novel framework for assessing the fragility of typical residential structures under both low and high wind speed conditions, specifically focusing on three key structural components: window frames, walls, and roofs. The assessment of structural probability-based fragility is performed using the newly developed limit state function and takes into account the influence of multiple non-deterministic factors, including vegetative conditions, wind speed, different temperature thresholds of structural components, and fire response time. Furthermore, to enable rapid prediction of structural probability-based fragility on the fireground, a virtual modelling (VM) technique, named extended support vector regression (X-SVR), is introduced and incorporated into the proposed fragility assessment framework. The efficiency and accuracy of this virtual modelling technique in assessing the bushfire fragility of structures under different wind speed intervals have been investigated and validated through a comprehensive case study of a real Australian house. The proposed framework is poised to provide valuable insights into optimizing SPP by swiftly identifying the most fragile structural components in practice.

Efficient seismic fragility assessment method for a frictional isolated bridge constrained by shape memory alloy cables under pulse-like ground motion

Utilizing shape memory alloy (SMA) cables to constrain frictional isolated bridges is considered an efficient approach to limit bearing displacement and prevent serious earthquake damage. Accurate seismic fragility assessments of this kind of structure are crucial for aseismic decision making. However, traditional assessment methods cannot quantitatively describe the impact of the pulse effect on pulse-type seismic motions, which may lead to inaccurate assessment results. Therefore, this study deduced a novel equation for seismic fragility assessment that considers the pulse effect. Firstly, the impact of the pulse effect is quantified. Then, a multivariable probabilistic seismic demand model (MV-PSDM) is developed that is conditioned on the pulse period, peak ground velocity, structural period, maximum friction coefficient and SMA consumption. Based on the MV-PSDM, an effective approach for predicting structural seismic vulnerability is recommended, which does not require finite element modeling or nonlinear time-history analysis. Finally, a novel equation for calculating the intensity measure corresponding to 50% damage probability is deduced. The results indicate that increased friction coefficients and SMA consumption can enhance structural seismic safety under pulse-type ground motions. However, when the ratio of pulse period to structural period is too small, increased friction coefficients or SMA consumption have no meaningful effect on the seismic fragility of the structure.

Performance Assessment of Reinforced Concrete Bridges Under Coupled Horizontal and Vertical Ground Motions Using Fragility Surfaces

ABSTRACT The objective of this study is to explore the seismic fragility of reinforced concrete bridges, specifically in response to the vertical components of ground motions, utilizing fragility surfaces. The examination of bridge responses involves the application of optimally selected intensity measures through three-dimensional nonlinear time-history analyses, encompassing uncertainties in both superstructure materials and soil–structure interaction effects. In this investigation, an extended Probabilistic Seismic Demand Model (e-PSDM) is employed, leveraging fragility surfaces to concurrently consider vertical and horizontal excitations. The results obtained from this approach are compared with traditional fragility curves. This study emphasizes Pile-cap displacement and drift ratio as pivotal engineering damage parameters, acknowledging their sensitivity to the influences of both soil–structure interaction effects and vertical ground motion. The fragility surfaces derived from the study reveal a correlation between increased vertical spectral accelerations and elevated probabilities of surpassing both slight damage and collapse limit states. These observations underscore the critical significance and practical utility of fragility surfaces in the context of performance-based seismic assessment and design for reinforced concrete bridges. The findings from this research contribute valuable insights into the nuanced behaviour of reinforced concrete bridges under seismic conditions, emphasizing the relevance of incorporating vertical components in fragility assessments for a more comprehensive understanding of structural vulnerability.

Fragility Assessment of a Long-Unit Prestressed Concrete Composite Continuous Girder Bridge with Corrugated Steel Webs Subjected to Near-Fault Pulse-like Ground Motions Considering Spatial Variability Effects

Prestressed concrete composite girder bridges with corrugated steel webs (PCCGBCSWs) are extensively employed in bridge construction because of their low dead weight, fast construction, and high prestressing efficiency. Moreover, PCCGBCSWs will experience deformation and failure of the corrugated steel webs, including steel fatigue and fracture, during earthquakes. These changes will introduce safety hazards, which can be addressed via bridge disaster prevention and mitigation. Because near-fault pulse-like ground motions (NFPLGMs) have high peak accelerations, these motions can easily cause damage to a bridge. Therefore, in this study, a seismic fragility assessment is performed for long-unit PCCGBCSWs subjected to NFPLGMs considering spatial variability effects, and a sensitivity evaluation of the seismic fragility is conducted considering girder type, bearing type, ground motion type, and apparent wave velocity to offer a point of reference for seismic design. The results show that PCCGBCSWs are less vulnerable than concrete bridges. The shock absorption effect of the friction pendulum bearing is better than that of the viscous damper. The impact of NFPLGMs on bridges is greater than that of near-fault non-pulse-like ground motions (NFNPLMs) and far-fault ground motions (FFGMs). The seismic fragility under nonuniform excitation conditions is greater than that under uniform excitation conditions, showing an increasing trend with decreasing apparent wave velocity.

An extended generalized conditional intensity measure method for aftershock ground motion selection

AbstractThis study proposes an extended generalized conditional intensity measure (EGCIM)‐based approach to selecting aftershock ground motions that match the target aftershock EGCIM distributions. The main purposes of the proposed methodology are threefold: (a) to consider the multiple characteristics of aftershock ground motions (e.g., amplitude, frequency contents, cumulative effects, and duration), (b) to account for the correlations between mainshocks (MS) and aftershocks (AS) as well as cross‐correlations between AS IMs, and (c) to associate with the conventional mainshock GCIM approach to enforce mainshock‐consistency for practical applications. For these purposes, three components of the EGCIM methodology for aftershock ground motion selection are utilized: (1) the multivariate aftershock EGCIM distributions of any vector of aftershock intensity measures (IMs) are constructed conditioned on two MS‐AS IMs, (2) the correlations between mainshocks and aftershocks as well as the cross‐correlations between AS IMs are considered, and (3) the random realizations of aftershock IMs are generated as a target using the aftershock EGCIM distributions to select aftershock ground motions from the specific database. The proposed methodology is applied to a case study in the LPCC station in New Zealand, whose aftershock EGCIM distributions of the considered 18 IMs are constructed for the case scenario. Among them, the correlations between mainshocks (MS) and aftershocks (AS) as well as the cross‐correlations between AS IMs are determined using the total residuals (epsilons) based on 662 real MS–AS ground‐motion pairs. Several examples are then discussed to illustrate the application of the proposed aftershock EGCIM approach, including the comparison of the aftershock acceleration spectrum with the ASK14 model and the effects of different components of the aftershock IM weight vector. Then, the proposed approach is compared with the conventional aftershock synthesis methods. It is observed that the conventional methods perform biased representations of different aftershock characteristics, of which the limitations are improved in the proposed approach. Moreover, a sensitivity study is performed for a typical midrise structure to investigate the effects of aftershock ground motion selection on the aftershock fragility analysis. The results indicate that the selection of aftershock records considering different AS characteristics has a notable impact on the aftershock fragility assessment. The uncertainties associated with record‐to‐record variations in aftershock fragility analysis can be effectively reduced by using the proposed selection approach that incorporates the comprehensive ground motion characteristics. The findings in this study promote the extension of the existing methods for aftershock ground motion selection, which can be applied to structural design or seismic risk analysis considering the aftershock effects.

A Simplified Approach of Analytical Seismic Fragility Analysis Using the Endurance Time Method

ABSTRACT The endurance time (ET) method is an effective dynamic analysis method for seismic response analysis of structures. It has been recently used for analytical fragility analysis. However, the available ET-based fragility analysis methods have two limitations: 1) the prediction error of the structural median responses estimated by the ET method is ignored; and 2) the record-to-record variability inherent earthquake ground motions is not well considered. To overcome the above limitations, another ET-based fragility analysis method is proposed, where only three times of ET nonlinear analyses are required. To do this, three specific endurance time excitation functions (ETEFs) are generated in correspondence to the mean and 16% and 84% percentile of response spectra of a selected suite of ground motion records (i.e. ETE F m , ETE F v 1 and ETE F v 2 , respectively). The structural response under ETE F m is used to estimate the median response of structures under the selected suite of ground motion. Moreover, the structural responses under ETE F v 1 and ETE F v 2 are used to quantify the record-to-record variability in earthquake ground motions. The fragility relationships are developed by both point and interval estimate methods since another logarithmic standard deviation is introduced to account for the difference between the median responses predicted using ETE F m and those predicted by the dynamic analysis. To validate the proposed method, two RC frame structures with six and nine stories are taken as the study cases. The fragility results based on the proposed ET-based method and those based on the cloud method are compared. It is found that the proposed ET-based fragility analysis method could generate reliable fragility estimation, whereas requiring limited computation cost. The proposed method would provide another simplified way for the rapid fragility assessment of structures.

Utilizing advanced machine learning approaches to assess the seismic fragility of non-engineered masonry structures

Seismic fragility assessment provides a substantial tool for assessing the seismic resilience of these buildings. However, using traditional numerical methods to derive fragility curves poses significant challenges. These methods often overlook the diverse range of buildings found in different regions, as they rely on standardized assumptions and parameters. Consequently, they may not accurately capture the seismic response of various building types. Alternatively, extensive data collection becomes essential to address this knowledge gap by understanding local construction techniques and identifying the relevant parameters. This data is crucial for developing reliable analytical approaches that can accurately derive fragility curves. To overcome these challenges, this research employs four Machine Learning (ML) techniques, namely Support Vector Regression (SVR), Stochastic Gradient Descent (SGD), Random Forest (RF), and Linear Regression (LR), to derive fragility curves for probability of collapse in terms of Peak Ground Acceleration (PGA). To achieve the research objective, a comprehensive input/output dataset consisting of on-site data collected from 646 masonry walls in Malawi is used. Adopted ML models are trained and tested using the entire dataset and then again using only the most highly correlated features. The study includes a comparative analysis of the efficiency and accuracy of each ML approach and the influence of the data used in the analyses. Random Forest (RF) technique emerges as the most efficient ML approach for deriving fragility curves for the surveyed dataset in terms of achieved lowest values for evaluation metrics of the ML methods. This technique scored the lowest Mean Absolute Percentage Error (MAPE) of 16.8 %, and the lowest Root Mean Square Error (RMSE) of 0.0547. These results highlight the potential of ML techniques, particularly RF, in derivation of fragility curves with proper levels of accuracy.

Performance-based plastic design and seismic fragility assessment for chevron braced steel frames considering aftershock effects

Observations from past earthquakes demonstrated that buildings in high seismic regions might be exposed to several aftershocks following the mainshock which can significantly increase the damage level. Since aftershocks have the potential to increase the vulnerability of buildings damaged under mainshocks, it is crucial to consider aftershock effects in the structural design phase. Performance-based Plastic Design (PBPD) method is an innovative seismic design method in which the building designed by this method shows a desirable performance under severe ground motions. PBPD allows the designer to avoid time-consuming trial and error process of analyses that are usually done in Performance-based Design method to reach a desirable performance. However, this efficient method is only valid for mainshocks only and does not consider aftershock effects in the structural design process. In this study, initially, the seismic performance (interstory drift and plastic hinges distribution) of the three 3-, 6-, and 9- story PBPD designed Chevron-braced Steel frames (CBSF) are compared under mainshocks (MS) and mainshock-aftershock (MS-AS) sequences. Subsequently, a PBPD method is developed for CBSFs considering the aftershock effects in the structural design process. Incremental dynamic analysis (IDA) has been performed using a suite of mainshocks and aftershock ground motions to develop a design base shear modification factor. Using the developed method, the performance of CBSFs under MS and MS-AS sequences is evaluated and compared with the existing PBPD method. Fragility curves are developed to compare the seismic vulnerability of the frames designed based on PBPD and proposed PBPD methods under MS-AS sequences. The outcomes of this study provide a practical design approach for CBSFs under MS-AS sequences and shows that the structures designed using developed PBPD method show more desirable behavior under MS-AS sequences compared with the structures designed using the conventional PBPD method.

Optimizing seismic fragility assessments for high-speed railway track bridges: a novel multi-parameter methodology and intensity measure selection

This research innovatively presents a multi-parameter seismic fragility analysis methodology anchored on Blending ensemble learning tailored for the high-speed railway track-bridge (HSRTB) system. Leveraging ensemble machine learning models, a seismic demand model encapsulating multiple earthquake intensity measures (IMs) is formulated. The research progresses to deduce the mean seismic fragility representations for single, dual, and composite earthquake parameters. Key findings of this investigation underscore that the advanced methodology aligns well with the Monte Carlo (MC) fragility, signifying its robustness. Crucially, earthquake IM parameters, Sa(0.5) and Sa(0.3)_ASI, emerged as the optimal choices for singular and dual-parameter seismic fragility delineations. Further enriching this research, a composite parameter optimization technique rooted in multi-CPU genetic algorithms is proposed. This avant-garde method remarkably minimizes the fragility estimation error, emphasizing its unparalleled efficacy in enhancing the precision of fragility evaluations.

Fragility Analysis Framework for Bridges Subjected to Successive Natural Hazards

Bridges are key parts of transportation networks and hence, their post-hazard condition is vital for the recovery of the regions affected by natural hazards. However, the fact that they are often subjected to more than one destructive natural hazard during their life span resulting in accumulated damage that may influence their capacity has attracted relatively little research interest, while almost no design standards take it into consideration. The multiple hazard events may be successive single events, separated by considerable time intervals (e.g. an earthquake followed by a flood event), combined or cascading multiple-hazard events (e.g, landslide after an earthquake), or even simultaneous events. The main objective of this study is to propose an effective framework for the development of multiple-hazard fragility curves of bridges considering the effect of subsequent events and taking into account different possible damage scenarios of the bridge critical components, i.e. piers, bearings and the abutment-backfill systems. In this framework, the effect of the damage level of the critical components and their interdependence on the fragility assessment for multiple events is examined and compared with the bridge fragility for single events. A pilot case study is also included in the present work, aiming to highlight the effect of the initial damage state on the final fragility estimate of a typical riverine bridge.

Enhanced Stochastic Approaches of 1 : 4 PCCV in Nuclear Power Plant: Uncertainty Quantification and Fragility Assessment

Probabilistic evaluation of the internal pressure capacity before excessive leakage is essential for ensuring preemptive response in case of a severe accident in a prestressed concrete containment vessel (PCCV) subjected to internal pressure in a nuclear power plant. Therefore, in this study, we conducted a fragility analysis to evaluate the probabilistic internal pressure capacity for damage states before excessive leakage. Three damage states were classified, and a finite element (FE) model was developed based on the experimental test results of a 1 : 4 scale PCCV under the overpressurization condition at Sandia National Laboratory. The three damage states were determined as the onset of inelastic behavior (DS1), onset of leakage (DS2), and excessive leakage (DS3). Fragility analysis was performed using a validated FE model to consider uncertainties in material properties and prestressing force. The Latin hypercube sampling method was used to perform uncertainty quantification, and normality tests verified that the samples exhibited normal distributions. The internal pressure capacity variability in DS1 and DS2 was higher than that in DS3. DS1 is the point at which the compressive deformation caused by the prestressing force was converted into tensile deformation because of the increase in the internal pressure, which resulted in tensile concrete cracking. Furthermore, DS2 is the state in which localized damage of the liner occurred and cracks in the concrete spread. Thus, the internal pressure capacity for DS1 and DS2 exhibited high variability because of the uncertainty of the prestressing force and material properties. Moreover, the median capabilities of DS1, DS2, and DS3 were ~1.85, 2.61, and 3.45 times the design pressure, respectively. Therefore, material and structural uncertainties in nuclear power plants should be appropriately considered, and a conservative assessment of the damage state before excessive leakage should be performed for preemptive response in the case of severe accidents.

Fragility curves derivation under fire actions for different types of bridges

The Italian infrastructure network of bridges is complex, due to the orography of the territory and the presence of different hazard sources. Furthermore, during their service life these infrastructures can be subjected also to extreme actions such as the fire. This paper presents a procedure for the fragility curves derivation under fire actions for different types of bridges. The novelty the work is to apply the fragility assessment also to the fire resistance aspects, especially related to the infrastructures. Two case study pilot R.C. and composite steel-R.C. bridges are modelled by assigning combined loads according to the fire load combination and deriving structural response under fire scenarios. By using the linear regression, the structural response parameters of the bridges are correlated with fire intensity, considering different performance levels. Finally, lognormal fragility curves are obtained, measuring the capacity of the case study bridges. The study also shows which of the fire scenario parameters can be better correlated to the structural response of the bridges.

Drift-based fragility assessment of nonductile reinforced concrete columns failing in shear under cyclic loading

The paper presents drift-based fragility functions for nonductile reinforced concrete (RC) columns having light transverse reinforcement steel ratio which predominantly fail in shear. These fragilities were developed for four key damage states (i.e., light cracking, severe cracking, shear failure, and loss of axial load carrying capacity) associated with their structural performance observed in laboratory tests and repairability. For this purpose, experimental results of 71 column specimens tested under cyclic lateral loading were collected from 22 research programs; particularly, drift ratios associated to the column specimens tested to reach axial collapse. It is shown that the shear span-to-depth ratio and level of axial load ratio have influence on the drift-based fragilities associated to the damage states considered in this investigation. Additionally, several sources of epistemic uncertainty due to specimen-to-specimen, finite-sample, column shear span-to-depth aspect ratio, and level of axial compression load were quantified from the experimental database. The introduced drift-based fragilities are a very useful tool to assess the expected damage of existing buildings, such as school buildings that might exhibit the short captive column effect.

Towards reliable seismic fragility assessment of highway bridges with oblong columns considering the drift-based capacity directionality effect

Highway bridges in seismic zones are commonly designed with oblong columns, featuring different force-displacement relationships and seismic capacities along different response directions. However, the state-of-art seismic fragility assessment treats seismic demand and capacity models as two independent models, which cannot capture the in-between directional dependence and correlation for oblong columns. This study develops direction-dependent seismic capacity limit state models and proposes a multi-step analysis framework to assess the seismic fragility of highway bridges with flexure-controlled oblong columns. Cyclic pushover analyses are conducted along different loading directions to identify direction-sensitive column drift ratios against four damage states. These drift ratios are utilized to regress a closed-form model, namely the directional capacity ratio model, to quantify the changes in drift capacities as a function of the column response angle. This model is integrated into an analysis framework to directly simulate the demand-capacity ratio (DCR) time history, where the peak value is utilized to assess the seismic fragility of the oblong column. The case study indicates that the most severe seismic damage to an oblong column is not necessarily along its principal axis. The proposed analysis framework outperforms existing approaches in having more reliable fragility estimates for the oblong column and bridge system.

Seismic Fragility Curves of Combined Multiple Tunnel Complexes in Soft Soils

Seismic fragility assessment is the probability of damage exceeding a certain design limit. The dynamic performance of a combined multiple tunnel complex is less explored and requires thorough study. This research is based on the numerical approach to evaluate the damage caused to the two new types of tunnel complexes, i.e. twin and triple tunnel complexes in a soft soil profile. A two-dimensional (2D) finite element analysis is performed to determine the induced bending moments for each of the tunnel complexes and develop the seismic fragility curves. A set of full acceleration-time histories are applied to the soil–tunnel complex system by varying embedment depths in different soft soil profiles. From the results, it is concluded that increasing the embedment ratio results in an increased probability of tunnel damage. The developed fragility curves are also inter-compared for both the tunnel complexes to evaluate the better performer during a seismic event. This study serves as an initial step toward the guidelines to determine the percentage of incurred damage and design the combined multiple tunnel complex in a seismic-prone area.

Performance indices and fragility assessment of steel frame structure with bolted low-yield-point steel connection components

A resilient steel frame structure equipped with replaceable ductile and energy-dissipative connection components was developed in this study. Connective components, such as splice plates and T-stubs are made of low-yield-point steels (LYPs), which have superior ductility and energy dissipation capacity. The plastic hinge can be separated from the column surface by local weakening, thus concentrating local damage within low-yield-point steel connection components (LYP-Cs) to effectively enhance ductility of the structure. Five-story and ten-story bolted steel frame structures with four configuration parameters were designed to investigate the seismic performance and damage development of steel frame structures with LYP-Cs (SF-LYP-Cs). Corresponding numerical models were established. Welded steel frame structures with traditional reduced beam sections (SF-RBS) were also established for comparison. Pushover analyses were conducted to explore the effect of structural fuses and to obtain multi-stage performance indices of the resilient steel frame structure based on energy dissipation proportion (EDP) and damage behavior. Incremental dynamic analysis was performed to verify proposed performance indices, and seismic performance of SF-LYP-Cs was evaluated via fragility analysis. The results showed that LYP-Cs were not only effective structural fuses but also effectively delayed the damage development in the primary members, thus reducing the failure probability of the structures. The multi-stage performance indices were conductive to describe the multiple lines of resistance and effects of structural fuses. A larger weakening degree and smaller beam height mitigated plastic damage development in primary members. When LYP-Cs dominate the system’s energy dissipation, the section sizes of columns and the number of structural stories exert only slight influence on the structural performance indices.