Fragility Assessment Research Articles

Convolutional variational autoencoder for ground motion classification and generation toward efficient seismic fragility assessment

AbstractThis study develops an end‐to‐end deep learning framework to learn and analyze ground motions (GMs) through their latent features, and achieve reliable GM classification, selection, and generation of simulated motions. The framework is composed of an analysis workflow that transforms and reconstructs GMs through short‐time Fourier transform (STFT), encodes and decodes their latent features through convolutional variational autoencoder (CVAE), and classifies and generates GMs by grouping and interpolating latent variables. A benchmark study is established to confirm the minor difference between original GMs and the corresponding reconstructed accelerograms. The encoded latent space reveals that certain latent variables are directly linked to the dominant physical features of GMs. Resultantly, clustering latent variables using the k‐means algorithm successfully classifies GMs into different groups that vary in earthquake magnitude, soil type, field distance, and fault mechanism. By linearly interpolating two parent latent variables, simulated GMs are generated with consistent class information and matching response spectra. Furthermore, seismic fragility models are developed for a steel frame building and a concrete bridge using different sets of GMs. Using five classified, top‐ranked motions, regardless of recorded or simulated accelerograms, can achieve reasonable and efficient fragility estimates compared to the case that adopts 230 GMs. The proposed deep learning framework addresses two compelling questions regarding seismic fragility assessment: How many GMs are sufficient and what types of motions should be selected.

Fragility assessment of highway embankment resting on liquefaction-susceptible soil

Fragility curve defines the probability of a structure exceeding a damage level for various levels of loading intensity. The present study presents a vulnerability analysis of a road embankment structure exposed to liquefaction-induced deformation due to earthquake loading. The numerical simulations are based on 2D finite element analysis considering liquefaction-susceptible soil as an elasto-plastic effective stress-based UBC3D-PLM model. The model parameters are developed through a calibration procedure with respect to the laboratory test results from past literature. The level of damage is described in terms of peak embankment settlement (PES) with increasing ground motion intensity (PGA). The fragility analyses have been carried out using an incremental dynamic analysis (IDA) considering a set of 9 different ground motions, which have been scaled to 16 different intensity levels. A wide range of parameters, including the relative density of liquefiable foundation soil, the geometry of the embankment, the thickness of the liquefiable layer, and the effect of densification on embankment response, have been considered in order to evaluate the vulnerability response of embankment subjected to liquefiable foundation soil. Study envisaged the relative density and thickness of liquefiable layer as primary and embankment geometry as secondary parameters having significant effect.

Seismic fragility assessment of low-rise reinforced concrete frame: A comparative study of bare and infill model

Most of the residential structures designed in Nepal are low-rise reinforced concrete (RC) frames. They are designed following the guidelines given in the Nepal Building Code, especially, the mandatory rule of thumb. In analyzing and designing most of the reinforced concrete structures in the urban and semi urban areas of Nepal, only bare frame model is considered. The additional effect caused by the infill walls are neglected. In this research, a comparative seismic fragility assessment of low-rise RC frame is conducted. Two cases are assumed; with and without the consideration of the unreinforced masonry infill. Macro modelling approach is followed for modelling the infill effect. Results clearly indicate that the inclusion of the infills drastically reduce the roof displacement compared to the bare frame model during a seismic shaking. This is attributed to the fact that the inclusion of the infill imparts more stiffness to the structure during a seismic-shaking compared to the bare frame model and hence the displacement is reduced. Furthermore, seismic fragility of the frame structure is also overstated when the effect of infill is not taken into consideration. The inclusion of infills reduced the structural fragility to significant extent. In this regard, the bare frame model was found to be more vulnerable to seismic shaking compared to the infill model.

Effects of wave load models on the uplift fragility assessment of pile-supported wharves and piers exposed to storm surge and waves

Pile-supported wharves and piers may suffer structural damage during extreme coastal events, which may result in port closures that can cause significant economic losses. Risk analysis can estimate the post-hazard functionality of ports though the structural damage assessment of these structures prior to coastal events. However, assumptions on the selected demand estimates may significantly affect the estimated probability of structural damage. Therefore, this study aims to shed light on the sensitivity of the wave model selection for the risk assessment of pile-supported wharves and piers when subjected to storm surge and waves. The examined structural damage is the uplift of the deck, and the risk assessment is conducted through the development of fragility curves for a typical deck-pile connection, for which fragility curves are developed for different wave models. Uncertainties are also considered in parameters affecting the demand and capacity of the examined deck-pile connection and are propagated through the Monte Carlo simulation using the Latin Hypercube Sampling. The results indicate changes to the uplift probability because of the selected wave model. Thus, wave model selection can significantly affect the uplift failure probability. In addition, the study proposes parameterized fragility models to enable the uplift risk assessment across a region. The presented results aim to throw light on the proper model selection to produce more realistic risk assessment estimates towards the resilience of coastal infrastructure.

Effect of buoyancy loads on the tsunami fragility of existing reinforced concrete frames including consideration of blow-out slabs

Currently available performance-based methodologies for assessing the fragility of structures subjected to tsunami neglect the effects of tsunami-induced vertical loads due to internal buoyancy. This paper adopts a generalized methodology for the performance assessment of structures that integrates the effects of buoyancy loads on interior slabs during a tsunami inundation. The methodology is applied in the fragility assessment of three case-study frames (low, mid and high-rise), representative of existing masonry-infilled reinforced concrete (RC) buildings typical of Mediterranean region. The paper shows the effect of modelling buoyancy loads on damage evolution and fragility curves associated with different structural damage mechanisms for existing RC frames with breakaway infill walls including consideration of blow-out slabs. The outcomes attest that buoyancy loads affect the damage assessment of buildings during a tsunami, especially in the case of mid and high-rise structures with blow-out slabs. The rate of occurrence of slabs uplift failure increases with the number of stories of the building, indicating the need to account for such damage mechanism when assessing the performance of structures. It is also found that buoyancy loads slightly affect the fragility curves associated to other structural damage mechanisms for existing RC buildings commonly monitored for fragility assessment.

Fracture Mechanics–Based Fragility Assessment of Pre-Northridge Welded Column Splices

Fracture Mechanics–Based Fragility Assessment of Pre-Northridge Welded Column Splices

Seismic Fragility Assessment of SMRFs Equipped with TMD Considering Cyclic Deterioration of Members and Nonlinear Geometry

This paper presents seismic fragility curves to assess the effect of far-field ground motions on the behavior of high-rise steel moment resisting frame (SMRF) structures equipped with Tuned Mass Damper, considering the cyclic deterioration of members and P-Delta effect in the nonlinear region. For this purpose, three 8-, 20-, and 30-story SMRF structures are selected, 44 earthquake record sets are extracted from the FEMA P-695, Incremental Dynamic Analysis (IDA) is operated, and four structural damage states are considered through the framework of HAZUS, including slight, moderate, extensive, and complete. Maximum structural inter-story drift and floor acceleration are employed to quantify the damage states, and spectral acceleration is used as the intensity measure. Results show that the Tuned Mass Damper can reduce the probability of damage under earthquake excitation in all damage states for both structural and non-structural elements. The decline varies from 4.0% to 20.0%, depending on the ground motion intensity level, based on engineering demand parameters. Moreover, it is clear that nonlinear properties and component deterioration under cyclic excitation can affect structural response in all damage states, which concerns the obtained curves.

A Seismic Fragility Assessment Method for Urban Function Spatial Units: A Case Study of Xuzhou City

Cities that experience earthquake disasters face a lot of uncertainties and unsustainability resulting from the fragility of their infrastructure, which should be considered in engineering. This study proposes a seismic fragility assessment framework for urban functional spatial units in order to improve the traditional structural fragility assessment criteria that are currently applied in urban planning. First, appropriate spatial units are classified for the study area, the functional categories of the study area are determined using urban Point of Interest (POI) data, and the functional proportion of the spatial units is calculated. Secondly, considering the classification of different seismic fortification levels represented by different construction ages, and considering the possible building forms and HAZUS’s classification system of building structures in order to establish the correlation between building functions and building structures, the methods of a field survey and a questionnaire survey are adopted to match the functions with the most likely building structures. After this, based on the assumption of the lognormal distribution of ground motion intensity, a mixed method is adopted to calculate the mean value μ¯ for the fragility of functional space units. The Monte Carlo method is then used to discretize the data and statistically obtain the standard deviation β¯ for the fragility of functional space units, and the fragility curve is then fitted. A district in Xuzhou City, China, was used as a case study to verify this assessment framework. The results showed that: (1) the fragility of functional space units was greatly affected by the proportion of defense standards in different periods in the unit, which reflected the average level of fragility within the unit. (2) The unit loss index of units built after 2001 with a proportion of less than 50% is basically above the average loss level of the study area. (3) The simulated damage ratio of the assessment results under the three levels, namely frequent earthquake, fortified earthquake and rare earthquake, is consistent with the previously experienced earthquake damage. The paper concludes that it is helpful to design and utilize seismic fragility predicting formulas and technologies at the functional spatial unit level for urban planning, which is meaningful for the formulation of planning strategies, reducing risks to infrastructure and delivering sustainable development.

Fragility assessment of an outrigger structure system based on energy method

SummaryFragility curves development in structures has always been a focus of research interest among structural and earthquake engineers for which the maximum story drift is usually considered as the engineering demand parameter (EDP) known as the conventional approach. This paper aims at calculating the fragility curves of a tall building with outrigger braced system by considering the plastic strain energy as the EDP and compare it with the conventional approach. In addition, the effect of optimizing the position of outriggers on the exceedance probability of the structure under near‐ and far‐fault seismic loadings is investigated in this paper. Fragility curves of this structure in four performance levels including immediate occupancy (IO), life safety (LS), collapse prevention (CP), and instability is extracted based on the conventional method. The fragility curves for the aforementioned performance levels are also extracted based on the plastic strain energy and compared with the conventional approach. The results have demonstrated that optimizing the location of the bracing system would lower the exceedance probability of the structure. Moreover, the exceedance probability of the investigated building with outrigger braced system under far‐fault records in various levels is more than that of near‐fault records. It is also concluded that the conventional approach would lead to more conservative results compared with the energy approach.

Development of a new framework based on Gaussian regression process for rapid fragility analysis of 2-DoF base-isolated structures

This paper develops metamodels (or surrogate models) to predict the fragility parameters of structures isolated with friction pendulum (FP) isolators. An equivalent inelastic two-degree-of-freedom (2DoF) system is utilized to model the base-isolated structures.6000 system simulations are initially established based on the probability distribution of input parameters. Then, incremental dynamic analyses are carried out to achieve structural data for the fragility function generation. The developed dataset of the fragility parameters (median and dispersion) is divided into training and testing sets to train and testthe efficiency of the developed metamodels, respectively.Powerful machine learning tool, namely, Gaussian Process Regression (GPR) is utilized for mapping structural input parameters to output (or target) parameters, i.e., median and dispersion of the fragility functions. GPRs are kernel-based probabilistic models, with kernel functions constituting their core components. In this study, the predictive quality of the GPR is evaluated considering different kernel functions to obtain the most accurate and reliable predictions. The results indicate that automatic relevance determination (ARD) kernel functions are much more efficient than isotropic kernel functions. Statistical performance metrics indicate that, among the implemented kernel functions, ARD Matern 3/2 is preferable for both the superstructure and FP isolator. The proposed GPR-based prediction metamodels exhibit excellent performance in the prediction of the fragility parameters of the superstructure and isolator for all considered limit states. Using the developed metamodels, conducting a rapid seismic fragility assessment on 2DoF systems that are representative of base-isolated structures is possible. At last, metamodels are exploited in seismic reliability analysis to assess their precision for further investigations. The results of seismic reliability-based performance and relationships between the displacement ductility demand and strength reduction factor reaffirm the efficiency, sufficiency, proficiency, and practicality of the GPR-based generated metamodels.

Fragility assessment of traditional wooden houses in Madagascar subjected to extreme wind loads

Cyclones are a common hazard in Madagascar, each year causing fatalities and damage to the physical and socioeconomic infrastructure. Residential infrastructures are a critical sector within the built environment and studying their performance under natural hazards is a significant step for assessing the risk and resilience of a community. In the coastal regions of Madagascar, more than 80% of houses are self-built, non-engineered traditional wooden houses constructed based on heritage practices and using low or no-cost materials collected in nearby areas or forests. These traditional wooden houses are particularly vulnerable to cyclonic winds, and in this paper, a novel approach is used to evaluate their structural performance and to predict their likelihood of failure under extreme wind conditions. The structural systems and their damage due to extreme winds were first evaluated based on field surveys and collected information such as post-disaster reports. A range of field tests was then carried out at two coastal sites to evaluate the strength of the members and connections identified as commonly used for constructing traditional wooden houses in Madagascar. Damage fragility curves were subsequently developed based on the performance of the connections of roof coverings, wall claddings, the roof structural system, and the performance of columns embedded into the ground and combined to predict the structure's performance. The experimental methods and results presented in this study can be exploited to improve the existing Malagasy guidelines for cyclone resistance of traditional wooden houses published in 2016. The developed fragility curves can also be used to represent traditional wooden houses within a community for risk or resilience assessment under cyclonic wind conditions.

Regional seismic risk and resilience assessment: Methodological development, applicability, and future research needs – An earthquake engineering perspective

Given the devastating losses incurred by past major earthquake events together with the ever-increasing global seismic exposures due to population growth and urbanization, strategic decision-support tools are required to help stakeholders make more contemplated decisions that promote seismic resilience of the built environment. Such decision-support is enabled by regional seismic risk and resilience assessment, which holistically incorporates the various underlying physics processes and uncertainties for quantitative and probabilistic assessment of regional seismic hazard impacts, and has thereby attracted increasing research focus over the past twenty years. As a significant departure from the traditional site-specific assessment, where only an individual structure and site-specific seismic hazard are of interest, such regional-level assessment introduces additional dimensions and complexity. To date, there is a lack of review studies summarizing the related research advancements in seismic risk and resilience assessment from a regional-level perspective in the context of earthquake engineering. This study fills this gap by conducting a systematic review covering: the methodological development of regional seismic risk assessment (RSRiA) across its key modules, including hazard analysis, exposure modeling, fragility assessment, and consequence evaluation, as well as the associated uncertainty quantification and propagation; the development of resilience metrics, restoration modeling and planning in regional seismic resilience assessment (RSReA); and the applicability of existing computational workflows. Insights into the features, applicability, compatibility, and limitations of existing models and tools are provided. This study also highlights the challenges and future directions toward further advancing the research frontiers of RSRiA and RSReA.

Wind Uplift Fragility Assessment Method of 360° Standing Seam Roof System and Its Application in Wind Damage Estimation of UHV Converter Station

Wind Uplift Fragility Assessment Method of 360° Standing Seam Roof System and Its Application in Wind Damage Estimation of UHV Converter Station

Seismic fragility assessment of concrete gravity dams under near source synthetic ground motions

This study aims at seismic fragility assessment of concrete gravity dams under synthetic near source ground motions. The numerical modelling of the dam-reservoir-foundation coupled system and the nonlinear time history analysis are carried out in ABAQUS. Two sets of synthetic near source records characterized by forward-directivity and fling-step effects are generated using an empirical stochastic approach. Maximum value of the seismic response quantities of the coupled system are obtained as engineering demand parameters (EDP) and various ground motions parameters are selected as intensity measurement (IM). Fragility functions are generated from the cloud response data (EDP-IM pairs) using a Probabilistic Seismic Demand Model (PSDM).

Seismic fragility assessment for highway bridges incorporating multi-level shape memory alloy cable dampers

An innovative multi-level shape memory alloy (SMA) cable damper is proposed for bridges in near-fault seismic regions. This study commences with the introduction of a constitutive material model for simulating SMA cables. The proposed model not only considers the self-centering hysteretic property but also accounts for the strength degradation and residual strain accumulation effects. Subsequently, the layout and working mechanism of the proposed multi-level SMA cable damper is presented. A seismic fragility analysis framework involving Box-Cox transformation and Bayesian inference is subsequently presented. The Box-Cox transformation is utilized to establish the nonlinear probabilistic seismic demand models (PSDMs), and the Bayesian-based logistic regression is employed to formulate fragility functions. Finally, a three-span continuous reinforced concrete (RC) girder bridge incorporating the multi-level SMA dampers is selected as an example to demonstrate the proposed framework. A total of 160 near-fault ground motions, containing pulse and non-pulse motions, are applied along the longitudinal direction of the bridge. To investigate the influences of different parameter values of the SMA cable damper on fragility functions, various parameters are generated with respect to a central composite design philosophy. Based on the seismic fragility analysis, it is found that the SMA isolation damper reduces the damage probabilities of the bearing and pier for all four damage states. In addition, the failure probability of the bearing decreases with the increase of the axial stiffness of the SMA damper, which is opposite to the pier. Moreover, the optimum designed SMA damper can significantly reduce the damage probability of the case study bridge, and the parameter values of the damper should be carefully selected to achieve the desired seismic performance.

Machine learning-driven probabilistic seismic demand model with multiple intensity measures and applicability in seismic fragility analysis for nuclear power plants

A novel machine learning (ML) framework is applied in mapping intensity measures (IMs) to seismic engineering demand parameter (EDP). It is an efficient and accurate approach to establishing the probabilistic seismic demand model (PSDM) with multiple IMs for nuclear power plant (NPP). The optimal IM set on the performance of the prediction is further discussed herein. A total of 33 IMs are used to represent the characteristics of ground motions (GMs) comprehensively and significant IMs are identified by recursive random forest (RRF). 14 algorithms are used for determining the most optimal ML model. The generalization ability of the proposed ML model is empirically tested against traditional models based on scalar and vector IMs in a new dataset. ML is found to have absolute superiority in the construction of PSDM with inelastic correlation. Moreover, a promising methodology for deriving the fragility curve is presented based on multiple stripe analysis (MSA) driven by ML. By training the model, the workload of nonlinear time-history analysis (NLTHA) can be replaced, and the large inelastic behavior can be captured considering the stiffness degradation of NPP when it is subjected to high-intensity effects. It is meaningful for the fragility assessment of NPP beyond a design-basis event.

Fragility framework for corroded steel moment-resisting frame buildings subjected to mainshock-aftershock sequences

This study proposes a framework for the seismic fragility assessment of steel moment-resisting frames exposed to different rates of corrosion and subjected to real mainshock-aftershock (MS-AS) sequences. The inherent uncertainties in the structural characteristics may significantly affect the structural performance. Thus, in addition to the demand parameters, the framework considers randomness in the capacity parameters using the Latin hypercube sampling. Three frames are modeled in OpenSees and then subjected to nine real as-recorded MS-AS sequences to illustrate the application of the framework. Four limit states are defined based on the maximum interstory drift ratio and the multiple stripe analysis is chosen for the fragility assessment. The presented framework allows for the plot of the fragility surfaces for each corrosion level conditioned on both the mainshock and the aftershock intensity. The results indicate that corrosion and aftershock may significantly affect the seismic fragility especially for the extreme limit states.

Seismic Response Estimation and Fragility Curve Development Using an Innovative Response Bound Method

Incremental dynamic analysis (IDA) is one of the widely used methods for structural assessment analysis and fragility curve development, given its unique capabilities in taking into account the aleatory uncertainties of earthquake records and its ability to provide a desirable statistical population of the system response. However, the strong dependence of the results on the number of selected records, the record selection process and scaling procedure, as well as the associated high computational costs are some of the obstacles, which limit the practicality of the IDA method especially in the case of large-scale structures. In the present study, an alternative approach called “Response Bounds” is proposed to estimate the expected range of structural responses under earthquakes with different intensity levels and to develop seismic fragility curves. To reduce computational costs and address the challenges associated with the record selection, a novel scenario-based Endurance Time (ET) analysis method is adopted. The good agreement between the fragility results of 5-, 10-, and 15-storey steel moment-resisting frames obtained by the proposed method and the IDA (less than 9% error) demonstrated the accuracy and reliability of the predicted results. The method could also estimate the mean loss ratio from fragility curves with less than 5% error in all cases. The proposed response-bound method can significantly reduce the computational costs of conventional seismic fragility assessment methods, and therefore can be used as an efficient tool for seismic reliability analysis in practical applications.

Multi‐hazard fragility assessment of monopile offshore wind turbines under earthquake, wind and wave loads

AbstractThis study establishes a multi‐hazard probabilistic assessment framework for assessing the integrity of monopile offshore wind turbines (OWT) under the stochastic coupled effect of wind, wave and earthquake loading. The procedure deals with the entire operational range of inflow wind speed (i.e., 3–25 m/s), for which the probability of failure under multi‐hazard excitations is found to be non‐negligible. Numerical analysis is performed by implementing nonlinear finite‐element models of the OWT developed in OpenSees. The dynamic response of the OWT system under wind‐ and wave‐load combinations is individually validated against those obtained from the aero‐hydro‐servo‐elastic simulator OpenFAST. Following the Latin‐hypercube approach, a cloud‐based assessment procedure is then performed with an ensemble of 300 earthquake ground motions, from which the multi‐hazard performance of the OWT regarding the serviceability limit state (SLS) and the ultimate limit state (ULS) can be evaluated. The epistemic uncertainty associated with various loads, structural properties, and soil conditions is also accounted for. Based on this probabilistic assessment framework, the sensitivity of the resulting OWT fragility surfaces to different statistical regression methods and wind—ground motion intensity measure pairs (IM‐pairs) is further scrutinised. Regression methods are comparatively evaluated. The efficiency, practicality, proficiency and sufficiency of various IM‐pairs are examined for the purpose of assessing operating OWT multi‐hazard fragility functions. The optimum IM‐pair is then employed in a trained Gaussian Process Regression (GPR) scheme for cloud data regression to assess the multi‐hazard fragility of the system. The derived multi‐hazard fragility function shows that the contribution of seismic forces in structural demand for a design‐level earthquake is comparable to those caused by operational‐level wind and wave loads.

Probabilistic-based discrete model for the seismic fragility assessment of masonry structures

Classical Finite-Element and Discrete-Element strategies are expensive to carry when analysing masonry structures in the inelastic range, under a seismic excitation, and considering uncertainty. Their application to the seismic fragility assessment of masonry structures through non-linear time-history analysis becomes thus a challenge. The paper addresses such difficulty by presenting an alternative probabilistic-based numerical strategy. The strategy couples a discrete macro-element model at a structural-scale with a homogenization model at a meso-scale. A probabilistic nature is guaranteed through a forward propagation of uncertainty through loading, material, mechanical, and geometrical parameters. An incremental dynamic analysis is adopted, in which several assumptions decrease the required computational time-costs. A random mechanical response of masonry is provided by numerical homogenization, using Latin hypercube sampling with a non-identity correlation matrix, and only a reduced number of representative random samples are transferred to the macro-scale. The approach was applied to the seismic fragility assessment of an English-bond masonry mock-up. Its effectiveness was demonstrated, and its computational attractiveness highlighted. Results may foster its use within the seismic fragility assessment of larger structures, and the opportunity to better analyze the effect of material and geometric-based uncertainties in the stochastic dynamic response of masonry structures.