Effects of ground-motion sequences on fragility and vulnerability of case-study reinforced concrete frames

Aljawhari, Karim; Gentile, Roberto; Freddi, Fabio; Galasso, Carmine

doi:10.1007/s10518-020-01006-8

Cited by 42 publications

(44 citation statements)

References 55 publications

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“…Therefore, this frame does not conform to modern seismic requirements. A non-ductile behaviour characterizes it due to the lack of strength hierarchy rules, sufficient longitudinal reinforcement, poor confinement, and susceptibility to develop brittle failure mechanisms (see [31] for more details). According to this distinction, the two case-study frames include a pre-code bare (PB) frame and a specialcode bare (SB) frame.…”

Section: Considered Building Typologiesmentioning

confidence: 99%

Investigating Ground-Motion Duration Effects on Building Portfolio Loss Estimates

Otárola¹,

Gentile²,

Sousa³

et al. 2021

Proceedings of the 8th International Conference on Computational Methods in Structural Dynamics and Earthquake Engineering (COM

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Earthquake-induced ground-motion duration can be an important factor to consider when assessing ground-motion damage potential, as evidenced by recent earthquake events worldwide. In current practice, duration is commonly relegated to implicit, qualitative considerations. This study introduces a framework to explicitly quantify the influence of duration on building portfolio direct economic losses. To this end, a simulation-based probabilistic risk modelling framework is developed for different synthetic building portfolios impacted by a case-study seismic source. Two building typologies, representative of distinct vulnerability classes in southern Europe, are considered. A simulation-based probabilistic seismic hazard analysis is performed, explicitly simulating duration jointly with spectral-shape-related intensity measures. Sets of long and one-to-one spectrally-equivalent short duration ground-motion records are selected and then used jointly to perform nonlinear dynamic analysis and derive fragility models for each considered building typology. Fragility relationships are derived by using average spectral acceleration as the primary intensity measure and: 1) maximum inter-storey drift ratio as a demand parameter, indirectly accounting for ground-motion duration (through the adopted nonlinear modelling strategy); 2) maximum inter-storey drift ratio as demand parameter, explicitly considering duration as an intensity measure together with spectral shape, in a vectorvalued format. For each case, vulnerability models are developed by combining the fragility relationships with a building-level damage-to-loss model. The portfolio expected annual losses estimated using the described vulnerability models are critically compared and discussed. Depending on the location/portfolio, the impact of ground-motion duration can be significant, and the proposed approaches allow an analyst to account for it in a practical way.

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Section: Considered Building Typologiesmentioning

confidence: 99%

Investigating Ground-Motion Duration Effects on Building Portfolio Loss Estimates

Otárola¹,

Gentile²,

Sousa³

et al. 2021

Proceedings of the 8th International Conference on Computational Methods in Structural Dynamics and Earthquake Engineering (COM

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“…In turn, this does not allow developing statistically robust fragility models conditioned on the initial DS due to the MS. To overcome this, while avoiding the use of synthetic ground motions 31 or substantial amplitude scaling of real records (e.g. IDA), a randomized approach based on real records is adopted, as done in Aljawhari et al 5 The resulting artificial sequences may represent multiple ground shaking that may occur in the form of typical ASs or triggered events. The seed ground motions (crustal only) are collected from three different databases: (a) the 2012 KKiKSK ground-motion database; 32 (b) the database developed by Goda and Taylor; 33 (c) the 100 records with the highest PGA in the SIMBAD Database.…”

Section: Assembled Ground-motion Sequencesmentioning

confidence: 99%

“…26 The relevant seismological parameters (e.g. magnitude and source-to-site distance ranges, soil types) are reported in Aljawhari et al 5 By separately considering both horizontal components of such records (MS only), 626 ground motions are selected. It is worth mentioning that this arbitrary selection of records is consistent with the adopted cloud-based response analysis approach, which does not require a hazard-consistent suite of ground-motion records.…”

Section: Assembled Ground-motion Sequencesmentioning

confidence: 99%

“…state-dependent fragility). Most studies derive seismic fragility in terms of maximum interstorey drift thresholds [3][4][5] , although in some cases this is considered in conjunction with the residual drift 6 . This may create inconsistencies in the resulting statistical models due to inappropriate consideration of damage accumulation.…”

Section: Introductionmentioning

confidence: 99%

“…This allows one to retain the reliability of the adopted DS thresholds, as the deformation-energy conversion can start from any widely accepted/validated, deformation-based EDP limit. It is proposed to calibrate the PSDM through a cloud-based nonlinear time-history analyses (NLTHA) using artificial MS-AS sequences assembled via a randomized approach 5 . This approach does not require a site-specific, hazard-consistent record selection (e.g.…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Hysteretic energy‐based state‐dependent fragility for ground‐motion sequences

Gentile

Galasso

2020

Earthq Engng Struct Dyn

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A framework to derive state‐dependent fragility relationships of structures subjected to ground‐motion sequences (e.g. mainshock‐aftershock (MS‐AS) or triggered earthquakes) is proposed. The hysteretic energy dissipated in the sequence is adopted as the main demand parameter, as it is a cumulative measure monotonically increasing with the length of the excitation. For a structure subjected to earthquake‐induced ground motions, it is not possible to define a closed‐form representation of the hysteretic energy as a function of the peak deformation. However, based on theoretical considerations, the hysteretic energy‐peak deformation trend is discussed, highlighting that (a) the significant duration of the ground motion explains the variability of the hysteretic energy for a given peak deformation; (b) the hysteretic energy dissipated in an AS decreases (for a given AS peak displacement) if the peak displacement in the MS increases. A vector‐valued probabilistic seismic demand model consistent with these considerations is proposed in the form of a surface relating the hysteretic energy in the sequence to the peak deformation in the MS and a ground‐motion intensity measure of the AS. This is calibrated via sequential cloud‐based time‐history analyses. The framework is demonstrated for 14 reinforced concrete frame buildings with different height, plastic mechanisms, and infill distributions. The results show the feasibility of the proposed approach, effectively capturing damage accumulation without inconsistencies in the obtained statistical model. The framework may be used for risk‐assessment applications explicitly incorporating ground‐motion sequences. The hysteretic energy versus peak deformation relationship may also be exploited in problems involving long‐duration ground motions or soft soils.

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A Bayesian network‐based probabilistic framework for updating aftershock risk of bridges

Tubaldi

Turchetti

Fayaz

et al. 2022

Earthq Engng Struct Dyn

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The evaluation of a bridge's structural damage state following a seismic event and the decision on whether or not to open it to traffic under the threat of aftershocks (ASs) can significantly benefit from information about the mainshock (MS) earthquake's intensity at the site, the bridge's structural response, and the resulting damage experienced by critical structural components. This paper illustrates a Bayesian network (BN)-based probabilistic framework for updating the AS risk of bridges, allowing integration of such information to reduce the uncertainty in evaluating the risk of bridge failure. Specifically, a BN is developed for describing the probabilistic relationship among various random variables (e.g., earthquakeinduced ground-motion intensity, bridge response parameters, seismic damage, etc.) involved in the seismic damage assessment. This configuration allows users to leverage data observations from seismic stations, structural health monitoring (SHM) sensors and visual inspections (VIs). The framework is applied to a hypothetical bridge in Central Italy exposed to earthquake sequences. The uncertainty reduction in the estimate of the AS damage risk is evaluated by utilising various sources of information. It is shown that the information from accelerometers and VIs can significantly impact bridge damage estimates, thus affecting decision-making under the threat of future ASs.

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Effects of ground-motion sequences on fragility and vulnerability of case-study reinforced concrete frames

Cited by 42 publications

References 55 publications

Investigating Ground-Motion Duration Effects on Building Portfolio Loss Estimates

Investigating Ground-Motion Duration Effects on Building Portfolio Loss Estimates

Hysteretic energy‐based state‐dependent fragility for ground‐motion sequences

A Bayesian network‐based probabilistic framework for updating aftershock risk of bridges

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