Seismic intensity measures for risk assessment of bridges

O’Reilly, Gerard J.

doi:10.1007/s10518-021-01114-z

Cited by 32 publications

(7 citation statements)

References 58 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Note that in the previous IM syntaxis,

Rot

indicated the rotation of the ground‐motion components, D indicates the period dependency, and 50 indicates the percentile value used to compute the demand. The previous IM is estimated as the geometrical mean of 12 equally‐spaced

RotD50

pseudo‐acceleration spectral ordinates 45 within the range [0.5 T 3 ,1.5 T 1 ], where T 1 is the dominant structural period in the longitudinal direction (i.e., the fundamental structural period of the considered structure/bridge) and T 3 is the dominant structural period in the transversal direction 46 . In Figure 2B, a scatter plot of moment magnitude (

{M}_w

) and closest distance to the rupture (

{R}_{rup}

) for the selected ground motions within the sequences are shown (

avgS{A}_{GM1}

and

avgS{A}_{GM2}

are the

avgSA

s related to GM1 and GM2, respectively).…”

Section: Methodsmentioning

confidence: 99%

“…The previous IM is estimated as the geometrical mean of 12 equally-spaced 𝑅𝑜𝑡𝐷50 pseudo-acceleration spectral ordinates 45 within the range [0.5𝑇 3 ,1.5𝑇 1 ], where 𝑇 1 is the dominant structural period in the longitudinal direction (i.e., the fundamental structural period of the considered structure/bridge) and 𝑇 3 is the dominant structural period in the transversal direction. 46 In Figure 2B, a scatter plot of moment magnitude (𝑀 𝑤 ) and closest distance to the rupture (𝑅 𝑟𝑢𝑝 ) for the selected ground motions within the sequences are shown (𝑎𝑣𝑔𝑆𝐴 𝐺𝑀1 and 𝑎𝑣𝑔𝑆𝐴 𝐺𝑀2 are the 𝑎𝑣𝑔𝑆𝐴s related to GM1 and GM2, respectively). Note that to build the ground-motion sequences the two ground-motion waveforms are appended with a padding of zeros equivalent to the length of 20𝑇 1 .…”

Section: Ground-motion Sequencesmentioning

confidence: 99%

See 1 more Smart Citation

Fragility and vulnerability analysis of deteriorating ordinary bridges using simulated ground‐motion sequences

Otárola

Fayaz

Galasso

2022

Earthq Engng Struct Dyn

View full text Add to dashboard Cite

Highway bridges are critical components of the lifeline transport infrastructure in urban areas. They are designed with the expectation of not sustaining significant structural/non‐structural damage after major earthquake‐induced ground shaking. However, in the current structural performance‐based assessment practice, the effects of a pre‐damaged state during ground‐motion sequences are often neglected. Additionally, environmentally induced deterioration mechanisms (e.g., steel rebar corrosion) may exacerbate the consequences of such ground‐motion sequences on the seismic structural performance during the bridge design lifetime; yet such effects are commonly overlooked. This study proposes a computational methodology to derive state‐dependent fragility and vulnerability relationships (i.e., explicitly depending on the damage state achieved by the bridge structure during a first shock) for bridge structures subjected to chloride‐induced corrosion deterioration and ground‐motion sequences. The methodology is demonstrated for a case‐study ordinary bridge structure (representing a typical bridge vulnerability class in southern California) under seismic sequences assembled from the CyberShake 15.12 (hybrid) simulated ground‐motion database. In the proposed approach, parameterised (i.e., dependent on the corrosion deterioration level) vector‐valued probabilistic seismic demand models are developed for the bridge components (i.e., columns and shear keys). These models, calibrated through sequential cloud‐based nonlinear time‐history analyses, relate the dissipated hysteretic energy in the ground‐motion sequence to a deformation‐based engineering demand parameter induced by the first shock and a ground‐motion intensity measure of the second shock for a given corrosion deterioration level. Fragility relationships are first derived for a single ground motion at the component‐level; state‐dependent fragility relationships are then derived by considering the additional damage induced by a second ground motion within the simulated sequence (structure‐specific damage states are considered). Furthermore, a component‐based simulation approach accounting for the correlations across the components’ response is utilised to derive fragility relationships at the system level (i.e., for the bridge structure). Finally, appropriate damage‐to‐loss models for ordinary bridges are used to derive state‐dependent vulnerability relationships. The results demonstrate the significant impact of earthquake‐induced ground‐motion sequences and environmentally‐induced corrosion deterioration, emphasising the necessity of accounting for this multi‐hazard threat in the structural performance‐based assessment of bridges. Relative variations up to 120% can be found in the system‐level state‐dependent fragility median values comparing the results for the bridge in pristine and deteriorated conditions.

show abstract

“…Note that in the previous IM syntaxis,

Rot

RotD50

{M}_w

) and closest distance to the rupture (

{R}_{rup}

) for the selected ground motions within the sequences are shown (

avgS{A}_{GM1}

and

avgS{A}_{GM2}

are the

avgSA

s related to GM1 and GM2, respectively).…”

Section: Methodsmentioning

confidence: 99%

Section: Ground-motion Sequencesmentioning

confidence: 99%

Fragility and vulnerability analysis of deteriorating ordinary bridges using simulated ground‐motion sequences

Otárola

Fayaz

Galasso

2022

Earthq Engng Struct Dyn

View full text Add to dashboard Cite

show abstract

“…Furthermore, all bridges were grouped into four hazard zones, for which a conditional spectrum record selection was carried out using an automated tool (Ozsarac et al, 2021) considering two possible soil conditions (soft and stiff) to obtain ground motion record sets for each zone. These sets of 30 bi-directional earthquake records are conditioned on AvgSa, which is an intensity measure (IM) recently shown (Abarca et al, 2021;O'Reilly, 2021) to be quite advantageous when assessing multiple bridge structures compared to other IMs like PGA, PGV or Sa(T) commonly used. The AvgSa for this case was defined with a period range of 0.1s to 1.7s and spacing of 0.1s, and was used to condition the record selection for nine return periods of ground shaking, ranging from 98 to 9975 years.…”

Section: Methodsmentioning

confidence: 99%

Exposure knowledge impact on regional seismic risk assessment of bridge portfolios

Abarca

Monteiro

O’Reilly

2022

Bull Earthquake Eng

Self Cite

View full text Add to dashboard Cite

The lack of structural information on existing bridges is a common problem faced by engineers when performing regional seismic risk assessment of large bridge portfolios. In most regions, the bridge inventory is composed of structures built over decades and detailed structural information of the existing configurations is difficult to obtain and can be expensive to survey. Most of the regional risk studies for bridges are done with incomplete exposure knowledge and usually rely on macro taxonomy-based approaches that average fragility information of assets with similar configurations. This leads to an unknown level of uncertainty in the results that is commonly not quantified or accurately communicated to the stakeholders. Accordingly, there is a need for a better understanding on how much uncertainty can be expected in results using such approaches, as well as for recommendations to those dealing with this type of project to define an appropriate required minimum knowledge of the inventory to obtain reasonable results. In this study, the seismic risk assessment of a portfolio of 617 bridges with complete structural information was performed and its results were used as a benchmark to quantify the expected uncertainty when considering different knowledge levels using a taxonomy-based approach as well as a machine learning model. The obtained results suggest that having detailed information on at least one third of the portfolio leads to a considerable reduction in uncertainty and that machine learning models can outperform traditional taxonomy-based methodologies only when a considerable level of knowledge of the inventory is available.

show abstract

“…An analysis of two case-study buildings found that peak ground velocity (PGV) tended to be a reasonable predictor of structure displacement demands, which was also noted in past works like Ryan and Chopra. 37,38 Different combinations of IMs may be used to minimise dispersion in seismic response prediction, with studies [39][40][41][42][43][44] investigating optimal IMs for assessing existing buildings. For base-isolated structures, Sa(T iso ) will be employed herein due to its simplicity and physical meaning.…”

Section: Characterising Normalised Fpb Hysteretic Behaviourmentioning

confidence: 99%

Risk‐based seismic design of base‐isolated structures with single surface friction sliders

O’Reilly

Yagi

Suzuki

et al. 2022

Earthq Engng Struct Dyn

Self Cite

View full text Add to dashboard Cite

Choosing friction pendulum isolators to avoid problems with device displacement capacity or boundary wall collision is a critical part of the seismic design of base isolation systems. This paper developed a probabilistic method to quantify the risk of failure in single friction pendulum bearing (FPB) devices. This was done by calibrating a demand-intensity model for FPBs from numerical analysis for several device property combinations. These properties encompassed the dynamic friction coefficient and effective radius of curvature-key parameters impacting these FPB devices' seismic response. Through this demand-intensity model, a closed-form and relatively simple approach to quantify the mean annual frequency of exceeding a given device displacement threshold, or risk of failure, was proposed. By applying this simplified method to several case study structures and comparing it with a more extensive assessment involving multiple stripe analysis (MSA) using hazard-consistent ground motions, the proposed simplified approach could provide very accurate estimates of displacement-based failure risk in FPB devices under the assumption of no non-linear behaviour in the superstructure. This proposed approach implies that structural engineers can now quickly assess the actual failure rates of different FPB device combinations used in practice to give a more uniform level of safety or reliability when designing and assessing FPB-isolated systems. It is also arguably much simpler, direct and accurate than currently available code-based approaches.

show abstract

Seismic intensity measures for risk assessment of bridges

Cited by 32 publications

References 58 publications

Fragility and vulnerability analysis of deteriorating ordinary bridges using simulated ground‐motion sequences

Fragility and vulnerability analysis of deteriorating ordinary bridges using simulated ground‐motion sequences

Exposure knowledge impact on regional seismic risk assessment of bridge portfolios

Risk‐based seismic design of base‐isolated structures with single surface friction sliders

Contact Info

Product

Resources

About