Spectral shape proxies and nonlinear structural response

Bojórquez, Edén; Iervolino, Iunio

doi:10.1016/j.soildyn.2011.03.006

Cited by 169 publications

(165 citation statements)

References 19 publications

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“…The selected measures of source-to-site distance are the epicentral distance R epi as a point-source distance metric, and the Joyner-Boore distance R JB as an extended-source distance metric. The present evaluation on the linear or logarithmic dependencies of the natural logarithm of the collapse capacities is consistent with the studies of Cornell et al (1979), Abrahamson and Silva (1997), Bianchini et al (2009), andBojórquez andIervolino (2011) on the considered ground motion characteristics, such as the magnitude, the natural logarithm of the sourceto-site distance, and the natural logarithm of the scaling factors. Initially, scatter plots have been used to explore by visual inspection the possible linear or non-linear relationship between paired sets consisting of the natural logarithm of the collapse capacities and the considered parameter.…”

Section: Sufficiency and Scaling Robustness Of The Utilized Intensitysupporting

confidence: 92%

“…However, most of these studies did not address the collapse limit state, and were mainly focused on the efficiency of the considered IMs. The properties of sufficiency, scaling robustness and hazard computability have been studied by Shome and Cornell (1999), Luco and Cornell (2007), Bianchini et al (2009), andBojorquez andIervolino (2011), among others.…”

Section: Introductionmentioning

confidence: 99%

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Intensity measures that reduce collapse capacity dispersion of P-delta vulnerable simple systems

Tsantaki

Adam

Ibarra

2016

Bull Earthquake Eng

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The study evaluates two alternative seismic intensity measures (IMs) that reduce the collapse capacity dispersion of inelastic non-degrading single-degree-of-freedom (SDOF) systems vulnerable to the P-delta effect. This dispersion of collapse capacity is caused by record-to-record variability, which refers to frequency content variation of the ground motions used in the dynamic analyses. This reduction (of dispersion) is achieved utilizing efficient elastic pseudo-spectral acceleration based IMs. The first set of evaluated IMs is based on the spectral pseudo-acceleration averaged in a certain period interval between the structural period and an elongated period. The ''optimal'' lower bound of the period interval corresponds to the structural period of vibration, since naturally in an SDOF system no higher modes effects do exist. The ''optimal'' upper bound of the period interval for averaging, referred to as elongated period, is found to be 1.6 times the system period. The second IM considered in the study is the 5 % damped spectral pseudo-acceleration at the system period in the presence of gravity loads, which is a single target IM. The most widely accepted IM, the 5 % damped pseudo-spectral acceleration at the system period without P-delta, serves as the benchmark IM. The results show that both proposed IMs lead to a reduction of the collapse capacity dispersion compared to the benchmark IM outcomes. The IM based on the averaged spectral acceleration of the ''optimal'' period interval is more efficient up to a negative post-yield stiffness ratio of 0.45, while the single target IM based on the system period in the presence of gravity loads is superior for extreme negative post-yield stiffness ratios larger than 0.45. Additionally, the sufficiency and the scaling robustness property of the considered IMs with respect to the natural logarithm of the record-dependent individual collapse capacities is discussed for a wide range of structural configurations.

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Section: Sufficiency and Scaling Robustness Of The Utilized Intensitysupporting

confidence: 92%

Section: Introductionmentioning

confidence: 99%

Intensity measures that reduce collapse capacity dispersion of P-delta vulnerable simple systems

Tsantaki

Adam

Ibarra

2016

Bull Earthquake Eng

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“…The white noise samples are chosen as n w = 200. For the domain X characterization n c = 1000 seismicity scenarios are considered in range [6 8] for M, [10 100] km for R, [300 1600] m/s for V s, 30 and discrete {0,1} for F. These ranges correspond to the ones for which the initial predictive relationships 15 were developed. The samples for the SVM-based characterization of X are chosen as n s = 10000 with δ d = 9 (latter corresponding to radius of 3 standard deviations away from mean).…”

Section: Details For Metamodel Developmentmentioning

confidence: 99%

“…These scenarios are denoted herein as SC 1 , SC 2 , and SC 3 , respectively. Figure 11 shows spectral plots for a smaller (due to space limitations) selection of seismicity scenarios, defined by combinations of M [6.2, 6.8, 7.4, 8] and R [30,60,90] km, for SC 1 . For each of the 12 M-R combinations, the curves corresponding to the target IM, the unmodified model, and the predictions by the three aforementioned model modifications are shown to facilitate comparisons.…”

Section: Implementation For Different Seismicity Scenariosmentioning

confidence: 99%

Modification of stochastic ground motion models for matching target intensity measures

Tsioulou

Taflanidis

Galasso

2017

Earthq Engng Struct Dyn

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SummaryStochastic ground motion models produce synthetic time-histories by modulating a white noise sequence through functions that address spectral and temporal properties of the excitation. The resultant ground motions can be then used in simulation-based seismic risk assessment applications. This is established by relating the parameters of the aforementioned functions to earthquake and site characteristics through predictive relationships. An important concern related to the use of these models is the fact that through current approaches in selecting these predictive relationships, compatibility to the seismic hazard is not guaranteed. This work offers a computationally efficient framework for the modification of stochastic ground motion models to match target intensity measures (IMs) for a specific site and structure of interest. This is set as an optimization problem with a dual objective. The first objective minimizes the discrepancy between the target IMs and the predictions established through the stochastic ground motion model for a chosen earthquake scenario. The second objective constraints the deviation from the model characteristics suggested by existing predictive relationships, guaranteeing that the resultant ground motions not only match the target IMs but are also compatible with regional trends. A framework leveraging kriging surrogate modeling is formulated for performing the resultant multi-objective optimization, and different computational aspects related to this optimization are discussed in detail. The illustrative implementation shows that the proposed framework can provide ground motions with high compatibility to target IMs with small only deviation from existing predictive relationships and discusses approaches for selecting a final compromise between these two competing objectives. | INTRODUCTIONThe growing interest in performance-based earthquake engineering 1,2 and in simulation-based, seismic risk assessment approaches 3,4 has increased in the past decades the relevance of ground motion modeling techniques. These techniques describe the entire time-series of seismic excitations, providing a characterization appropriate for dynamic time-history analysis. UndoubtedlyThis is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.

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“…For the latter, they proposed a simple analytical expression that links the initial period T 1 to an elongated period and illustrated that the geometric mean of the spectral accelerations evaluated across that period band, leads to a notable reduction in the seismic collapse capacity dispersion. An additional scalar IM based on S a (T 1 ) and a parameter N p that accounts for the spectral shape in a period range, was proposed by Bojorquez & Iervolino [6] and was found to have good efficiency.…”

Section: Introductionmentioning

confidence: 99%