In the context of seismic risk assessment as per the performance-based earthquake engineering paradigm, a probabilistic description of structural vulnerability is often obtained via dynamic analysis of a nonlinear numerical model. It typically involves subjecting the structural model to a suite of ground-motions that are representative, as a sample, of possible seismic shaking at the site of interest. The analyses' results are used to calibrate a stochastic model describing structural response as a function of seismic intensity. The sample size of ground motion records used is, nowadays, usually governed by computation-time constraints; on the other hand, it directly affects the estimation uncertainty which is inherent in risk analysis carried out in this way. Recent studies have suggested methodologies for the quantification of estimation uncertainty, to be used as tools for determining the appropriate number of records for each application on an objective basis. The present study uses one of these simulation-based methodologies, based on standard statistical inference methods and the derivation of structural fragility via incremental dynamic analysis, to investigate the accuracy of the risk estimate (e.g., the annual failure rate) vs the size of ground motion samples. These investigations consider various scalar intensity measures and confirm that that the number of records required to achieve a given level of accuracy for annual failure rate depends not only on the dispersion of structural responses, but also on the shape of the hazard curve at the site. This indicates that the efficiency of some frequently-used intensity measures is not only structure-specific but also site-specific.

Ground motion sample size vs estimation uncertainty in seismic risk / Baltzopoulos, G.; Iervolino, I.; Baraschino, R.. - (2019). (Intervento presentato al convegno 13th International Conference on Applications of Statistics and Probability in Civil Engineering tenutosi a Seoul (South Korea) nel 26-30 May 2019).

Ground motion sample size vs estimation uncertainty in seismic risk

Baltzopoulos G.;Iervolino I.;Baraschino R.
2019

Abstract

In the context of seismic risk assessment as per the performance-based earthquake engineering paradigm, a probabilistic description of structural vulnerability is often obtained via dynamic analysis of a nonlinear numerical model. It typically involves subjecting the structural model to a suite of ground-motions that are representative, as a sample, of possible seismic shaking at the site of interest. The analyses' results are used to calibrate a stochastic model describing structural response as a function of seismic intensity. The sample size of ground motion records used is, nowadays, usually governed by computation-time constraints; on the other hand, it directly affects the estimation uncertainty which is inherent in risk analysis carried out in this way. Recent studies have suggested methodologies for the quantification of estimation uncertainty, to be used as tools for determining the appropriate number of records for each application on an objective basis. The present study uses one of these simulation-based methodologies, based on standard statistical inference methods and the derivation of structural fragility via incremental dynamic analysis, to investigate the accuracy of the risk estimate (e.g., the annual failure rate) vs the size of ground motion samples. These investigations consider various scalar intensity measures and confirm that that the number of records required to achieve a given level of accuracy for annual failure rate depends not only on the dispersion of structural responses, but also on the shape of the hazard curve at the site. This indicates that the efficiency of some frequently-used intensity measures is not only structure-specific but also site-specific.
2019
Ground motion sample size vs estimation uncertainty in seismic risk / Baltzopoulos, G.; Iervolino, I.; Baraschino, R.. - (2019). (Intervento presentato al convegno 13th International Conference on Applications of Statistics and Probability in Civil Engineering tenutosi a Seoul (South Korea) nel 26-30 May 2019).
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11588/770719
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