### Abstract

Nonlinear dynamic analysis is of ten used to develop fragility curves within the framework of seismic risk assessment and performance-based earthquake engineering. In the present article, fragility curves are derived from randomly generated clouds of structural response results by using least squares and sum-of -squares regression, and maximum likelihood estimation. Different statistical measures are used to estimate the quality of fragility functions derived by considering varying numbers of ground motions. Graphs are proposed that can be used as guidance regarding the number of calculations required for these three approaches. The effectiveness of the results is demonstrated by their application to a structural model. The results show that the least-squares method for deriving fragility functions converges much faster than the maximum likelihood and sumof -squares approaches. With the least-squares approach, a few dozen records might be sufficient to obtain satisfactory estimates, whereas using the maximum likelihood approach may require several times more calculations to attain the same accuracy.

Language | English |
---|---|

Pages | 97-113 |

Number of pages | 17 |

Journal | Earthquake Spectra |

Volume | 31 |

Issue number | 1 |

DOIs | |

Publication status | Published - 1 Feb 2015 |

### Fingerprint

### Keywords

- nonlinear dynamic analysis
- fragility curves
- risk assessment
- statistical measures

### Cite this

*Earthquake Spectra*,

*31*(1), 97-113. https://doi.org/10.1193/102912EQS320M

}

*Earthquake Spectra*, vol. 31, no. 1, pp. 97-113. https://doi.org/10.1193/102912EQS320M

**Influence of the number of dynamic analyses on the accuracy of structural response estimates.** / Gehl, Pierre; Douglas, John; Seyedi, Darius M.

Research output: Contribution to journal › Article

TY - JOUR

T1 - Influence of the number of dynamic analyses on the accuracy of structural response estimates

AU - Gehl, Pierre

AU - Douglas, John

AU - Seyedi, Darius M.

PY - 2015/2/1

Y1 - 2015/2/1

N2 - Nonlinear dynamic analysis is of ten used to develop fragility curves within the framework of seismic risk assessment and performance-based earthquake engineering. In the present article, fragility curves are derived from randomly generated clouds of structural response results by using least squares and sum-of -squares regression, and maximum likelihood estimation. Different statistical measures are used to estimate the quality of fragility functions derived by considering varying numbers of ground motions. Graphs are proposed that can be used as guidance regarding the number of calculations required for these three approaches. The effectiveness of the results is demonstrated by their application to a structural model. The results show that the least-squares method for deriving fragility functions converges much faster than the maximum likelihood and sumof -squares approaches. With the least-squares approach, a few dozen records might be sufficient to obtain satisfactory estimates, whereas using the maximum likelihood approach may require several times more calculations to attain the same accuracy.

AB - Nonlinear dynamic analysis is of ten used to develop fragility curves within the framework of seismic risk assessment and performance-based earthquake engineering. In the present article, fragility curves are derived from randomly generated clouds of structural response results by using least squares and sum-of -squares regression, and maximum likelihood estimation. Different statistical measures are used to estimate the quality of fragility functions derived by considering varying numbers of ground motions. Graphs are proposed that can be used as guidance regarding the number of calculations required for these three approaches. The effectiveness of the results is demonstrated by their application to a structural model. The results show that the least-squares method for deriving fragility functions converges much faster than the maximum likelihood and sumof -squares approaches. With the least-squares approach, a few dozen records might be sufficient to obtain satisfactory estimates, whereas using the maximum likelihood approach may require several times more calculations to attain the same accuracy.

KW - nonlinear dynamic analysis

KW - fragility curves

KW - risk assessment

KW - statistical measures

UR - http://www.scopus.com/inward/record.url?scp=84922712096&partnerID=8YFLogxK

U2 - 10.1193/102912EQS320M

DO - 10.1193/102912EQS320M

M3 - Article

VL - 31

SP - 97

EP - 113

JO - Earthquake Spectra

T2 - Earthquake Spectra

JF - Earthquake Spectra

SN - 8755-2930

IS - 1

ER -