Assessment of fragility models based on the Sept 19th, 2017 earthquake observed damage

Sancha, Azucena Román-de la; Mayoral, Juan M.; Hutchinson, Tara C.; Candia, Gabriel; Montgomery, Jack; Tepalcapa, S.

doi:10.1016/j.soildyn.2019.105707

Cited by 13 publications

(3 citation statements)

References 22 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Similar closure patterns were observed in several other roads. A relationship between the damage states considered in some fragility curves and the structural damage observed in buildings for the earthquake in Mexico City in 2017 was identified by [65]. Considering those relations and the observed closure pattern, a new criterion for road closure was adopted for this research, which can be replicated in densely populated urban areas, where safety policies following major earthquakes are applied.…”

Section: Segments Closure Criteriamentioning

confidence: 99%

“…The analytical fragility curves, presented in Table 8, were selected to determine the probability of damage to structures in the study area. The damage prediction capabilities of these functions were assessed after the 2017 Mexico City earthquake [65]. However, the authors recognize there is still a degree of uncertainty related to the site-particular assumptions inherent in the fragility functions selected for the analyses.…”

Section: Fragility Curvesmentioning

confidence: 99%

See 1 more Smart Citation

Multivariable Analysis of Transport Network Seismic Performance: Mexico City

Sancha

Silva

2020

Sustainability

View full text Add to dashboard Cite

In densely populated urban areas, predicting the post-earthquake performance of a transport network is a particularly challenging task that requires the integration of modeled structural seismic response, damage scenarios, and resulting traffic behavior. Previous approaches assessing the vulnerability and performance of networks after earthquakes have not succeeded in capturing and estimating the interdependencies between seismic risk parameters and key traffic behavior variables. This paper presents a methodology, based on data analysis and optimization, where the dynamic traffic modeling and probabilistic seismic hazard assessment are coupled, to link and characterize key network performance variables after extreme earthquakes and establish a multivariable seismic performance measure. The methodology is used to study the transport network in the southern part of Mexico City for a set of scenarios. The seismic environment is established through uniform hazard spectra derived for firm soil. Damage to structures is estimated considering site response and using fragility functions. Dynamic traffic modeling is developed to simulate damage-induced road closures and resulting in traffic variations. Post-earthquake network performance is evaluated through data envelopment analyses, obtaining sets of seismic performance boundaries, and seismic performance maps. The methodology offers a quantitative tool with applications in the planning of urban areas that are sustainable and seismic resilient.

show abstract

Section: Segments Closure Criteriamentioning

confidence: 99%

Section: Fragility Curvesmentioning

confidence: 99%

Multivariable Analysis of Transport Network Seismic Performance: Mexico City

Sancha

Silva

2020

Sustainability

View full text Add to dashboard Cite

show abstract

“…In the literature, four key types of techniques can be found for seismic fragility analysis of structures, i.e. the empirical, hybrid, experimental, and analytical methods [34][35][36][37]. However, in these studies, all structure parameters are assumed to be deterministic.…”

Section: Introductionmentioning

confidence: 99%

Dynamic reliability calculation of random structures by conditional probability method

Kubica,

Ahmed,

Muhammad

et al. 2024

Eksploatacja i Niezawodność – Maintenance and Reliability

View full text Add to dashboard Cite

For the composite random reliability problem, based on the Markov hypothesis of the dynamic response spanning action, two procedures of conditional probability explanation are accomplished: to derive the 2nd-order approximate expression for the calculation of the dynamic reliability of the random structure based on Taylor expansion method; secondly is to determine a mathematical sampling technique based on the Kriging model derive from the statistical analysis. Between them, the sampling procedure by the Kriging interpolation model meets the nonlinear correlation among dynamic reliability and structural random boundaries. Consequently, the finite element results can be used instantly to anatomize the significance of random structural parameters on dynamic reliability, avoiding the tedious and cumbersome theoretical derivation. The numerical example outcomes demonstrate that the numerical sampling method established upon the Kriging model is inconsiderate to the ratio to represent the dispersion and has additional benefits in computational verisimilitude and calculation productivity

show abstract

Efficient seismic fragility analysis of structures from dynamic reliability perspective

Liao

Zhang

et al. 2022

Engineering Structures

View full text Add to dashboard Cite

Assessment of fragility models based on the Sept 19th, 2017 earthquake observed damage

Cited by 13 publications

References 22 publications

Multivariable Analysis of Transport Network Seismic Performance: Mexico City

Multivariable Analysis of Transport Network Seismic Performance: Mexico City

Dynamic reliability calculation of random structures by conditional probability method

Efficient seismic fragility analysis of structures from dynamic reliability perspective

Contact Info

Product

Resources

About