Premium
Fractional order intensity measures for probabilistic seismic demand modeling applied to highway bridges
Author(s) -
Shafieezadeh Abdollah,
Ramanathan Karthik,
Padgett Jamie E.,
DesRoches Reginald
Publication year - 2012
Publication title -
earthquake engineering and structural dynamics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 2.218
H-Index - 127
eISSN - 1096-9845
pISSN - 0098-8847
DOI - 10.1002/eqe.1135
Subject(s) - probabilistic logic , spectral acceleration , acceleration , girder , measure (data warehouse) , bridge (graph theory) , intensity (physics) , incremental dynamic analysis , structural engineering , seismic loading , seismic analysis , computer science , peak ground acceleration , engineering , mathematical optimization , mathematics , ground motion , statistics , physics , data mining , medicine , classical mechanics , quantum mechanics
SUMMARY Probabilistic seismic analysis of structures involves the construction of seismic demand models, often stated as probabilistic models of structural response conditioned on a seismic intensity measure. The uncertainty introduced by the model is often a result of the chosen intensity measure. This paper introduces the concept of using fractional order intensity measures (IMs) in probabilistic seismic demand analysis and uses a single frame integral concrete box‐girder bridge class and a seismically designed multispan continuous steel girder bridge class as case studies. The fractional order IMs considered include peak ground response and spectral accelerations at 0.2 and 1.0 s considering a single degree of freedom system with fractional damping, S a d − T n α, as well as a linear single degree of freedom system with fractional response, S a r − T n α. The study reveals the advantage of fractional order IMs relative to conventional IMs such as peak ground acceleration, peak ground velocity, or spectral acceleration at 0.2 and 1.0 s. Metrics such as efficiency, sufficiency, practicality, and proficiency are measured to assess the optimal nature of fractional order IMs. The results indicate that the proposed fractional order IMs produce significant improvements in efficiency and proficiency, whereas maintaining practicality and sufficiency, and thus providing superior demand models that can be used in probabilistic seismic demand analysis. Copyright © 2011 John Wiley & Sons, Ltd.