Simulation-Based Fragility Relationships for Unreinforced Masonry Buildings

Abstract

Unreinforced masonry (URM) structures represent a significant portion of the residential building stock of the Central and Eastern United States (CEUSA), accounting for 15% of homes in the 8-state region impacted by the New-Madrid Seismic Zone and an even greater portion of the building stock in most other regions of the world. In addition to significant population, the brittle nature of URM buildings further supports a thorough consideration of seismic response given the susceptibility to severe failure modes. Currently, there is a pressing need for analytically based fragility curves for URM buildings. In order to improve the estimation of damage state probabilities through the development of simulation-based masonry fragilities, an extensive literature survey is conducted on pushover analysis of URM structures. Using this data, capacity diagrams are generated, from which damage exceedance limit states are defined.Demand is simulated using synthetically derived accelerograms representative of the CEUSA.Structural response is evaluated using an advanced capacity spectrum method developed at the Mid-America Earthquake Center. Capacity, demand, and response are thus derived analytically and response data is used to generate an improved and uniform set of fragility curves for use in loss-assessment software via a framework amenable to rapid expansion of pushover database and variation of ground motion records. A set of best practices is hereby developed for selection and use of experimental and analytical data, input ground motions, analysis of structural capacity, limit state definitions, seismic design categories, and probabilistic analysis methods. Curves are expressed in multiple forms for wide range of use in loss-assessment applications. Results are discussed and compared with other relationships developed in the literature, along with those generated using HAZUS opinion-based capacity data. The parameters of the improved fragility relationships developed and presented in this thesis are provided and suggested for reliable use in seismic loss assessment software.iii To my wife, Erin iv ACKNOWLEDGMENTS

Seismic fragility assessment of nonstructural components in unreinforced clay brick masonry buildings

“…The latter is estimated from the propagation of the uncertainties from a set of "primary" parameters, eg, material and quality of construction (β C ) and modelling (β M ). The former has been typically determined using stochastic approaches, eg, a Monte Carlo simulation with primary parameter being material properties, while the latter has been assumed in a subjective manner, eg, 0.3 in Frankie et al ( 19 ) and Erberik ( 16 ). A Federal Emergency Management Agency (FEMA) document, Seismic Performance Assessment of Buildings (FEMA P-58; FEMA 17 ), presents a set of fragility functions for chimneys (based on Osteraas and Krawinkler 40 ) and parapets (based on Osteraas and Krawinkler 41 ) located in, respectively, timber frame and URM buildings.…”

“…The properties should be calibrated using tests on masonry piers. A set of macroelement cohesion and friction as calibrated in Nakamura et al Incremental dynamic analysis (IDA) was performed to obtain building acceleration responses, with PGA being assumed as the IDA parameter (FEMA 18 ; Frankie et al 19 ). A suite of six real normal or strike-slip, shallow, earthquake time-histories (see spectral acceleration, S a , in Figure 11) recorded mostly on shallow or narrow deep soils were used, with the associated M w ranging from 5.9 to 6.6.…”

“…These data are shown for roof-level components by the bold lines in Figure 13 for two PGA levels of 0.1 and 0.3 g. As discussed earlier, it was necessary to include an additional source of variability to the seismic demand to reflect different structural configurations. This source has been commonly assumed as 0.3 (eg, in Erberik 2008 andFrankie et al 2013), but the results for the two one-storey buildings in Figure 12A were used to make an interpretation of the parameter for the relatively low ranges of PGA and/or structural period.…”

“…Past studies, eg, Erberik (2008), Park et al (), Rota et al (), Frankie et al (), Lagomarsino and Cattari (), D'Ayala and Meslem ; D'Ayala et al ), and Rossetto et al (), have considered the seismic fragility of URM buildings, but very few investigations included URM components. The latter has often been either outside the scope of the studies or considered as being equivalent to slight‐to‐moderate damage to the LLRS.…”

“…The latter is estimated from the propagation of the uncertainties from a set of “primary” parameters, eg, material and quality of construction ( β C ) and modelling ( β M ). The former has been typically determined using stochastic approaches, eg, a Monte Carlo simulation with primary parameter being material properties, while the latter has been assumed in a subjective manner, eg, 0.3 in Frankie et al () and Erberik ().…”