Title:
Seismic Fragility Assessment of High Strength Reinforced Concrete Columns Considering Parameter Uncertainty
Author(s):
A H M Muntasir Billah and M Shahria Alam
Publication:
Symposium Paper
Volume:
293
Issue:
Appears on pages(s):
1-18
Keywords:
RC columns, high strength materials, seismic fragility, uncertainty, failure probability.
DOI:
10.14359/51686238
Date:
10/4/2013
Abstract:
Application of high performance materials in construction combines the advantages of reducing the use of materials, cross-section and reinforcement congestion. Although the application of high strength concrete (HSC) has been gaining popularity in high-rise building construction, parameters affecting the performance of HSC members are still under investigation. The use of high strength steel can result in reduced steel congestion and low cost associated with transportation and installation of rebars. Although many design codes and guidelines apply restrictions on the yield strength of steel reinforcement, high-strength steel (HSS) rebars are still a viable option for longitudinal reinforcement in columns of multi-story moment-frame buildings designed to resist earthquake motions. In this study, a numerical approach has been undertaken for the seismic fragility analysis of RC columns and frames with HSS and HSC. Fragility curves provide the flexibility to deal with the uncertainty in geometric properties, along with the typical uncertainties such as material and ground motion uncertainties. Latin Hypercube Sampling (LHS) technique is employed to quantify the uncertainties associated with different modeling parameters such as concrete compressive strength, yield strength of longitudinal and transverse reinforcement, gross geometries and ground motions. Probabilistic seismic demand model (PSDM) is used to develop fragility curves. The fragility curves thus developed quantify the vulnerability of high strength RC columns and frames and show their effectiveness in reducing the probability of failure compared to regular strength RC columns.