Multi-Regression Analysis to Enhance the Predictability of the Seismic Response of Buildings

Several methodologies for assessing seismic risk extract information from the statistical relationship between intensity of ground motions and structural response. The first group is represented by measures (IMs) whilst latter engineering demand parameters (EDPs). higher correlation them, lesser uncertainty in estimating damage structures. In general, IMs are composed either a single (scalar-based IMs) or features both motion structure (vector-valued IMs); category provides efficiency to explain EDPs when compared one. This paper explores how find new vector-valued IMs, which highly correlated with EDPs, means multi-regression analysis. To do so, probabilistic nonlinear dynamic analyses have been performed considering seven-story reinforced concrete building as testbed. At stage, 30 scalar-based 4 (i.e., 120 groups IM-EDP pairs studied). Afterwards, responses classified elastic, inelastic combination both. It has analyzed behaves making these classifications. Then, 435 created enhance predictability scalar 1740 analyzed). Again, most efficient identified. Sufficiency, another property desired also examined. Results show that sufficiency predict response increase IMs. sophistication important consequences terms design assessment civil