Intense research and refinement of the tools used in performance-based seismic engineering have been made,but the maturity and accuracy of these methods have not been adequately confirmed with actual data from the fie...Intense research and refinement of the tools used in performance-based seismic engineering have been made,but the maturity and accuracy of these methods have not been adequately confirmed with actual data from the field. The gap between the assumed characteristics of actual building systems and their idealized counterparts used for analysis is wide. When the randomly distributed flaws in buildings as they exist in urban areas and the extreme variability of ground motion patterns combine,the conventional procedures used for pushover or dynamic response history analyses seem to fall short of reconciling the differences between calculated and observed damage. For emergency planning and loss modeling purposes,such discrepancies are factors that must be borne in mind. Two relevant examples are provided herein. These examples demonstrate that consensus-based analytical guidelines also require well-idealized building models that do not lend themselves to reasonably manageable representations from field data. As a corollary,loss modeling techniques,e.g.,used for insurance purposes,must undergo further development and improvement.展开更多
文摘Intense research and refinement of the tools used in performance-based seismic engineering have been made,but the maturity and accuracy of these methods have not been adequately confirmed with actual data from the field. The gap between the assumed characteristics of actual building systems and their idealized counterparts used for analysis is wide. When the randomly distributed flaws in buildings as they exist in urban areas and the extreme variability of ground motion patterns combine,the conventional procedures used for pushover or dynamic response history analyses seem to fall short of reconciling the differences between calculated and observed damage. For emergency planning and loss modeling purposes,such discrepancies are factors that must be borne in mind. Two relevant examples are provided herein. These examples demonstrate that consensus-based analytical guidelines also require well-idealized building models that do not lend themselves to reasonably manageable representations from field data. As a corollary,loss modeling techniques,e.g.,used for insurance purposes,must undergo further development and improvement.
