Adaptive Multi-Scale Modeling of Structures Under Earthquake Loads

Abstract

Civil structures are designed using the load and resistance factor design (LRFD) philosophy in most parts of the world which recognizes the uncertainty in the determination of loads and strengths. A specific structure can be viewed as a sample of the LRFD space and its material properties and external loads are not known in prior at any time of service life. To understand and evaluate the actual behavior of an engineering structure, real-time structural monitoring and modeling taking into account its practicality and cost restraint is necessary during an extreme event. In this study, adaptive multi-scale modeling of structures is conceptualized and exemplified with a four-story, two-bay steel building. A structure is divided into many groups, each having similar geometries and identical materials due to structural symmetry. For each group, the most critical structural member referred to as “master member†is modeled with fiber elements and the remaining members called “slave members†are with beam and plates elements. The material behavior of the master member can be introduced to the modeling of slave members in real time, based on the premise that the latter can be related to the former in terms of construction processes and the noise characteristics can be related to the structural damage under various external loads. Emphasis is placed on the development of an overall adaptive multi-scale modeling framework with load monitoring and resistance evaluation in real time. Towards this end, the master member is instrumented with an array of sensors for material property and structural behavior monitoring, and the slave members are numerically simulated with a finite element model established in ABAQUS. To verify and support the premise, finite element updating is performed in this study to ensure that the interface between the master member and the slave members is compatible in terms of forces and displacements under a predetermined evaluation criterion.