ABSTRACT
Finite Element (FE) model calibration is an essential but very computationally-intensive task for real world civil structures, e.g., bridges, buildings and dams etc., which are usually large in size and represented by thousands of elements for achieving good analysis results. Although performing one analysis run of such a large FE model may take less than a minute with a well-developed FE model solver, but it is preventive to embed such a full-analysis FE solver into an iterative process for model calibration, which often requires for tens or even hundreds of thousands of FE model analysis runs. Therefore, it is of great importance and interest in developing an effective and efficient approach for FE model calibration of large structure systems. In this paper, an effective framework for the accelerated FE model calibration, based on authors’ previous work in FE model calibration, has been presented by integrating the substructure analysis or Component Modal Synthesis (CMS) with parallel genetic algorithm optimization provided by Darwin optimization framework. It enables the parallel solution evaluation processes on a many-core machine or in distributed manner across a cluster of computers. This is a powerful computation framework that has been tested on a FE model calibration of a highway bridge approach span in New York City. This study has proved that the developed tool is effectively tailored for the applications of many real world structures including but not limited to bridges. A calibrated FE model can well present the structural conditions and can be used for condition-based maintenance and facilitate structural life-cycle asset performance management.
