A tool to identify parameter errors in finite element models

A popular method for updating finite element models with modal test data utilizes optimization of the model based on design sensitivities. The attractive feature of this technique is that it allows some estimate and update of the physical parameters affecting the hardware dynamics. Two difficulties are knowing which physical parameters are important and which of those important parameters are in error. If this is known, the updating process is simply running through the mechanics of the optimization. Most models of real systems have a myriad of parameters. This paper discusses an implementation of a tool which uses the model and test data together to discover which parameters are most important and most in error. Some insight about the validity of the model form may also be obtained. Experience gained from applications to complex models will be shared.