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Abstract: Finite element model updating is an optimization problem to identify and correct uncertain modeling parameters. In conventional model updating, physically incompatible criteria, which designate differences between analytical and experimental results, are combined into a single-objective function using weighting factors. There are no general rules for selecting the weighting factors since they are not directly related to the dynamic behavior of the updated model. Thus, a necessary approach is to solve the time-consuming optimization problem repeatedly by varying the values of weighting factors until a satisfactory solution is obtained. In this work, an interactive multiobjective optimization technique called satisficing trade-off method is introduced to avoid the difficulty. It is relatively easy to state what kind of solutions is satisfactory considering the correlations of the initial FE model with the experimental results, the importance of individual modal properties, and measurement errors, etc. The satisficing trade-off method uses this information directly in the optimization process and finds a Pareto solution which is nearest to the given information. Moreover, as the method provides the tangent hyperplane which approximates the Pareto surface in the neighborhood of the obtained Pareto solution, the desired updated model can be found in a few iterations. [Copyright &y& Elsevier]

Abstract: Finite-element model updating is an inverse problem to identify and correct uncertain modeling parameters, which leads to better predictions of the dynamic behavior of a target structure. Unlike other inverse problems, the restrictions on selecting parameters are very high since the updated model should maintain its physical meaning. That is, only the regions with modeling errors should be parameterized and the variations of the parameters should be kept small while the updated results give acceptable correlations with experimental data. To avoid an ill-conditioned numerical problem, the number of parameters should be kept as small as possible. Thus it is very difficult to select an adequate set of updating parameters which meet all these requirements. In this paper, the importance of updating parameter selection is illustrated through a case study, and an automated procedure to guide the parameter selection is suggested based on simple observations. The effectiveness of the suggested procedure is tested with two example problems, one is a simulated case study and the other is a real engineering structure. [Copyright &y& Elsevier]

Finite element model updating is a procedure to minimise the differences between analytical and experimental results and is usually posed as an optimisation problem. In model updating process, one requires not only satisfactory correlations between analytical and experimental results, but also maintaining physical significance of updated parameters. For this purpose, setting up of an objective function and selecting updating parameters are crucial steps in model updating. These require considerable physical insight and usually trial-and-error approaches are common to use. In conventional model updating procedures, an objective function is set as the weighted sum of the differences between analytical and experimental results. But the selection of the weighting factors is not clear since the relative importance among them is not obvious but specific for each problem. In this work, multiobjective optimisation technique is introduced to extremise several objective terms simultaneously. Also the success of finite element model updating depends heavily on the selection of updating parameters. In order to avoid an ill-conditioned numerical problem, the number of updating parameters should be kept as small as possible. Such parameters should be selected with the aim of correcting modelling errors and modal properties of interest should be sensitive to them. When the selected parameters are inadequate, then the updated model becomes unsatisfactory or unrealistic. An improved method to guide the parameter selection is suggested. [Copyright &y& Elsevier]

A damage detection technique based upon an incompletely measured experimental model is studied. Conventional methods such as force balance method are effective to detect damage locations as long as the initial finite element model is accurate and the responses at all the degrees of freedom can be measured experimentally. But these two conditions are practically impossible to be met, with the exception of geometrically simple structures. This work suggests a damage detection method not utilising an accurate analytical finite element model but based upon incompletely measured frequency responses, noting that the reduced dynamical system is an inverse of incompletely measured frequency responses. This work also discusses frequency regions where the suggested method works satisfactorily. From both numeric and test examples, it is found that the proposed method can be an alternative to conventional damage detection methods. [Copyright &y& Elsevier]