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Abstract: FE model updating techniques are used to update dynamic FE models of structures in the light of modal test data. Iterative methods of model updating that update a set of chosen parameters of the model, so as to reduce the difference between the natural frequencies and the mode shapes of the FE model and the corresponding quantities obtained through a modal test on the structure, are probably the most widely used methods. Once experimental modal data has been identified, a necessary prior step, before updating can be carried out, is that of establishing the correspondence between the FE model modes and the experimentally identified modes. It is however experienced that, many a times a situation is encountered where not all of the modes identified through an experiment can be correlated with certainty with those predicted by the FE model and some experimental modes may be left uncorrelated. There could be several reasons for this lack of correlation as identified in the paper. But the consequence is that such uncorrelated modes cannot be used in FE model updating using existing iterative methods based on modal data even when they form valid known pieces of information about the structure. This is a disadvantage since it reduces the quantity of experimental data available for model updating and hence makes the updating process less effective in yielding an updated model that is a closer representation of the structure. This paper identifies this as a limitation of the existing iterative methods of model updating based on modal data and puts forward a notion of FE model updating using uncorrelated modes. The paper proposes a solution to overcome this limitation in the form of a new method of FE model updating that accepts both correlated as well as uncorrelated modes for updating. This is in contrast to all the current iterative modal data based methods of model updating that are based on the assumption of availability of correlated mode pairs and hence cannot use uncorrelated mode shapes and corresponding natural frequencies in the updating process. Formulation of the proposed method is described followed by a couple of numerical examples based on a beam structure to validate the method. The robustness of the method in the presence of simulated noise is also studied. Another numerical example of a more complex F-shape structure is also presented. The method is then validated though an experimental study. The proposed method is found to successfully update an FE model yielding correct estimates of the updating parameters in the presence of uncorrelated modes. [Copyright &y& Elsevier]

Abstract: In this paper the closed form expression of the exact dynamic stiffness matrix of an Euler–Bernoulli beam in the presence of an arbitrary number of concentrated cracks is derived. The procedure adopted for the evaluation of the dynamic stiffness matrix is based on the availability of the exact closed form solution of the vibration modes of the multi-cracked beam, derived by the same authors in a previous paper. The knowledge of the exact explicit dynamic stiffness matrix of the multi-cracked beam makes the direct evaluation of the exact global dynamic stiffness matrix of damaged frame structures possible. Furthermore, it allows the exact evaluation of the frequencies and the corresponding vibration modes, consistent with the distributed parameter model, through the application of the well-known Wittrick–Williams algorithm. Some numerical applications, relative to the evaluation of frequencies and the corresponding mode shapes of multi-cracked framed structure, are reported. Furthermore, the closed-form solution has been validated by comparing with some exact results available in the literature, for a simple single cracked frame. Finally, further new results for a multi-cracked frame have been compared with those obtained by a finite element simulation. [Copyright &y& Elsevier]

Model-based damage detection entails the calibration of damage-indicative parameters in a physics-based computer model of an undamaged structural system against measurements collected from its damaged counterpart. The approach relies on the premise that changes identified in the damage-indicative parameters during calibration reveal the structural damage in the system. In model-based damage detection, model calibration has traditionally been treated as a process, solely operating on the model output without incorporating available knowledge regarding the underlying mechanistic behavior of the structural system. In this paper, the authors propose a novel approach for model-based damage detection by implementing the Extended Constitutive Relation Error (ECRE), a method developed for error localization in finite element models. The ECRE method was originally conceived to identify discrepancies between experimental measurements and model predictions for a structure in a given healthy state. Implementing ECRE for damage detection leads to the evaluation of a structure in varying healthy states and determination of discrepancy between model predictions and experiments due to damage. The authors developed an ECRE-based damage detection procedure in which the model error and structural damage are identified in two distinct steps and demonstrate feasibility of the procedure in identifying the presence, location and relative severity of damage on a scaled two-story steel frame for damage scenarios of varying type and severity. [ABSTRACT FROM AUTHOR]

This paper presents an optimization-based inverse procedure for the determination of external loads applied to a given mechanical structure, by using information concerning the dynamic behavior of the system and its corresponding finite element model. The influence of the stress-stiffening effect on the dynamic characteristics of structural systems is used to establish a relation between the dynamic responses and the applied external forces. An optimization problem is formulated in which the objective function represents the difference between the measured modal characteristics of the loaded structure and their finite element counterparts. The loading parameters (magnitude, position and direction) assumed as being unknown, are considered as design variables. The identification procedure is illustrated by means of numerical simulations and experimental tests, in which a heuristic technique known as LifeCycle model was used. [Copyright &y& Elsevier]