Estimation of beam material random field properties via sensitivity-based model updating using experimental frequency response functions. (1st March 2018) - Machado, M.R.; Adhikari, S.; Dos Santos, J.M.C.; Arruda, J.R.F.
Highlights: Sensitivity-based updating with measured FRFs to estimate spatially distributed parametersparameters. Beam Spectral Element including distributed random parameters. Extension of model updating procedures to enhance the description of structural dynamic models. Estimation of spatially distributed parameters applied to experimental data of a 3D printing beam. Technique to estimate distributed parameter from dynamic response under stochastic environment. Abstract: Structural parameter estimation is affected not only by measurement noise but also by unknown uncertainties which are present in the system. Deterministic structural model updating methods minimise the difference between experimentally measured data and computational prediction. Sensitivity-based methods are very efficient in solving structural model updating problems. Material and geometrical parameters of the structure such as Poisson's ratio, Young's modulus, mass density, modal damping, etc. are usually considered deterministic and homogeneous. In this paper, the distributed and non-homogeneous characteristics of these parameters are considered in the model updating. The parameters are taken as spatially correlated random fields and are expanded in a spectral Karhunen-Loève (KL) decomposition. Using the KL expansion, the spectral dynamic stiffness matrix of the beam is expanded as a series in terms of discretized parameters, which can be estimated using sensitivity-based model updating techniques. Numerical and experimental tests involving a beam with distributed bending rigidity and mass density are used to verify the proposed method. This extension of standard model updating procedures can enhance the dynamic description of structural dynamic models.