The present study aims at developing a surrogate modeling method able to represent both non-stationarity and the propagation of uncertainties in the dynamic response of complex structures with time-dependent characteristics. Toward this end, AutoRegressive (ARX) models with random time-varying parameters are introduced. More specifically, the parameters of the introduced model are expanded on a multidimensional basis, with one of the dimensions corresponding to a scheduling variable dependent of time and the rest of them to the probability space of the uncertain input parameters. Linear parameter varying basis functions and polynomial chaos basis are utilized for this purpose with the resulting Polynomial Chaos Linear Parameter Varying ARX (PC-LPV-ARX) model being fully described by a finite number of deterministic coefficients of projection that may be estimated by a linear maximum likelihood method. In order to illustrate the workings of the method, the whole procedure is applied for the construction of a surrogate model of the vibration response of a wind turbine blade under normal operation. The surrogate is estimated from simulated data obtained by FAST (an aeroelastic computeraided engineering tool for the simulation of horizontal axis wind turbines), while the value of the average wind speed within each analysis period is assumed to be uncertain following a normal distribution. In overall, thisstudy aims at demonstrating the effectiveness and applicability of the proposed method for the estimation of non-stationary surrogate models of low order that are capable of accurate approximation of large scale numerical models.
|Titel||Safety and Reliability of Complex Engineered Systems - Proceedings of the 25th European Safety and Reliability Conference, ESREL 2015|
|Redaktører||Luca Podofillini, Bruno Sudret, Božidar Stojadinović, Enrico Zio, Wolfgang Kröger|
|Status||Udgivet - 2015|