Torodd S. Nord

Model-Based Estimation of Hydrodynamic Forces on the Bergsoysund Bridge

Knowledge of excitation loads on bridges are important for reliable design. Load models are however prone to uncertainties. Force identification using dynamic response measured on full-scale structures can be used to reduce the uncertainty. In this contribution, numerical simulations are performed to examine the feasibility of force identification on the floating pontoon Bergsoysund Bridge. We present a practical case study in which wave excitation forces and motion induced forces are estimated using only acceleration output. The sensor network considered represents the monitoring system currently installed on the bridge. A reduced order model with 26 modes is used to represent the structure in the identification. Wave force time series are generated by Monte Carlo simulations, and the acceleration response is obtained from a frequency domain solution of the equations of motion. The generated acceleration data is polluted with noise and subsequently used for identification. The results show that a joint input-state estimation algorithm is able to adequately identify a subset of hydrodynamic forces acting on the pontoons in the presence of both measurement and model errors. The translational forces are identified with a larger accuracy than the moments. Lastly, considerations and improvements for an analysis with experimental field data are presented.

MODEL-BASED JOINT INPUT-STATE ESTIMATION ON A THIN-WALLED CANTILEVER BEAM

In the field of structural dynamics, measuring external forces directly is often not feasible, whereas structural response data is far more accessible. Force identification is an inverse problem concerned with estimating forces using measured dynamic response. This paper presents a practical application of a joint input-state estimation algorithm. The algorithm gives minimum-variance unbiased estimates of states and input forces in a discrete-time linear system, where stochastic noise in the measurement data and model description are accommodated for. An experimental study of a thin-walled cantilever beam is presented to demonstrate joint input-state estimation. The finite element modelling is done in the software ABAQUS with shell elements. A modally reduced order model is created, containing 13 selected modes. We introduce the general approach of obtaining strain measurements in a modal format. A sensor network is designed from a discussion on optimal placement of accelerometers and strain gauges. It is also shown that the sensor network constitute a sufficient observational ensemble for estimation of states and forces. The studies demonstrate successful identification of forces generated by a simple mass-spring system. In addition, the strain is predicted at a location not co-located with the sensor network. The predicted strain agrees well with a reference strain measured at the same location. Lastly, we address some of the practical problems encountered and recommendations for further experiments.