The project SensoTwin is dedicated to the task of increasing the service life of wind turbine rotor blades through detailed recording of the structure, individual manufacturing conditions and the resulting residual stresses using advanced prediction methods, so that the potential service life of the rotor blades can be recognized and used more efficiently.
Digital twins of the rotor blades are created using novel methods of linking experiments, simulations, key data from manufacturing as well as actual impacts during the service life to produce a realistic mathematical model to represent and predict relevant parameters of the service life. One aspect is the prediction of residual stresses in fiber-reinforced polymers, which demands material models enabled to simulate a variety of manufacturing-induced processes and effects. Departing from the outcome of the experimental curing characterization observing various physical material properties with special focus on the time and temperature dependent evolvement of the latter, representative material parameters to describe the development of the degree-of-cure, elastic properties, thermal expansion behavior and chemical shrinkage are determined. Calling on experimental data, obtained from individual isothermal tests, covering the materials’ relevant temperature ranges, the according parameters are determined by a surface-based application of the Levenberg–Marquardt algorithm, employing underlying well-known functions, e.g., equations based on Di Benedetto or Arrhenius.
The resulting material models’ accessibility is supported by a developed code base to allow for integration of the individual models into commercial software, e.g., Finite-Element software and appertaining plug-ins, on the one hand, and, on the other hand, to enable the development of purposive multi-scale models to gain better knowledge of the curing-induced processes during manufacturing and the interdependencies of curing polymer and reinforcing inlays.