Digital models for (flexible) Aerospace system behaviour are often high-order and have to be reduced when used in combination with models from complementary disciplines or where many parametric iteration steps are required, such as for design optimisation. Typical examples are control-structure interaction problems, such as vibration attenuation of satellite solar arrays and aero-elasticity and dynamic load alleviation of aircraft. In this module methods are discussed for realising a reduced order model (ROM) from a higher order model. To avoid multiple repetitions of often-costly reduction processes in cases where model parameters are varied, e.g. for system optimization, model parameters should be set for these ROMs to yield so-called P-ROMs. The effect of varied parameters can then be covered on the level of the previously established ROM simply by updating these via the new relevant parameters. The related methods are also called ‘hard computing’ methods because of the mathematically based approach, requiring a relatively well-structured set of the initial full-order systems of equations. These methods can be applied to a multitude of aerospace problems such as vibration control for satellites in orbit and dynamic aero-elastic load alleviation for aircraft. Possibilities for reducing computational effort when using P-ROMS, such as for design optimisation tasks for space structures, are also discussed. - Lecturer: Professor Horst Baier (Technical University Munich).