Experimental Dynamics

Overview

Engineering science has the aspiration to approach the fundamental challenges of our contemporary civilization: mobility, food and energy supply. All this must be maintained and improved while the global threat of climate change enforces efficiency and sustainability. The need to create a sustainable global society also determines the areas that are covered in Experimental Dynamics: rotating machinery, cornerstones of energy supply and mobility; lightweight structures, cutting-edge engineering enabling today’s vehicles and buildings; medical engineering, fundamental part of astonishing break-throughs that reshaped human society; and more.

The focus of Experimental Dynamics lies on the analysis of mechanical properties based on test set-ups. With a vast number of applications comes a wide range of scientific and technological aspects: which properties are of interest – durability, vibration or aging effects? Is the focus on linear oscillation, non-linear joints, multi-physical magnetic bearings, humanoid robots, or even human cells? The overall objective also points towards more technical questions such as the analysis domain and the used measurement gear where specifically-built sensors, cameras or laser-vibrometers are a part of the available tools. Questions and areas of ongoing progress that substantially influence our research.

An experiment can only be set up appropriately when the expected observations are based on a solid theoretical foundation. Generally, an experimental investigation is justified when the analyzed system is too complex or contains too many unknowns to treat is solely numerically. Similar to other empirical disciplines, scientific and technological progress is rooted in the iteration of experiment and theory. Experimental insight is required to continuously sharpen the simulated forecast. This connection between Experimental Dynamics and simulation is vital and extends beyond the pure exchange of parameter values, yielding the area of Experimental and Hybrid Substructuring.

Experiments are necessary, however, setting up prototypical test environments of entire systems is, in many cases, prohibitively expensive. It is crucial to extend efficiency and sustainability to the experimental testing itself. In Experimental Dynamics this is tackled by the substructuring paradigm: the combination of experimental and numerical analysis on substructure level allows for the isolated analysis of complex substructures which may not be simulated in sufficient detail, followed by a hybrid prediction on assembly level. Despite the seemingly straightforward theoretical basis, the successful experimental implementation of Hybrid Substructuring is far from trivial, resulting in our efforts on System Identification and Real-Time Hybrid Substructuring.