Abstract

Since Finite Element Analysis (FEA) has emerged, the comparison of simulation results with experimental results has become a big issue. Who has to be considered as ‘Master’, and who has to follow? Experiments used much longer than FEA were often seen as the ‘Master’, and the question was, how to match the simulation results and experimental results. It was clear from the very beginning that this challenge can only be solved by using suitable optimization methods, where the parametrization has to be done on the simulation side. Now, optimization methods are available in simulation. So, one has to consider the type of experiments and the type of test specimen, in order to see which analysis and optimization methods are required to start a matching process. One frequently used experiment is called ‘Hammering Test’, where acceleration transfer functions are measured over a certain frequency range. This leads to a direct comparability with a frequency response analysis in simulation. But the situation is becoming more complex, if we consider not only single parts in the experiments but assembled parts in a prestressed state. Then simulation has to take a static loading into account and contact is becoming a crucial point. The main problem is that the experiment does usually not provide any contact pressure distribution of the assembly, but the simulation has to take this effect into account. This is important, because a low contact pressure allows for more vibrations of two coupled parts than a high contact pressure. And what is a low contact pressure, and what is a high contact pressure? As an industrial example, we consider a disc brake, where we use not only the hammering test results for the single parts but also for the assembly with different brake pressures. Therefore, we could try to match the single parts and the assembly as well. The remaining question is, which are the parameters for the matching process. Under the assumption that the geometry of the parts is exact enough in experiment and simulation, because their congruency can be measured, the remaining parameters are the material properties. In fact, a non-homogeneous distribution of material properties for cast or forged parts is obvious. The paper will describe the process of modeling, analysis, and optimization to match simulation results and the experimental results. For the comparison of both results, the concept of FRAC (Frequency Response Assurance Criterion) is used, which correlates the frequency response curves of test and simulation.