Modelling product variability and data uncertainty in structural dynamics engineering: overview of achievements of the mc-rtn maduse

Abstract eng:
In the FP6 Marie Curie network Maduse (2004-2008), 23 engineers from 14 countries have worked for more than 30 person years at 6 universities and 3 companies to develop advanced methodologies that deal with non-determinism. First of all, the nature of uncertainty is characterized as either variability (aleatory uncertainty), when scatter occurs over different realisations, or epistemic uncertainty, when insufficient knowledge is available to determine the precise value of a model parameter. Likewise, there are two categories of methods that each apply for one category of problems. A variability case is treated with a probabilistic model, using probability density functions. An epistemic uncertainty case on the other hand is modelled with a possibilistic model, using interval or fuzzy numbers. Both categories of models require a quite different approach. Input data are different, and so are numerical formalisms to capture the type of non-determinism and also calculation procedures that predict how the uncertainty propagates through the analysis. Ultimately, the interpretation of the result is very different too. Probabilistic methods allow for a statistical interpretation, whereas possibilistic methods only give bounds on the output quantities. The network has focussed on the application to dynamic response calculation, a technical field of ever increasing importance. Although several industrial sectors were within the scope of the project, the automotive sector was the main project driver. The network has not only

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