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Hier finden Sie wissenschaftliche Publikationen aus den FraunhoferInstituten. Quantification of uncertainty in the mathematical modelling of a multivariable suspension strut using bayesian interval hypothesisbased approach
 Pelz, P.F.: Uncertainty in Mechanical Engineering III : Selected, peerreviewed papers from the 3rd International Conference on Uncertainty in Mechanical Engineering, ICUME 2018, November 15th  16th, 2018, Darmstadt DurntenZurich: TTP, 2018 (Applied mechanics and materials 885) ISBN: 9783035713107 (Print) ISBN: 9783035723106 ISBN: 9783035733105 S.317 
 International Conference on Uncertainty in Mechanical Engineering (ICUME) <3, 2018, Darmstadt> 

 Englisch 
 Konferenzbeitrag 
 Fraunhofer LBF () 
 Bayesian interval hypothesis; mathematical model; model validation; marginal likelihood; suspension strut; uncertainty 
Abstract
Mathematical models of a suspension strut such as an aircraft landing gear are utilized by engineers in order to predict its dynamic response under different boundary conditions. The prediction of the dynamic response, for example the external loads, the stress and the strength as well as the maximum compression in the springdamper component aids engineers in early decision making to ensure its structural reliability under various operational conditions. However, the prediction of the dynamic response is influenced by model uncertainty. As far as the model uncertainty is concerned, the prediction of the dynamic behavior via different mathematical models depends upon various factors such as the model's complexity in terms of the degrees of freedom, material and geometrical assumptions, their boundary conditions and the governing functional relations between the model input and output parameters. The latter can be linear or nonlinear, axiomatic or empiric, time variant or timeinvariant. Hence, the uncertainty that arises in the prediction of the dynamic response of the resulting different mathematical models needs to be quantified with suitable validation metrics, especially when the system is under structural risk and failure assessment. In this contribution, the authors utilize the Bayesian interval hypothesisbased method to quantify the uncertainty in the mathematical models of the suspension strut.