摘要：When mechanical systems are modeled, uncertainties should be taken into account for improving the predictability of the model. In this work a two d.o.f. (degrees of freedom) dynamical system is used to compare two strategies to model uncertainties in structural dynamics. Uncertainties are considered present only on the spring stiffnesses. In the first approach, uncertainties are inserted into each spring stiffness. A probabilistic model is constructed for each random variable associated to each spring stiffness. In the second approach, uncertainties are considered in a global way, that is, a probability model is constructed for the stiffness matrix. In both approaches, the probability density functions are deduced from the Maximum Entropy Principle, using only the available information. The simple example used is helpful to assure a better understanding of the two approaches. The event space generated by each strategy will be shown and it will be discussed how good they are to predict data uncertainties and model uncertainties.
其他摘要：When mechanical systems are modeled, uncertainties should be taken into account for improving the predictability of the model. In this work a two d.o.f. (degrees of freedom) dynamical system is used to compare two strategies to model uncertainties in structural dynamics. Uncertainties are considered present only on the spring stiffnesses. In the first approach, uncertainties are inserted into each spring stiffness. A probabilistic model is constructed for each random variable associated to each spring stiffness. In the second approach, uncertainties are considered in a global way, that is, a probability model is constructed for the stiffness matrix. In both approaches, the probability density functions are deduced from the Maximum Entropy Principle, using only the available information. The simple example used is helpful to assure a better understanding of the two approaches. The event space generated by each strategy will be shown and it will be discussed how good they are to predict data uncertainties and model uncertainties.
