Abstract
In this paper, the problem of the evaluation of the uncertainties that originate in the complex design process of a new system is analyzed, paying particular attention to multibody mechanical systems. To this end, the Wiener-Shannon’s axioms are extended to non-probabilistic events and a theory of information for non-repetitive events is used as a measure of the reliability of data. The selection of the solutions consistent with the values of the design constraints is performed by analyzing the complexity of the relation matrix and using the idea of information in the metric space. Comparing the alternatives in terms of the amount of entropy resulting from the various distribution, this method is capable of finding the optimal solution that can be obtained with the available resources. In the paper, the algorithmic steps of the proposed method are discussed and an illustrative numerical example is provided.
Highlights
In industrial applications, the final design solution is almost always an engineering approximation, intrinsically prone to uncertainties
Solutions consistent with the values of the design constraints may be selected by analyzing the complexity of the relation matrix and using the idea of information in the metric space
This is true in the design process of multibody mechanical systems composed of several bodies constrained by kinematic joints
Summary
The final design solution is almost always an engineering approximation, intrinsically prone to uncertainties. The Wiener-Shannon’s axioms can be extended to non-probabilistic events so much so that it is possible to introduce a theory of information for non-repetitive events as a measure of the reliability of data To this end, solutions consistent with the values of the design constraints may be selected by analyzing the complexity of the relation matrix and using the idea of information in the metric space. In the development of new industrial technology, the designer has the task of selecting among alternative solutions for complex systems In this general process, besides a set of objective technical requirements, the designer must take into account some subjective factors that only he is able to quantify. If the data on distribution are not well-known, it is possible to use the principle of maximum entropy to achieve a consistent solution to the problem
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