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Statistical Characterization of Segregation Distance Among Cable Bundles Aboard Aircraft
Abstract
Due to the large amount of electrical equipment aboard modern aircraft, several EMC problems appear which can be tackled by filtering disturbances at the equipment inputs and shielding cable links (braiding, covering, over-braiding). Among the others, the segregation between interfering cables or bundles of cables becomes crucial to ensure that coupling constraints will not exceed the equipment susceptibility threshold. The aim of this work is to statistically characterize the coupling between cable bundles and its minimization by optimization under stochastic constraints. The Monte Carlo method is used, and an interpolation scheme based on Smolyak grids is investigated to accelerate the computation.
... As efficient alternative, in order to analyze a minimal set of configurations, a stochastic collocation method based on Smolyak quadrature is considered ( [3], [4]). The stochastic collocation method combines the Monte-Carlo approach with the polynomial approximation of stochastic quantities. ...
... This usually results in a poor accuracy of the surrogated model employed with the Kriging approach. This happens also in case of the Smolyak approach, as reported in [4]. Pertinent inclusion of losses decreases of the quality factor of resonances and increases the accuracy of the smart methods. ...
Modern aircraft hosts a large number of electric systems. Due to the transition to a More Electrical Aircraft, future platforms will use even more electric systems. This increases the complexity of the EWIS design from an EMC point of view. When possible, segregation between potentially interfering cables or bundles is a convenient solution to avoid EMC problems. Due to the huge number of installation configurations, the evaluation of the minimal segregation distance between two interacting bundles can be unfeasible. To overcome this situation, a specialized tool has been developed, based on a statistical approach for the analysis of the interaction between couples of bundles. In the paper, the different modules needed for this analysis are detailed and described. Some canonical analysis are then reported to show the capabilities of the tool.
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