Periodic Reporting for period 2 - ANALYST (EM compatibility ANALYsis Statistical Techniques in aeronautics)
Reporting period: 2019-11-01 to 2021-01-31
Onboard equipment is supposed to sustain Electromagnetic (EM) susceptibility current and voltage levels. For a given constitution of an EWIS prototype, EM cross-coupling functions strongly depend on the distance between cables to such an extent that the safest way to avoid cross-coupling is to increase the distance between cables. In EWIS designs, electric cables are grouped together in “cable bundles” for which the EM compatibility of all cables is guaranteed. However, if two cables are in two different cable-bundles, the question is to determine the minimum distance to avoid EM susceptibility.
At the design stage of EWIS, the constitution of cables-bundles is generally known but the distance between bundles remains unknown. Of course, the smallest distance is pursued since it minimizes the EWIS footprint in the aircraft. However it increases the possibility of unacceptable EM cross-coupling. The EWIS installer must thereby have some tools to evaluate the distances and make them acceptable. Particularly, if this distance is lower that the distances of the airframer rules, such a tool must help justifying derogation.
In the Analyst project addresses the EM cross-coupling existing between the electric cables of an EWIS, the phenomenon can be summarized as follows: if an electric wire (source wire) carries a source that drives an electrical signal (a current or a voltage), this signal will induce a signal on close-by wires.
This research problem consists in simplifying the problem by studying two bundles of the same length, running in parallel or with a crossing angle. This problem must thereby cope with all ranges of variations of relevant cable-bundle geometrical parameters. The random variables of this problem are the heights of the two bundles, the length of the bundles, the angle in case the bundles are not parallel. Therefore, the ANALYST tool must manage uncertainty. The mathematical problem to solve is thereby formulated as the determination of the optimum distance between two parallel bundles in order not to trigger a susceptibility level with a given level of confidence (being aware of the probability of occurrence).
- Thorough investigation of the scope of validity and application of the Smart Monte Carlo with sensitivity study depending on the type and number of parameters. This analysis ended up with the requirement to achieve the statistical analysis by sub-bands,
- The selection of a series of existing module required to build and solve the Transmission-line (TL) model
- The evaluation of the performance of all the modules required for building the TL model and the statistical analysis. This investigation ended up with the requirement to optimize the TL p.u.l. parameter calculation improving the already existing GPU technique.
- The development of a frequency management module to be able to carry-out the analysis by frequency sub-bands
- The investigation on the way to use the Smolyak method for making the interpolation of the TL p.u.l. electrical parameters with very promising perspectives.
- The development of prototype versions of the Smart Monte Carlo tool using the COBYLA tool and the Kriging module of the OpenTRurns environment with the possibility to switch to Standard Monte Carlo in case of non-convergence of the internal Kriging method.
- The use of the smart Monte Carlo technique to achieve the self-compatibility of cable bundles,
- The definition of fully controlled consortium test-cases for which dedicated black boxes have been defined and developed to provide reference validation results.
- The development of the Compute module that includes all the optimized modules and the Smart Monte Carlo method.
- The development of the ANALYST tool based that the Compute Module and the user’s interface
- The validations comparing black-box, Compute Module (Smart and Standard Mote Carlo) and ANALYST too results
As several varying parameters are concerned (4 in our case), a Monte-Carlo based statistical solution is the most appropriate. This solution is not intrusive, robust and less time consuming than other methods such as Stochastic Collocation that are efficient only for low numbers of varying parameters. This MonteCarlo method accommodated well enhancement such as surrogate models based on Kriging and optimization algorithms based on COBYLA.
Using deterministic calculation modules as black boxes is of particular interest for generating statistical data bases and probability assessment. This approach is entirely in line with current trends based on deep learning and Artificial Intelligence. To this extent, such approaches provide a new justification to keep working on the EM-physics reliability of those deterministic computer methods (prediction of the amplitude of the resonances of transmission-lines responses, frequency-varying losses and the loss models to apply on wires and shields…) and improve their commuter efficiency (GPU-CPU, parallelization, use of built-in libraries such as OpenTurns…).
Specific modules have been developed to optimize the calculation procedure and its relevance (frequency management, assembling of bundle cross-sections, end-load junction calculation, frequency-dependent losses…. Particular efforts have been made on the calculation of Transmission-Line p.u.l. parameters (CLIG and Smolyak-based interpolation technique).
The impact of the project is also in terms of industrial process since this application addresses installation of cable harnesses in aircraft for which safety must be maintained while optimizing room inside the aircraft. From a societal point of view, the ANALYST application seeks for more confidence in safety assessment. The way to define high level rules to segregate cable bundles is a fully new approach compared to current installation rules based on empirical rules. Especially, the way the optimum distance as well as derogation distances are evaluated are all expressed in terms of a probability level, which is related to security confidence (not to trigger EM susceptibility).
The capability of a better defining the cable-bundle constitution, their routes, their protection has a real impact to protect environment and save energy, especially from the saving weight perspective in order to save electrical energy.
The ANALYST activity with it specific orientation to minimum distance optimization addresses both research and testing (optimization techniques, simulation and experimental tests). From this perspective, the potential of the outputs of ANALYST in terms of education are very high.