A unified framework is presented in order to build lattice constellations matched to both the Rayleigh fading channel and the Gaussian channel. The method encompasses the situations where the interleaving is done on the real components or on two-dimensional signals. In the latter case, a simple construction of lattices congruent to the densest binary lattices with respect to the Euclidean distance is proposed. It generalizes, in a sense to be clarified later, the structural construction proposed by Forney. These constellations are next combined with coset codes. The partitioning rules and the gain formula are similar to those used for the Gaussian channel.

Aircraft electrical power system (EPS), in charge of supplying power to aircraft electric systems, needs a reconfiguration capability in order to overcome cases of EPS component failures. During the design phase, EPS reconfiguration elicitation is a complex task due to the high number of failure combinations and to the aeronautical operational constraints, which are to be taken into account. Therefore a knowledge-based system is developed in order to help designers for such a task. It is based on the implementation of two different types of rules: mandatory and know-how rules. EPS connectivity is managed by graph-theory algorithms. The knowledge-based system is capable of producing several reconfiguration solutions. The knowledge-based system functioning is illustrated in detail on a simplified EPS. Results on an actual and modern EPS are also presented.I.

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More and more electric systems are embedded in today aircraft. As a result, the complexity of electrical power system design is increasing and the need of generic and efficient design methods is today required. Among numerous design tasks, the allocation of electric systems on the busbars of the electrical power system is considered as an important one since it has a direct impact on the aircraft mass. But due to the high number of possible allocations and regarding the large diversity of potential sizing cases for the equipments, finding the optimal allocation of electric loads is a hard task. In this paper, the problem is formalized mathematically. Then, four stochastic optimization methods are assessed on complex load allocation problems. Based on this assessment, a genetic algorithm using niching method is considered as the most appropriate algorithm for solving this aircraft design problem.