Fast reconstruction of aerodynamic shapes using evolutionary algorithms and virtual nash strategies in a CFD design environment

This paper compares the performances of two different optimisation techniques for solving inverse problems; the first one deals with the Hierarchical Asynchronous Parallel Evolutionary Algorithms software (HAPEA) and the second is implemented with a game strategy named Nash-EA. The HAPEA software is based on a hierarchical topology and asynchronous parallel computation. The Nash-EA methodology is introduced as a distributed virtual game and consists of splitting the wing design variables - aerofoil sections - supervised by players optimising their own strategy. The HAPEA and Nash-EA software methodologies are applied to a single objective aerodynamic ONERA M6 wing reconstruction. Numerical results from the two approaches are compared in terms of the quality of model and computational expense and demonstrate the superiority of the distributed Nash-EA methodology in a parallel environment for a similar design quality

Rediscovery Of Nyctibius Leucopterus (white-winged Potoo) In The Atlantic Forest Of Brazil

The first documented record of Nyctibius leucopterus in eastern Brazil, since its discovery and description at the beginning of XIX century, is detailed: one individual was tape-recorded and video-taped at Una Biological Reserve, southern Bahia, at 1 november 1999. Four subsequent records for the same region is provided.11114Bonalume, R., Ave descoberta em 1821 "reaparece (1999) Folha de São Paulo, Science, , 6 JuneCohn-Haft, M., Rediscovery of the White-winged Potoo (Nyctibius leucopterus) (1993) Auk, 110, pp. 391-394_ (1999) Family Nyctibiidae (Potoos), p. 288-301. In: J. del Hoyo, A. Elliott and J. Sargatal (eds.) Handbook of the Birds of the World, v. 5. Barcelona: Lynx EdicionsGrantsau, R., Lima, P.C., Santos, S.S., Lima, R.C.F., Nyctibius leucopterus, Wied 1821, redescoberto na Bahia depois de 177 anos. (1999) Atual. Orn, 89, p. 6Hardy, J.W., Reynard, G.B., Coffey Jr., B.B., (1997) Voices of the New World nightjars & their allies, , Ara Records, Gainnesville, FL, Ara-14. Revised edition(1992) Lista das espécies de aves brasileiras ameaçadas de extinção, , IBAMA , Brasília: IBAMALima, P.C., Santos, S.S., Lima, R.C.F., Aves raras e espécies ameaçadas de extinção no litoral norte da Bahia (e a redescoberta do Nyctibius leucopterus, Wied 1821, após 177 anos). (1999) A Tarde Rural, pp. 4-5. , 31 MayPaynter, R.L., Traylor, M.A., (1991) Ornithological gazetteer of Brazil, , Cambridge: Museum of Comparative ZoologyVanzolini, P.E., (1992) A supplement to the ornithological gazetteer of Brazil, , São Paulo: Museu de Zoologia, Universidade de São PauloWied, M., (1821) Reise nach Brasilien in den Jahren 1815 bis 1817, 2. , Frankfurt: H. L. BrönnerWied, M., (1830) Beiträge zur Naturgeschichte von Brasilien, 3. , Weimar: Landes-Industrie-Comptoir

A framework for multidisciplinary design and optimisation in aeronautics

This paper examines the initial development and application of a framework for Multidisciplinary Design and Optimisation (MDO) in aeronautics. Traditional deterministic optimisation techniques for MDO are effective when applied to specific problems and within a specified range. These methods are efficient to find optimal global solutions if the objective and constraints are differentiable. But if a broader application of the optimiser is desired, or when the complexity of the problem arises because they are multi-modal, involve approximation, are non-differentiable, or involve multiple objectives and physics, more robust and alternative numerical tools are required. Emerging techniques such as Evolutionary Algorithms (EAs) have shown to be robust as they require no derivatives or gradients of the objective function, have the capability of finding globally optimum solutions amongst many local optima, are easily executed in parallel, and can be adapted to arbitrary solver codes without major modifications. In this paper, the formulation and implementation of a framework for analysis and optimisation of multidisciplinary and multi-objective optimisation problems in aeronautics is described. The framework includes a Graphics User Interface (GUI) a robust EA optimiser, several design modules, and post-processing capabilities. The application of the method is then illustrated with application to a multi-objective wing design problem. Results indicate the practicality and robustness of the method in finding optimal solutions and trade-offs between the disciplinary analyses, and in producing a set of individuals represented in an optimal Pareto front