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Dynamic data driven applications systems (DDDAS) for multidisciplinary optimisation (MDO)

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Dynamic data driven applications systems (DDDAS) for multidisciplinary optimisation (MDO)

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dc.contributor.advisor Dolz Ruiz, Vicente es_ES
dc.contributor.advisor Kipouros, Timoleon es_ES
dc.contributor.author Patón Pozo, Pedro José es_ES
dc.date.accessioned 2020-05-04T10:24:44Z
dc.date.available 2020-05-04T10:24:44Z
dc.date.created 2016-09-28
dc.date.issued 2020-05-04 es_ES
dc.identifier.uri http://hdl.handle.net/10251/142210
dc.description.abstract [ES] Nowadays, the majority of optimisation processes that are followed to obtain new optimum designs involve expensive simulations that are costly and time comsuming. Besides, designs involving aerodynamics are usually highly constrained in terms of infeasible geometries to be avoided so that it is really important to provide the optimisers effective datum or starting points that enable them to reach feasible solutions. This MSc Thesis aims to continue the development of an alternative design methodology applied to a 2D airfoil at a cruise flight condition by combining concepts of Dynamic Data Driven Application Systems (DDDAS) paradigm with Multiobjec- tive Optimisation. For this purpose, a surrogate model based on experimental data has been used to run a multiobjective optimisation and the given optimum designs have been considered as starting points for a direct optimisation, saving number of evaluations in the process. Throughout this work, a technique for retrieving experi- mental airfoil lift and drag coefficients was conducted. Later, a new parametrisation technique using Class-Shape Transformation (CST) was implemented in order to map the considered airfoils into the design space. Then, a response surface model considering Radial Basis Functions (RBF) and Kriging approaches was constructed and the multiobjective optimisation to maximise lift and minimise drag was under- taken using stochastic algorithms, MOTSII and NSGA. Alternatively, a full direct optimisation from datum airfoil and a direct optimisation from optimum surrogate- based optimisation designs were performed with Xfoil and the results were compared. As an outcome, the developed design methodology based on the combination of surrogate-based and direct optimisation was proved to be more effective than a single full direct optimisation to make the whole process faster by saving number of evaluations. In addition, further work guidelines are presented to show potential directions in which to expand and improve this methodology. es_ES
dc.format.extent 176 es_ES
dc.language Inglés es_ES
dc.publisher Universitat Politècnica de València es_ES
dc.rights Reserva de todos los derechos es_ES
dc.subject DDDAS es_ES
dc.subject Airfoil optimisation es_ES
dc.subject Surrogate model es_ES
dc.subject Multiobjective optimisation es_ES
dc.subject Data mapping es_ES
dc.subject DDDOM es_ES
dc.subject Experimental data es_ES
dc.subject CST parametrisation es_ES
dc.subject Xfoil es_ES
dc.subject.classification MAQUINAS Y MOTORES TERMICOS es_ES
dc.subject.other Máster Universitario en Ingeniería Aeronáutica-Màster Universitari en Enginyeria Aeronàutica es_ES
dc.title Dynamic data driven applications systems (DDDAS) for multidisciplinary optimisation (MDO) es_ES
dc.type Tesis de máster es_ES
dc.rights.accessRights Abierto es_ES
dc.contributor.affiliation Universitat Politècnica de València. Departamento de Máquinas y Motores Térmicos - Departament de Màquines i Motors Tèrmics es_ES
dc.contributor.affiliation Universitat Politècnica de València. Escuela Técnica Superior de Ingeniería del Diseño - Escola Tècnica Superior d'Enginyeria del Disseny es_ES
dc.description.bibliographicCitation Patón Pozo, PJ. (2016). Dynamic data driven applications systems (DDDAS) for multidisciplinary optimisation (MDO). http://hdl.handle.net/10251/142210 es_ES
dc.description.accrualMethod TFGM es_ES
dc.relation.pasarela TFGM\56407 es_ES


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