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A general surface reconstruction method for post-processing of topology optimisation results

hal.structure.identifierInstitut de Mécanique et d'Ingénierie de Bordeaux [I2M]
dc.contributor.authorBERTOLINO, Giulia
hal.structure.identifierInstitut de Mécanique et d'Ingénierie de Bordeaux [I2M]
dc.contributor.authorCOSTA, Giulio
hal.structure.identifierInstitut de Mécanique et d'Ingénierie de Bordeaux [I2M]
dc.contributor.authorMONTEMURRO, Marco
IDREF: 171660978
hal.structure.identifierInstitut de Mécanique et d'Ingénierie de Bordeaux [I2M]
dc.contributor.authorPERRY, Nicolas
IDREF: 085512125
hal.structure.identifierConception collaborative [G-SCOP_CC ]
dc.contributor.authorPOURROY, Franck
dc.date.accessioned2021-05-14T09:40:45Z
dc.date.available2021-05-14T09:40:45Z
dc.date.issued2019-09-13
dc.date.conference2019-09-11
dc.identifier.urihttps://oskar-bordeaux.fr/handle/20.500.12278/76597
dc.description.abstractEnIn this work, a new semi-automatic surface reconstruction procedure is proposed. The main goal of the method is to reconstruct the boundary surface of a triangulation obtained as a result of a topology optimisation calculation. The reconstruction problem is articulated in two main phases: tessellation mapping and surface fitting. The first phase consists of retrieving a suitable map of the triangulation representing the boundary of the optimised topology. To this purpose, a segmentation of the original triangulation is performed and sub-domains (i.e. patches) are identified by means of a semi-automatic strategy. Then, a shape preserving parametrisation algorithm [1] is used on each patch in order to carry out the mapping and to preserve the real 3D shape of the boundary. The second phase deals with an original approach to the surface fitting problem: the problem is stated as a Constrained Non-Linear Programming Problem (CNLPP) by introducing a constraint on the maximum value of the Gaussian curvature of the boundary surface. In this study, the surface fitting problem is solved in the framework of Non-Uniform Rational Basis Splines (NURBS) surfaces. The main idea is to keep all the parameters defining the NURBS surface as design variables in order to state the surface fitting problem in the most general sense. Nevertheless, this fact implies two consequences of paramount importance, constituting just as many difficulties in solving the related CNLPP. Firstly, when the surface fitting problem is formulated by including the number of control points and the degrees of the basis functions among the unknowns, the overall number of design variables for the problem at hand is not fixed a-priori: hence, the resulting CNLPP is defined over a search space of variable dimension. Secondly, the numerical strategy chosen to face such a problemmust be able to handle design variables of different nature and to optimise, at the same time, the dimension of the design domain as well as the value of each constitutive parameter of the NURBS surface. In order to overcome the two aforementioned issues, the surface fitting phase is composed of two optimisation steps. Firstly, the ERASMUS (EvolutionaRy Algorithm for optimiSation of ModUlar Systems)tool [2] optimises both the value and the number of design variables by means of a two-level Darwinian strategy, allowing the simultaneous evolution of individuals and species. Secondly, the optimum solution provided by ERASMUS constitutes the initial guess for the local gradient-based optimization, which aims at improving the accuracy of the fitting surface. The proposed method coupled with the NURBS based SIMP algorithm [3], represents a valid solution for the semi-automatic post-processing of complex 3D shapes resulting from topology optimisation.
dc.language.isoen
dc.subject-Linear Programming
dc.subjectpost-processing
dc.subject3D
dc.title.enA general surface reconstruction method for post-processing of topology optimisation results
dc.typeCommunication dans un congrès avec actes
dc.subject.halSciences de l'ingénieur [physics]/Mécanique [physics.med-ph]/Génie mécanique [physics.class-ph]
dc.subject.halInformatique [cs]/Modélisation et simulation
bordeaux.hal.laboratoriesInstitut de Mécanique et d’Ingénierie de Bordeaux (I2M) - UMR 5295*
bordeaux.institutionUniversité de Bordeaux
bordeaux.institutionBordeaux INP
bordeaux.institutionCNRS
bordeaux.institutionINRAE
bordeaux.institutionArts et Métiers
bordeaux.countryIT
bordeaux.title.proceedingSIM AM 2019
bordeaux.conference.cityPavie
bordeaux.peerReviewedoui
hal.identifierhal-02297578
hal.version1
hal.origin.linkhttps://hal.archives-ouvertes.fr//hal-02297578v1
bordeaux.COinSctx_ver=Z39.88-2004&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.date=2019-09-13&rft.au=BERTOLINO,%20Giulia&COSTA,%20Giulio&MONTEMURRO,%20Marco&PERRY,%20Nicolas&POURROY,%20Franck&rft.genre=proceeding


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