Allying topology and shape optimization through machine learning algorithms
Article dans une revue avec comité de lecture
Author
MUÑOZ, D.
300772 Universitat Politècnica de València = Universitad Politecnica de Valencia = Polytechnic University of Valencia [UPV]
300772 Universitat Politècnica de València = Universitad Politecnica de Valencia = Polytechnic University of Valencia [UPV]
NADAL, E.
300772 Universitat Politècnica de València = Universitad Politecnica de Valencia = Polytechnic University of Valencia [UPV]
300772 Universitat Politècnica de València = Universitad Politecnica de Valencia = Polytechnic University of Valencia [UPV]
Date
2022-07Journal
Finite Elements in Analysis and DesignAbstract
Structural optimization is part of the mechanical engineering field and, in most cases, tries to minimize the overall weight of a given design domain, subjected to functionality constraints given in terms of stresses of displacements. The most relevant techniques are topology and shape optimization. Topology optimization provides the optimal material distribution layout into a given, static, design domain. On the other hand, shape optimization provides the optimal combination of the parameters that define the required parametrization of the domain's boundary. Both techniques have strengths and weaknesses, thus a hybrid optimization approach that combines the former techniques will define a more general structural optimization framework that will take advantage of their synergistic combination. The difficulty arises when communicating both techniques for which, in this paper, we propose a machine learning-based methodology.
Files in this item
Related items
Showing items related by title, author, creator and subject.
-
Manifold learning for coherent design interpolation based on geometrical and topological descriptors Article dans une revue avec comité de lectureIn the context of intellectual property in the manufacturing industry, know-how is referred to practical knowledge on how to accomplish a specific task. This know-how is often difficult to be synthesised in a set of rules ...
-
Article dans une revue avec comité de lectureDomain decomposition strategies and proper generalized decomposition are efficiently combined to obtain a fast evaluation of the solution approximation in parameterized elliptic problems with complex geometries. The classical ...
-
Article dans une revue avec comité de lectureMONTÉS, Nicolas; MORA, Marta C.; FALCÓ, Antonio; HILARIO, Lucia; ROSILLO, Nuria; NADAL, Enrique; CHINESTA SORIA, Francisco (MDPI AG, 2021)This paper presents a real-time global path planning method for mobile robots using harmonic functions, such as the Poisson equation, based on the Proper Generalized Decomposition (PGD) of these functions. The main property ...
-
Article dans une revue avec comité de lectureNADAL, Enrique; CUETO, Elias; ABISSET-CHAVANNE, Emmanuelle; CHINESTA SORIA, Francisco (Elsevier Masson, 2018)Even if the diffusion equation has been widely used in physics and engineering, and its physical content is well understood, some variants of it escape fully physical understanding. In particular, anormal diffusion appears ...
-
Article dans une revue avec comité de lectureAMORES, Víctor J.; MONTÁNS, Francisco J.; CUETO, Elías; CHINESTA SORIA, Francisco (Frontiers Media SA, 2022-05)We propose an efficient method to determine the micro-structural entropic behavior of polymer chains directly from a sufficiently rich non-homogeneous experiment at the continuum scale. The procedure is developed in 2 ...