Laboratorio CAD/CAM/CAE

URI permanente para esta comunidad

https://hdl.handle.net/10784/9117

Está en la capacidad de prestar servicios y entrenar asistentes para el mercado internacional en investigación y desarrollo de herramientas para diseño, manufactura y mecánica asistidos por computador (CAD/CAM/CAE).

Líneas de investigación: Applied Computational Geometry; Computational Mechanics; Computer Aided Geometric Design; Computer Aided Manufacturing; Geometric Modeling of Cultural Heritage; Geometric Modeling of Materials; Geometric Modeling of Terrain and Coastal Areas; Medical Images; Medical Kinematics; Robot Kinematics.
Código Minciencias: COL0013067.
Categoría 2019: A1.
Escuela: Ingeniería.
Departamento académico: Ingeniería Mecánica.
Coordinador: Juan Manuel Rodríguez Prieto.
Correo electrónico:jmrodrigup@eafit.edu.co

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Mostrando 1 - 3 de 3

Design of computer experiments applied to modeling compliant mechanisms
(DELFT UNIV TECHNOLOGY, FAC INDUST DESIGN ENG, 2010-01-01) Arango, D.R.; Acosta, D.A.; Durango, S.; Ruiz, O.E.; Universidad EAFIT. Departamento de Ingeniería Mecánica; Laboratorio CAD/CAM/CAE
This article discusses a procedure for force-displacement modeling compliant mechanisms by using a design of computer experiments methodology. This approach produces a force-displacement metamodel that is suited for real-time control of compliant mechanisms. The term metamodel is used to represent a simplified and efficient mathematical model of unknown phenomenon or computer codes. The metamodeling of compliant mechanisms is performed from virtual experiments based on factorial and space filling design of experiments. The procedure is used to modeling the quasi-static behavior of the HexFlex compliant mechanism. The HexFlex is a parallel compliant mechanism for nanomanipulating that allows six degrees of freedom of its moving stage. The metamodel of the HexFlex is performed from virtual experiments by the Finite Element Method (FEM). The obtained metamodel for the HexFlex is linear for the movement range of the mechanism. Simulations of the metamodel were conducted, finding good accuracy with respect to the virtual experiments. © Organizing Committee of TMCE 2010 Symposium.
Geodesic-based manifold learning for parameterization of triangular meshes
(Springer-Verlag France, 2016-11-01) Acosta, D.A.; Ruiz, O.E.; Arroyave, S.; Ebratt, R.; Cadavid, C.; Londono, J.J.; Acosta, Diego A.; Universidad EAFIT. Departamento de Ingeniería Mecánica; Laboratorio CAD/CAM/CAE
Reverse Engineering (RE) requires representing with free forms (NURBS, Spline, B,zier) a real surface which has been point-sampled. To serve this purpose, we have implemented an algorithm that minimizes the accumulated distance between the free form and the (noisy) point sample. We use a dual-distance calculation point to / from surfaces, which discourages the forming of outliers and artifacts. This algorithm seeks a minimum in a function that represents the fitting error, by using as tuning variable the control polyhedron for the free form. The topology (rows, columns) and geometry of the control polyhedron are determined by alternative geodesic-based dimensionality reduction methods: (a) graph-approximated geodesics (Isomap), or (b) PL orthogonal geodesic grids. We assume the existence of a triangular mesh of the point sample (a reasonable expectation in current RE). A bijective composition mapping allows to estimate a size of the control polyhedrons favorable to uniform-speed parameterizations. Our results show that orthogonal geodesic grids is a direct and intuitive parameterization method, which requires more exploration for irregular triangle meshes. Isomap gives a usable initial parameterization whenever the graph approximation of geodesics on be faithful. These initial guesses, in turn, produce efficient free form optimization processes with minimal errors. Future work is required in further exploiting the usual triangular mesh underlying the point sample for (a) enhancing the segmentation of the point set into faces, and (b) using a more accurate approximation of the geodesic distances within , which would benefit its dimensionality reduction.
Parametric curve reconstruction from point clouds using minimization techniques
(2013-01-01) Ruiz, O.E.; Cortés, C.; Aristizábal, M.; Acosta, D.A.; Vanegas, C.A.; Universidad EAFIT. Departamento de Ingeniería Mecánica; Laboratorio CAD/CAM/CAE
Curve reconstruction from noisy point samples is central to surface reconstruction and therefore to reverse engineering, medical imaging, etc. Although Piecewise Linear (PL) curve reconstruction plays an important role, smooth (C1-, C2-,?) curves are needed for many applications. In reconstruction of parametric curves from noisy point samples there remain unsolved issues such as (1) high computational expenses, (2) presence of artifacts and outlier curls, (3) erratic behavior of self-intersecting curves, and (4) erratic excursions at sharp corners. Some of these issues are related to non-Nyquist (i.e. sparse) samples. In response to these shortcomings, this article reports the minimization-based fitting of parametric curves for noisy point clouds. Our approach features: (a) Principal Component Analysis (PCA) pre-processing to obtain a topologically correct approximation of the sampled curve. (b) Numerical, instead of algebraic, calculation of roots in point-to-curve distances. (c) Penalties for curve excursions by using point cloud to - curve and curve to point cloud. (d) Objective functions which are economic to minimize. The implemented algorithms successfully deal with self - intersecting and / or non-Nyquist samples. Ongoing research includes self-tuning of the algorithms and decimation of the point cloud and the control polygon.

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Examinando Laboratorio CAD/CAM/CAE por Autor "Acosta, D.A."

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