Laboratorio CAD/CAM/CAE
URI permanente para esta comunidad
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
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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Examinando Laboratorio CAD/CAM/CAE por Autor "Acosta, Diego A."
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Ítem Design of computer experiments applied to modeling of compliant mechanisms for real-time control(SPRINGER, 2013-07-01) Acosta, Diego A.; Restrepo, David; Durango, Sebastian; Ruiz, Oscar E.; Universidad EAFIT. Departamento de Ingeniería Mecánica; Laboratorio CAD/CAM/CAEThis article discusses the use of design of computer experiments (DOCE) (i.e., experiments run with a computer model to find how a set of inputs affects a set of outputs) to obtain a force-displacement meta-model (i.e., a mathematical equation that summarizes and aids in analyzing the input-output data of a DOCE) of compliant mechanisms (CMs). The procedure discussed produces a force-displacement meta-model, or closed analytic vector function, that aims to control CMs in real-time. In our work, the factorial and space-filling DOCE meta-model of CMs is supported by finite element analysis (FEA). The protocol discussed is used to model the HexFlex mechanism functioning under quasi-static conditions. The HexFlex is a parallel CM for nano-manipulation that allows six degrees of freedom (x, y, z, ? x, ? y, ? z ) of its moving platform. In the multi-linear model fit of the HexFlex, the products or interactions proved to be negligible, yielding a linear model (i.e., linear in the inputs) for the operating range. The accuracy of the meta-model was calculated by conducting a set of computer experiments with random uniform distribution of the input forces. Three error criteria were recorded comparing the meta-model prediction with respect to the results of the FEA experiments by determining: (1) maximum of the absolute value of the error, (2) relative error, and (3) root mean square error. The maximum errors of our model are lower than high-precision manufacturing tolerances and are also lower than those reported by other researchers who have tried to fit meta-models to the HexFlex mechanism. © 2012 Springer-Verlag London Limited.Ítem Design of computer experiments applied to modeling of compliant mechanisms for real-time control(Springer London, 2013-07) Acosta, Diego A.; Restrepo, David; Durango, Sebastián; Ruíz, Óscar E.; Universidad EAFIT. Departamento de Ingeniería Mecánica; Laboratorio CAD/CAM/CAEThis article discusses the use of design of computer experiments (DOCE) (i.e., experiments run with a computer model to find how a set of inputs affects a set of outputs) to obtain a force–displacement meta-model (i.e., a mathematical equation that summarizes and aids in analyz-ing the input–output data of a DOCE) of compliant mechanisms (CMs) -- The procedure discussed produces a force–displacement meta-model, or closed analytic vector function, that aims to control CMs in real-time -- In our work, the factorial and space-filling DOCE meta-model of CMs is supported by finite element analysis (FEA) -- The protocol discussed is used to model the HexFlex mechanism functioning under quasi-static conditions -- The HexFlex is a parallel CM for nano-manipulation that allows six degrees of freedom (x, y, z, hx, hy, hz) of its moving platform -- In the multi-linear model fit of the HexFlex, the products or inter-actions proved to be negligible, yielding a linear model (i.e.,linear in the inputs) for the operating range -- The accuracy of the meta-model was calculated by conducting a set of computer experiments with random uniform distribution of the input forces -- Three error criteria were recorded comparing the meta-model prediction with respect to the results of the FEA experiments by determining: (1) maximum of the absolute value of the error, (2) relative error, and (3) root mean square error -- The maximum errors of our model are lower than high-precision manufacturing tolerances and are also lower than those reported by other researchers who have tried to fit meta-models to the HexFlex mechanismÍtem Fitting of Analytic Surfaces to Noisy Point Clouds(2013-01-01) RUIZ, OSCAR EDUARDO; Arroyave-Tobón, S.; Acosta, Diego A.; Universidad EAFIT. Departamento de Ingeniería Mecánica; Laboratorio CAD/CAM/CAEFitting -continuous or superior surfaces to a set of points sampled on a 2-manifold is central to reverse engineering, computer aided geometric modeling, entertaining, modeling of art heritage, etc. This article addresses the fitting of analytic (ellipsoÍtem 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/CAEReverse 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.Ítem Geodesic-based manifold learning for parameterization of triangular meshes(Springer Verlag, 2014) Acosta, Diego A.; Ruíz, Óscar E.; Arroyave, Santiago; Ebratt, Roberto; Cadavid, Carlos; Londono, Juan J.; Universidad EAFIT. Departamento de Ingeniería Mecánica; Laboratorio CAD/CAM/CAEReverse Engineering (RE) requires representing with free forms (NURBS, Spline, Bézier) a real surface which has been pointsampled -- 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 dualdistance 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 geodesicbased dimensionality reduction methods: (a) graphapproximated 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 uniformspeed 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 reductionÍtem Graphs of optimally fit features in assessment of geometric tolerances(2014) Ruíz, Óscar E.; Congote, John; Acosta, Diego A.; Universidad EAFIT. Departamento de Ingeniería Mecánica; Laboratorio CAD/CAM/CAEThis article presents an industrial application case of geometric constraint graphs, whose nodes are statistically optimal instances of manufacturing or design features and whose edges are usual geometric relations used in tolerance applications -- The features might be virtual ones -- As a consequence, they may lie beyond the piece’s extents -- The geometric constraint graph may have cyclic topology -- Contrary to deterministic geometric constraint graphs, tolerance constraint graphs admit numerical slacks, due to their stochastic nature -- The methodology has been applied in industrial scenarios, showing superiority to traditional material features for the assessment of tolerancesÍtem Parametric Curve Reconstruction from Point Clouds using Minimization Techniques(SCITEPRESS, 2013) Ruíz, Óscar E.; Cortés, C.; Aristizábal, M.; Acosta, Diego A.; Vanegas, Carlos A.; Universidad EAFIT. Departamento de Ingeniería Mecánica; Laboratorio CAD/CAM/CAESmooth (C1-, C2-,...) curve reconstruction from noisy point samples is central to reverse engineering, medical imaging, etc -- Unresolved issues in this problem are (1) high computational expenses, (2) presence of artifacts and outlier curls, (3) erratic behavior at self-intersections and sharp corners -- Some of these issues are related to non-Nyquist (i.e. sparse) samples -- Our work reconstructs curves by minimizing the accumulative distance curve cs. point sample -- We address the open issues above by using (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 polygonÍtem Sensitivity analysis in optimized parametric curve fitting(EMERALD GROUP PUBLISHING LIMITED, 2015-03-02) Ruiz, Oscar E.; Cortes, Camilo; Acosta, Diego A.; Aristizabal, Mauricio; Universidad EAFIT. Departamento de Ingeniería Mecánica; Laboratorio CAD/CAM/CAEPurpose-Curve fitting from unordered noisy point samples is needed for surface reconstruction in many applications. In the literature, several approaches have been proposed to solve this problem. However, previous works lack formal characterization of the curve fitting problem and assessment on the effect of several parameters (i.e. scalars that remain constant in the optimization problem), such as control points number (m), curve degree (b), knot vector composition (U), norm degree (k ), and point sample size (r) on the optimized curve reconstruction measured by a penalty function ( f ). The paper aims to discuss these issues. Design/methodology/approach-A numerical sensitivity analysis of the effect of m, b, k and r on f and a characterization of the fitting procedure from the mathematical viewpoint are performed. Also, the spectral (frequency) analysis of the derivative of the angle of the fitted curve with respect to u as a means to detect spurious curls and peaks is explored. Findings-It is more effective to find optimum values for m than k or b in order to obtain good results because the topological faithfulness of the resulting curve strongly depends on m. Furthermore, when an exaggerate number of control points is used the resulting curve presents spurious curls and peaks. The authors were able to detect the presence of such spurious features with spectral analysis. Also, the authors found that the method for curve fitting is robust to significant decimation of the point sample. Research limitations/implications-The authors have addressed important voids of previous works in this field. The authors determined, among the curve fitting parameters m, b and k, which of them influenced the most the results and how. Also, the authors performed a characterization of the curve fitting problem from the optimization perspective. And finally, the authors devised a method to detect spurious features in the fitting curve. Practical implications-This paper provides a methodology to select the important tuning parameters in a formal manner. Originality/value-Up to the best of the knowledge, no previous work has been conducted in the formal mathematical evaluation of the sensitivity of the goodness of the curve fit with respect to different possible tuning parameters (curve degree, number of control points, norm degree, etc.). © Emerald Group Publishing Limited.Ítem Sensitivity analysis in optimized parametric curve fitting(Emerald Group Publishing, 2015) Ruíz, Óscar E.; Cortés, Camilo; Acosta, Diego A.; Aristizábal, Mauricio; Universidad EAFIT. Departamento de Ingeniería Mecánica; Laboratorio CAD/CAM/CAEPurpose – Curve fitting from unordered noisy point samples is needed for surface reconstruction in many applications -- In the literature, several approaches have been proposed to solve this problem -- However, previous works lack formal characterization of the curve fitting problem and assessment on the effect of several parameters (i.e. scalars that remain constant in the optimization problem), such as control points number (m), curve degree (b), knot vector composition (U), norm degree (k), and point sample size (r) on the optimized curve reconstruction measured by a penalty function (f) -- The paper aims to discuss these issues -- Design/methodology/approach - A numerical sensitivity analysis of the effect of m, b, k and r on f and a characterization of the fitting procedure from the mathematical viewpoint are performed -- Also, the spectral (frequency) analysis of the derivative of the angle of the fitted curve with respect to u as a means to detect spurious curls and peaks is explored -- Findings - It is more effective to find optimum values for m than k or b in order to obtain good results because the topological faithfulness of the resulting curve strongly depends on m -- Furthermore, when an exaggerate number of control points is used the resulting curve presents spurious curls and peaks -- The authors were able to detect the presence of such spurious features with spectral analysis -- Also, the authors found that the method for curve fitting is robust to significant decimation of the point sample -- Research limitations/implications - The authors have addressed important voids of previous works in this field -- The authors determined, among the curve fitting parameters m, b and k, which of them influenced the most the results and how -- Also, the authors performed a characterization of the curve fitting problem from the optimization perspective -- And finally, the authors devised a method to detect spurious features in the fitting curve -- Practical implications – This paper provides a methodology to select the important tuning parameters in a formal manner -- Originality/value - Up to the best of the knowledge, no previous work has been conducted in the formal mathematical evaluation of the sensitivity of the goodness of the curve fit with respect to different possible tuning parameters (curve degree, number of control points, norm degree, etc.)