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Ítem 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/CAEThis 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.Ítem 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/CAECurve 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.