2019
DOI: 10.1115/1.4041680
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Radial Basis Functions Update of Digital Models on Actual Manufactured Shapes

Abstract: In the mechanical engineering world, there is a growing interest in being able to create so-called “digital twins” to assess the impact to performance or response. Part of the challenge is to be able to include and assess manufactured geometries as opposed to nominal design intent, particularly for components that are sensitive to small shape variations. In this paper, we show how the update of digital models adopted in computer aided engineering (CAE) can be conducted according to a mesh morphing workflow bas… Show more

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Cited by 11 publications
(2 citation statements)
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“…Examples of aerospace applications can be found in [18], where it is coupled to an adjoint solver for an external aerodynamic optimization problem, and in [19], where it is applied to model the ice accretion on an aerofoil. In [20], RBFs are used to generate the surface of a measured wind tunnel model. Several problems were successfully faced with RBF mesh morphing in other fields of engineering such as nautical [21], biomedical [22], automotive [23], train [24], and oil and gas [25].…”
Section: Introductionmentioning
confidence: 99%
“…Examples of aerospace applications can be found in [18], where it is coupled to an adjoint solver for an external aerodynamic optimization problem, and in [19], where it is applied to model the ice accretion on an aerofoil. In [20], RBFs are used to generate the surface of a measured wind tunnel model. Several problems were successfully faced with RBF mesh morphing in other fields of engineering such as nautical [21], biomedical [22], automotive [23], train [24], and oil and gas [25].…”
Section: Introductionmentioning
confidence: 99%
“…Schleich et al [32] introduced a holistic DT reference model for design geometry inspection based on the Skin Model Shapes concept. To deal with geometric reconstruction problems, Biancolini and Cella [249] presented a mesh morphing workflow based on radial basis functions for model validation.…”
Section: Engineering Plm Stages Descriptionmentioning
confidence: 99%