Transformation of a thin-walled solid model into a surface model via solid deflation

Sheen, Dong-Pyoung; Son, Tae-geun; Myung, Dae-Kwang; Ryu, Cheolho; Lee, Kunwoo; Yeo, Tae Jung

doi:10.1016/j.cad.2010.01.003

Cited by 33 publications

(14 citation statements)

References 27 publications

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“…There are dimension reduction methods (Rezayat, 1998;Donaghy et al, 2000;Sheen et al, 2010), which reduce the dimension of a shape, and feature removal methods (Venkataraman et al, 2002;Zhu and Menq, 2002;Sun et al, 2009), which remove the small or unnecessary features of a shape. In dimension reduction methods, thin-walled solids are converted into faces by extracting the mid-surfaces, and long cylindrical solids are converted into edges.…”

Section: Related Workmentioning

confidence: 99%

CAD model simplification using feature simplifications

Yoon

Kim²

2016

JAMDSM

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Section: Related Workmentioning

confidence: 99%

CAD model simplification using feature simplifications

Yoon

Kim²

2016

JAMDSM

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“…They are usually available for existing buildings but they are too detailed to use in GIS simulation. Analysis becomes complex and the efficiency of computation is low (Sheen et al, 2010). Thus model generalization is required -small details (e.g.…”

Section: Introductionmentioning

confidence: 99%

Cad Construction Method of 3d Building Models for Gis Analysis

Bogusławski

Gold

Rahman

2012

ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci.

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ABSTRACT:Buildings are often modelled as two-dimensional (2D) footprints which are extruded to simple cubes. Buildings are also represented as more complex objects with roofs, facades, etc. -in this case they are polyhedra, sometimes of a complex shape. These allow for visualisation and analysis of a wide area like a city, but micro-scale analysis of interiors is not possible. An example can be rescue operation simulation where information about the internal structure of a building and the external terrain is crucial to improve the response time. It demands a three-dimensional (3D) model where each room is represented as a separate element; there are also doors, windows, walls and other objects that have to be included. Even complex geometrical models can be easily constructed using Computer-Aided Design (CAD) systems. However, lack of semantic information and topological relations makes such models poor choices for GIS analysis. With the new dual half-edge (DHE) data structure and a set of Euler operators a 3D model can be built as in CAD systems, and represented as a cell complex. Construction of non-manifold objects is also possible. An advantage of the DHE is simplicity -only edges and nodes are used. Because of the 3D duality implemented in the structure volumes (cells) and faces are also present in the model. The geometry of a model is constructed explicitly by using Euler operators: connections between elements are created automatically, and semantic information is represented with attributes which can be assigned to any element of the model.

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“…if Figure 8 refers to interfaces of surface type, these configurations can be extended to interfaces of volume type. More specifically, it can be noticed that the configuration where I G is orthogonal to the mid-surfaces of S 1 and S 2 both is lacking of robust solutions [16,21] and other connections can require deviation from mid-surface location to improve the mesh quality. Figure 10b illustrates such configurations and further details will be given in Section 6.…”

Section: Processing Connections Between 'Idealizable' Sub Domainsmentioning

confidence: 99%

“…Among them, the face-pairing [16,21] works from nearly parallel faces of CAD models, which produces robust results on a reduced set of configurations, and Medial Axis Transform (MAT) methods work on mesh models, which is more generic, but produce complex geometry in connection areas. More recently, Robinson and Armstrong [17] used the MAT to identify thin regions candidate to idealization.…”

Section: Prior Workmentioning

confidence: 99%

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Idealized models for FEA derived from generative modeling processes based on extrusion primitives

Boussuge

Léon

Hahmann

et al. 2014

Engineering with Computers

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Abstract. Shape idealization transformations are very common when adapting a CAD component to FEA requirements. Here, an idealization approach is proposed that is based on generative shape processes used to decompose an initial B-Rep object, i.e. extrusion processes. The corresponding primitives form the basis of candidate sub domains for idealization and their connections conveyed through the generative processes they belong to, bring robustness to set up the appropriate connections between idealized sub domains. Taking advantage of an existing construction tree as available in a CAD software does not help much because it may be complicated to use it for idealization processes. Using generative processes attached to an object that are no longer reduced to a single construction tree but to a graph containing all non trivial construction trees, is more useful for the engineer to evaluate variants of idealization. From this automated decomposition, each primitive is analyzed to define whether it can idealized or not. Subsequently, geometric interfaces between primitives are taken into account to determine more precisely the idealizable sub domains and their contours when primitives are incrementally merged to come back to the initial object.

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Transformation of a thin-walled solid model into a surface model via solid deflation

Cited by 33 publications

References 27 publications

CAD model simplification using feature simplifications

CAD model simplification using feature simplifications

Cad Construction Method of 3d Building Models for Gis Analysis

Idealized models for FEA derived from generative modeling processes based on extrusion primitives

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