A small feature suppression/unsuppression system for preparing B-rep models for analysis

Lee, K. Y.; Armstrong, Cecil; Price, Mark; Lamont, J.

doi:10.1145/1060244.1060258

Cited by 37 publications

(19 citation statements)

References 13 publications

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“…Different application domains' requirements lead to a wide variety of feature definitions. In CAE applications, the focus has been set on removing detail features to simplify models before meshing [4,8]. A particular domain, mostly studied in the 80-90s is the recognition of machining features.…”

Section: Prior Workmentioning

confidence: 99%

Idealized Models for FEA Derived from Generative Modeling Processes Based on Extrusion Primitives

Boussuge

Léon

Hahmann

et al. 2014

Proceedings of the 22nd International Meshing Roundtable

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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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Section: Prior Workmentioning

confidence: 99%

Idealized Models for FEA Derived from Generative Modeling Processes Based on Extrusion Primitives

Boussuge

Léon

Hahmann

et al. 2014

Proceedings of the 22nd International Meshing Roundtable

View full text Add to dashboard Cite

show abstract

“…In case of volumetric entity based techniques, the features are simplified by operating on volumetric entities from the model. The major techniques reported under this category are effective volume [Lee05a,Choi02], cellular representation [Lee04,Lim04], and voxel [He95,Andu02] based approaches. In the explicit feature representation based techniques, the feature information and semantics is explicitly extracted from CAD model or is present in the model in addition to geometric and topological data.…”

Section: Terminologymentioning

confidence: 99%

“…The transformation operations on cells are represented using the concept of cell maps [Lee05a,Ragh98]. In one of the earlier approaches, Bidarra et al discussed application of the concept of cellular complex for developing feature addition and removal operators from the cellular representation of a model [Bida98].…”

Section: Terminologymentioning

confidence: 99%

“…The techniques where operators defined using such cellular transformation acts on surface entities like faces, edges and points for simplification, are studied under the surface entity based category in this paper. This technique uses cell to cell transformation functions for simplifying models by suppressing features for Finite Element Analysis model preparation [Lee05a]. Authors have presented a general methodology to suppress or reinstate features from a B-Rep model by using invertible cell to cell mapping.…”

Section: Size Based Entity Decimationmentioning

confidence: 99%

“…Features are an integral part of modern CAD model and they are used in virtually all the domains of product life cycle, namely design, manufacturing, analysis and maintenance. Even the presence of a single, relatively small geometric feature can increase the size of the underlying discrete physical simulation problem by as much as 10-fold [Whit03,Lee05a]. If we run a finite element analysis on a part with hundreds of small features as shown in Fig.1, the computational time will be very large.…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

A survey of CAD model simplification techniques for physics-based simulation applications

Thakur

Banerjee

Gupta

2009

Computer-Aided Design

163

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Automated CAD model simplification plays an important role in effectively utilizing physicsbased simulation during the product realization process. Currently a rich body of literature exists that describe many successful techniques for fully-automatic or semi-automatic simplification of CAD models for a wide variety of applications. The purpose of this paper is to compile a list of the techniques that are relevant for physics-based simulations problems and to characterize them based on their attributes. We have classified them into the following four categories: techniques based on surface entity based operators, volume entity based operators, explicit feature based operators, and dimension reduction operators. This paper also presents the necessary background information in the CAD model representation to assist the new readers. We conclude the paper by outlining open research directions in this field.

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Analysis‐aware defeaturing of complex geometries with Neumann features

Antolín,

Chanon

2023

Numerical Meth Engineering

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Local modifications of a computational domain are often performed in order to simplify the meshing process and to reduce computational costs and memory requirements. However, removing geometrical features of a domain often introduces a non‐negligible error in the solution of a differential problem in which it is defined. In this work, we extend the results from Buffa et al. (Math Models Methods Appl Sci. 2022; 32(02):359–402.) by studying the case of domains containing an arbitrary number of distinct Neumann features, and by performing an analysis on Poisson's, linear elasticity, and Stokes' equations. We introduce a simple, computationally cheap, reliable, and efficient a posteriori estimator of the geometrical defeaturing error. Moreover, we also introduce a geometric refinement strategy that accounts for the defeaturing error: starting from a fully defeatured geometry, the algorithm determines at each iteration step which features need to be added to the geometrical model to reduce the defeaturing error. These important features are then added to the (partially) defeatured geometrical model at the next iteration, until the solution attains a prescribed accuracy. A wide range of two‐ and three‐dimensional numerical experiments are finally reported to illustrate this work.

show abstract

A small feature suppression/unsuppression system for preparing B-rep models for analysis

Cited by 37 publications

References 13 publications

Idealized Models for FEA Derived from Generative Modeling Processes Based on Extrusion Primitives

Idealized Models for FEA Derived from Generative Modeling Processes Based on Extrusion Primitives

A survey of CAD model simplification techniques for physics-based simulation applications

Analysis‐aware defeaturing of complex geometries with Neumann features

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