Quantitative control of idealized analysis models of thin designs

Authors:
Ming Li;Junzhe Zheng;Ralph R. Martin
Affiliations:
State Key Laboratory of CAD & CG, Zhejiang University, PR China;State Key Laboratory of CAD & CG, Zhejiang University, PR China;School of Computer Science & Informatics, Cardiff University, UK
Venue:
Computers and Structures
Year:
2012

Citing 17
Cited 0

A posteriori error bounds and global error control for approximation of ordinary differential equations

SIAM Journal on Numerical Analysis
Domain decomposition: parallel multilevel methods for elliptic partial differential equations

Domain decomposition: parallel multilevel methods for elliptic partial differential equations
On the Topological Derivative in Shape Optimization

SIAM Journal on Control and Optimization
Estimation of local modeling error and goal-oriented adaptive modeling of heterogeneous materials: I. Error estimates and adaptive algorithms

Journal of Computational Physics
Estimation of modeling error in computational mechanics

Journal of Computational Physics
Iterative Methods for Sparse Linear Systems

Iterative Methods for Sparse Linear Systems
A small feature suppression/unsuppression system for preparing B-rep models for analysis

Proceedings of the 2005 ACM symposium on Solid and physical modeling
Feature-based multiresolution modeling of solids

ACM Transactions on Graphics (TOG)
Adaptation of CAD model topology for finite element analysis

Computer-Aided Design
Feature sensitivity: A generalization of topological sensitivity

Finite Elements in Analysis and Design
A posteriori evaluation of simplification details for finite element model preparation

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

Computer-Aided Design
Review: A posteriori error estimation techniques in practical finite element analysis

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

Computer-Aided Design
Automated mixed dimensional modelling from 2D and 3D CAD models

Finite Elements in Analysis and Design
Modeling and discretization errors in large eddy simulations of hydrodynamic and magnetohydrodynamic channel flows

Journal of Computational Physics
Estimating the effects of removing negative features on engineering analysis

Computer-Aided Design

Quantified Score

Hi-index	0.00

Visualization

Abstract

When preparing a design model for engineering analysis, model idealization is often used, where defeaturing, and/or local dimension reduction of thin regions, are carried out. This simplifies the analysis, but quantitative estimates of the idealization error, the analysis error caused by this idealization, are necessary if the results are to be of practical use. The paper focuses on a posteriori estimation of such idealization error, via both a theoretical analysis and practical algorithms. Our approach can compute bounds for the errors induced by dimension reduction, defeaturing or both in combination. Performance of our error estimate is demonstrated using examples.