检索结果-南通市图书馆

A regularization scheme for explicit level-set XFEM topology optimization

Frontiers of Mechanical Engineering 2019年第2期14卷 153-170页

作者： Markus J.GEISS Jorge L.BARRERA Narasimha BODDETI Kurt MAUTE Ann and H.J.Smead Department of Aerospace Engineering Sciences University of Colorado at BoulderBoulderCO 80309-0429USA Singapore University of Technology and Design SUTD Digital Manufacturing and Design CentreSingapore 487372Singapore

Regularization of the level-set(LS)field is a critical part of LS-based topology optimization(TO)approaches.Traditionally this is achieved by advancing the LS field through the solution of a Hamilton-Jacobi equation combined with a reinitialization scheme.This approach,however,may limit the maximum step size and introduces discontinuities in the design process.Alternatively,energy functionals and intermediate LS value penalizations have been proposed.This paper introduces a novel LS regularization approach based on a signed distance field(SDF)which is applicable to explicit LSbased TO.The SDF is obtained using the heat method(HM)and is reconstructed for every design in the optimization process.The governing equations of the HM,as well as the ones describing the physical response of the system of interest,are discretized by the extended finite element method(XFEM).Numerical examples for pro?blems modeled by linear elasticity,nonlinear hyperelasticity and the incompressible Navier-Stokes equations in two and three dimensions are presented to show the applicability of the proposed scheme to a broad range of design optimization problems.

关键词： level-set regularization explicit level-sets XFEM CutFEM topology optimization heat method signed distance field nonlinear structural mechanics fluid mechanics

来源：

维普期刊数据库评论

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

Characterization of a human brain cortical surface mesh using discrete curvature classification and digital elevation model

引用

Journal of Biomedical Science and Engineering 2012年第3期5卷 133-140页

作者： Kamel Aloui Amine Nait-Ali Mohamed Saber Naceur LiSSi EA LaboratoryUniversite Paris-Est Creteil(UPEC)CreteilFrance LTSIRS Laboratory National Engineering SchoolTunisTunisia

In this paper we present a novel approach for brain surfacec characterization based on convexity and concavity analysis of cortical surface mesh. Initially, volumetric Magnetic Resonance Images (MRI) data is processed to generate a discrete representation of cortical surface using low-level segmentation tools and level-sets method. Afterward, pipeline procedure for brain characterization/labeling is developed. The first characterization method is based on discrete curvature classification. This is consists on estimating curvature information at each vertex in the cortical surface mesh. The second method is based on transforming the brain surface mesh into Digital Elevation Model (DEM), where each vertex is designed by its space coordinates and geometric measures related to a reference surface. In other word, it consists on analyzing the cortical surface as a topological map or an elevation map where the ridge or crest lines represent cortical gyri and valley lines represents sulci. The experimental results have shown the importance of these characterization methods for the detection of significant details related to the cortical surface.

关键词： Brain Curvature DEN level-sets MRI Mapping Surface Mesh

来源：

维普期刊数据库评论

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

A New Useful Biometrics Tool Based on 3D Brain Human Geometrical Characterizations

引用

Journal of Signal and Information Processing 2012年第2期3卷 198-207页

作者： Kamel Aloui Amine Nait-Ali Saber Naceur National Engineering School of Tunis LTSIRS LaboratoryBelvedereTunisia UniversitéParis-Est CréteilFrance

Previous clinical research studies consider the existence of differences among normal individual cerebral cortex and show that some features such as cerebral sulci are unique for each individual so that human brains are anatomically different and unique to each individual. In this work, we highlight the idea which consists in using medical data, such as brain MRI images for the purpose of individual identification or verification. In other words, we raise the following question: can one identify individuals using their brain geometry characteristics? Our aim is to validate the feasibility of this new biometrics tool based on human brain characterization. The proposed approach differs from existent biometrics modalities (e.g. fingerprint, hand, etc.) in the sense that brain features cannot be modified by individuals as it is the case when using fake fingerprints, or fake hands. In this work, we consider volumetric Magnetic Resonance Images (MRI) from which brain shapes are extracted using a 3D level-sets segmentation approach. Afterwards, geometrical descriptors are extracted from the 3D brain volume and from a projected version which provide specific features such as the isoperimetric ratio, the cortical surface curvature and the Gyrification index. Evaluations performed on a set of MRI images obtained from (MeDEISA) database show that it is possible to distinguish between individuals using their brain characteristics. Preliminary results are particularly encouraging.

关键词： Brain MRI Cortex Cortical folding level-sets biometrics Projection Curvature

来源：

维普期刊数据库评论

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

欢迎您,

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

在线全文

在线全文

在线全文

请选择保存的检索档案：

请选择收藏分类：

通借通还

欢迎您,

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

在线全文

在线全文

在线全文

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：