Improving the conditioning of XFEM/GFEM for fracture mechanics problems through enrichment quasi-orthogonalization

正交化 扩展有限元法 统一的划分 有限元法 数学 水准点(测量) 应用数学 断裂力学 计算力学 算法 数学优化 数学分析 结构工程 工程类 大地测量学 地理
作者
Konstantinos Agathos,Stéphane Bordas,Eleni Chatzi
出处
期刊:Computer Methods in Applied Mechanics and Engineering [Elsevier BV]
卷期号:346: 1051-1073 被引量:75
标识
DOI:10.1016/j.cma.2018.08.007
摘要

Partition of unity enrichment is known to significantly enhance the accuracy of the finite element method by allowing the incorporation of known characteristics of the solution in the approximation space. However, in several cases it can further cause conditioning problems for which a number of remedies have been proposed in the framework of the extended/generalized finite element method (XFEM/GFEM). Those solutions often involve significant modifications to the initial method and result in increased implementation complexity. In the present work, a simple procedure for the local near-orthogonalization of enrichment functions is introduced, which significantly improves the conditioning of the resulting system matrices, while requiring only minor modifications to the initial method. Although application to different types of enrichment functions is possible, the resulting scheme is specialized for the singular enrichment functions used in linear elastic fracture mechanics and tested through benchmark problems.

科研通智能强力驱动
Strongly Powered by AbleSci AI
科研通是完全免费的文献互助平台,具备全网最快的应助速度,最高的求助完成率。 对每一个文献求助,科研通都将尽心尽力,给求助人一个满意的交代。
实时播报
夏弥2016完成签到,获得积分20
2秒前
2秒前
ephore应助爱学习的叭叭采纳,获得30
2秒前
汉堡包应助等待的音响采纳,获得10
3秒前
俏皮谷蓝发布了新的文献求助10
3秒前
Akim应助JingMa采纳,获得10
5秒前
5秒前
7秒前
eloise完成签到,获得积分10
9秒前
9秒前
森山完成签到,获得积分10
10秒前
11秒前
11秒前
顾矜应助科研通管家采纳,获得10
12秒前
12秒前
英俊的铭应助科研通管家采纳,获得10
12秒前
12秒前
12秒前
Jasper应助科研通管家采纳,获得30
12秒前
12秒前
12秒前
12秒前
12秒前
Ava应助科研通管家采纳,获得10
12秒前
12秒前
12秒前
英姑应助科研通管家采纳,获得10
12秒前
12秒前
汉堡包应助科研通管家采纳,获得50
13秒前
13秒前
13秒前
13秒前
CodeCraft应助科研通管家采纳,获得10
13秒前
我不会乱起名字的完成签到,获得积分10
13秒前
13秒前
华仔应助科研通管家采纳,获得10
13秒前
赘婿应助科研通管家采纳,获得10
13秒前
bkagyin应助科研通管家采纳,获得10
13秒前
夏弥2016发布了新的文献求助10
14秒前
CipherSage应助lxx采纳,获得30
16秒前
高分求助中
(应助此贴封号)【重要!!请各用户(尤其是新用户)详细阅读】【科研通的精品贴汇总】 10000
PowerCascade: A Synthetic Dataset for Cascading Failure Analysis in Power Systems 2000
Various Faces of Animal Metaphor in English and Polish 800
Signals, Systems, and Signal Processing 610
Superabsorbent Polymers: Synthesis, Properties and Applications 500
Photodetectors: From Ultraviolet to Infrared 500
On the Dragon Seas, a sailor's adventures in the far east 500
热门求助领域 (近24小时)
化学 材料科学 医学 生物 纳米技术 工程类 有机化学 化学工程 生物化学 计算机科学 物理 内科学 复合材料 催化作用 物理化学 光电子学 电极 细胞生物学 基因 无机化学
热门帖子
关注 科研通微信公众号,转发送积分 6351680
求助须知:如何正确求助?哪些是违规求助? 8166200
关于积分的说明 17185782
捐赠科研通 5407783
什么是DOI,文献DOI怎么找? 2862981
邀请新用户注册赠送积分活动 1840543
关于科研通互助平台的介绍 1689612