{"title":"Variational formulation and monolithic solution of computational homogenization methods","authors":"Christian Hesch, Felix Schmidt, Stefan Schuß","doi":"10.1002/nme.7567","DOIUrl":null,"url":null,"abstract":"<p>In this contribution, we derive a consistent variational formulation for computational homogenization methods and show that traditional FE<span></span><math>\n <semantics>\n <mrow>\n <msup>\n <mo> </mo>\n <mrow>\n <mn>2</mn>\n </mrow>\n </msup>\n </mrow>\n <annotation>$$ {}^2 $$</annotation>\n </semantics></math> and IGA<span></span><math>\n <semantics>\n <mrow>\n <msup>\n <mo> </mo>\n <mrow>\n <mn>2</mn>\n </mrow>\n </msup>\n </mrow>\n <annotation>$$ {}^2 $$</annotation>\n </semantics></math> approaches are special discretization and solution techniques of this most general framework. This allows us to enhance dramatically the numerical analysis as well as the solution of the arising algebraic system. In particular, we expand the dimension of the continuous system, discretize the higher dimensional problem consistently and apply afterwards a discrete null-space matrix to remove the additional dimensions. A benchmark problem, for which we can obtain an analytical solution, demonstrates the superiority of the chosen approach aiming to reduce the immense computational costs of traditional FE<span></span><math>\n <semantics>\n <mrow>\n <msup>\n <mo> </mo>\n <mrow>\n <mn>2</mn>\n </mrow>\n </msup>\n </mrow>\n <annotation>$$ {}^2 $$</annotation>\n </semantics></math> and IGA<span></span><math>\n <semantics>\n <mrow>\n <msup>\n <mo> </mo>\n <mrow>\n <mn>2</mn>\n </mrow>\n </msup>\n </mrow>\n <annotation>$$ {}^2 $$</annotation>\n </semantics></math> formulations to a fraction of the original requirements. Finally, we demonstrate a further reduction of the computational costs for the solution of general nonlinear problems.</p>","PeriodicalId":13699,"journal":{"name":"International Journal for Numerical Methods in Engineering","volume":null,"pages":null},"PeriodicalIF":2.7000,"publicationDate":"2024-07-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/nme.7567","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Journal for Numerical Methods in Engineering","FirstCategoryId":"5","ListUrlMain":"https://onlinelibrary.wiley.com/doi/10.1002/nme.7567","RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"ENGINEERING, MULTIDISCIPLINARY","Score":null,"Total":0}
引用次数: 0
Abstract
In this contribution, we derive a consistent variational formulation for computational homogenization methods and show that traditional FE and IGA approaches are special discretization and solution techniques of this most general framework. This allows us to enhance dramatically the numerical analysis as well as the solution of the arising algebraic system. In particular, we expand the dimension of the continuous system, discretize the higher dimensional problem consistently and apply afterwards a discrete null-space matrix to remove the additional dimensions. A benchmark problem, for which we can obtain an analytical solution, demonstrates the superiority of the chosen approach aiming to reduce the immense computational costs of traditional FE and IGA formulations to a fraction of the original requirements. Finally, we demonstrate a further reduction of the computational costs for the solution of general nonlinear problems.
在这篇论文中,我们为计算均质化方法推导了一个一致的变分公式,并证明传统的 FE 和 IGA 方法是这个最一般框架的特殊离散化和求解技术。这使我们能够极大地增强数值分析以及对所产生的代数系统的求解。特别是,我们扩大了连续系统的维数,对高维问题进行了一致的离散化,并在之后应用离散无效空间矩阵来消除额外的维数。对于一个基准问题,我们可以得到一个解析解,这证明了所选方法的优越性,该方法旨在将传统 FE 和 IGA 公式的巨大计算成本降低到原始要求的一小部分。最后,我们展示了在解决一般非线性问题时计算成本的进一步降低。
期刊介绍:
The International Journal for Numerical Methods in Engineering publishes original papers describing significant, novel developments in numerical methods that are applicable to engineering problems.
The Journal is known for welcoming contributions in a wide range of areas in computational engineering, including computational issues in model reduction, uncertainty quantification, verification and validation, inverse analysis and stochastic methods, optimisation, element technology, solution techniques and parallel computing, damage and fracture, mechanics at micro and nano-scales, low-speed fluid dynamics, fluid-structure interaction, electromagnetics, coupled diffusion phenomena, and error estimation and mesh generation. It is emphasized that this is by no means an exhaustive list, and particularly papers on multi-scale, multi-physics or multi-disciplinary problems, and on new, emerging topics are welcome.