Web-based integrated cloud CAE platform for large-scale finite element analysis

Ihara, Yu; Hashimoto, Gaku; Okuda, Hiroshi

doi:10.1299/mel.17-00520

Cited by 6 publications

(3 citation statements)

References 6 publications

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“…We selected 82 CAD shapes randomly considering the first 200 shapes of the ABC dataset (Koch et al, 2019), generate first-order tetrahedral meshes with the mesher program Gmsh (Geuzaine & Remacle, 2009), and finally, performed finite element analysis (FEA) with the FEA program Fron-tISTR (Morita et al, 2016;Ihara et al, 2017). For more details about the used dataset, see Appendix D.1.…”

Section: Methodsmentioning

confidence: 99%

Isometric Transformation Invariant and Equivariant Graph Convolutional Networks

Horie,

Morita,

Hishinuma

et al. 2020

Preprint

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Graphs correspond to one of the most important data structures used to represent pairwise relations between objects. Specifically, using the graphs embedded in the Euclidean space is essential to solve real problems, such as object detection, structural chemistry analysis, and physical simulation. A crucial requirement to employ the graphs in the Euclidean space is to learn the isometric transformation invariant and equivariant features. In the present paper, we propose a set of the transformation invariant and equivariant models called IsoGCNs that are based on graph convolutional networks. We discuss an example of IsoGCNs that corresponds to differential equations. We also demonstrate that the proposed model achieves high prediction performance on the considered finite element analysis dataset and can scale up to the graphs with 1M vertices.

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Section: Methodsmentioning

confidence: 99%

Isometric Transformation Invariant and Equivariant Graph Convolutional Networks

Horie,

Morita,

Hishinuma

et al. 2020

Preprint

Self Cite

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“…It was developed in a national project in Japan, and is under continuous development and maintenance. Large-scale analysis cases with hundreds of millions of degrees of freedom using FrontISTR have been reported thus far [6,7]. In addition,…”

Section: Introductionmentioning

confidence: 99%

Large-scale parallel finite element analysis of interface failure in CFRP models

Yamaguchi

Hashimoto

Okuda

2020

JASSE

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Carbon fiber reinforced plastic composites (CFRP) exhibit complex failure mechanisms because they include fiber-matrix and interlaminar interfaces. Detailed modeling of fibers, matrices, and interfaces for conducting accurate progressive damage analysis requires large-scale finite element models. We developed parallel finite element analysis software, that can simulate failure of large-scale CFRP models including interfaces using cohesive elements. We verified the software comparing with proven commercial software. In addition, we validated the software using double cantilever beam tests. The simulation result agrees well with the experimental one. The software can analyze progressive interface damage of large-scale models with more than 77 million degrees of freedom.

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“…Ma et al [31] extracted features from SolidWorks and mapped them to a finite element analysis model in realtime for parallel machine tools. Imaging methods and data structures can provide large-scale cloud CAE services [32]. A service-oriented data exchange architecture for cloudbased design and manufacturing can replace the traditional functions of feature-based data exchange between heterogeneous CAD systems [33].…”

Section: Introductionmentioning

confidence: 99%

An Integrated Cloud CAE Simulation System for Industrial Service Applications

et al. 2019

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The cloud-based computer-aided engineering (CAE) technology expands the application scope of CAE, solves the problem of uneven distribution, and improves the efficiency of the simulation resources. Consequently, various industries are turning to cloud CAE technology to design their products. However, to utilize this technology fully, we must overcome problems, such as impracticality, inability to handle complex analysis objects, poor data transmission, and compatibility, and poor industrial applicability. Based on the ASP.NET, VB.NET, and ANSYS Parametric Design Language, this paper establishes an integrated cloud CAE simulation system for industrial service applications. The system: 1) connects the dispatching manager through the network and 2) clusters the servers according to their load and usage before dispatch, thereby enabling users to access the ANSYS software remotely. The model can be built either by inputting the dimensions of the parametric model through the page or by uploading a three-dimensional computeraided design (CAD) model that meets the format requirements. The material parameters and the boundary conditions also input through the page. Thus, clients can input their own parameters and analyze the server CAD. Finally, the CAE analysis results can be invoked by a page operation, saving meaningful results on the server to be accessed directly by users. The proposed simulation system serves the needs of users both quickly and efficiently. In the large-scale industrial application trials, enterprises responded favorably to the system. In particular, it properly solves the CAE analysis problems of small-and medium-sized machinery and equipment enterprises. INDEX TERMS Integrated design, APDL, CAE, digital design, load balancing, service platform.

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Web-based integrated cloud CAE platform for large-scale finite element analysis

Cited by 6 publications

References 6 publications

Isometric Transformation Invariant and Equivariant Graph Convolutional Networks

Isometric Transformation Invariant and Equivariant Graph Convolutional Networks

Large-scale parallel finite element analysis of interface failure in CFRP models

An Integrated Cloud CAE Simulation System for Industrial Service Applications

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