Xi Zou
An Abaqus plugin for efficient damage initiation hotspot identification in large-scale composite structures with repeated features
Zou, Xi; Yan, Shibo; Ilkhani, Mohammad Reza; Brown, Louise; Jones, Arthur; Hamadi, Maxime
Authors
Shibo Yan
Dr MOHAMMAD REZA ILKHANI MOHAMMAD.ILKHANI@NOTTINGHAM.AC.UK
SENIOR RESEARCH FELLOW
Dr LOUISE BROWN LOUISE.BROWN@NOTTINGHAM.AC.UK
ASSISTANT PROFESSOR
Arthur Jones
Maxime Hamadi
Abstract
© 2021 Elsevier Ltd Identifying the hotspots for damage initiation in large-scale composite structure designs presents a significant challenge due to the high modelling cost. For most industrial applications, the finite element (FE) models are often coarsely meshed with shell elements and used to predict the global stiffness and internal loads. Because of the lack of detailed descriptions for the composite materials and 3D stress states, most of the established failure criteria are not applicable. In this work we present an Abaqus plugin tool which implements a framework to identify the hotspots by using a pre-computed database generated for specific, heavily-repeated feature types based on a given structural model. Developed with an object-oriented implementation in Python, this software is split into two main parts, specifically for feature generation and structural analysis. The pre-computed model presents a full 3D description for the considered feature and works as a submodel to the coarse structure model driven by a one-way transfer of the boundary conditions. The presented framework is an analysis tool for efficient sizing of large-scale composite structures, as it enables 3D damage analysis of the structures in critical zones with significant savings of the modelling and computational cost. The results are compared with conventional FE modelling and satisfactory agreement is observed. In addition, the software also enables the pre-computed database to be stored in an HDF5 data file for further reuse on new structures with the same feature.
Citation
Zou, X., Yan, S., Ilkhani, M. R., Brown, L., Jones, A., & Hamadi, M. (2021). An Abaqus plugin for efficient damage initiation hotspot identification in large-scale composite structures with repeated features. Advances in Engineering Software, 153, Article 102964. https://doi.org/10.1016/j.advengsoft.2020.102964
Journal Article Type | Article |
---|---|
Acceptance Date | Dec 24, 2020 |
Online Publication Date | Jan 18, 2021 |
Publication Date | Mar 1, 2021 |
Deposit Date | Jan 21, 2021 |
Publicly Available Date | Jan 19, 2022 |
Journal | Advances in Engineering Software |
Print ISSN | 0965-9978 |
Electronic ISSN | 1873-5339 |
Publisher | Elsevier |
Peer Reviewed | Peer Reviewed |
Volume | 153 |
Article Number | 102964 |
DOI | https://doi.org/10.1016/j.advengsoft.2020.102964 |
Keywords | General Engineering; Software |
Public URL | https://nottingham-repository.worktribe.com/output/5249387 |
Publisher URL | https://www.sciencedirect.com/science/article/abs/pii/S0965997820310103 |
Additional Information | This article is maintained by: Elsevier; Article Title: An Abaqus plugin for efficient damage initiation hotspot identification in large-scale composite structures with repeated features; Journal Title: Advances in Engineering Software; CrossRef DOI link to publisher maintained version: https://doi.org/10.1016/j.advengsoft.2020.102964; Content Type: article; Copyright: © 2021 Elsevier Ltd. All rights reserved. |
Files
MARQUESS_software_paper_revised
(3.7 Mb)
PDF
You might also like
The Friction of Radially Loaded Hybrid Spindle Bearings under High Speeds
(2023)
Journal Article
Rotor Vibration Control using Multi-Three-Phase Permanent Magnet Synchronous Machines
(2023)
Presentation / Conference Contribution
Design of an aircraft generator with radial force control.
(2023)
Journal Article
Surface Permanent Magnet Synchronous Machines: High Speed Design and Limits
(2022)
Journal Article
Downloadable Citations
About Repository@Nottingham
Administrator e-mail: discovery-access-systems@nottingham.ac.uk
This application uses the following open-source libraries:
SheetJS Community Edition
Apache License Version 2.0 (http://www.apache.org/licenses/)
PDF.js
Apache License Version 2.0 (http://www.apache.org/licenses/)
Font Awesome
SIL OFL 1.1 (http://scripts.sil.org/OFL)
MIT License (http://opensource.org/licenses/mit-license.html)
CC BY 3.0 ( http://creativecommons.org/licenses/by/3.0/)
Powered by Worktribe © 2025
Advanced Search