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Multiscale Analysis of AiRframe Structures and Quantification of UncErtaintieS System

Deliverables

Dissemination and Exploitation Plan

A Dissemination and Exploitation Plan will be developed early in the project and will be reported against in the interim and final reports to ensure progress against the plan.

Review of the state of the art regarding multi-scale methods

This deliverable consists of a review of the state of the art regarding multi-scale methods, for application to typical sub-assemblies of multifunctional fuselage and large aircraft, from components

Document describing sources of modelling uncertainties

Document describing sources of modelling uncertainties in predictive virtual simulation of aerospace structures, their potential impact on the accuracy results and ranking in terms of priority for performing uncertainty quantification within a virtual testing context; additionally a sensitivity ranking for idealisation rules, the aim is to understand the margin of error we introduce by derogating from a specific idealisation rule.

Delivery of meso and macro-scale strategies & new multi-scale framework

Delivery of meso and macro-scale strategies, with particular focus on meso/macro, hot spot criteria list and their respective definition & new multi-scale framework consisting of: - Report on approach taken and structure of software - Models used for testing and validation including input data and results of preliminary system tests - Online repository containing software tools (including source code) forming the new framework - User manual containing instructions and examples of use.

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Publications

The Identification of Failure Initiation Hotspots in Idealised Composite Material Component Models Using a “Bottom-Up Database” Method

Author(s): Zou, X.; Yan, S.; Rouse, J.; Matveev, M.; Li, S.; Jones, I. A.; Hamadi, M.; Fouinneteau, M.
Published in: Proceedings of 18th European Conference on Composite Materials, Issue Jun 24, 2018, 2018

An efficient multiscale surrogate modelling framework for composite materials considering progressive damage based on artificial neural networks

Author(s): Shibo Yan, Xi Zou, Mohammad Ilkhani, Arthur Jones
Published in: Composites Part B: Engineering, Issue 194, 2020, Page(s) 108014, ISSN 1359-8368
DOI: 10.1016/j.compositesb.2020.108014

Experimental and numerical investigation of interface damage in composite L-angle sections under four-point bending

Author(s): Zou, X., Yan, S., Matveev, M., Rouse, J. P., & Jones, I. A.
Published in: Journal of Composite Materials, Issue 30 Times/Year, 2020, ISSN 0021-9983