Uncertainty quantification of pure and mixed mode interlaminar fracture of fibre-reinforced composites via a stochastic reduced order model

Pouresmaeeli, S.; Falzon, Brian

doi:10.1016/j.compstruct.2021.114683

Cited by 4 publications

(2 citation statements)

References 24 publications

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“…Although a lot of research has recently been done to propose more advanced UQ&M methods for engineering problems, only a few are the examples of them being applied to strength analysis methods for composites that use analytical [40] or numerical [41] tools requiring negligible computational effort, thus making the execution of hundreds or thousands of calibration runs perfectly acceptable.…”

Section: Advanced Finite Element Analysis (Fea) Tools For Composite M...mentioning

confidence: 99%

Uncertainty quantification for advanced progressive damage models for composites by means of efficient emulators and bootstrapping

Catalanotti¹

2022

Composites Part A: Applied Science and Manufacturing

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Section: Advanced Finite Element Analysis (Fea) Tools For Composite M...mentioning

confidence: 99%

Uncertainty quantification for advanced progressive damage models for composites by means of efficient emulators and bootstrapping

Catalanotti¹

2022

Composites Part A: Applied Science and Manufacturing

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“…31,32 When exploring SHM applications involving fracture mechanics problems, where localised damage features are involved, ROMs have been reported to balance accelerated model evaluations with precision, thus offering an attractive framework for problems of condition assessment or damage localisation. 33,34 For example, POD-based reduction has been employed to address multi-scale 35 or inter-layer models of failure, 36,37 whereas a number of references have proposed basis enrichment techniques that refine the projection basis in an adaptive manner during the online analysis, either via Krylov subspaces 38 or by evaluating the response in regions with localised features of interest in a full-order dimension when needed. 39,40 Similarly, some works combine reduced bases obtained for the healthy system, with a local full-order representation of damaged areas, 41,42 or local modes to represent damage.…”

Section: Introductionmentioning

confidence: 99%

Accelerating structural dynamics simulations with localised phenomena through matrix compression and projection‐based model order reduction

Agathos,

Vlachas,

Garland

et al. 2024

Numerical Meth Engineering

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In this work, a novel approach is introduced for accelerating the solution of structural dynamics problems in the presence of localised phenomena, such as cracks. For this category of problems, conventional projection‐based Model Order Reduction (MOR) methods are either limited with respect to the range of system configurations that can be represented or require frequent solutions of the Full Order Model (FOM) to update the low‐dimensional spaces, in which solutions are represented. In the proposed approach, low‐dimensional spaces, constructed for the healthy structure, are enriched with appropriately selected columns of the flexibility matrix of the system. It can be shown that these spaces contain the solution to the original problem for the static case, while their dimension is much smaller. In order to allow their online construction for arbitrary localised features, the full flexibility matrix of the system should be available. To this end, a hierarchical representation is used for the matrices involved, allowing to compute the flexibility matrix efficiently and with reduced memory requirements. The resulting method offers significant speedups, without sacrificing the flexibility and accuracy of the full order model. The performance and limitations of the approach are studied through a series of examples in structural dynamics.

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Uncertainty quantification and global sensitivity analysis for composite cylinder shell via data-driven polynomial chaos expansion

Chen

Xin-hu

Shen

et al. 2022

J. Phys.: Conf. Ser.

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The mechanical properties of composite material exhibit inherent variation with uncertainty. Uncertainties in material properties propagate and result in uncertainties of mechanical performance of structure made of composite material. Polynomial chaos expansion (PCE) is implemented to carry out uncertainty quantification (UQ) and global sensitivity analysis (GSA) of cylinder shell made of composite material for this paper. A case study concerning eigenvalue buckling load of composite cylinder shell is investigated. Design of experiment (DOE) is conducted by utilizing Latin hypercubic sampling. Then data-driven PCE is established and later validated. Statistical moments (mean and standard deviation) and Sobol sensitivity indices of eigenvalue buckling load are obtained respectively. It is found that the PCE can serve as an efficient approach to handle UQ and GSA in engineering applications.

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Uncertainty quantification of pure and mixed mode interlaminar fracture of fibre-reinforced composites via a stochastic reduced order model

Cited by 4 publications

References 24 publications

Uncertainty quantification for advanced progressive damage models for composites by means of efficient emulators and bootstrapping

Uncertainty quantification for advanced progressive damage models for composites by means of efficient emulators and bootstrapping

Accelerating structural dynamics simulations with localised phenomena through matrix compression and projection‐based model order reduction

Uncertainty quantification and global sensitivity analysis for composite cylinder shell via data-driven polynomial chaos expansion

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