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Multiscale Stochastic Fracture Mechanics of Composites Informed by In-Situ X-Ray CT Tests

Sencu, Razvan Mihai

[Thesis]. Manchester, UK: The University of Manchester; 2017.

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Abstract

This thesis presents the development of a new multiscale stochastic fracture mechanics modelling framework informed by in-situ X-ray Computed Tomography (X-ray CT) tests, which can be used to enhance the quality of new designs and prognosis practices for fibre reinforced composites. To reduce the empiricism and conservatism of existing methods, this PhD research systematically has tackled several challenging tasks including: (i) extension of the cohesive interface crack model to multi-phase composites in both 2D and 3D, (ii) development of a new in-house loading rig to support in-situ X-ray CT tests, (iii) reconstruction of low phase-contrast X-ray CT datasets of carbon fibre composites, (iv) integration of X-ray CT image-based models into detailed crack propagation FE modelling and (v) validation of a partially informed multiscale stochastic modelling method by direct comparison with in-situ X-ray CT tensile test results.

Layman's Abstract

These tasks and the achievements of this research are summarised below: (i) Multiscale modelling of crack propagation in 2DIn this method, a macro-scale domain is first discretised into a number of meso-scale elements (MeEs), in which potential discrete cracks are modelled by pre-inserted cohesive interface elements. A nonlinear microscale simulation is conducted for each MeE in parallel to obtain the crack patterns under different boundary conditions. Adaptively size-increasing MeEs are then simulated, until potential cracks seamlessly cross the boundaries of adjacent MeEs. The resultant cracks, are then integrated as Cohesive Interface Elements (CIEs) into a final anisotropic macro-scale model for modelling global mechanical responses.(ii) Development of new in-situ loading rig for X-ray CT testingA new in-situ X-ray CT loading rig was developed to overcome several shortcomings of the various commercially available equipment. The new rig included a number of innovative features such as: multipurpose loading modes and sample setups, fast sample mounting, fully integrated autonomous motion control, real-time data acquisition and flexibility in carrying out various in-situ loading programmes using under either tensile or compressive loading.(iii) Reconstruction of low phase-contrast X-ray CT image-based modelsThe reconstruction approach is based on identifying the individual fibre centres using a local maxima method and a Bayesian inference model applied to the stack of images. Stacks with reduced width are overlapped to ensure 3D fibre continuity. The approach is illustrated for a [45/90/-45/ 0] carbon fibre reinforced laminae.(iv) Integration of the X-ray CT image-based models in FE modellingThe numerical reconstruction method demonstrates that implementing realistic fibre mesh models in FE simulations of discrete cracks is currently feasible using a partitioning strategy in smaller size meso-scale models. Although the developed reconstruction method in this study is employed for tracking long and tortuous/ nonlinear fibres, the FE meso-scale modelling is implemented using cubic shape models of size 50µm. (v) Validation of the multiscale stochastic fracture mechanics modelling framework The model has been validated using a global model partially informed by X-ray CT in which the global simulation model incorporates details of meso-crack propagation mechanisms, carried out in parallel computation on the image-based meso-scale models. The two main validation tests are the load-displacement curves and the multidirectional damage patterns.

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Bibliographic metadata

Type of resource:
Content type:
Administered thesis
Form of thesis:
Traditional
Type of submission:
Doctoral level ETD - final
Thesis title:
Multiscale Stochastic Fracture Mechanics of Composites Informed by In-Situ X-Ray CT Tests
Degree type:
Doctor of Philosophy
Degree programme:
PhD Civil Engineering
Publication date:
2017-03-07T16:04:39
Institution:
The University of Manchester
Location:
Manchester, UK
Total pages:
218
Abstract:
This thesis presents the development of a new multiscale stochastic fracture mechanics modelling framework informed by in-situ X-ray Computed Tomography (X-ray CT) tests, which can be used to enhance the quality of new designs and prognosis practices for fibre reinforced composites. To reduce the empiricism and conservatism of existing methods, this PhD research systematically has tackled several challenging tasks including: (i) extension of the cohesive interface crack model to multi-phase composites in both 2D and 3D, (ii) development of a new in-house loading rig to support in-situ X-ray CT tests, (iii) reconstruction of low phase-contrast X-ray CT datasets of carbon fibre composites, (iv) integration of X-ray CT image-based models into detailed crack propagation FE modelling and (v) validation of a partially informed multiscale stochastic modelling method by direct comparison with in-situ X-ray CT tensile test results.
Layman's abstract:
These tasks and the achievements of this research are summarised below: (i) Multiscale modelling of crack propagation in 2DIn this method, a macro-scale domain is first discretised into a number of meso-scale elements (MeEs), in which potential discrete cracks are modelled by pre-inserted cohesive interface elements. A nonlinear microscale simulation is conducted for each MeE in parallel to obtain the crack patterns under different boundary conditions. Adaptively size-increasing MeEs are then simulated, until potential cracks seamlessly cross the boundaries of adjacent MeEs. The resultant cracks, are then integrated as Cohesive Interface Elements (CIEs) into a final anisotropic macro-scale model for modelling global mechanical responses.(ii) Development of new in-situ loading rig for X-ray CT testingA new in-situ X-ray CT loading rig was developed to overcome several shortcomings of the various commercially available equipment. The new rig included a number of innovative features such as: multipurpose loading modes and sample setups, fast sample mounting, fully integrated autonomous motion control, real-time data acquisition and flexibility in carrying out various in-situ loading programmes using under either tensile or compressive loading.(iii) Reconstruction of low phase-contrast X-ray CT image-based modelsThe reconstruction approach is based on identifying the individual fibre centres using a local maxima method and a Bayesian inference model applied to the stack of images. Stacks with reduced width are overlapped to ensure 3D fibre continuity. The approach is illustrated for a [45/90/-45/ 0] carbon fibre reinforced laminae.(iv) Integration of the X-ray CT image-based models in FE modellingThe numerical reconstruction method demonstrates that implementing realistic fibre mesh models in FE simulations of discrete cracks is currently feasible using a partitioning strategy in smaller size meso-scale models. Although the developed reconstruction method in this study is employed for tracking long and tortuous/ nonlinear fibres, the FE meso-scale modelling is implemented using cubic shape models of size 50µm. (v) Validation of the multiscale stochastic fracture mechanics modelling framework The model has been validated using a global model partially informed by X-ray CT in which the global simulation model incorporates details of meso-crack propagation mechanisms, carried out in parallel computation on the image-based meso-scale models. The two main validation tests are the load-displacement curves and the multidirectional damage patterns.
Additional digital content not deposited electronically:
not applicable
Non-digital content not deposited electronically:
not applicable
Keyword(s):
Thesis main supervisor(s):
Thesis co-supervisor(s):
Funder(s):
Degree grantor:
Language:
en

Institutional metadata

University researcher(s):
Academic department(s):

Record metadata

Manchester eScholar ID:
uk-ac-man-scw:307943
Created by:
Sencu, Razvan
Created:
7th March, 2017, 16:04:40
Last modified by:
Sencu, Razvan
Last modified:
10th August, 2017, 11:42:10

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