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Failure in Composites: Filling the knowledge gaps Giuliano Allegri ACCIS 2018 Conference November 22 nd , 2018 1
Transcript of Failure in Composites - University of Bristol · Failure of Composites 3 • Scopus search -...
Failure in Composites:Filling the knowledge gapsGiuliano Allegri
ACCIS 2018 Conference
November 22nd, 2018
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Failure of Composites2
• Scopus search - Title-Abs-Key ( composites AND failure AND ( delamination OR interlaminar OR translaminar OR intralaminar ) )
• 7000 + papers!
22/11/2018
ACCIS 2018 Conference
Failure of Composites3
• Scopus search - Title-Abs-Key ( composites AND failure AND ( delamination OR interlaminar OR translaminar OR intralaminar ) )
• 7000 + papers!
22/11/2018
ACCIS 2018 Conference
Carbon fiber market volume by region, 2014 - 2025 (Tons/Tons @ 2014)
x 2
x 3
No Growth Design Philosophy (CHM-17)4
• Substantiated by pyramid of testing• Knockdowns dictated by uncertainty (A- or B-basis)• Compound knockdowns for environmental effects (temperature & humidity)• No growth implies no “lifing” – fatigue accounted for via static strength knockdowns
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Coupons
Generic features
Specific features
Sub-components
Components
Test Analysis
CurrentTest backed up by Analysis
Prob
ability
Strength
B‐BasisA‐Basis
Beyond No Growth Design 5
• Analysis backed up by testing (“virtual testing”)• Data-rich approach to experimental testing (e.g. DIC + inverse FEM)• Probabilistic assessment of structural integrity (e.g. stochastic FEM)• Proper “lifing” of components (akin to ”damage tolerance” for metals)• Structural health monitoring
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Coupons
Generic features
Specific features
Sub-components
Components
Future
Test Analysis
Analysis backed up by Test
Test Analysis
CurrentTest backed up by Analysis
Fatigue Damage Growth6
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• Delamination responsible for 60% of failure incomposite structures (US DoD)
• Delamination initiate at interlaminar stress risers(e.g. free edges, ply drop-offs)
• Strongly dependent on environmental effects
(1) Micro‐Cracking (2) Delamination (3) Fibre‐Failure
(1) (2) (3)
Fatigue Delamination Growth7
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• Usually described by semi-empirical equations (e.g. Paris law)
• C and b dependent on: stress-ratio, mode-mixity, frequency, temperature,moisture, ageing….
Can such a problem be described using machine learning?
dadN
CGmaxb
Fatigue Delamination GrowthA Neural Network Approach
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1. Buckingham theorem (1914): similitude underlined by non-dimensionalgoverning parameters
2. Single Hidden-Layer Neural Network (SLHNN) trained via Extreme Learning(Huang, 2006) – it can represent (semi-)monotonicity constraints (embeddingprevious physical knowledge)
+c1
w1(1)
w1(2)
w1(3)
c2
cN
wN(3)
wN(2)
wN(1)
f
s Y
HiddenLayer
Z
Allegri G., Modelling fatigue delamination growth in fibre‐reinforced composites: Power‐law equations or artificial neural networks?, Materials and Design; 155, 59‐70, 2018
Fatigue Delamination GrowthA Neural Network Approach
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• Training performed in 0.1s on a standard desktop PC• Application example to fatigue delamination growth in T800H/#3631
G. Allegri., Modelling fatigue delamination growth in fibre‐reinforced composites: Power‐law equations or artificial neural networks?, Materials and Design; 155, 59‐70, 2018
Delamination SuppressionThrough-thickness Reinforcement (TTR)
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• Strong enhancement of interlaminar fracture toughness (40x mode I; 4x mode II)• Multi-scale modelling of delamination bridging via z-pins
0
10
20
30
40
0.0 0.2 0.4 0.6 0.8 1.0 G
*
(kJ/
m2)
G. Mohamed, G. Allegri, M. Yasaee, S.R. Hallett, Cohesive element formulation for z‐pin delamination bridging in fibre reinforced laminates, International Journal of Solids and Structures; 132: 232‐44, 2018
Cartie’ (2000)
Structural Health Monitoring via TTR 11
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• Through-thickness reinforcement (TTR) toughens the host material• Multifunctionality: TTR (z-pins) can be employed for detecting delamination in-
situ!
Structural Health Monitoring via TTR 12
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• Through-thickness reinforcement (TTR) toughens the host material• Multifunctionality: TTR (z-pins) can be employed for detecting delamination in-
situ!• Demonstration on ASTM-standard coupons
B. Zhang, G. Allegri, M. Yasaee, S.R. Hallett, I.K. Partridge, On the Delamination Self‐Sensing Function of Z‐Pinned Composite Laminates,Composites Science & Technology; 128: 138‐46, 2016.B. Zhang, G. Allegri, S.R. Hallett, An Investigation into Multi‐Functional Z‐pinned Composite Laminates, Materials & Design; 108: 679‐88, 2016.
Structural Health Monitoring via TTR 13
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• Through-thickness reinforcement (TTR)toughens the host material
• Multifunctionality: TTR (z-pins) can beemployed for detecting delamination in-situ!
• Demonstration on ASTM-standard DCBcoupons
B. Zhang, G. Allegri, M. Yasaee, S.R. Hallett, I.K. Partridge, On the Delamination Self‐Sensing Function of Z‐Pinned Composite Laminates,Composites Science & Technology; 128: 138‐46, 2016.B. Zhang, G. Allegri, S.R. Hallett, An Investigation into Multi‐Functional Z‐pinned Composite Laminates, Materials & Design; 108: 679‐88, 2016.
Acknowledgements14
• The author would like to acknowledge Rolls-Royce plc fortheir support of this research through the CompositesUniversity Technology Centre at the University of Bristol, UK
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