| People | Locations | Statistics |
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| Naji, M. |
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| Motta, Antonella |
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| Aletan, Dirar |
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| Mohamed, Tarek |
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| Ertürk, Emre |
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| Taccardi, Nicola |
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| Kononenko, Denys |
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| Petrov, R. H. | Madrid |
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| Alshaaer, Mazen | Brussels |
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| Bih, L. |
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| Casati, R. |
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| Muller, Hermance |
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| Kočí, Jan | Prague |
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| Šuljagić, Marija |
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| Kalteremidou, Kalliopi-Artemi | Brussels |
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| Azam, Siraj |
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| Ospanova, Alyiya |
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| Blanpain, Bart |
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| Ali, M. A. |
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| Popa, V. |
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| Rančić, M. |
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| Ollier, Nadège |
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| Azevedo, Nuno Monteiro |
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| Landes, Michael |
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| Rignanese, Gian-Marco |
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Eder, Martin Alexander
Technical University of Denmark
in Cooperation with on an Cooperation-Score of 37%
Topics
Publications (13/13 displayed)
- 2024Bayesian optimization-based prediction of the thermal properties from fatigue test IR imaging of composite couponscitations
- 2024In-situ and adhesive repair of continuous fiber composites using 3D printingcitations
- 2024Coupled heat transfer–crystallization analysis in continuous carbon fiber-reinforced thermoplastic composites 3D printing: simulation and experimental validation
- 2024Microstructural Evolution During Welding of High Si Solution-Strengthened Ferritic Ductile Cast Iron Using Different Filler Metalscitations
- 2024An experimentally validated thermomechanical model for a parametric study on reducing residual stress in cast iron repair welding
- 2023Corrosion surface morphology-based methodology for fatigue assessment of offshore welded structurescitations
- 2023Thermomechanical modeling and experimental study of a multi-layer cast iron repair welding for weld-induced crack predictioncitations
- 2022Effect of manufacturing defects on fatigue life of high strength steel bolts for wind turbinescitations
- 2022Corrosion Fatigue
- 2019Multiaxial Stress Based High Cycle Fatigue Model for Adhesive Joint Interfacescitations
- 2018An Improved Sub-component Fatigue Testing Method for Material Characterizationcitations
- 2018Effects of Coatings on the High-Cycle Fatigue Life of Threaded Steel Samplescitations
- 2015Fracture analysis of adhesive joints in wind turbine bladescitations
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article
Bayesian optimization-based prediction of the thermal properties from fatigue test IR imaging of composite coupons
Abstract
The prediction of the prevailing self-heat transfer parameters of a glass/epoxy composite coupon during fatigue testing in general and the distinction between viscoelastic- and frictional crack growth-related energy dissipation in particular, are not trivial problems. This work investigates the feasibility of predicting the convective film coefficient, the total work loss as well as the ratio between viscoelastic and fracture-induced damping from thermal images using Bayesian optimization in conjunction with 3D FE thermal analysis. To this end, glass fiber/epoxy biax coupons are pre-damaged by means of a drop weight impact machine and subsequently tested under uniaxial tension-tension high cycle fatigue conditions. IR images are taken of the self-heating thermal profile at steady-state conditions. Synthetic surface thermal images are generated by numerical thermal analysis of the damage distribution obtained by μ-CT scanning prior to testing. Bayesian optimization of the aforementioned parameters is conducted by minimizing the loss function between the as-measured and the synthetic IR image. The predicted work-loss is consequently validated against the measured hysteretic response, from which a very good agreement is found.