| 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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De Jesus, Abílio M. P.
in Cooperation with on an Cooperation-Score of 37%
Topics
Publications (12/12 displayed)
- 2023A Predictive Methodology for Temperature, Heat Generation and Transfer in Gigacycle Fatigue Testingcitations
- 2023Experimental parametric investigation on the behavior of adhesively bonded CFRP/steel jointscitations
- 2022Fatigue crack growth modelling by means of the strain energy density-based Huffman model considering the residual stress effectcitations
- 2022Fracture Characterization of Hybrid Bonded Joints (CFRP/Steel) for Pure Mode Icitations
- 2022Automation of Property Acquisition of Single Track Depositions Manufactured through Direct Energy Depositioncitations
- 2022A review of fatigue damage assessment in offshore wind turbine support structurecitations
- 2022Tensile Properties of As-Built 18Ni300 Maraging Steel Produced by DEDcitations
- 2021Probabilistic S-N curves for CFRP retrofitted steel detailscitations
- 2021Low-cycle fatigue modelling supported by strain energy density-based Huffman model considering the variability of dislocation densitycitations
- 2020Multiaxial fatigue assessment of S355 steel in the high-cycle region by using Susmel's criterioncitations
- 2020Study of the Fatigue Crack Growth in Long-Term Operated Mild Steel under Mixed-Mode (I plus II, I plus III) Loading Conditionscitations
- 2018Energy response of S355 and 41Cr4 steel during fatigue crack growth processcitations
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article
Low-cycle fatigue modelling supported by strain energy density-based Huffman model considering the variability of dislocation density
Abstract
The fatigue crack initiation and propagation phases have been widely studied by the scientific community. There are several models to describe low-cycle fatigue behaviour based on strain damage criteria, but the most widely used is the Coffin-Manson-Morrow relationship, normally used for the fatigue crack initiation modelling. In addition, strain-life models based on hardness measurements and monotonic properties of metals have also been suggested. There are also integrated fatigue models that describe both the fatigue crack initiation and propagation phases, such as the UniGrow, Huffman, Peeker, among others, where the concept of successive crack re initializations (increments) based on local approaches is adopted. In this paper, the low-cycle fatigue modelling based on Huffman approach using the strain energy density and considering dislocations density is investigated and discussed. For this, various methodologies to evaluating low-cycle fatigue strength based on Huffman approach and exploring different dislocation density parameters are suggested: (i) critical dislocation density driven by the highest strain amplitude; (ii) the mean value of the dislocation density of the available experimental fatigue data and, (iii) Monte Carlo (MC) stochastic prediction considering the variability of dislocation density and the cyclic strain hardening coefficient. Besides, the Monte Carlo stochastic simulations for obtaining the strain-life parameters, fatigue strength and ductility coefficients, it allows the generation of probabilistic fields for the low-cycle fatigue behaviour of metals. In this research, the experimental fatigue data of 1050, 6061-T651, and AlMgSi0.8 aluminium alloys are used to apply the suggested methodologies. A comparison between the experimental fatigue data and strain-life curves based on various suggested methodologies is made.