| 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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Knowles, David M.
University of Bristol
in Cooperation with on an Cooperation-Score of 37%
Topics
Publications (19/19 displayed)
- 2024A correlative approach to evaluating the links between local microstructural parameters and creep initiated cavitiescitations
- 2024Productive Automation of Calibration Processes for Crystal Plasticity Model Parameters via Reinforcement Learningcitations
- 2024Calibration and surrogate model-based sensitivity analysis of crystal plasticity finite element models
- 2024Towards a Data-Driven Evolutionary Model of the Cyclic Behaviour of Austenitic Steels
- 2024Effect of grain boundary misorientation and carbide precipitation on damage initiationcitations
- 2023Exploring 3D X-Ray Diffraction Method to Validate Approaches in Materials Modelling
- 2022A method to extract slip system dependent information for crystal plasticity modelscitations
- 2022The effects of internal stresses on the creep deformation investigated using in-situ synchrotron diffraction and crystal plasticity modellingcitations
- 2021Comparing Techniques for Quantification of Creep Cavities
- 2021The role of grain boundary ferrite evolution and thermal aging on creep cavitation of type 316H austenitic stainless steelcitations
- 2021Evaluation of fracture toughness and residual stress in AISI 316L electron beam weldscitations
- 2020Microstructure-informed, predictive crystal plasticity finite element model of fatigue-dwellscitations
- 2020A novel insight into the primary creep regeneration behaviour of a polycrystalline material at high-temperature using in-situ neutron diffractioncitations
- 2020A novel insight into the primary creep regeneration behaviour of a polycrystalline material at high-temperature using in-situ neutron diffractioncitations
- 2020The role of grain boundary orientation and secondary phases in creep cavity nucleation of a 316h boiler headercitations
- 2019Effect of Plasticity on Creep Deformation in Type 316h Stainless Steel
- 2019Development of Fatigue Testing System for in-situ Observation of Stainless Steel 316 by HS-AFM & SEMcitations
- 2018Influence of prior cyclic plasticity on creep deformation using crystal plasticity modellingcitations
- 2018Comparison of predicted cyclic creep damage from a multi-material weldment FEA model and the traditional r5 volume 2/3 weldment approach
Places of action
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article
A method to extract slip system dependent information for crystal plasticity models
Abstract
A tool to implement a length scale dependency to classical crystal plasticity simulations is presented. Classical crystal plasticity models do not include a size effect; therefore, the size of the grain does not influence the simulated deformation. Classical crystal plasticity advancements have been through the inclusion of stress or strain gradient based constitutive models to improve the simulation of length scale dependent deformation. However, this tool presents an alternative to implementing a length scale, where the influence of slip pile-up in the form of dislocations at grain boundaries as a potential to explaining the Hall-Petch effect in materials. This is achieved by calculating the slip distance in adjacent grains for each slip system, by assuming the total slip length spans the grain in the slip direction. These calculations can occur in two ways. The first is the analysis occurs at the start of the simulation, therefore, only occurs once. If this approach is used, the computational cost of this tool is minute. However, if the simulations consider large deformations, during which it is expected that the grains are going to undergo large rotations, then it would be advantageous to the have the tool recalculate the information during the analysis. Consequently, the computational cost would depend on the resolution of the modelled geometry, the number of grains, and the number of slip systems. The tool also provides a capability to develop constitutive models based on complex grain boundary features which can be implemented in classical crystal plasticity models and gradient based crystal plasticity models. The described calculation process is implemented through a Fortran subroutine, which has been designed to be easily used in crystal plasticity simulations. The presented tool also includes Python code designed to link with microstructures built using DREAM.3D to extract the required input data to the Fortran subroutine.<br/><br/>The proposed tool is not limited to classical crystal plasticity formulations, instead the data extracted and outputted from the Fortran subroutine can be used to serve alternative purposes in both stress and strain gradient crystal plasticity models.<br/><br/>The proposed tool can be modified to extract additional data to that presented.<br/><br/>The slip distance in the adjacent grain, the distance from the grain boundary of the current calculation point, and the interaction between slip systems between grains can be used in any crystal plasticity constitutive models.