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Computational Characterization of Fatigue in WC-Co Hardmetals

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Produktnummer: 185f5b9ef983f044d1a105bdbd024fee0f
Autor: Jiang, Keng
Themengebiete: Fatigue Finite element analysis Statistics WC-Co hardmetals
Veröffentlichungsdatum: 31.01.2024
EAN: 9783844093889
Auflage: 1
Sprache: Englisch
Seitenzahl: 145
Produktart: Kartoniert / Broschiert
Verlag: Shaker
Produktinformationen "Computational Characterization of Fatigue in WC-Co Hardmetals"
WC-Co hardmetals are composite materials comprising tungsten carbide (WC) as hard phases and cobalt (Co) as metallic binders. Generally, hardmetal components are subjected to cyclic loading, and fatigue performance is a critical requirement. Thus far, a sophisticated numerical methodology for investigating the microstructure-sensitive fatigue strength of hardmetals with computer-aided technologies has not been formulated. Therefore, a numerical approach for modeling the role of microstructure in influencing the fatigue resistance of hardmetals is required. In this thesis, a computational framework for assessing the fatigue of hardmetals by modeling the damage evolution and cracking in the microstructure is presented. The different material models applied in each phase model the brittle transgranular fracture in WC grains and the progressive crack growth in the binder phase. Missing material parameters are supplemented by additional experiments. The material models are implemented into finite element codes, and all numerical calculations are performed in Abaqus/Standard. The need to interpret simulation results on a statistical basis is addressed, rendering a demand for effectively creating numerous models. A set of user programs is developed for this purpose. Subsequently, the concept of fatigue indicator is introduced as a potential improvement for fast assessment. The workflow is applied to numerous realistic and synthetic microstructures. The influence of micro- and mesoscopic characteristics on the fatigue properties of hardmetals is investigated. The simulation results and experimental observations are consistent, demonstrating the reliability of the proposed computational methodology.

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