Area of expertise | Mécanique numérique et Matériaux |
Doctoral School | SFA - Sciences Fondamentales et Appliquées |
Supervisor | BERNACKI Marc |
Co-supervisor | PINO MUÑOZ Daniel |
Research unit | Centre de Mise en Forme des Matériaux |
Keywords | HIP process, HPC, Digital twins, Computational Metallurgy, Interface networks |
Abstract | One of the European Union’s objectives in climate change consists
of reaching net-zero greenhouse gas emissions by 2050. Such perspective puts the metallic materials industry, as a large contributor to carbon emissions, under tremendous pressure for change and requires the existence of robust computational materials strategies to enhance and design, with a very high confidence degree, new metallic materials technologies with a limited environmental impact. From a more general perspective, the in-use properties and durability of metallic materials are strongly related to their microstructures, which are themselves inherited from the thermomechanical treatments. Because of opportunities that powder metallurgy (PM) processes offer in both technical and economic points of view, these processes are increasingly used in industries for the manufacture of complex shaped parts for many applications. PM technologies, which allow the production of near-net-shape densified metal or ceramic parts with controlled microstructure, are very diverse but Hot Isostatic Pressing (HIP) appears as the key process when large complex parts, such like nuclear plant components (pipes, valves, impellers...), are required. The modeling of the powder densification during HIP and the prediction of the final microstructure through numerical simulation is an open and complex research problem. It is not easy to answer to seemingly simple questions like: is full densification achieved everywhere in the part? Will the as-HIPed shape allow to achieve the component? Did the powder microstructure lead to a satisfactory dense material which will exhibit good properties? What if I change the HIP parameters (pressure, temperature, time) or the powder production process? Indeed, theories that provide quantitatively correct predictions of local heterogeneities observed during densification of the granular packing, as well as theories able to predict the final polycrystalline grain size distribution, have long been sought to fill a critical link in our ability to model HIP process from start to finish. To date, such theories do not exist. In this context, multiscale materials modeling, and more precisely simulations at the mesoscopic scale, constitute the most promising numerical framework for the next decades of industrial simulations as it compromises between the versatility and robustness of physically-based models, computation times, and accuracy. The DIGIMU consortium and the RealIMotion ANR Industrial Chair are dedicated to this topic at the service of major industrial companies. |
Profile | Degree: MSc or MTech in Metallurgy or Applied
Mathematics, with excellent academic record. Skills: Numerical Modeling, Metallurgy, programming, proficiency in English, ability to work within a multi-disciplinary team. |
Funding | Financement d'une association ou fondation |
©2009 Mines ParisTech
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