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2025年巴黎高科 - CSC合作公派读博项目 - 课题No.44,46
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2025年巴黎高科 - CSC合作公派读博项目 - 课题No.44,46 2025 巴黎高科 - CSC公派博士项目 （12月8日截止） 网申通道：https://paristech.kosmopolead.com/phd 申请攻略：https://paristech.fr/fr/paristech-csc-phd-program-how-apply 课题44,46详情: TITLE: EFFICIENT AND ACCURATE PREDICTION OF PLASTIC INSTABILITIES IN THIN METAL SHEETS USING FAST FOURIER TRANSFORM (FFT) METHOD Topic number : 2024_044 Field : Material science, Mechanics and Fluids Subfield: ParisTech School: Arts et Métiers Research team : Numerical Methods, Instabilities and Vibrations Research team website: https://lem3.univ-lorraine.fr/departement- mmsv/ Research lab: LEM3 - Laboratoire d'étude des microstructures et de mécanique des matériaux Lab location: Metz Lab website: https://lem3.univ-lorraine.fr/ Contact point for this topic: BEN BETTAIEB Mohamed (Mohamed.BenBettaieb@ensam.eu) Advisor 1: Farid Abed-Meraim - Farid.ABEDMERAIM@ensam.eu Advisor 2: Mohamed BEN BETTAIEB - Mohamed.BenBettaieb@ensam.eu Advisor 3: Advisor 4: Short description of possible research topics for a PhD: The prediction of plastic instability, such as localized necking or plastic buckling, in sheet metals during forming processes represents a significant challenge. It is well known that the occurrence of such instability phenomena mainly depends on the mechanical and microstructural characteristics of the metal sheets, such as grain morphology and orientation and the crystallographic structure. To accurately account for these characteristics in instability predictions, several computational strategies based on multiscale schemes have been developed by the host research team. These strategies predict the onset of plastic instability by considering a polycrystalline aggregate as representative of the studied sheet. The mechanical constitutive equations are formulated at the single crystal (microscopic) scale, and a multiscale transition scheme is employed to determine the overall behavior of the polycrystalline aggregate from that of the single crystal constituents. An instability criterion, such as the Rice bifurcation theory or the initial imperfection approach, is coupled with the overall polycrystalline behavior to predict the incipience of localized necking at the macroscopic level. To ensure the transition between the single crystal and polycrystalline scales, the host research team initially used the self- consistent approach. More recently, the periodic homogenization approach has been used as an alternative to the self-consistent scheme. This evolution in multiscale modeling has been motivated by the enhanced accuracy of the periodic homogenization scheme in modeling polycrystalline behavior. Despite these significant improvements, the application of the periodic homogenization scheme in predicting the onset of localized instabilities poses some technical difficulties, such as the very high CPU requirements needed for running the computation strategy, especially for polycrystalline aggregates with complex microstructures, and numerical convergence problems that may arise particularly in the large deformation range. The objective of this thesis project is to develop a new computational strategy that circumvents the technical problems related to the use of the periodic homogenization scheme. This new approach, based on the Fast Fourier Transform (FFT) method, will enable a more detailed description of thin metal sheets with complex microstructures (incorporating realistic morphology of grains, grain boundaries, size effects, ...) with a reduced CPU time. The adoption of this new computational strategy is expected to significantly enhance the capabilities of our numerical tools used to predict the onset of localized necking. The single crystal constitutive models used in previous work by the host team will be integrated into this new computational strategy. These models will be improved to better describe the microscopic behavior by considering some key challenging effects not sufficiently investigated so far, such as non-associated plasticity, thermomechanical coupling, phase transformation effects, and more. The resulting computation strategy, based on the FFT method, will be coupled with the Rice bifurcation criterion by developing the suitable software tools. The algorithmic schemes and associated computational tools developed in this project will be validated by comparing the numerical predictions to several experimental results. Once fully validated, the developed computational strategy will be used in both academic and industrial contexts to provide guidelines and assistance in the design of new generations of metallic alloys with improved ductility. Required background of the student: - Solid background in non-linear solid mechanics and numerical methods; - Good analytical and programming skills (e.g., Matlab, Mathematica, C/C++, Fortran); - Good understanding of the physics of localized necking and associated modeling. - Previous experience with numerical schemes and their implementations in software environments would be an asset. A list of (5 max.) representative publications of the group: (Related to the research topic) 1. Franz, G., Abed-Meraim, F., Berveiller, M., 2013. Strain localization analysis for single crystals and polycrystals: Towards microstructure- ductility linkage, International Journal of Plasticity, Vol. 48, pp 1–33. 2. Akpama, H.K., Ben Bettaieb, M., Abed-Meraim, F., 2017. Localized necking predictions based on rate–independent self–consistent polycrystal plasticity: Bifurcation analysis versus imperfection approach, International Journal of Plasticity, Vol. 91, pp 205–237. 3. Zhu, J., Ben Bettaieb, M., Abed-Meraim, F., 2020. Investigation of the competition between void coalescence and macroscopic strain localization using the periodic homogenization multiscale scheme, Journal of the Mechanics and Physics of Solids. Vol. 143, 104042. 4. Zhu, J., Ben Bettaieb, M., Zhou, S., Abed-Meraim, F., 2023. Ductility limit prediction for polycrystalline aggregates using a CPFEM-based multiscale framework, International Journal of Plasticity. Vol. 167, 103671. 5. Zhou, S., Ben Bettaieb, M., Abed-Meraim, F., 2024. A physically-based mixed hardening model for the prediction of the ductility limits of thin metal sheets using a CPFE approach, International Journal of Plasticity. Vol. 176, 103946. TITLE: DEVELOPMENT OF SURROGATE MODELS FOR METAL FORMING PROCESSES Topic number : 2024_046 Field : Design, Industrialization - Material science, Mechanics and Fluids Subfield: ParisTech School: Arts et Métiers Research team : Research team website: Research lab: LCFC - Laboratoire de conception, fabrication, commande Lab location: Metz Lab website: lcfc.ensam.eu Contact point for this topic: BALAN - Tudor - tudor.balan@ensam.eu Advisor 1: Tudor Balan - tudor.balan@ensam.eu Advisor 2: Régis Bigot - regis.bigot@ensam.eu Advisor 3: Lazhar Homri - lazhar.homri@ensam.eu Advisor 4: Short description of possible research topics for a PhD: The development of data-driven surrogate models for complex metal forming processes is crucial for speeding up the design and ramp-up phases, as well as to deal with variabilities and drifting in production phase. The convergence of advanced technologies and new data analytics provide real-time feedback for process characterization and key features identification. Associated models must deal with numerous challenging specificities: complex geometries; discrete parameters (e.g., the number of forming steps); time evolution of tensorial quantities... that could be tackled within the PhD thesis project. The scientific challenges lie in the identification and formulation of the parameters and variables to describe the complexity of these manufacturing processes, particularly their incremental / sequential nature to ensure real-time prediction and optimization. Required background of the student: The candidate should be initiated to data-driven approaches and in particular surrogate model development (polynomial chaos, kriging, neural networks...). Some background in metal forming processes would be helpful, and scientific / technical curiosity for this application field is needed. A certain experience in programing (Python) is necessary. A list of (5 max.) representative publications of the group: (Related to the research topic) 1. Zouhri, W., Homri, L. & Dantan, JY. Identification of the key manufacturing parameters impacting the prediction accuracy of support vector machine (SVM) model for quality assessment. Int J Interact Des Manuf 16, 177–196 (2022). 2. W Zouhri, JY Dantan, B Häfner, N Eschner, L Homri, G Lanza, O Theile, Characterization of laser powder bed fusion (L-PBF) process quality: A novel approach based on statistical features extraction and support vector machine, Procedia CIRP 99, 319-324 3. K Slimani, M Zaaf, T Balan, Accurate surrogate models for the flat rolling process, Int J Material Forming 16 (2023) 23, DOI: 10.1007/s12289-023-01744-5 4. Fays, S., Baudouin, C., Langlois, L., Borsenberger, M., Balan, T., Bigot, R., Compensation of billet variabilities through metamodel-based optimization in open die forging (2024) Int J Advanced Manuf Technology, 132 (3-4), pp. 1665-1678. 5. Uribe, D., Baudouin, C., Durand, C., Bigot, R., Predictive control for a single-blow cold upsetting using surrogate modeling for a digital twin, Int J Material Forming, 17 (2024), art. no. 7. |
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