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2025年巴黎高科 - CSC合作公派读博项目 - 课题No.34,35
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2025年巴黎高科 - CSC合作公派读博项目 - 课题No.34,35 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34,35详情: TITLE: OPTIMIZATION OF FILLING STAGE DURING CASTING PROCESS USING ARTIFICIAL INTELLIGENCE Topic number : 2024_034 Field : Material science, Mechanics and Fluids Subfield: Numerical methods, FE simulation ParisTech School: Arts et Métiers Research team : Research team website: Research lab: LAMPA - Laboratoire angevin de mécanique, procédés et innovation Lab location: Angers Lab website: https://lampa.ensam.eu/ Contact point for this topic: BEN SAADA Mariem mariembensaada@ensam.eu Advisor 1: Amine AMMAR - amine.ammar@ensam.eu Advisor 2: Mariem BEN SAADA - mariem.bensaada@ensam.eu Advisor 3: MARIE BEDEL - marie.bedel@ensam.eu Advisor 4: Short description of possible research topics for a PhD: Filling is a critical stage of casting as it directly impacts the final mechanical quality of the cast part. Indeed, if a mold cavity is filled too slowly, the metal solidifies before filling completion, inducing misrun defects. On the other hand, when filling too fast, the turbulent flow leads to oxide entrapment and mold erosion (1). In order to avoid those critical defects, an appropriate filling system has to be designed. Such design rules currently exist only for gravity casting, and are based on a very simplified approach, where a filling system is made of a sprue, runners and ingates whose dimensions are given by empirical expressions (2). If those standard design rules permit to avoid misrun defect, fluid flow is always turbulent in the filling system (3), thus systematically inducing oxides in the cast parts. Some recent studies proposed filling system optimization by using Machine Learning (ML) methods (4). However, only the dimensions of a fixed filling system were optimized (5,6). Reconsideration of filling system design in itself is still hardly considered (7). To our best knowledge, such a design reconsideration has never been performed by using ML based algorithms without geometrical constrains. However, the revolution of sand printing technology makes the geometrical constrains associated with mold making totally outdated. When considering this new technology, innovative and much more optimized filling system design rules can be developed, by considering only thermal and fluid flow constrains. Today, foundry engineers can predict the cast products characteristics without having to perform numerous time-consuming trial-and-error experiments. It is hence possible nowadays in metal casting processes to apply powerful tools and models developed with reasonable number of simulations that allows predicting parts defects and controlling complex processes (8). On the other hand, approaches combining physics based reduced order models were recently developed, enabling parametric studies, and data-driven model enrichment in the so-called hybrid modelling framework. A high accuracy is obtained with respect to the experimental measurements, while proceeding under the stringent real-time constraint (9). Therefore, in this PhD study, these approaches could be extended and enriched with Generative Design approach to optimize the filling stage of casting. To do so, an adapted casting software will be used, which combines fluid flow dynamic and heat transfer, to study the impact of different parameters on head loss during filling; mold design, mold surface condition, metal viscosity or casting speed will be considered. Then the generated numerical data will be used to develop a predictive model of head loss by using hybrid physical-data driven techniques via Machine-Learning (ML) technologies and their integration into the detailed analytical and numerical modellings. Such a model will then be used to optimize filling system design, therefore optimizing filling speed and flow rate while mastering casting yield and associated heat loss. The newly proposed design rules for filling systems will be eventually validated by experimental comparison, performed on the foundry facility of LAMPA laboratory, on both standard and optimized designs. Required background of the student: Continum Mechanics, Numerical methods, FE simulation A list of (5 max.) representative publications of the group: (Related to the research topic) 1. 1. Bedel M, Sanitas A, El Mansori M. Geometrical effects on filling dynamics in low pressure casting of light alloys. Journal of Manufacturing Processes. 1 sept 2019;45:194-207. 2. 2. Campbell J. Complete Casting Handbook: Metal Casting Processes, Metallurgy, Techniques and Design. Butterworth-Heinemann; 2015. 1055 p. 3. 3. Cross M, McBride D, Croft TN, Williams AJ, Pericleous K, Lawrence JA. Computational modeling of mold filling and related free-surface flows in shape casting: An overview of the challenges involved. Metall Mater Trans B. 1 déc 2006;37(6):879-85. 4. 4. Ambekar SA, S.B.Jaju. A review on optimization of gating system for reducing defect. International Journal of Engineering Research and General Science. 2014;2(1):93-8. 5. 9. Ammar, A., Ben Saada, M., Cueto, E. et al. Casting hybrid twin: physics-based reduced order models enriched with data-driven models enabling the highest accuracy in real-time. Int J Mater Form 17, 16 (2024). TITLE: PHOTONIC CRYSTALS WITH STIMULI-RESPONSIVE HYDROGELS Topic number : 2024_035 Field : Chemistry, Physical chemistry and Chemical Engineering - Physics, Optics - Material science, Mechanics and Fluids Subfield: ParisTech School: ESPCI Paris - PSL Research team : Soft Polymer Networks Research team website: Research lab: SIMM - Sciences et ingénierie de la matière molle Lab location: Paris Lab website: https://www.simm.espci.fr Contact point for this topic: yvette.tran@espci.fr Advisor 1: Yvette TRAN - yvette.tran@espci.fr Advisor 2: Advisor 3: Advisor 4: Short description of possible research topics for a PhD: Recent advances in micro- and nano-technologies present opportunities to control optical properties in a way that is not possible with the materials provided by nature. Additional performances in terms of modulability and switchability using soft technology by means of synthetic stimuli-responsive polymer hydrogels could offer unprecedented enhanced devices. The general idea of the thesis is to develop photonic crystals with switchable properties based on a fine control of the architecture of stimuli-responsive hydrogels. Photonic crystals with high spectral shift will be designed thanks to the platform of nano- to micro- structures of temperature-responsive hydrogels developed in our group. Colloidal crystals will be obtained through the organized close-packing of polymer colloids which characteristics (size, distance...) can be finely adjusted. Two different strategies will be used to add thermo-responsive properties. (i) The direct approach consists of coating PNIPAM responsive hydrogel nanoparticles. (ii) The indirect approach consists of first coating polystyrene PS nanoparticles molds and then infiltrating the empty space with PNIPAM hydrogel matrix. The polymer nanoparticles can also be enriched with metallic gold to increase the optical contrast. The swelling-collapse of responsive hydrogel allows the reversible change of photonic crystals periodicity. The thesis includes the synthesis of (PS and PNIPAM) polymer colloids, the synthesis of functionalized PNIPAM precursors for hydrogel matrix elaboration and the fabrication of responsive photonic crystals by coating and infiltration techniques. The structure of photonic crystals will be finely characterized by various techniques available in ESPCI (DLS, ESEM, ETEM, ellipsometry, AFM). They will also be characterized by large instruments techniques such as X-ray reflectivity and GISAXS at SOLEIL synchrotron. The devices will be investigated for applications in optics. Required background of the student: Primary background in materials science and chemical engineering A list of (5 max.) representative publications of the group: (Related to the research topic) 1. Martwong, E.; Tran, Y. Lower Critical Solution Temperature phase transition of poly(PEGMA) hydrogel films. Langmuir 2021, 37, 8585-8593 2. Dompé, M.; Cedano Serrano, F. J.; Heckert O.; Tran, Y.; Hourdet, D.; Van den Heuvel, N.; Van der Gucht, J.; Creton, C.; Kamperman, M. Thermoresponsive Complex Coacervate-Based Underwater Adhesive. Adv. Mater. 2019, 31, 1808179 3. D’Eramo, L.; Chollet, B.; Leman, M.; Martwong, E.; Li, M.; Geisler, H.; Dupire, J.; Kerdraon, M.; Vergne, C.; Monti, F.; Tran, Y.; Tabeling, P. Microfluidic actuators based on thermo-responsive hydrogels. Nature Microsyst. Nanoeng. 2018, 4, 17069 4. Chollet, B.; Li, M.; Martwong, E.; Bresson, B.; Fretigny, C.; Tabeling, P.; Tran, Y. Multiscale surface-attached hydrogel thin films with tailored architecture. ACS Appl. Mat. Interfaces 2016, 8, 11729-11738 5. Li, M.; Bresson, B.; Fretigny, C.; Cousin, F.; Tran, Y. Submicrometric films of surface-attached polymer networks: temperature-responsive properties. Langmuir 2015, 31, 11516-11524 |
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