CNRS UMR 8201 LAMIH
17 May 2023
- CNRS UMR 8201 LAMIH
- Research Field
- Researcher Profile
- Recognised Researcher (R2)
Leading Researcher (R4)
First Stage Researcher (R1)
Established Researcher (R3)
- Application Deadline
- 30 Aug 2023 – 22:00 (UTC)
- Type of Contract
- Job Status
- Offer Starting Date
- 1 Sep 2023
- Is the job funded through the EU Research Framework Programme?
- Not funded by an EU programme
- Is the Job related to staff position within a Research Infrastructure?
Under normal production conditions, the forming tool get worn progressively. Replacing the damaged tool with a new one is expensive and environmentally unfriendly. Today, Additive manufacturing (AM) offers new possibilities for rapid prototyping of complex parts and for repairing tools made of expensive materials . Application of AM for repairing operations is a hot topic because it can give worn parts a second life, using cheaper additional material, resulting in a more environmentally friendly process than replacing the part with a new one. To perform the repair operations, machining operations should be performed first to remove the damaged part, and AM is carried out secondly to perform repair operations. On another hand, AM allows the use of hybrid materials within the same tool, allowing to strengthen the resistance performance of the repaired tool [2-4]. As it is known, the process parameters play a key role on the final mechanical properties of the final produced part, hence it is important to understand the physical phenomena and optimize them in order to improve the final quality of the part . Thus, both numerical and experimental investigations will be carried using the digital twin approach to optimize the process parameters.
A quick review of the literature has shown that meshless methods have been applied successfully for the simulation of the AM process , with the advantage of no remeshing or degradation of solution quality. In this context, the Smoothed particle hydrodynamics (SPH) method has been developed since 2014 at LAMIH to solve structural problems undergoing large deformations . It is proposed in the present PhD thesis, to extend to make it able to simulate tool repair by AM [9-16]. The SPH method presents natural advantages for the simulation of material deposition in additive manufacturing problems. As no mesh is required, the material particles are tracked directly, it is also suitable to handle large material deformations, moving interfaces, or even phase change.
The thesis work aims to develop a multiphysics and multiscale framework using the SPH technique for the simulation of tooling repair process and optimize the AM process parameters. The multiphysics aspect concerns the thermomechanical modeling of material deposition during the AM process. A micromechanical material modeling of the repaired zone will be developed through homogenization techniques to allow a macroscopic constitutive law which can be used in a structural calculation framework. The multiscale aspect concern the development of a multilevel resolution technique using two different discretizations of the tool with two distinct simulations that interact with each other : a refined simulation concerning the small repaired zone and a macroscopic simulation of the remaining of the tool with an exchange interface ensuring the continuity of the fields between the two simulations.
The second part of this thesis is the development of optimization methods using metamodeling techniques based on experimental designs and response surfaces in order to optimize the choice of material and the control of parameters fabrication (wire diameter, feed rate, trajectory, thermal cycles, etc.). This optimization will be multi-objective, ensuring the achievement of a repaired tool with: a minimum residual stresses in the repaired zone, high-performance mechanical characteristics on the surface, good mechanical performances under severe loading (high strain rate , high thermal gradients) and increased durability through fatigue/tribology studies.
It should be emphasized the important generic nature of this thesis work, because the numerical tool developed can be applied in other forming processes (forging, stamping, cutting, etc.).
A last aspect and not the least, concerns the perspectives of the thesis work, in particular with the development based on Artificial Intelligence (AI) using machine learning techniques. The experimental and numerical results can be used as digital twin for the training process. This AI tool will be used for the optimization of process parameters. Such a tool will be valuable in the industrial field, since it can predict the best AM process parameters, without performing expensive numerical simulation and experimental measurements.
The experimental measurements will be conducted at LAMIH, and the main mission of PhD student will be concern the numerical developments and dialogue between the experiments and numerical simulations.
Funding category: Contrat doctoral
PHD Country: France
A Master or engineering degree in mechanical engineering, with a solid knowledge in mechanics of materials, numerical modeling, and mastering of Ls-Dyna or Radioss. The candidate must have good skills in programming (Fortran and/or C++), a preliminary experience in experiments is a plus.
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- CNRS UMR 8201 LAMIH
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