Applied Mechanics -Damage of plant fibres and its influence on the failure of bio-based composites: a multi-scale approach using in situ X-ray tomography characterization and finite element numerical modeling.
In the context of the ecological transition and efforts to reduce the carbon footprint of materials, the incorporation of bio-based components into composites represents a major strategic opportunity.
Among these solutions, the use of plant-based fibers (such as flax or hemp) as a substitute for synthetic reinforcements in composites is attracting growing interest. Indeed, these plant fibers exhibit competitive tensile properties, with specific stiffness levels comparable to those of glass fibers.
Mécanique Appliquée / GMP : Lecturer MCF - Section 60 -Besançon
TEACHING ACTIVITIES
The courses will be taught at the Besançon-Vesoul University Institute of Technology (IUT), part of Marie and Louis Pasteur University (UMLP), within the Mechanical and Production Engineering (GMP) department. The Bachelor's Degree in Technology (B.U.T) GMP is a three-year vocational course (Bac+1 to +3) that prepares students for middle management positions. All teaching will take place at the Besançon site, on the Bouloie campus.
The successful candidate will be required to:
Mécanique Appliquée / ISIFC : Lecturer - Section 60 - Besançon
Lecturer - Section 60 - ISIFC - Mechanics and Design for Health
Numéro national du poste : UFC000002974
TEACHING ACTIVITIES
Mécanique Appliquée / PEC : Lecturer - Section 60 - Besançon
Lecturer - Section 60 - Mechanical Design, field of materials science,
Numéro national du poste : Transformation 1PRAG1498A (UFC000201241)
------------
TEACHING ACTIVITIES
IUT Besançon-Vesoul: Bachelor’s Degree in Technology
Skills-based approach (2019 IUT reform)
Dole site - Packaging Department
Interventions in the 1st, 2nd and 3rd years of the BUT programme
Mécanique Appliquée : Lecturer - Section 60 - Besançon
Lecturer - Section 60
Structural Dynamics
Numéro : 1PRUN0667A
DMA : Physics-Informed Neural Networks for Structural Dynamics
Description : Physics-Informed Neural Networks (PINNs) have emerged as a paradigm for solving forward and inverse problems in computational mechanics by integrating physical laws directly into the learning process. Recently reintroduced by Raissi et al. (2019), PINNs enforce governing equations, typically partial differential equations (PDEs), as constraints in the neural network loss function, enabling the use of sparse or indirect data to infer system behavior.[...]
Applied Mechanics: "Solid hydrogen storage by reversible hydriding"
The thesis will be housed in the Applied Mechanics Department (~110 people including ~50 teacher-researchers, researchers and technicians). The Mat'éco team is structured around two areas of application: bio-based composite materials and hydrogen storage. It has around ten PhD and Masters students working on multiscale and multimodal experimental techniques and numerical simulations using finite elements or discrete elements, with the aim of considering thermo-mechanical couplings as well as chemical, hydrous or gaseous couplings.









