Centre des Matériaux
Pierre-Marie Fourt
Pierre-Marie Fourt
Lecture
Bio-based aerogels: new eco-friendly porous materials for thermal insulation and controlled release
| Area of expertise | Mechanics |
| Doctoral School | ISMME - Systems Engineering, Materials, Mechanics, Energy |
| Supervisor | M. Cristian OVALLE-RODAS |
| Co-supervisor | M. Jean-Luc BOUVARD |
| Research unit | Centre of materials |
| Contact | https://www.mat.minesparis.psl.eu/formation/doctorat/propositions-de-sujets-de-these/ |
| Starting date | October 1st 2024 |
| Keywords | Model-free, local field, Digital Image Correlation (DIC), heat build-up, semi-crystalline polymers |
| Abstract | In this work, we propose using a paradigm known as data-driven simulation, consisting of formulating calculations directly from experimental material data and pertinent essential constraints and conservation laws, bypassing the empirical material modelling step of conventional computing altogether. Essential constraints and conservation laws such as compatibility and equilibrium remain unchanged, as do all the numerical schemes used in their discretization, such as finite elements, time-integrators, etc. Such conservation laws confer mathematical structure to the calculations, and this mathematical structure carries over to the present data-driven paradigm. However, in data-driven simulation the experimental material-data points are used directly in calculations rather than an empirical material model. In this manner, material modelling empiricism, error and uncertainty are eliminated entirely and no loss of experimental information is incurred. Whereas the data-driven paradigm has been formulated in the context of computational mechanics and, specifically elastic quasi-static problems, we believe that its range and scope is much larger. By contrast, inelastic materials raise the fundamental problem of sampling history-dependent material behaviour. Such sampling should provide appropriate coverage of possible processes and evolutions of the system and is thus likely to result in exceedingly large and complex data sets. The use of tools from Data Science and Big Data management may be expected to be particularly beneficial in dealing with such data sets. Using the local fields – strain and surface temperature – the calculations will consider, for the first time, the global and local response of the material. Furthermore, the true temperature of the material will be taken into account. |
| Profile | Engineer and / or Master of Science - Good level of general and scientific culture. Good level of knowledge of French (B2 level in french is required) and English. (B2 level in english is required) Good analytical, synthesis, innovation and communication skills. Qualities of adaptability and creativity. Teaching skills. Motivation for research activity. Coherent professional project. Prerequisite (specific skills for this thesis): Applicants should supply the following : • a detailed resume • a copy of the identity card or passport • a covering letter explaining the applicant’s motivation for the position • detailed exam results • two references : the name and contact details of at least two people who could be contacted • to provide an appreciation of the candidate • Your notes of M1, M2 • level of English equivalent TOEIC to be sent to recrutement_these@mat.mines-paristech.fr |
| Funding | Concours pour un contrat doctoral |
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