Objective
Bio-based construction materials are air-fiber systems, such as wood, hemp, cellulose, flax, etc., possibly coated with a mineral paste. They represent a promising solution for carbon emission reduction, due to their low production cost and their partial or full recyclability. Moreover, they bring more comfort to the occupants thanks to their moisture-buffering capacity, and they require less energy for heating or cooling. These qualities are obtained through exchanges between water vapor and bound water, i.e. water absorbed in the solid structure, combined with heat transfers. Consequently, understanding and predicting water and heat (hygrothermal) transfers in such materials is essential to selecting them appropriately, adjusting their conditions of use, and designing innovative materials. However, the current analysis of their performance is generally based on limited evaluations at a global scale or via macroscopic models lacking physical information.
My idea is instead to open the black box and start from the fiber scale, to explicitly describe the internal physical processes at this scale, including sorption dynamics, bound water diffusion, fiber configuration, etc., and then to progressively complete and extend this approach to full-scale materials. This can be used to build for the first time a generic description, understanding, and modelling, of hygrothermal phenomena in bio-based construction materials. This physical description will be supported and enriched by several experimental innovations. Notably, internal measurements of the spatial distribution of moisture content and temperature in time will be obtained from non-invasive time-resolved magnetic resonance imaging (MRI), which can be used to validate the models and determine diffusion properties in an unequivocal way. Finally, I will develop an open-source software predicting hygrothermal characteristics and performance based on material characteristics and history of ambient conditions.
Fields of science (EuroSciVoc)
CORDIS classifies projects with EuroSciVoc, a multilingual taxonomy of fields of science, through a semi-automatic process based on NLP techniques.
CORDIS classifies projects with EuroSciVoc, a multilingual taxonomy of fields of science, through a semi-automatic process based on NLP techniques.
- engineering and technologymaterials engineeringfibers
- natural sciencescomputer and information sciencessoftware
- humanitieshistory and archaeologyhistory
- agricultural sciencesagriculture, forestry, and fisheriesforestry
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Programme(s)
- HORIZON.1.1 - European Research Council (ERC) Main Programme
Topic(s)
Funding Scheme
HORIZON-ERC - HORIZON ERC GrantsHost institution
77454 Marne-La-Vallee
France