Descrizione del progetto DEENESFRITPL Modellizzazione del trasporto reattivo in mezzi porosi eterogenei su più scale Comprendere e modellizzare il trasporto reattivo in mezzi porosi è fondamentale per prevedere le reazioni biogeochimiche di campo, che svolgono un ruolo fondamentale nelle attuali questioni ambientali, come la gestione delle risorse idriche e il sequestro di anidride carbonica. Una delle principali sfide scientifiche consiste nel catturare la dinamica dei processi accoppiati di miscelazione dei soluti e le reazioni chimiche in mezzi porosi eterogenei su scale spaziali multiple. Finanziato nell’ambito del programma Marie Skłodowska-Curie, il progetto ChemicalWalks affronterà questo problema accoppiando per la prima volta la teoria lamellare della miscelazione e il modello chimico delle passeggiate casuali continue per la cinetica di reazione in condizioni di miscelazione incompleta. Mostra l’obiettivo del progetto Nascondi l’obiettivo del progetto Obiettivo Understanding and modelling reactive transport in porous media is fundamental to predicting field-scale biogeochemical reactions, which play a key role in current environmental issues such as water resources management and carbon dioxide sequestration. A major scientific challenge is to capture the dynamics of coupled solute mixing and reaction processes in the context of multiscale heterogeneity, which characterise most natural porous media. In particular, the impact of pore-scale mixing on large- (Darcy-)scale reactive transport is a critical scientific question. ChemicalWalks addresses this question by coupling for the first time the lamella theory of mixing, developed by the host supervisor, and the chemical CTRW model for reaction kinetics under incomplete mixing, recently developed by the ER. While the lamella theory has successfully quantified mixing processes and fluid-fluid reactions at pore scale, its application to fluid-solid reactions, which are ubiquitous in natural systems, remains to be explored. The key idea of ChemicalWalks is to use the lamella theory to determine how pore-scale concentration distributions control the distribution of fluid-solid reaction rates, and formalize a predictive theory for upscaled reaction kinetics through the chemical CTRW framework (WP1). The complementary expertise of the researcher and the host will ensure a particularly efficient two-way transfer of knowledge to achieve this goal. This will open the door to the development of a hybrid computational method, quantifying the effect of pore-scale mixing on Darcy-scale reactive transport phenomena at a scale relevant to environmental applications (WP2). ChemicalWalks will be firmly rooted on a career development plan and supported by scientific training in state-of-the-art mixing theories and data processing and interpretation techniques, placing the fellow at the forefront of reactive transport modelling. Campo scientifico natural sciencesearth and related environmental scienceshydrologynatural sciencescomputer and information sciencescomputational scienceengineering and technologyenvironmental engineeringnatural resources managementwater managementnatural sciencescomputer and information sciencesdata sciencedata processing Programma(i) H2020-EU.1.3. - EXCELLENT SCIENCE - Marie Skłodowska-Curie Actions Main Programme H2020-EU.1.3.2. - Nurturing excellence by means of cross-border and cross-sector mobility Argomento(i) MSCA-IF-2018 - Individual Fellowships Invito a presentare proposte H2020-MSCA-IF-2018 Vedi altri progetti per questo bando Meccanismo di finanziamento MSCA-IF-EF-ST - Standard EF Coordinatore UNIVERSITE DE RENNES I Contribution nette de l'UE € 184 707,84 Indirizzo RUE DU THABOR 2 35065 RENNES CEDEX Francia Mostra sulla mappa Regione Bretagne Bretagne Ille-et-Vilaine Tipo di attività Higher or Secondary Education Establishments Collegamenti Contatta l’organizzazione Opens in new window Sito web Opens in new window Partecipazione a programmi di R&I dell'UE Opens in new window Rete di collaborazione HORIZON Opens in new window Costo totale € 184 707,84
