Obiettivo How are deep mantle processes related to the mapped geological record? How can we reconcile geochemical observations with geophysical inferences? These are first order unanswered questions despite our steady progress in imaging the Earth's internal structure and understanding the high temperature and pressure properties of minerals. To make a breakthrough, we have to understand solid-state convection in the Earth's mantle in much greater detail. Much is known about the physical processes, such as melting and the delicate interaction between thermal and chemical buoyancy, but the parameters that enter their mathematical description are not very well known. Once these parameters are determined, the thermo-chemical evolution of our planet can self-consistently be modelled. The state-of-the-art is to roughly estimate these parameters and qualitatively compare the modelling to some relevant geophysical, geochemical or geological observations. This comparison is not comprehensive and never explains all observables. We propose a radically new approach, where all observables are used together to infer these parameters directly, using a fully non-linear Bayesian inference technique based on neural networks. This will determine for the first time the initial conditions at the Earth's formation, the Earth-like flow parameters essential to model the thermo-chemical evolution of our planet and produce models that are simultaneously consistent with the main different geophysical and geochemical datasets. Campo scientifico natural sciencesearth and related environmental sciencesgeochemistrynatural sciencesmathematicsapplied mathematicsstatistics and probabilitybayesian statisticsnatural sciencesphysical sciencesastronomyplanetary sciencesplanetsnatural sciencesearth and related environmental sciencesgeophysicsnatural sciencescomputer and information sciencesartificial intelligencecomputational intelligence Programma(i) FP7-IDEAS-ERC - Specific programme: "Ideas" implementing the Seventh Framework Programme of the European Community for research, technological development and demonstration activities (2007 to 2013) Argomento(i) ERC-AG-PE10 - ERC Advanced Grant - Earth system science Invito a presentare proposte ERC-2012-ADG_20120216 Vedi altri progetti per questo bando Meccanismo di finanziamento ERC-AG - ERC Advanced Grant Istituzione ospitante UNIVERSITEIT UTRECHT Contributo UE € 2 447 200,00 Indirizzo HEIDELBERGLAAN 8 3584 CS Utrecht Paesi Bassi Mostra sulla mappa Regione West-Nederland Utrecht Utrecht Tipo di attività Higher or Secondary Education Establishments Ricercatore principale Jeannot Alphonse Trampert (Prof.) Contatto amministrativo Bas Leeflang (Dr.) Collegamenti Contatta l’organizzazione Opens in new window Sito web Opens in new window Costo totale Nessun dato Beneficiari (2) Classifica in ordine alfabetico Classifica per Contributo UE Espandi tutto Riduci tutto UNIVERSITEIT UTRECHT Paesi Bassi Contributo UE € 2 447 200,00 Indirizzo HEIDELBERGLAAN 8 3584 CS Utrecht Mostra sulla mappa Regione West-Nederland Utrecht Utrecht Tipo di attività Higher or Secondary Education Establishments Ricercatore principale Jeannot Alphonse Trampert (Prof.) Contatto amministrativo Bas Leeflang (Dr.) Collegamenti Contatta l’organizzazione Opens in new window Sito web Opens in new window Costo totale Nessun dato EIDGENOESSISCHE TECHNISCHE HOCHSCHULE ZUERICH Svizzera Contributo UE € 1 033 400,00 Indirizzo Raemistrasse 101 8092 Zuerich Mostra sulla mappa Regione Schweiz/Suisse/Svizzera Zürich Zürich Tipo di attività Higher or Secondary Education Establishments Contatto amministrativo Paul J. Tackley (Prof.) Collegamenti Contatta l’organizzazione Opens in new window Sito web Opens in new window Costo totale Nessun dato
