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University of Lorraine
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87 Projects, page 1 of 18
  • Funder: European Commission Project Code: 101032994
    Overall Budget: 184,708 EURFunder Contribution: 184,708 EUR

    Subsurface modelling using geoscientific data is essential to understand the Earth and to sustainably manage natural resources. Geology and geophysics are two critical aspects of such modelling. Geological and geophysical models have different resolutions and are sensitive to different features. Considering only geological or geophysical aspects often leads to contradictions as creating an Earth model is a highly non-unique problem. In addition, the sensitivity of the data is limited and many objects cannot be differentiated by a single discipline. The only way to address this is solving the longstanding challenge of integrating of geological data and knowledge (orientation data, contacts and ontologies) and geophysical methods (physical fields). Recent techniques usually focus on features the data is sensitive to and merely use one discipline to falsify hypotheses from the other. Such approach prevents considering the full range of potential outcomes, and fails to exploit the sensitivity of both approaches. This project proposes a different philosophy to solve the challenge of connecting geological and geophysical modelling. It first involves the development of a novel method integrating the two model types in a single framework giving them equal importance. Geological and geophysical data will be modelled simultaneously through an implicit functional mapping one domain into the other by linking their respective models. This will allow the simultaneous recovery of compatible geological and geophysical models. Secondly, this project will use a new hybrid deterministic-stochastic optimisation technique to explore the range of subsurface scenarios to estimate the diversity of features that cannot be differentiated based on the available data. Thirdly, after proof-of-concept, the method will be applied to two cases: imaging of a mantle uplift in the Pyrenees Mountains (France/Spain), and study of potential new subsurface scenarios around the Kevitsa mine (Finland).

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  • Funder: European Commission Project Code: 298060
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  • Funder: European Commission Project Code: 101075208
    Overall Budget: 1,498,010 EURFunder Contribution: 1,498,010 EUR

    Low regularity dynamics are used for describing various physical and biological phenomena near criticality. The low regularity comes from singular (random) noise or singular (random) initial value. The first example is Stochastic Partial Differential Equations (SPDEs) used for describing random growing interfaces (KPZ equation) and the dynamic of the euclidean quantum field theory (stochastic quantization). The second concerns dispersive PDEs with random initial data which can be used for understanding wave turbulence. A recent breakthrough is the resolution of a large class of singular SPDEs through the theory of Regularity Structures invented by Martin Hairer. Such resolution has been possible thanks to the help of decorated trees and their Hopf algebras structures for organising different renormalisation procedures. Decorated trees are used for expanding solutions of these dynamics. The aim of this project is to enlarge the scope of resolution given by decorated trees and their Hopf algebraic structures. One of the main ideas is to develop algebraic tools by the mean of algebraic deformations. We want to see the Hopf algebras used for SPDEs as deformation of those used in various fields such as numerical analysis and perturbative quantum field theory. This is crucial to work in interaction with these various fields in order to get the best result for singular SPDEs and dispersive PDEs. We will focus on the following long-term objectives: - Give a notion of existence and uniqueness of quasilinear and dispersive SPDEs. - Derive a general framework for discrete singular SPDEs. - Develop algebraic structures for singular SPDEs in connection with numerical analysis, perturbative quantum field theory and rough paths. - Use decorated trees for dispersive PDEs with random initial data and derive systematically wave kinetic equations in Wave Turbulence. - Develop a software platform for decorated trees and their Hopf algebraic structures.

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  • Funder: European Commission Project Code: 621727
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  • Funder: European Commission Project Code: 101040994
    Overall Budget: 1,436,090 EURFunder Contribution: 1,436,090 EUR

    Thermal engines, refrigeration systems and heat pumps rely on thermodynamic cycles, in which an inert working fluid converts input thermal and mechanical energies into another useful energy form (work or heat) by cyclically transforming its thermal energy content. Although the selection of the working fluid is the main lever to increase their performances, whatever the fluid is, recorded efficiencies remain far below the highest achievable ones. This deficiency is strongly affecting the exploitation of waste heat and renewable thermal energies by closed power cycles, as well as representing the main cause of the slow performance improvement of heat pumps and cooling technologies. With the aim to effectively increase the performances of thermodynamic cycles, I propose to investigate a radically new thermodynamic structure, resulting from the use of equilibrated reactive working fluids instead of inert ones. Preliminary calculations have indeed shown that the simultaneous conversion of the thermal and chemical energy of reactive fluids may result in the intensification of these energy conversion processes. This project applies an original methodology that integrates thermodynamic and kinetic predictive tools to discover and characterize suitable reactive fluids, allowing for the quantification of the effects of reaction features on cycle performance and the optimization of the cycle?s configuration. The novelty of such a solution approach and comprehensiveness of the applied methodology builds the innovative character of REACHER. Probably due to the complex multi-disciplinarity of the problem or to the negligence of this possible way to convert chemical energy in thermodynamic cycles, this field has remained substantially unexplored. The successful development of REACHER will provide the former fundamental understanding on how chemical energy can be efficiently exploited in the intensification of thermodynamic cycles for power, refrigeration and heating purposes.

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