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these developments have focused on conventional hydrocarbons under purely gaseous conditions. In contrast, SAF combustion in GTs occurs in a multiphase regime, where complex interactions between liquid fuel droplets
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Description REALISE - Bridging Igneous Petrology and Machine Learning for Science and Society About the REALISE Doctoral Network REALISE will train 15 Doctoral Candidates at the interface of igneous petrology
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. Géotechnique, 68(10) 918-930. https://doi.org/10.1680/jgeot.17.P.161 [6] Sanvitale N., Zhao B., Bowman E. & O’Sullivan C. (2021) Particle-scale observation of seepage flow in granular soils using PIV and CFD
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, the fusion community has started to develop fast surrogate models based on Machine Learning / AI models to speed up significantly the employed tools. Such tools have demonstrated to be generally applicable and
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the European Funds for a Modern Economy Programme (FENG 2021-2027). Principal Investigator: dr hab. Taras Parashchuk Short description of the project: The aim of the EcoCool project is to develop efficient and
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focus on translational Research, Development & Deployment which focus on specific area of the energy value chain, and a number of Living labs and Testbeds which facilitate large scale technology
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23.01.2026, Academic staff The Chair of Structural Analysis is seeking a highly motivated research associate (m/f/d) for our research project focused on developing methodologies for high fidelity
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develop an algorithm for gas emission localisation and quantification using advection-diffusion models, CFD, and Navier-Stokes equations. Working alongside Durham. Key tasks include: · Integrating
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CFD technologies. As the PhD researcher on this project, you will investigate and develop the numerical and algorithmic components needed to make this hybrid high order to low order strategy practical
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ensures safe operations. Our activities are related primarily to development and application of numerical modelling, e.g. CFD, FEA, FSI, optimization, ML, but we are also involved in both experiments and