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disturbances. Current control methods generally rely on simplified interaction models based on constant aerodynamic coefficients, quasi-static approximations, potential flow models, or experimentally identified
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a more representative composition and storage under controlled conditions; validation of the kinetic models and of the browning prediction model. [1] Phosanam, A., Chandrapala, J., Zisu, B
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Inria, the French national research institute for the digital sciences | Villeneuve la Garenne, le de France | France | about 2 months ago
institutes, with the student spending substantial time at each site to leverage their complementary experimental platforms and expertise. The PhD candidate will focus on developing novel control and modeling
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to understand deformation-controlled hydrogen systems by integrating seismic observations and THMC physical modeling at three complementary sites: Comminges (primary target), Oman, and New Caledonia. The central
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, France to complete the project. Objectives The objective of this PhD project is to develop advanced numerical modelling tools to support the digital twins of refractory materials, with the aim
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for the development of more predictive preclinical platforms. This PhD project is part of the ANR JCJC EXOFLEX project, which aims to develop an instrumented microfluidic platform capable of simultaneously controlling
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interferometry, etc.), (v) Predictive modelling of coupled phenomena (reactive transport, rock-water interactions, etc.), (vi) Uncertainty quantification (Monte Carlo, meta-modelling), and (vii) Risk analysis. The
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rules for ceramic shell mould clusters; Experimental validation of the relationships between microstructure and thermal shock resistance; Development of multi-scale finite element models for predicting
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at the Laplace laboratory, where numerical and analytical models are being developed to predict plasma potential control and flux entrainment from polarized electrodes. During the third year of the thesis project
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of the MOST (Modelling and Simulation of Turbulence) team focus on the numerical prediction of turbulent and multiphase flows with a broad range of objectives from fundamental understanding of flow properties