Sort by
Refine Your Search
-
disturbances. Current control methods generally rely on simplified interaction models based on constant aerodynamic coefficients, quasi-static approximations, potential flow models, or experimentally identified
-
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
-
, 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
-
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
-
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
-
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
-
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
-
methodological comparison between mechanistic vector control models and macroscopic SIR-type models calibrated on serological survey data. Currently, risk indicators (e.g., R₀ estimation) derived from mosquito
-
processing and statistical analysis. The PhD thesis will be supervised by two supervisors, Corentin Louis (Chargé de Recherche CNRS, Observatoire de Paris) and Baptiste Cecconi (Astronome, Observatoire de
-
between pollution control efficiency, electrochemical yield, and energy recovery potential; • Develop coupled electrochemical and hydrodynamic models to predict process behavior; • Participate in