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particle detectors, as well as technical research and development and associated applications for energy, health, and environment. The laboratory has important technical staff (approximately 280 engineers
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, without the use of simulation software familiar to process engineers. In this thesis, we aim to: - Propose generative models for other types of cycles, based on existing models. To do this, we could use
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technologies, and integrate machine learning-driven digital twins for predictive combustion modeling. The research program will cover a wide range of e-fuels (H₂, NH₃, CH₃OH, DME, OME) and their applications in
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-flexible technologies, and integrate machine learning-driven digital twins for predictive combustion modeling. The research program will cover a wide range of e-fuels (H₂, NH₃, CH₃OH, DME, OME) and their