ENVIRONMENTAL FLOWS
Environmentals Flows and Safety
Objectives
Data-driven high fidelity weather forecasting
Fast prediction of dynamic wind loads using machine learning algorithms
In-situ measurements for the detection and validation of damage drivers
Improvement of mitigation strategies for protection against extreme weather events
Expand range of dispersion scenarios to be experimentally and numerically simulated
Fast prediction of dynamic wind loads using machine learning algorithms
In-situ measurements for the detection and validation of damage drivers
Improvement of mitigation strategies for protection against extreme weather events
Expand range of dispersion scenarios to be experimentally and numerically simulated
Droplet Cloud Ignition
Topics
Dispersion Studies
Wind loading
Onshore and offshore studies
Wind loading
Onshore and offshore studies
Some current funded projects
- SeaFD: Realistic wind load computations for offshore wind turbines
- PhairyWind: Improving meteorology for offshore wind energy
- HyPer SMM: Performance Assessment of Sand Mitigation Measures
Contact
Prof. Delphine Laboureur - This email address is being protected from spambots. You need JavaScript enabled to view it.