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Active STUDENTSHIP UKRI Gateway to Research

Self-adaptive and machine learning methods for two-dimensional stochastically perturbed shallow water equations


Funder Engineering and Physical Sciences Research Council
Recipient Organization University of Sussex
Country United Kingdom
Start Date Feb 01, 2021
End Date Nov 12, 2028
Duration 2,841 days
Number of Grantees 2
Roles Student; Supervisor
Data Source UKRI Gateway to Research
Grant ID 2732303
Grant Description

The project focusses on computer simulation of flood phenomena, and the influence of rain patterns, including climate change induced variability, which play a crucial role in the economy. The risk-assessment can help save lives and alleviate costs to citizens, businesses and governments. The complexity of flood phenomena requires simulations and statistical solutions for accurate estimation of flood risk.

Ambiental Technical Solutions Ltd, a business specialised to flood-risk assessment, numerical simulation to provide insight to real-life situations for customers

All Grantees

University of Sussex

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