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Bayesian optimisation of radial-inflow turbines

High-density fluids are commonly use in renewable applications, and in particular for low-to-medium renewable power cycles using Organic Rankine cycles (ORC). The optimisation of the turbo-expander, a key component in these cycles, is of critical importance for robust design.This project aims at optimising such turbo-expander for ORC using Bayesian techniques that allow for uncertainties to be accounted for in the optimisation process. This is an important aspect while considering the strong impact of uncertainties on the fluid flow properties and …

Study level
Vacation research experience scheme
Faculty of Engineering
School of Mechanical, Medical and Process Engineering

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