Experimental conditions of industrial processes at elevated temperatures, such as for steel manufacture, often depend on the composition of the gas atmosphere. Industrial furnaces for reheating or annealing off steels need to have an accurately defined gas composition and flow profile in order to achieve high product quality. Besides the overall composition of the atmosphere, local concentrations of oxygen and water vapour can significantly deviate from a statistical average. Such local maxima/minima near gas injection valves etc. and the velocity of the injected gas can lead to dramatic shifts of the oxidation potential near the sample surface.
In order to find an optimal strategy to adjust the gas parameters in a furnace and to avoid the formation of dead zones, this project aims to combine flow simulations and local thermodynamic equilibrium assumptions between individual gas species.
This theoretically predicts the local atmospheric conditions during a large-scale industrial process (e.g. continuous annealing) in such a general way, that the danger of high temperature corrosion during steel manufacture can be predicted.
Theoretical findings will be compared to local measurements of temperature, humidity and oxygen amount in order to validate the model under real production conditions. This helps to define the maximum tolerable process window that still yields to the desired product quality.
The ideal candidate should have an interest in steel-related topics and modelling. They should be willing to work both individually and as part of a team. The candidate should also be self-motivated and possess sufficient programming skills.
You should have a 1st or 2.1 Hons degree or equivalent in any of the physical sciences (chemistry, physics, engineering, materials and mathematics).
For funding requirements, applications will only be accepted from UK/EU residents.