The changeable British weather has inspired a new theory that could improve the performance of fusion devices – aiding the quest to use the processes that power the Sun for cleaner energy.
Culham researcher Fulvio Militello has developed a framework for understanding the seemingly random structures – known as filaments – that erupt at the edge of the hot plasma fuel inside fusion experiments. Perhaps influenced by the amount of wet weather in the UK, Fulvio’s model compares the movement of filaments to the behaviour of raindrops, in the way each is different and follows a path of its own.
It’s a concept that could prove key when it comes to future reactor-scale fusion machines; telling scientists more about how these filaments interact with the walls of the machine.
The model is used for estimating potential outcomes while also allowing for random variations in one or more inputs over time. Each filament is a different strength, initial speed, size, amplitude and position. But all of them follow certain rules as they move – these rules are known from physics theory and have been demonstrated in previous experiments. The fact each filament is different to one another while obeying physics rules has seen them compared to the way raindrops are each individual but all hit the pavement.
And if scientists can understand more about the behaviour of filaments, it will make it easier to predict their effect on the reactor walls, and potentially learn to control them.
Eruptions at the edge of a plasma
In future reactor-scale machines such as ITER and DEMO, where plasmas will be much more energetic, the protection of plasma-facing components will be vital. Filaments, like coronal loops in the sun, start as eruptions at the edge of a plasma – caused initially by plasma instabilities – but once they collide with the reactor wall, they can damage the atomic structure of the wall and degrade it. Any way to predict and control these heated filaments will therefore be advantageous to building efficient reactors.
Fulvio Militello’s model recognises each filament is different, randomly generated and behaves differently from the others. Using the laws of motion, he estimates how they behave collectively and their total effect as they collide with the wall. The input of the framework comes from experimental measurements in Culham’s MAST device and other devices, as well as theoretical models.
A big advantage of the statistical framework means it does not rely on simulations – therefore avoiding the lengthy time such a simulation might take on a supercomputer.
Fulvio Militello said: “Often randomness is not chaos, which means the characteristics of the filaments are distributed in a certain predictable way. In other words, while each filament is different from another, not all sizes or amplitude are equally likely.
“Experimentally, we can measure how likely it is to obtain a certain characteristic in the filament population. Humans, like filaments are all different, but statisticians can tell you how likely it is to find a blond person in a crowd of 100 random people. It’s the same with this theory.”