David Kirtley

And so that's really fascinating that we've been able to push those boundaries.

Yeah, each of the different simulations we analyze and use it to design different parts of the machine.

So at the MHD level, where we actually have the circuit model, now our design team uses this to design the circuitry, where we're designing which capacitor to use, which switch to use, how many cables to use, literally to that level, how big of a cable to use.

So as we're doing power plant designs right now, those are the tools we're using today, every day.

The team is using...

Then you can go one level deeper and say, okay, let's use these more advanced computational tools about stability to say, okay, great, but I now know the circuitry, but let's look at the magnetic field topology.

How do I design the magnet, the shape of the magnet exactly, the timing of the magnet exactly?

I have to trigger one magnet and the next magnet next to it and the next magnet next to it.

How do I have that shape and that design?

And so that's where you're using those more advanced tools.

Now those, unfortunately, those are still,

too slow.

And so those simulations may take a day or two to run.

And so an operator right now does a lot of simulations ahead of time, then collects data through their operations of the machines, making these field reverse configurations, going through parameter sweeps.

And then the simulation team then goes back and looks at that data and compares it with simulations.

I'm really excited about some of the things we're seeing in artificial intelligence and reinforced learning to be able to speed up that process.

And so we're watching and starting to work on that now of can we now, rather than using it where we use it today, where we...

do a simulation to design a machine or a test, run the test.

And then over the next couple of days, compare the testing with the simulation and use that to inform what we're going to run for the next set of tests.

But in fact, do it more real time where you're now an operator can pull up what the AI or what the machine learning would have predicted it should have done.