alt Hacker NewsAI for real-time fusion plasma behavior prediction and manipulation
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There is a lot of AI research in the nuclear fusion space. For inertial confinement fusion (a competing technology to magnetic confinement fusion, e.g., tokamaks) the National Ignition Facility (NIF) used it for their experiment that resulted in "ignition."
My lab is collaborating with researchers at the Laboratory for Laser Energetics to use AI to improve inertial confinement fusion (ICF). We recently put out this paper [1] using Kolmogorov-Arnold Networks (KANs) to predict the outcome of ICF experiments. Currently, existing physics simulators are based on old Fortran code, are slow, and have a high error between their predictions and actual laser shots, so among other goals, we are trying to build better predictors using neural networks. This is needed since it is hard to rapidly iterate on real data, since they only have a dataset of around 300 ICF shots.
About 20 years ago I was an undergrad at the university of Padova (italy), and in the outskirts of the city (in Legnaro) there was a fusion experiment. The fusion device was in one building and the control room was in an adjacent building. Back then we were using CRT monitors and each time there was a fusion event, the magnetic confinement field was so strong that the image on all the screens in the control room would simultaneously shift on one side and then spring back when the field was turned off. Across buildings.
the Porcini Mushroom is wrong, because when you cut a part of this mushroom the Yellow become Blue, and it is by this way one of rare blue element in Nature.
> However, uncovering these inter-correlations analytically is too complex to be achieved analytically.
sigh.. I guess that's cool and all, you're exited about your work, that's great. But can we please polish our prose a little more and stop using buzz words like "groundbreaking", "now.. for the first time", "unprecedented" etc? Such distractions seriously undermine the legibility (and frankly, also taint the credibility by negatively biasing readers) of the claims.
Neutrons make hardware radioactive.
Many on Hacker News fantasize about fusion (not fission) reactors. These fusion reactors will be an intense source of fast neutrons. All the hardware in a fusion reactor will become radioactive. Not to mention the gamma rays.
If you have to deal with radioactive materials, why not just use fission? After 70 years of working with fission reactors, we know how to build and operate them at 95%+ efficiency. Fission can provide all the power we need.
Today there are 440 nuclear fission reactors operating in 32 countries. 20% of America's grid power comes from nuclear fission. If you want to develop energy technology, focus on improving fission. For example, TRISO fuel (https://news.ycombinator.com/item?id=41898377) or what Lightbridge is doing (https://www.ltbridge.com/lightbridge-fuel). Hacker News is hostile to fission and defeatist (unable to contemplate innovation in fission technology) but this attitude will gradually change.
Quoting John Carmack: "Deuterium fusion would give us a cheap and basically unlimited fuel source with a modest waste stream, but it is an almost comically complex and expensive way to generate heat compared to fission, which is basically 'put these rocks next to each other and they get hot'."
>Nuclear power plants are largely considered as one of the most reliable sources of energy. Inside the plants, reactors use fission to heat water into steam, which is then used to spin turbines and produce carbon-free electricity. However, nuclear fission produces nuclear waste, which requires great amounts of regulation for safe storage and disposal.
This is an odd angle to highlight. The risk of long-lived nuclear waste is extremely overblown, and the sheer volume of it that we produce (or even would produce, in the worst case of a once-through fuel cycle and nuclear power providing 100% of our energy needs for a century) pales in comparison to the amount of toxic and radioactive fly ash that even a single coal plant produces in a decade.
The real problems with nuclear fission power are threefold, in my opinion:
1. It is too expensive in terms of capital costs. Fusion will likely not help with this, but building a lot of identical large fission plants would probably help with economies of scale. Solar plus batteries might still end up being cheaper though.
2. Accidents have the potential to be catastrophic. Think Fukushima or Chernobyl, where entire towns have to be abandoned due to contamination. Fusion would help here, I believe.
3. There is a major proliferation concern. A civilian nuclear power program, especially one with breeder reactors, is not very far away from producing a fission bomb, and the short-lived high-activity nuclear wastes could be stolen and misused to make a dirty bomb. Fusion is perhaps better in this way, though an operating fusion reactor would be a very powerful neutron source of its own.
I know AI is the buzzword du jour, but this is really ML, and really just advanced cybernetic control systems. Deep learning systems have a high enough degree of variety necessary to control short time step nonlinear systems like the plasma in a tokamak.
> Nuclear power plants are largely considered as one of the most reliable sources of energy.
Reliable how?
I mean we first have the issue is we've never built one so how we can judge reliability?
I assume the author is alluding to the apparent abundance of fuel for nuclear fusion. This is and isn't true. Obviously hydrogen (particularly protium) is abundant. Deuterium is relatively abundant, even at ~150ppm. Tritium needs to be produced in a nuclear reactor.
Current hydrogen fusion models revolve around dueterium-tritium ("D-T") fusion. This is because you need to neutrons to sustain the reaction but that presents two huge problems:
1. Because everything is at such high temperature, you eject fast neutrons. This is an energy loss for the system and there's not really a lot you can do about it; and
2. Those free fast neutrons destroy your containment vessel and reactor (as do free Helium nuclei aka alpha particles).
And then after you do all that you boil water and turn a turbine just like you do in a coal or natural gas plant.
So "reliable" is an interesting and questionable claim.
There are other variants like so-called aneutronic fusion (eg Helium-3, which is far from abundant) and those aren't really "neutron free". They're really just "fewer neutrons".
So what about containment? Magnetic fields can contain charged particles and you have various designs (eg tokamak, stellarator) and that's what the AI is for here I guess.
But the core problem is to make this work you superheat the plasma so you're dealing with a turbulent fluid. That's inherently problematic. Any imperfection or failure in your containment field is going to be a problem.
Stars deal with this by being large and thus using sheer size (ie neutrons can't go that far without hitting another nucleus) and gravity.
It increasingly seems to me that commercial nuclear fusion power generator is a pipe dream, something we simply want to be true. I'm not convinced it'll ever be commercially viable.
I'd love to be proven wrong and certainly won't stop anyone from trying.
In a way AI is the new blockchain. Go back a few years and you had a gold rush of startups attaching every idea to "blockchain" to build hype. That's what AI is now. I don't think it fundamentally changes any of the inherent problems in nuclear fusion.
When Marketing gets invited to the Grant Proposal meeting
See also https://www.ri.cmu.edu/ai-meets-fusion-cmu-princeton-join-fo...
(that was the submitted link but we changed it via https://news.ycombinator.com/item?id=42077657)