Contest: Longest train based nuclear reactor
Posted: Mon Oct 25, 2021 11:02 pm
by mrvn
I'v been playing around with putting steam from nuclear reactors into fluid wagons. I started with L>LFFFF trains but you need a lot of trains and congestion sets in.
So I've been thinking: What is the longest train you can fill from a nuclear reactor directly (heat exchanger -> pump -> fluid wagon)?
I was going for maximum speed so 3 pumps per fluid wagon. But if you can produce more trains per minute with less ... No idea what is ideal.
The steam per fuel should be maximized, which I believe only allows a 2xN reactor design.
Results fall into 2 categories:
1) reactor overheats so you have to delay refueling a bit every cycle
For this the delay should be minimal. Add another fluid wagon if you can to take away more steam to keep the reactor cooler. But overall the steam per second it the deciding factor.
2) reactor cools down so the train waits a bit on filling
For this the waiting should be minimal. The question should be: how short a train can you fuel without the reactor overheating when burning fuel without pause?
But again the steam per second is more important. If a longer wait produces more steam then go for it.
Example for category 1:
I figured out experimentally that you can fill a 15 fluid wagon train with an end stop with heat exhangers on both sides of the train when using heat pipes. With 16 fluid wagons the last heat exchanger drop to 500°C with the reactor at 1000°C. It might be impossible to not waste fuel with 15 fluid wagons.
Can you beat that with heat pipes? Maybe have a through station with the reactor in the middle of the train and using only 2 pumps per fluid wagon? Fill 2 trains in parallel.
Example for category 2:
Here is my test setup with a 50 fluid wagon train. 50 you say? I thought at 16 the heat exchangers had low temp? Well, nuclear reactors conduct heat a lot better:
It uses a 2x4 reactor that is actually fueled and all others are just heat conductors. A 2x4 reactor can sustain 112 heat exhcnagers. The 50 fluid wagons use 150. And even with the pause between trains the 2x4 reactor cools down. The train should probably be shorter to meet the rules above. So this doesn't qualify, it's just an example of what you can do. It's also cheating with infinity pipes for the water. YOu should have offshore pumps or bring water by train.
Can you suggest improvements to keep it at 50 fluid wagons or make it even longer? Fueling a larger reactor becomes a problem.
Maybe a small section of heat pipes and then switching to nuclear reactors is the way to go. That would leave room for inserters to fuel a larger reactor. Other ideas?
So I've been thinking: What is the longest train you can fill from a nuclear reactor directly (heat exchanger -> pump -> fluid wagon)?
I was going for maximum speed so 3 pumps per fluid wagon. But if you can produce more trains per minute with less ... No idea what is ideal.
The steam per fuel should be maximized, which I believe only allows a 2xN reactor design.
Results fall into 2 categories:
1) reactor overheats so you have to delay refueling a bit every cycle
For this the delay should be minimal. Add another fluid wagon if you can to take away more steam to keep the reactor cooler. But overall the steam per second it the deciding factor.
2) reactor cools down so the train waits a bit on filling
For this the waiting should be minimal. The question should be: how short a train can you fuel without the reactor overheating when burning fuel without pause?
But again the steam per second is more important. If a longer wait produces more steam then go for it.
Example for category 1:
I figured out experimentally that you can fill a 15 fluid wagon train with an end stop with heat exhangers on both sides of the train when using heat pipes. With 16 fluid wagons the last heat exchanger drop to 500°C with the reactor at 1000°C. It might be impossible to not waste fuel with 15 fluid wagons.
Can you beat that with heat pipes? Maybe have a through station with the reactor in the middle of the train and using only 2 pumps per fluid wagon? Fill 2 trains in parallel.
Example for category 2:
Here is my test setup with a 50 fluid wagon train. 50 you say? I thought at 16 the heat exchangers had low temp? Well, nuclear reactors conduct heat a lot better:
- 50-wagon-nuclear.png (808.22 KiB) Viewed 8498 times
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
It uses a 2x4 reactor that is actually fueled and all others are just heat conductors. A 2x4 reactor can sustain 112 heat exhcnagers. The 50 fluid wagons use 150. And even with the pause between trains the 2x4 reactor cools down. The train should probably be shorter to meet the rules above. So this doesn't qualify, it's just an example of what you can do. It's also cheating with infinity pipes for the water. YOu should have offshore pumps or bring water by train.
Can you suggest improvements to keep it at 50 fluid wagons or make it even longer? Fueling a larger reactor becomes a problem.
Maybe a small section of heat pipes and then switching to nuclear reactors is the way to go. That would leave room for inserters to fuel a larger reactor. Other ideas?