Accurate belt segment measurements
Posted: Sat Apr 27, 2019 3:48 pm
by ignatio
I found myself wondering exactly how long belt segments are, or more precisely how long it takes for an item to get from one end to the other.
The wiki page (as of the time of this posting) tells us that straight segments have 32 "slots", which are travelled 1 slot per tick on a yellow belt, hence it takes 32 ticks from one end to the other. (The page also tells us items take up 9 slots, which is no longer accurate in 0.17, but this is not about that bit of stale info.)
The length of a straight is correct. But then the page describes turns, and says the outer lane of a turn is 37 slots and the inner lane is alternating between 13 and 14 slots, and I couldn't get it to work like that: I did some spirals with turns in only one direction, and cancelling out the straights I got that the successive inner turns took:
13, 13, 13, 14, 13, 13, 13, 14, 13, 13, 13, ...
I.e. only every 4th turn takes 14 ticks, or, put differently, an inner turn seems to be 13.25 slots long. Outer turns too don't quite take 37 ticks each:
36, 37, 37, 37, 37, 37, 37, 37, 36, 37, 37, ...
First I thought that was some off-by-one problem in my test rigs, but it's perfectly repeatable.
Now I got intrigued, so I set up circular belts of different sorts where single items go round and round. Then I added some circuitry to predict the lap times - when the constants are right it should line up perfectly with the real measurements regardless how many laps it takes for the cycle to repeat.
With some deductions from the lap times of those circuits we can measure the fractional slots for each type of belt segment, also including sideloaded belts, underground belts, splitters, etc. I included some sanity checks too, like checking that left and right turns take the same time.
Rather than dealing with fractional "slots" we can scale things up to whole numbers, and so we find that there are in fact 8 times more positions:
An observation is that it's possible to get items to travel faster by converting inner turns to sideloaded segments. However it doesn't affect the throughput, i.e. items per second.
Based on these findings I'm going to update the wiki page, and also fix the stale item size info at the same time. But I thought to post here first in case there are thoughts on this.
If you want to try it out yourself I've attached the blueprint below. It requires that the infinity chest is unlocked, which you can do with the Creative Items mod, but other than that it should work on vanilla. The test is enabled by turning on the constant combinator in the top left corner. Because I'm a bit lazy with the combinator logic, the speakers will alert when the test is turned on or off, but once that has died down after the start there should be no more alerts as long as it's kept running.
The wiki page (as of the time of this posting) tells us that straight segments have 32 "slots", which are travelled 1 slot per tick on a yellow belt, hence it takes 32 ticks from one end to the other. (The page also tells us items take up 9 slots, which is no longer accurate in 0.17, but this is not about that bit of stale info.)
The length of a straight is correct. But then the page describes turns, and says the outer lane of a turn is 37 slots and the inner lane is alternating between 13 and 14 slots, and I couldn't get it to work like that: I did some spirals with turns in only one direction, and cancelling out the straights I got that the successive inner turns took:
13, 13, 13, 14, 13, 13, 13, 14, 13, 13, 13, ...
I.e. only every 4th turn takes 14 ticks, or, put differently, an inner turn seems to be 13.25 slots long. Outer turns too don't quite take 37 ticks each:
36, 37, 37, 37, 37, 37, 37, 37, 36, 37, 37, ...
First I thought that was some off-by-one problem in my test rigs, but it's perfectly repeatable.
Now I got intrigued, so I set up circular belts of different sorts where single items go round and round. Then I added some circuitry to predict the lap times - when the constants are right it should line up perfectly with the real measurements regardless how many laps it takes for the cycle to repeat.
With some deductions from the lap times of those circuits we can measure the fractional slots for each type of belt segment, also including sideloaded belts, underground belts, splitters, etc. I included some sanity checks too, like checking that left and right turns take the same time.
Rather than dealing with fractional "slots" we can scale things up to whole numbers, and so we find that there are in fact 8 times more positions:
- Straight segments have 256 positions per lane.
- Yellow belts move items at 8 positions per tick, red 2*8=16, and blue 3*8=24 positions/tick.
- Underground segments and splitters also have 256 positions per lane.
- The outer lanes in turns have 295 positions.
- The inner lanes in turns have 106 positions.
- Straights and underground entrances sideloaded "early" have 188 positions.
- Straights and underground exits sideloaded "late" have 68 positions.
An observation is that it's possible to get items to travel faster by converting inner turns to sideloaded segments. However it doesn't affect the throughput, i.e. items per second.
Based on these findings I'm going to update the wiki page, and also fix the stale item size info at the same time. But I thought to post here first in case there are thoughts on this.
If you want to try it out yourself I've attached the blueprint below. It requires that the infinity chest is unlocked, which you can do with the Creative Items mod, but other than that it should work on vanilla. The test is enabled by turning on the constant combinator in the top left corner. Because I'm a bit lazy with the combinator logic, the speakers will alert when the test is turned on or off, but once that has died down after the start there should be no more alerts as long as it's kept running.
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