4 ms·

I've worked on a hobby ballistics simulator for some time now. This is of course a well studied field, with military applications going back hundreds of years.

by roel_v 7y ago

I've worked on a hobby ballistics simulator for some time now. This is of course a well studied field, with military applications going back hundreds of years. What's interesting (well, it was to me) is that the state if the art is not closed form solutions, because as you refine solutions and take into account bullet spin, wind, Coriolis effect etc, that becomes too cumbersome. Modern ballistics uses discrete simulation to calculate trajectories.

galangalalgol 7y ago
Something like montecarlo sequential resampling? Do you have any good papers you could reference?
- throwlaplace 7y ago
  Why would you use Monte Carlo for this? There's no randomness as stated. What op is probably talking about is numerical solutions to pdes (which is also considered "simulation").
  - roel_v 7y ago
    "Ballistics: Theory and Design of Guns and Ammunition" by Carlucci et al. is (from what I can tell - again I'm just a hobbiest, it's the book I work from most) a thorough yet accessible standard work on this topic, detailed in the mathematics, lots of references, covers most of the details that matter, yet 'practical' - you can tell the authors were in the military where they had to produce results and not just papers. I'm not 100% sure how to exactly classify the approach in terms of mathematics. It's basically just 'over the next 10 cm, the bullet drops this much, yaws this much, rolls this much, ...' etc, so basically just incrementally calculating position. Very 'primitive' from a math point of view, but that's exactly what I found interesting - how a brute force numerical approach is considered superior to an elegant closed form solution. Edit: I should add that part of the reason for this is that some of the external forces on a bullet are non-continuous, like wind coming around a building. That sort of pesky real world effects makes elegant solutions a lot more difficult.
    - semi-extrinsic 7y ago
      This sounds a lot like what GP is saying, a time integration algorithm to solve a set of ODEs. Probably it's a variant of velocity Verlet? https://en.wikipedia.org/wiki/Verlet_integration https://en.wikipedia.org/wiki/Verlet_integration

by roel_v 7y ago

galangalalgol 7y ago

Something like montecarlo sequential resampling? Do you have any good papers you could reference?

throwlaplace 7y ago
Why would you use Monte Carlo for this? There's no randomness as stated. What op is probably talking about is numerical solutions to pdes (which is also considered "simulation").
- roel_v 7y ago
  "Ballistics: Theory and Design of Guns and Ammunition" by Carlucci et al. is (from what I can tell - again I'm just a hobbiest, it's the book I work from most) a thorough yet accessible standard work on this topic, detailed in the mathematics, lots of references, covers most of the details that matter, yet 'practical' - you can tell the authors were in the military where they had to produce results and not just papers. I'm not 100% sure how to exactly classify the approach in terms of mathematics. It's basically just 'over the next 10 cm, the bullet drops this much, yaws this much, rolls this much, ...' etc, so basically just incrementally calculating position. Very 'primitive' from a math point of view, but that's exactly what I found interesting - how a brute force numerical approach is considered superior to an elegant closed form solution. Edit: I should add that part of the reason for this is that some of the external forces on a bullet are non-continuous, like wind coming around a building. That sort of pesky real world effects makes elegant solutions a lot more difficult.
  - semi-extrinsic 7y ago
    This sounds a lot like what GP is saying, a time integration algorithm to solve a set of ODEs. Probably it's a variant of velocity Verlet? https://en.wikipedia.org/wiki/Verlet_integration https://en.wikipedia.org/wiki/Verlet_integration