Fundamentals of Iterative Prediction with Varying Force: Difference between revisions
(Created page with "It is rare to have a force which is perfectly constant, and iterative analysis of more realistic varying-force systems is substantially more complicated. A toy model demonstra...") |
No edit summary |
||
Line 14: | Line 14: | ||
Just as with a constant force, this lets us write out for some iteration at <math> (x_0,t_0)</math> that | Just as with a constant force, this lets us write out for some iteration at <math> (x_0,t_0)</math> that | ||
<math> p_{final} = p_{initial} + F(x_0,t_0) < | <math> p_{final} = p_{initial} + F(x_0,t_0)\Delta t </math> | ||
Which we combine with kinematics to produce a new position and time <math> (x_1, t_1) <math>. | Which we combine with kinematics to produce a new position and time <math> (x_1, t_1) </math>. The difference we now have is that whereas before <math> F(x_0,t_0) = F(x_1,t_1) </math>, we must now recalculate <math> F(x,t) </math> using the relevant formula. This will take the form of an extra step in each iteration. | ||
===A Computational Implementation=== |
Revision as of 14:05, 30 May 2019
It is rare to have a force which is perfectly constant, and iterative analysis of more realistic varying-force systems is substantially more complicated. A toy model demonstrates how programs may be written to analyze these systems.
Main Idea
The physics of iterative prediction with varying force is the same as for prediction with constant force, but it is necessary to generalize the mathematical expressions, which adds complexity to the code.
A Mathematical Model
To begin with, consider a one dimensional force, which may vary with both space and time. Then we write this as [math]\displaystyle{ F(x,t) }[/math]. Now, using the momentum principle, we know that [math]\displaystyle{ F = \frac{\text{d}p}{\text{d}t} }[/math], which in discrete terms is [math]\displaystyle{ \Delta p = F\Delta t }[/math].
Just as with a constant force, this lets us write out for some iteration at [math]\displaystyle{ (x_0,t_0) }[/math] that
[math]\displaystyle{ p_{final} = p_{initial} + F(x_0,t_0)\Delta t }[/math]
Which we combine with kinematics to produce a new position and time [math]\displaystyle{ (x_1, t_1) }[/math]. The difference we now have is that whereas before [math]\displaystyle{ F(x_0,t_0) = F(x_1,t_1) }[/math], we must now recalculate [math]\displaystyle{ F(x,t) }[/math] using the relevant formula. This will take the form of an extra step in each iteration.